Creating professional Facebook posts for your newsagency or retail shop doesn't have to be a chore. In 2026, Artificial Intelligence (AI) allows shop owners to generate high-quality, engaging social media content in under four minutes.

A few days ago, I released a social media calendar for 2026 designed explicitly for newsagents. I wanted to help shop owners get organised for the year ahead. Since then, I have received quite a few enquiries like last year, but one reaction shocked me. Several people told me it was "too much work" and that writing these posts for every calendar event would take ages.

This is not true.

Writing a high-quality post on Facebook takes less than 4 minutes. In 2026, the technology available to us now is incredible and here to save you time. Today, I will show you exactly how.

The Facebook Reality Check

Before we get into the "how-to," we need to have a serious conversation about the "where." To do this, you must have a business Facebook account.

If you do not have one yet, you are, frankly, leaving money on the table. Your business needs one. In this day and age, a retail business without a digital storefront on social media is invisible to a huge chunk of the local community. So if you don't have a page, stop reading this right now. Go make one up. It is free and essential. In 2026, businesses need a Facebook business page to survive and thrive. For the rest of you who are ready to go, let's look at a simple method to get your marketing done in record time.

Why You Can't Afford to Be Invisible

Many independent retailers tell me they rely on foot traffic. That is great, but where does foot traffic come from? Often, it comes from a Google search or a Facebook recommendation.

If a local customer searches for "birthday cards near me" or "magazines in [Suburb Name]," and your competitor has an active Facebook page with photos, while yours does not, guess where they are going?

You are not just competing with the shop down the road; you are competing for attention on the screen in your customer's pocket.

The 4-Minute Method: A Step-by-Step Guide

As we all know, things change rapidly in the world of AI. However, the core principles I am showing you here will likely remain the same for a long time. I intend to update this article when Facebook AI is finally released for business in Australia. These steps are relevant only for January 2026.

I will perform this live for my own business page to show you how easy it is. Please follow along with your own business page.

Step 1: Get Your Visuals Ready

First, you need an image. Facebook is a visual platform. Text alone often gets ignored as people scroll through their feeds. You have two main options here:
Both can be used.

Supplier Images

These are professional and clean, but they can sometimes look a bit "cold." Also, they are not from you; others have them too. What you are trying to sell is the product, not you. Plus, you may get into a copyright problem later.

Your Own Photos

These are authentic and perform better.

I have discussed how to take a photo yourself here.
A photo showing your actual shop is often better. Customers love to see the human side of a business. A photo of you, clearly standing and holding the product, works wonders. It builds trust.

I suggest you take about 10 pictures. Don't overthink it, snap away. Then, review them and select the top two.

Step 2: Open Your Business Page

Now, call up your business page on your computer or tablet. Look for the box at the top that asks, "What's on your mind?" See the red arrow 

This is where the magic starts. I have added the selected image. See the blue arrow.

You can add multiple photos if you like, but often one strong image is enough, and two is better.

Step 3: Select Your AI Tool

Now, I have decided to stick to a free AI for this demonstration. Only a few of my customers, or SMB retailers in general, have paid accounts for these services. That is perfectly fine, but you do not need to spend money to get great results, as I will show you here how to do it for free.

Select the AI that you want to use. You have plenty of options: ChatGPT, Gemini (Google), Grok, Deepseek, etc. These are all good and have free versions.

On Facebook, Meta AI is specifically designed for this task, but Facebook is currently restricting its full use on some business accounts in Australia, and it has just acquired Manus, which promises to make massive changes in AI.

Step 4: The Prompt

This is the part that scares people, but it is actually the easiest part. You need to tell the AI what to do. We call this a "prompt."

You don't need to be a computer programmer. You need to speak to it as if you were talking to an advertising agent.

Use this prompt, see the blue arrow above. 

Write a friendly but professional Facebook post for my business talking about [Product Name]. Keep it under 150 words. Use Australian spelling =====.

Using Supplier Content

Now, add a few lines about the product. If you are unsure what to say, you can use the description from the supplier's advertisement.

For my example, I want to talk about the customer-facing screens in our POS system.

I found this text:
"One of the most popular features in modern POS software is a customer-facing screen. These digital displays display detailed order information to customers, including their orders, tax, discounts, and loyalty information during the checkout process. You often see customer-facing displays in retail businesses."

I put this in, see the blue arrow above. 

Now, see the red arrow, I got a fine copy. The grammar and spelling are fine. I didn't have to stare at a blank screen wondering what to say. The AI took the facts about the screen, like how it improves accuracy and speeds up the queue, and turned them into an advertisement for my customers. I would suggest including your shop details as well.

So I pasted that text into my advertisement.

Step 5: The Result

I hit "Enter," and within seconds, the AI gave me a professional advertisement.

See the blue arrow in the image above? That is the text I cut and pasted directly into my Facebook post.

Step 6: Publish and Schedule

And then I saved it. See the image above for the final result.

As I said, the whole operation would take less than 4 minutes. I now have a professional Facebook advertisement for nothing—zero cost.

Why This Matters for Your Shop

The beauty of this method is that it is easy to repeat.

You can use the same process for holidays. For example, the Chinese New Year is coming up soon. You could take a photo of your red cards, envelopes, decorations, etc, tell the AI "Write a post wishing my customers a Happy Chinese New Year," and you are done. If in doubt, use your top-selling report in your POS System to tell you what sold well in your shop during the Chinese New Year.

Consistency is key in retail marketing. You don't need to be a professional writer. You need to do it; don't worry about perfection, as you can continually improve as you learn more.

Ready to save even more time?
Download our 2026 Social Media Calendar for Newsagents below and use this 4-minute method to fill your entire month's schedule today.

Download 2026 Calendar Here

Written by:

Bernard Zimmermann is the founding director of POS Solutions, a leading point-of-sale system company with 45 years of industry experience, now retired and seeking new opportunities. He consults with various organisations, from small businesses to large retailers and government institutions. Bernard is passionate about helping companies optimise their operations through innovative POS technology and enabling seamless customer experiences through effective software solutions.

I was at a retail meeting recently, and the topic that got people talking and thinking was "virtual cashiers." It is already happening in America. Here's how it works: instead of having a cashier standing at your counter, you have a screen. On that screen is a real person, live via video, like Zoom. That person is working in another country, maybe the Philippines or India, but they are is your cashier in your shop.

The setup depends on what kind of business you run.

For Quick-Service Businesses

Say you run a fast-food shop; the virtual cashier works just like a regular cashier. They greet the customer, take the order, enter it into your POS system, and guide the customer to tap their card on the payment terminal. Between customers, they can answer your phone, monitor your security cameras, or handle other tasks.

For Retail Shops

If you run a newsagency, chemist, pet shop, or similar business, it works as a hybrid between self-checkout and a staffed counter. The customer scans their own items with a barcode scanner, while the virtual cashier monitors everything via a camera feed. They can help if a barcode won't scan, handle age verification for tobacco, or answer questions. Most importantly, they watch to make sure everything gets scanned, which will address the biggest problem with self-checkouts: theft. Today, self-checkout theft can be 16 times higher than with traditional cashiers. Some are going back to cashiers, and so few SMB retailers are rejecting them.

The Money Side of Things

Let me be blunt about the costs.

Right now, if you employ a casual cashier in Australia, you're paying around $27 per hour base rate, plus often casual loading. Then there's superannuation at 11.5%. And weekends? That's when it really hurts: 150% on Saturdays and 175% on Sundays. If you're open seven days a week, 12 hours a day, you're looking at over $85,000 a year for one full-time cashier position.

Now compare that to virtual cashier rates. Even if you're paying double or triple the local rate in India or Pakistan, you're looking at $6 to $9 an hour. That is a potential savings of $60,000 or more per year, per position. It's no wonder that so many were interested in the retail meeting.

As a virtual cashier watches the transaction through a camera, another major cost-saving is theft, since the customer knows someone is watching. They can't "accidentally" forget to scan items, and it's harder to swap barcodes, the banana trick where people swap a barcode on a cheaper item onto a dearer one..

What would be needed to set it up?

When we thought it through, it did not seem as complicated as it might sound.

• Professional remote desktop software so the virtual cashier can control your POS system
• A monitor facing the customer showing the cashier's video feed
• At least two cameras, one pointed at the customer, and the other at the scanning area
• Good quality microphone and speakers for a clear two-way conversation
• Reliable, fast internet (this is not negotiable; it would need to be business-grade, not home broadband)
• Recording capability for any disputes or investigations
• We could easily make it better with our AI 

So yes, there's an upfront cost for this equipment, but when you're saving $60,000 a year, it's minor. 

I am sure we could do it right now with some of our clients.

Things to Consider

It's worth thinking about.

I'm not going to pretend this is a perfect solution, nothing is, and there are legitimate concerns, but the reality is that your retail margins are tight and getting tighter. Labour costs keep going up. Theft keeps eating into your profits and your customers are increasingly comfortable with technology.

Now ask yourself what matters most to your customers? The lowest price, or a local person behind the counter? My gut feeling is that most will vote with their wallets.

Written by:

Bernard Zimmermann is the founding director of POS Solutions, a leading point-of-sale system company with 45 years of industry experience, now retired and seeking new opportunities. He consults with various organisations, from small businesses to large retailers and government institutions. Bernard is passionate about helping companies optimise their operations through innovative POS technology and enabling seamless customer experiences through effective software solutions.

Now people are looking at using Artificial Intelligence (AI) to improve their business. We have seen firsthand here how such AI tools can be used. I was reading a recent survey of social media (advertisers) managers by Metricool here, and I immediately saw another use of how these AI tools can be used.

Survey Insights on AI Usage

Metricool did a deep analysis, and what struck me was just how many of these people 96% were using AI to create advertisements. 72.6% doing so daily. Interestingly, half of them rely on free versions of tools such as ChatGPT, Google Gemini, or Perplexity. So what they do is available to any retailer.

The first point that stands out is the efficiency gain. Nearly 79% of respondents say AI saves them significant time. Another 77.9% value AI most for generating ideas to promote products, followed by 72.5% who use it for writing content. When it comes to quality, the survey shows promising results. Of those who compared AI-generated material to traditional content, 59% found it on par, 33% deemed it better, and only 8% said it was worse. As professionals in marketing, our standards are high, so imagine how this could elevate our efforts, as we are not professional copywriters. For SMB businesses, this means producing tailored ads quickly, without outsourcing or spending hours.

Real-World Retail Example: Father's Day Campaign

Let's explore how this plays out for SMB retailers. Say you're preparing for Father's Day. You could prompt an AI tool just as I did here. Note, I use Perplexity, which we offered our readers here at a significantly discounted rate a while ago. It has a space set up for a fictional newsagency.

I liked the last idea, so I asked the AI to write a Facebook post.

Now I did like it but thought maybe I should ask for a few other ideas so I asked

I did like the post 1 idea the best, but it was a bit short so I went 

This all took under a minute to generate. If I was to post it to Facebook, I would add a quick photo from my your mobile and then I would have a decent Facebook post advertising my shop.

Practical Tips for Getting Started

Start simple

Choose a free AI tool, I like Perplexity, but Google Gemini or ChatGPT, all are also excellent.

Now experiment, like using your POS System reports to find your top ten selling products. Now ask AI to generate a Facebook post for the shop to market one of these products.

Edit your Facebook post

I find it good to ask for a few different ideas, and feel free to contribute.  

Post your Facebook post

Remember to add a photo.

Monitor results.

Track your results.

Looking Ahead: Empower Your Business

Embracing AI in advertising helps SMB retailers to compete.

Written by:

Bernard Zimmermann is the founding director of POS Solutions, a leading point-of-sale system company with 45 years of industry experience, now retired and seeking new opportunities. He consults with various organisations, from small businesses to large retailers and government institutions. Bernard is passionate about helping companies optimise their operations through innovative POS technology and enabling seamless customer experiences through effective software solutions.

Yesterday, I discussed the report that you can quickly get for doing price checks on products in your area. Now I will review the options for getting the report. As I discussed yesterday here, suppliers present you with many products, but it's hard to know the real retail price and your item's margin, so Australian retailers are using free AI tools that automate price checks. These tools help you quickly compare prices, avoid idle stock, and maximise margins without manual searches, saving time and boosting profits. The problem is that manually checking prices via search engines is time-consuming.

In comparison, a simple Google Shopping search works for a single product. If, for example, I want to check 40 products and it takes me a minute or so to do one, I am looking at an hour of work. This is why, when you have many items to check, that's where AI can help, as it offers a quicker way to get real-time insights. Not only that, but it provides a deep analysis and local relevance. This allows you to get real figures so you can improve customer satisfaction and boost your bottom line.

In our test, we focused on free AI systems to keep things accessible for small operators. We limited evaluations to no-cost options, ensuring recommendations fit tight budgets. By the end, you'll have clear guidance on which AI tool might suit your needs.

Our Evaluation Approach

Using the scoring system below, we tested six free AI tools with a query.

"What price is Monopoly Indiana Jones Edition in Keysborough, Victoria, Australia?"

As usual, we used a Structured Scoring System.

To fairly assess these AI tools, we adopted a 100-point scoring system based on key criteria essential for retailers.

The categories include:

• Accuracy (30 points): How closely the AI's price data matches verified market values. Google Shopping was used as a benchmark here.
• Relevance and Personalisation (20 points): Most of our clients are local, so we gave points to their location and business context.
• Completeness and Depth (20 points): Coverage of options, variations, and caveats.
• Helpfulness and User-Friendliness (15 points): Actionable advice and ease of use.
• Clarity and Structure (10 points): Organisation and readability. Who has the time to work out things? If it can be read and absorbed quickly, the better.
• Ethical Handling (5 points): Did it state any limitations in its analysis?

This system ensures objectivity, much like how a POS analyses sales data to recommend stock levels. We evaluated six popular AIs: Deepseek, Qwen, Claude, Grok, Gemini Google, and ChatGPT. Let's dive into the results, highlighting how each could enhance your shop.

Here's how each performed, starting with the lowest scorers.

Claude

Summary: Lacking Specifics

We failed it as it did not give prices. We are testing for prices, and it provided none.

We liked that it openly admitted it can't fetch real-time prices and provided some helpful information. However, if you are looking at price checking, forget it.

Deepseek

Summary: Solid Local Focus with Room for Precision

Deepseek performed respectably, scoring 75 out of 100. It provided price ranges of $40–$60 for standard editions and $70–$100 for collectors, which are somewhat realistic but slightly overestimate everyday values. What surprised us was that it excelled in local relevance by suggesting stores like Parkmore Shopping Centre in Keysborough, complete with contact tips.

The tool's structure, with bullet points and headings, makes it user-friendly. We liked that it urged you to check current prices. Overall, Deepseek offers a good starting point for SMB retailers seeking local insights without complexity.

Grok

Summary: Comprehensive with Accurate Ranges

Grok earned 80 points, delivering prices from $28–$108 across retailers, with both notes on shipping and local checks. It was personalised to Keysborough by mentioning Parkmore, though it leaned more national in focus.

While its structure had minor issues, Grok's actionable advice, such as visiting stores, makes it practical. It included helpful links without overpromising.

Qwen

Summary: Good Online Depth

With a score of 84, Qwen stands out for its balanced approach. It quoted realistic online prices of $35–$60, and we liked that it stated the local unavailability in the local shopping centre, Keysborough. A detail critical to retailers in pricing.

Qwen's clear lists and engaging tone add to its appeal.

Gemini Google

Summary: A Top Performer

Because it has access to Google shopping information, it impressed us with its retail prices, ranging from $17.50 to $80. It was heavily tailored to Keysborough locations like Parkmore. Its local focus and structure, which included tables, make it highly user-friendly.

ChatGPT

Summary: Depth and Helpfulness in Equal Measure

ChatGPT scored 90; it ticked most of the boxes: an image to confirm that you have the right product, detailed tables with prices $17.50–$73.95, strong local tie-ins, and noted caveats. Its completeness, including delivery tips, makes it a standout for comprehensive analysis.

Based on these scores, here's what stood out overall.

Overall Insights and Recommendations

Although all AI tools handled ethics well by admitting limitations, we liked that Deepseek and Gemini, in particular, urged real-time verification. Never assume that AI is correct.

Gemini (Google) and ChatGPT are good choices; they both excel in depth and relevance.

Practical Tips for Implementing AI in Your POS

1) Embracing AI for price checking positions your store for success.

2) To get started, I suggest that you choose Google Gemini or ChatGPT.

3) Test some products from your shop. I suggest starting with your top sellers and then some dead stock.

4) Get a feel of the reports.

5) Make a trip to the local shops to check the accuracy.

Start today!

Written by:

Bernard Zimmermann is the founding director of POS Solutions, a leading point-of-sale system company with 45 years of industry experience, now retired and seeking new opportunities. He consults with various organisations, from small businesses to large retailers and government institutions. Bernard is passionate about helping companies optimise their operations through innovative POS technology and enabling seamless customer experiences through effective software solutions.

Using AI to set pricing decisions can help you determine prices and stay competitive. If the price is too high, your customers walk away; if it's too low, you're selling too cheaply. For many retailers, finding that ideal point is tricky in a marketplace that can change their prices overnight. I have discussed this issue earlier here as well.

In today’s market, you should trust your gut to assess how your pricing compares. Free AI tools can provide quick, localised insights into what your competitors are charging. Knowing this, it is easier to set prices without taking up too much time.

Let’s go through an example.

The Challenge: Knowing the True Retail Price

Imagine running a shop in Keysborough and considering stocking Monopoly: Indiana Jones Edition. Your supplier gives it a great rap, tells you a wholesale cost, quotes a retail price, but how do you confirm their retail price and determine if it's as good a seller as they claim?

Traditionally, you’d go to a local shopping centre and look around—that's maybe an hour of work, plus how can you leave the shop for an hour over one product? Or you might hit Google Shopping, search for the product name, and scan the listings there. That’s easy enough for one product. But say you’re reviewing 40 items — suddenly you’re looking at an hour or more of work, clicking through results, checking conditions, and making sure you’re comparing the same SKU.

The fact is that doing it manually is time-consuming and prone to human error.

Where AI Changes the Game

This is where AI-powered price comparison tools like ChatGPT can revolutionise the problem by instantly scanning multiple retailers, comparing their prices, identifying their promotions, and localising them for your specific location.

For example, I picked a game as a sample, "Monopoly: Indiana Jones Edition".

So I ran a query in ChatGPT "What price is Monopoly Indiana Jones Edition in Keysborough, Victoria, Australia?"

in Keysborough through ChatGPT’s data tools. In a matter of seconds, I received a summary that:

• Confirmed the correct product with an image reference (avoiding costly mix-ups). Green square
• Highlighted a typical local retail range: $65–$70, with a benchmark example from Toyworld at $69.99. Purple square
• Flagged that JB Hi-Fi had a special promotion potentially lower than the market average — perhaps even below your wholesale cost. Maybe you can get it cheaper. Black square
• Noted that in many cases the product was marked as “on order” rather than available for immediate purchase. This makes me suspicious that it's such a great seller.

So I decided to check for availability.

Why This Matters to Your Pricing Strategy

Beyond just pricing, understanding competitor promotions can dictate your sales tactics.

Setting a Competitive Yet Profitable Price

Knowing the local going rate means you can confidently set your price within the $65–$70 band without underpricing or scaring buyers off. If the market is consistent at that range, you’re on safe ground.

Tracking Competitor Promotions

If a competitor runs a temporary promotion, you need to decide whether to run your offers, maintain your current strategy, or drop the product.

Managing Availability to Your Advantage

If many competitors have the product “on order” only, as you can see here, you can leverage this scarcity.

Saving Time

Instead of spending hours doing manual searches, you are getting instant results.

From Price Insights to Actionable Retail Decisions

Here’s where a modern POS system ties it all together. AI pricing insights are powerful on their own, but when integrated into your POS, start by checking your top-selling items or dead stock, and see whether you are competing on price or convenience. Doing this will give you AI-driven price insights.

Bringing It Back to Your Store

Smart pricing is not about being the cheapest, but also about understanding your place in the market to stay competitive.

AI-powered retail price optimisation solutions now integrate, process, and analyse data from across the organisation in near real-time. This level of visibility and control provides retailers with the rapid insights needed to make smart pricing decisions.

Tomorrow, I will discuss the AI tools in detail for doing these price comparisons.

Written by:

Bernard Zimmermann is the founding director of POS Solutions, a leading point-of-sale system company with 45 years of industry experience, now retired and seeking new opportunities. He consults with various organisations, from small businesses to large retailers and government institutions. Bernard is passionate about helping companies optimise their operations through innovative POS technology and enabling seamless customer experiences through effective software solutions.

Australian retailers are today exploring AI-powered POS analysis to gain deeper insights from their POS system reports. While AI offers substantial potential, it is crucial to understand its current limitations, especially when integrating it with POS system analytics in today's business.

What I would like to discuss is the issue of utilising the information in your POS System to drive an AI analysis. It is something that my company was one of the first to explore with OpenAI, the creators of what is now ChatGPT, years ago.

Data Quality and System Integration

Like any advice, the effectiveness of AI-driven POS analytics depends on the quality and completeness of the information we give it. If the information you feed it has errors, then I doubt analysis will help. That is why a manual review of the information you are feeding the AI is so critical. It is also why many are saying that now is the best time to utilise AI to review your stock, as the information in your POS System has been verified during the stocktake you have just completed.

These data challenges lay the groundwork for further issues, such as the risk of AI hallucinations, which we explore next.

Hallucinations

Hallucinations are not just an AI problem. In human conversation, topics often drift, leading to another topic. AI can behave similarly, sometimes producing nonsensical or, worse, convincing but incorrect results.

The significant issue here, at worst, is that the AI has said something so convincing that it's difficult to dispute its accuracy. Our clients have sent me such examples.

In contrast, programmers audit traditional POS system reports, which are based directly on actual transaction data and clients' stated needs. It provides you with focused information on the real needs of the business and greater reliability for informed business decisions. An example is a report generated by an AI system, Perlexity, that incorrectly identified a non-existent sales trend a newsagent sent me. If the newsagent had listened to it, they would have ordered a lot of unsellable stock.

Local Market Dynamics

AI systems often lack a sophisticated understanding of local market conditions, regulatory requirements, and cultural factors that significantly impact Australian retail operations. This limitation becomes evident when AI tools recommend a strategy to one of our clients based on an American holiday or season that is of minor significance in Australia. A classic example, which I recently discussed here, was a gardening tip from the US, where the seasons are reversed. An excellent tip for gardening in spring is of little use to an Australian retailer in autumn. 

When you ask an AI for advice, you have, like any other advisor, to tell it of what we call localisation issues that your shop faces. For example, say you are a pet supplier. There is a significant difference in the advice someone would give you if you are a large retailer with a small department for pet supplies or a small business exclusive pet retailer. Before asking for advice, specify as much as possible; for example, it's better to say, rather than

"What can you tell me I should do based on this information?"

say

"My Pet Shop is in the Dingley Village Shopping Centre, which is a well-established neighbourhood retail hub anchored by Woolworths, which generates steady daily foot traffic and creates strong cross-shopping opportunities for specialty stores like my pet shop. The centre's tenant mix is focused on essential services, making it resilient to economic fluctuations and attractive to the local community, which is characterised by above-average incomes and a family-oriented demographic. While Woolworths' in-store pet section, internet and nearby major pet chains present direct competition, the centre's strong local customer base and consistent visitor flow provide a solid foundation for us.

Now, what can you tell me based on the information from my POS System that I am giving you now?"

I find using AI to create such a summary works well. Once you have it store this description as you will often need it once you start analysing with AI. Many AIs allow you to make a character for your shop. I will discuss this more in another post.

The information you get now is much more relevant.

Transparency of the advice

Due to the way AI operates, it's often impossible to follow the reasoning. We call it a "Black Box". We know what we put in, and we see what we get out, but how does it go from in to out? Most of us, if we do not understand the logic, are reluctant to use it, and with the hallucination issue, it may be dangerous to follow its advice.

Historical Patterns

What I love about AI is that it's terrific at finding incredible patterns in your information. Still, it can struggle to adapt quickly to sudden market changes or unprecedented events that it is not aware of. Retail markets often change rapidly, requiring immediate strategic adjustments.

What you need to do here is tell the AI when this happens.

"redo as what you should have taken into account ....blaa blaa blaa........".

Like any advisor, you often need to give them another go if they get it wrong.

AI often requires multiple attempts to achieve satisfactory results.

Technical Implementation and Operational Requirements

Successfully utilising AI analytics for POS data requires some practice to build up your technical expertise. It's not hard, but like most things, it does take some practice. The more you use it, the better results you will get and the more you will get out of it.

Please, based on my experience, the most reliable way to feed your POS data into an AI tool is by exporting reports as Excel or CSV files. Excel is better, but some AIs do not like it. If so, use CSV. Both provide a standardised format that the AI is designed to process. When you supply your information, do not simply import your existing reports to get quality insights. The less you ask the AI to guess, the better.

Creating an Excel or CSV file is simple in our POS System. From any report, press the red arrow.

However, most POS Systems can export your reports into Excel or CSV.

Use Excel or CSV, not the report, which often invites trouble. 

Actionable information

Having extensive volumes of information is rarely much use; what we need are actionable insights. Many experience that when this happens, paralysis reduces decision-making efficiency rather than enhancing it. What I suggest you do is, if the AI does this, ask it, "What actionable steps that directly support our business objectives and operational improvements can you make from this?"

The Essential Role of Your Expertise

For AI today, human judgment is essential. It's your business, your livelihood and ultimately your decision. It's crucial to double-check before making business decisions.

How to use AI for Retail

The key to successful AI implementation lies in viewing its limitations as opportunities for strategic improvement. Retailers who set realistic expectations and thoroughly validate can gain advantages while ensuring operational reliability.

AI is brilliant, but you need to be thinking too.

Written by:

Bernard Zimmermann is the founding director of POS Solutions, a leading point-of-sale system company with 45 years of industry experience, now retired and seeking new opportunities. He consults with various organisations, from small businesses to large retailers and government institutions. Bernard is passionate about helping companies optimise their operations through innovative POS technology and enabling seamless customer experiences through effective software solutions.

Today, it is said that integrating Artificial Intelligence (AI) into financial reporting processes has enhanced the quality of financial reports by significantly improving accuracy, timeliness, transparency, and compliance and has much promise for SMB Businesses that cannot afford a full-time accountant. However, when we tested AI on financial reports here, we found many errors. Others who followed our advice and duplicated what we did told us it was beneficial, but they picked up several errors.

AI-powered financial report generators rapidly transform how many Australian retailers approach accounting, reporting, and business analysis. As these technologies have become accessible and affordable, many SMB Business owners are increasingly looking into them to cut costs and give them better and more intelligent decision-making. However, the critical question remains: How accurate and reliable are these AI financial reporting tools in real-world retail scenarios? This review thoroughly assesses different AI models, drawing on our independent research and real-world testing to help you make informed decisions for your business.

The Importance of Reliable Financial Reporting in Retail

Financial reporting is a compliance requirement for many retailers, but should be the backbone of sound business management. That is what it is designed to do. Financial reports can help with inventory planning, cash flow forecasting, and business decisions. However, even minor errors can lead to problems. The quality of the information here is critical.

In-Depth Analysis: How Each AI Financial Report Generator Performs

Now, we fed the six models listed below with unaudited reports of two years of financial statements and asked them to assess the company's financial position. A discussion of the test done is here. We will soon test using the reports in our POS to integrate into the financial reports. 

Here, what we are trying to assess is

How well did each AI do at pointing out errors

This is important as if you can correct the figures before giving them to the accountant, you can save them a lot of work. Save them a few hours that could save you a thousand dollars off your accounting bill. AI error reduction is a big plus.

The errors in the AI

The biggest problem with AI today is that it will produce errors. Most of these errors are classed as hallucinations; a better description is going off track. Some AI promoters claim that their system does not suffer from this, but I do not believe them. Humans make mistakes; AI makes mistakes. Neither humans nor AI are infallible. With today's technology, human oversight remains essential.

Grok

From this perspective, Grok emerged as a leader in AI financial report generators. After reviewing the figures, we gave the data a precision rate of 97%. Grok was particularly effective at identifying business risks and discrepancies, such as figure mismatches and unusual reporting patterns. However, it did not always flag significant structural errors, such as negative liabilities in the books and misclassifying a loan. For accuracy, Grok was the best.

Google’s AI

Google’s AI tools are widely known and used for financial reporting. I think you will find it the easiest to use. Its accuracy was good; we gave it a 95% data precision rate. I was not too happy with some of its tax advice. We liked that it explicitly called out odd liability presentations and discrepancies. Maybe it could have beaten Grok if we had corrected that, fed it back in, and redid the report.

Claude

Claude, we gave it a 93% data precision rate. Claude missed some critical errors in liabilities and equity and did not flag many errors, all of which could mislead SMB business owners.

ChatGPT

ChatGPT was unexpected, as we had read an academic research paper showing it was better than human analysts in financial statement analysis. That may be true, but in our tests, it scored 85% in data precision. Interesting for something highly thought of after it made some structural accounting errors. It did not flag anything as an error.

Qwen

Qwen is designed for enterprise applications, not SMB businesses, and we found it had an 83% data precision. It lacked precision in ratio calculations and left an incomplete reconciliation between the trial balance and profit and loss statements. We are not sure if it is programmed well with Australian accounting standards.

DeepSeek

DeepSeek is a favourite now as it's so cheap. It got 80% data precision. I suppose you pay for what you get here.

Common Pitfalls and What Retailers Should Watch For

Across all models, the most common errors flagged included data inconsistencies, business risks like revenue decline, and fundamental reconciliation issues. However, even the top performers tended to miss or underplay critical structural errors such as negative liability balances, misclassified loans, and negative opening equity. These are significant issues for retailers, as they can lead to unreliable reports and poor decision-making if not addressed.

Conclusion: Choosing the Right AI Financial Report Generator for Your Retail Business

The comparative analysis shows that while AI financial report generators are advancing rapidly, none are flawless. Grok and Google’s AI currently offer the highest accuracy for retail financial reporting, but even these leaders require human oversight to catch critical errors. Still, by alerting the owner to mistakes in their books, both Grok and Google AI could have saved about a thousand dollars in accounting costs.

Best Practices for SMB Retailers Using AI Financial Tools

I recommend that SMB retailers conduct quarterly financial analyses using these AI tools, export data from their accounting software (e.g., MYOB and QuickBooks), and review AI-generated reports for trends, risks, and recommendations.

We suggest combining outputs from multiple AI models (as we did) and merging their reports for a more robust analysis.

Learn how to review these AI outputs.

I am sure doing this can provide you with timely business insights.

Written by:

Bernard Zimmermann is the founding director at POS Solutions, a leading point-of-sale system company with 45 years of industry experience. He consults to various organisations, from small businesses to large retailers and government institutions. Bernard is passionate about helping companies optimise their operations through innovative POS technology and enabling seamless customer experiences through effective software solutions.

Many small and medium-sized retailers across Australia operate without the benefit of a dedicated accountant. It is an everyday reality, with most relying on periodic check-ins with external advisors rather than having in-house financial expertise. As a result, regular strategic analysis of financial reports can fall by the wayside, leaving business owners at a disadvantage when making timely, data-driven decisions. With the rapid advancement of AI financial analysis tools, a pressing question has emerged: Can artificial intelligence reliably analyse SMB financial reports and deliver the kind of actionable business insights that drive retail success?

It emerged in a recent meeting with several clients, many of whom look to us as leaders in AI technology for retail in our market space. A big question arose: How good is AI at analysing financial reports for SMB retailers? The reality is that most small retailers in Australia don't have a permanent accountant. Unlike large organisations with in-house finance teams, most SMBs only catch up with their accountant once a year, which puts them at a disadvantage regarding regular, data-driven business decisions. Many would like an accountant to review their figures and give some advice, but time and financial considerations are real.

To answer this question, we undertook a practical experiment to reflect Australian retailers' real-world challenges. The aim was to determine whether today's leading AI accounting tools could step in where regular financial analysis is often lacking, especially for businesses using platforms like MYOB or QuickBooks.

Could AI deliver the financial insight needed without an accountant by drawing on real-world testing and current best practices in retail financial management in SMB retailing?

Our Test Methodology

Here's how we structured the test to ensure it was fair, practical, and relevant to everyday retail operations:

Reports Provided:

We used real-world reports from MYOB or QuickBooks, which had errors and inconsistencies you'd expect from an SMB business without a trained bookkeeper. So we used their data, and we ran for two years.

Profit and Loss Statement

Balance Sheet

Trial Balance

Then put them into a single PDF

Our prompt

After refining our approach through multiple iterations, we developed a comprehensive prompt for the AI platforms.

The test

The Free AI Landscape

Like so much in the world, not all AI tools are equal; some are better than others, and each has account limitations. So we tested six popular tools to the maximum the free version allowed. 

ChatGPT (OpenAI)

Claude (Anthropic)

DeepSeek

Google AI

Grok 3

Qwen

Evaluation Criteria for AI Tool Performance

Now, we know that all of them are good, but there is always a case where even the best six runners in the world have one who is better, and that is what we wanted to find out: the best free AI for retailers.

When running the report, we put the best possible model on the highest free level.

Scoring the AI Performance

To objectively compare the AI-generated reports, we implemented a 100-point scoring system based on:

Overall Business Health: Did the AI assess the company's financial position accurately?

Trend Analysis: How well did it identify the direction of the company?

Key Performance Insights: Did it break down revenue, profitability, cash flow, and operational efficiency?

Problem and Risk Assessment: Could it pinpoint areas requiring attention and highlight potential risks?

Actionable Recommendations: Were the suggestions practical, relevant, and implementable?

Communication and Usability: Was the report easy to understand and follow?

Error Handling: Did the AI flag data inconsistencies and avoid being misled by errors?

Scoring Guidelines:

Now, we had a grading system that was

90–100: Exceptional Business Insight

80–89 Strong Business Analysis

70–79 Adequate Assessment

60–69 Poor Business Assessment

Below 60 Fail

Detailed results by AI

Claude

Score: 88/100 — Strong Business Analysis

Overall Business Health (23/25):

• Gave a clear, accurate summary: highlighted a 10.2% revenue decline and a 30.4% net income drop,
• Balanced strengths (identified a strong balance sheet with concerns on the company's shrinking revenue

Trend Analysis (9/10):

• Nailed the year-over-year trend, contextualising declines and highlighting the need for urgent action.

Key Performance Insights (27/30):

• Broke down revenue by segment
• Noted labour revenue decline (-15%)
• Analysed gross margins, which are up, and net margin, which was down
• Flagged cash and inventory issues

Problem & Risk Assessment (18/20):

• Prioritised risks: liquidity constraints, inventory overstock, and bad debts
• Could have expanded on market/competitive risks.

Strategic Recommendations (17/20):

• Practical advice: weekly cash flow monitoring, inventory optimisation, service diversification.
• It suggested digital transformation and market expansion, but it should have gone deeper into a long-term strategy.

Communication & Usability (3/5):

• Well-structured, logical, but dense—could be more concise for busy owners.

Error Handling:

• +3 bonus for flagging data quality issues without losing focus.

Summary:
Claude delivered a highly detailed, data-driven report with actionable advice, only let down by its length and slightly dense style.

Google

Score: 85/100 — Strong Business Analysis

Overall Business Health (22/25):

• Clear on declining health
• Balanced positives (profitability) with concerns (liquidity, inventory).

Trend Analysis (9/10):

• Strong in historical context, less predictive about future trends.

Key Performance Insights (26/30):

• Detailed on revenue declines and margin shifts.
• Flagged inventory days (752 days in FY24) are a significant concern.
• Some working capital ratios were missed due to data presentation.

Problem & Risk Assessment (17/20):

• Identified key risks: revenue drop, inventory build-up, and bad debts.
• Could have ranked risks more sharply.

Strategic Recommendations (16/20):

• Practical calls for inventory reduction and credit control.
• Some recommendations (like scenario planning) were less actionable.

Communication & Usability (4/5):

• Clear, structured, and accessible.

Error Handling:

• +3 bonus for handling data inconsistencies without losing the thread.

Summary:
Google's report was well-organised, with strong practical recommendations and a solid structure, though its strategic vision could have been more forward-looking and detailed.

Grok

Score: 82/100 — Strong Business Analysis

Overall Business Health (21/25):

• Accurate on decline (revenue -10.2%, net income -30.4%), but less specific in some areas.

Trend Analysis (9/10):

• The downward trend was correctly identified, but the future outlook was generic.

Key Performance Insights (25/30):

• Covered revenue and margin declines, but not as deep on drivers.
• Noted liquidity and inventory issues, but lacked much information about working capital, something essential in SMB retailing.

Problem & Risk Assessment (16/20):

• Flagged revenue and liquidity risks, but prioritisation was vague.

Strategic Recommendations (16/20):

• Practical advice on cash flow and inventory, but lacked specificity.

Communication & Usability (4/5):

• Well-structured and clear.

Error Handling:

• +2 bonus for addressing data quality without overemphasis.

Summary:
Grok produced a solid, readable report with reasonable recommendations, though it lacked the detail and strategic sharpness seen in others.

DeepSeek

Score: 80/100 — Strong Business Analysis

Overall Business Health (20/25):

• Clear on decline (revenue -10.2%, net income -30.4%), noted equity growth (+10.9%).

Trend Analysis (8/10):

• A downward trend was identified, but the future outlook was general.

Key Performance Insights (24/30):

• Evaluated revenue decline, solid on margins, but less on specific drivers and operational ratios.

Problem & Risk Assessment (16/20):

• Flagged revenue and liquidity risks, but didn't rank them by impact.

Strategic Recommendations (16/20):

• Practical but broad suggestions.

Communication & Usability (4/5):

• Well-organised and clear.

Error Handling:

• +2 bonus for noting data inconsistencies without overemphasis.

Summary:
DeepSeek gave a firm overview and reasonable recommendations but lacked specificity and depth.

5. Qwen

Score: 75/100 — Adequate Assessment

Overall Business Health (18/25):

• Provided a basic overview but made a significant data error by misstating one department's growth.

Trend Analysis (8/10):

• A downward trend was noted, but the analysis was surface-level.

Key Performance Insights (22/30):

• Missed key revenue drivers and superficial operational analysis.

Problem & Risk Assessment (15/20):

• Identified issues but lacked nuance.

Strategic Recommendations (15/20):

• Practical, but generic and not innovative.

Communication & Usability (5/5):

• Clear and concise.

Error Handling:

• -5 penalty for data misinterpretation.

Summary:
Qwen's report was easy to read but was undermined by errors and a lack of depth.

6. ChatGPT

Score: 78/100 — Adequate Assessment

Overall Business Health (19/25):

• Summarised the decline, but used rounded numbers, which caused it to lack precision.

Trend Analysis (8/10):

• A downward trend was noted, but the analysis was fundamental.

Key Performance Insights (23/30):

• Reasonable on revenue and margins, but lacked detail and segment analysis.

Problem & Risk Assessment (16/20):

• Flagged liquidity and inventory risks but didn't assess the impact.

Strategic Recommendations (16/20):

• Practical, but generic.

Communication & Usability (4/5):

• Clear but slightly verbose.

Error Handling:

• No bonus or penalty.

Summary:

ChatGPT produced a basic, readable report with reasonable recommendations but lacked the depth and precision needed.

What This Means for SMB Retailers

The findings are encouraging. AI financial analysis tools have reached a level that can genuinely support SMB retailers in understanding their business performance. Even when presented with imperfect data, the best AI platforms can identify significant risks and opportunities and offer valuable insights.

The top performers, Claude and Google, delivered strong, actionable business analysis. These platforms identified critical risks, such as declining revenue and tightening cash flow, and offered practical recommendations that retailers could implement immediately.

Claude's report was the best. It provided clear summaries and highlighted both strengths and concerns. Its recommendations focused on weekly cash flow monitoring, inventory optimisation, and service diversification.

Google's analysis was well-structured and accessible. It balanced a clear-eyed view of business health with practical calls for inventory reduction and tighter credit control. While its strategic outlook could be more forward-looking, it handled inconsistencies in the data with confidence.

The others were adequate, and they all could do the job.

My Expert Commentary

As someone with deep experience in retail and POS systems, I believe these developments are a genuine opportunity for SMB retailers. AI tools do not substitute for expert advice; we did notice that not one AI produced what we would call an exceptional report; however, they significantly assist those lacking regular access to accountants. The capacity to conduct thorough financial analyses in minutes, utilising data exported directly from accounting software can revolutionises strategic planning and daily operations.

This AI-driven financial analysis empowers retailers to identify emerging trends before they escalate into critical issues, help make informed decisions regarding pricing, inventory, and supplier management, identify areas for improving operational efficiency and to concentrate on the most essential metrics: cash flow, profit margins, and stock turnover.

My Professional Recommendation

I strongly recommend that every SMB retailer in Australia conduct a serious financial analysis at least once a quarter using these AI tools. Here's how you can do it:

1. Export your financials (P&L, Balance Sheet, Trial Balance) from your accounting software.
2. Feed them into a top-rated AI; I suggest Claude or Google with the prompt above.
3. Review the AI's report for trends, risks, and recommendations.
4. Act on the insights
5. Repeat this analysis at least quarterly. Regular reviews can let you adapt quickly to changing business conditions.

If you need help setting this up, reach out for a chat. If there is enough interest, I will do a webinar.

Written by:

Bernard Zimmermann is the founding director at POS Solutions, a leading point-of-sale system company with 45 years of industry experience. He consults to various organisations, from small businesses to large retailers and government institutions. Bernard is passionate about helping companies optimise their operations through innovative POS technology and enabling seamless customer experiences through effective software solutions.

Today, AI-driven POS Systems are revolutionising the information flow to retailers. AI reporting offers advanced analytics and predictive insights compared to traditional POS system reporting. I love its ability to allow users to ask questions and research topics, enabling us to make more informed business decisions. Train your model with your information, and ask questions. If you do not understand something, you can ask for more information. It is brilliant. If anyone wants to attend a webinar on these functions, let me know.

While AI-powered analytics often deliver revolutionary insights, most users usually do not need them. Many retailers find that traditional POS reporting provides the information required for day-to-day business operations, which remains today's cornerstone of retail reporting.

The Trust Advantage of POS System Reporting

In business, POS systems have been refined over the decades, offering reporting functionality that captures actual transactions. Almost all errors have been worked out of the system, so retailers can confidently use this information to make business decisions.

The challenge with AI reporting systems lies in "hallucinations". These occur when the AI often generates plausible but factually incorrect information. Recent evaluations of advanced AI systems indicate hallucination rates of about 1.1% on simple tasks, and I have seen figures of 30-50% in complex tasks reported. What happens is that the AI, when asking your question, goes off track. It then moves along this track into nonsense. What is dangerous is that sometimes it appears plausible and can be hard to spot. It creates significant risks for retailers who might make substantial decisions based on inaccurate analysis. While doing a study, a pet shop retailer in Brisbane considered increasing its stock levels in dog toys based on an AI report trend. That trend did not exist. If they had followed it, they could have brought much excess inventory. Luckily, they picked it up. By contrast, when a POS system shows a 24-month history of a product sold, that figure represents a real figure.

Operational Speed and Accessibility

Timing becomes critical in retail environments where rapid decision-making directly affects sales outcomes. Our modern POS systems generate comprehensive reports within seconds for free. The system does not require an internet connection or an AI subscription.

Industry-Specific Relevance for Australian Retail

POS systems are designed specifically for retail operations. It incorporates Australian terminology and KPIs that align directly with Australian business practices. Standard POS reports include daily sales summaries, staff performance metrics, inventory turnover rates, and GST calculations, all of which conform to Australian requirements. An AI report, while powerful, often struggles with Australian-specific requirements. We have noticed that an AI analysis usually uses international accounting terminology that requires translation. When doing the report, we must do Google searches to determine what is being said. I have discussed this problem in depth here when we ran 100s of AI reports. 

Security and Compliance for Australian Businesses

We have a big problem here, as much of the information in your POS System is restricted. For example, in Australia, we have strict privacy laws. Your POS systems incorporate security features specifically designed for this retail environment. These security measures have evolved over many years and are focused on retail-specific security requirements. Using AI for business reporting typically involves transmitting all your business data to third-party cloud services, raising concerns regarding data storage locations, retention policies, and potential use of proprietary business information. More dangerous is that all your information can be accessed by people in your organisation. Its hard to restrict parts of your payroll information so some of your staff might get what others earn. 

Transparency in Reporting Methodology

When a POS system identifies top-selling products, the calculation methods are transparent and verifiable. You can do the calculation manually to figure out how it works. If the results appear unusual, you can easily check the report. This transparency builds confidence in the process.

AI-generated reports generally suffer from what we call "the black box problem." We get a result, but no one knows the reasoning behind its recommendations, making it difficult for anyone to understand the findings.

Consistent Reporting Over Time

POS reporting remains consistent over time. Once a retailer masters it, they know how to use it, what it gives them, and how to make meaningful comparisons over time.

AI systems face challenges with what we call "model drift." When you do the same thing, use the same prompts, you probably get different responses, each run of a report gives a different answer.Each run is an experiment. 

When to Use Each Reporting Type

The clear advantages of traditional POS reporting for day-to-day retail operations, POS reporting excels in managing daily operations, staff performance evaluation, inventory control, cash flow monitoring, tax compliance, and comparative performance analysis. These functions form the operational backbone of Australian retail businesses.

I like to think of AI reporting as going to see an expert. They often have great knowledge in a particular area of your business and can help you examine the situation. They can tell you about subtle patterns in the industry and what is likely to happen, giving you insights, but you need to be very careful about accepting their advice without further thought. What we love is its ability to allow you to ask questions and explore.

Implementation Recommendations for Australian Retailers

For Australian retailers considering their reporting, you need a robust POS System that provides the fundamental business metrics.

When evaluating AI tools, take their advice with a grain of salt. We expect that in ten years, AI reporting will take over, but not yet. We are all experimenting with it. Its a lot of fun but think of it as science experiment.

Written by:

Bernard Zimmermann is the founding director at POS Solutions, a leading point-of-sale system company with 45 years of industry experience. He consults to various organisations, from small businesses to large retailers and government institutions. Bernard is passionate about helping companies optimise their operations through innovative POS technology and enabling seamless customer experiences through effective software solutions.

One of AI's great promises is to take data and produce advanced information. The problem is that today, we have too much information that is hard to process; it's just too much. So, let's see what happens when we take real point-of-sale software data and put this promise to the test.

So, we decided to test the AI's understanding of a typical SMB retail shop from its customer's sales report. Knowing your customers is essential for retail success, and we will check whether an AI customer data analysis can help us make informed decisions about them.

The added question is which free AI tools can perform this task most effectively. Only a few SMB retailers have paid accounts for AI ChatBots, so we decided to restrict our tests to the free version. As you will see, we immediately ran into problems with this during this test.

Okay, let's test that and see.

Our Test

We have already established a comprehensive evaluation process to determine which AI systems deliver the most actionable insights here.

So, we challenged six leading free AI systems to analyse real customer sales performance data from 2023 and 2024.

Each AI system received identical instructions: "Using data from the attached CSV files, analyse and compare sales performance and visit frequency for top customers in an Australian Newsagency between 2023 and 2024. Identify key changes in behaviour for the highest-value customers."

For a fair assessment, we evaluated each system's customer analysis report using nine key performance indicators and scored out of 10:

Evaluation Framework

Quality of Information

How accurate was the data presented about customer behaviour and trends? If it's not correct, it's worse than useless.

Usefulness

Do these insights improve a retail business? We do not need useless information.

Clarity

Was the analysis presented straightforwardly and clearly?

Actionability

Did the report provide clear, implementable recommendations?

Accuracy

Were the calculations and conclusions drawn from the data correct? AI is known for giving wrong results. This is a common problem of AIs.

Adaptability

Did the analysis take into account specific retail contexts and customer demographics?

Depth of Analysis

Did the report go beyond surface-level observations to uncover meaningful patterns?

Creativity

Were there innovative suggestions for addressing the identified changes in customer behaviour?

Customer-Centric Approach

Did the analysis effectively segment customers and provide tailored approaches?

Testing Limitations

Unlike our pricing study, we encountered several practical limitations with free AI access immediately:

Claude and Chatgpt required paid accounts to process our instructions, so they failed the free test. However, as they are very important AI chatbots, we decided to test them with our paid accounts, but they failed immediately.

QWEN would only process our prompt by editing it in the window's notebook, so we had to redo the tests with consolidated data. Doing this with QWEN requires some computer skills, which others do not need. We marked it down for this.

All the other AI systems could process our request without issue using their free tier offerings.

Immediately, we saw that when we analysed the solutions, not all of them offered the same ability.

Results Summary

The performance rankings revealed interesting shifts from our previous pricing analysis:

Interestingly, while Google AI topped our previous pricing study, it ranked last for customer analysis.

Detailed Analysis of Each AI Tool

ChatGPT (Score: 78/90)

On the paid version, and I stress the paid-only

Strengths

• We thought it showed exceptional clarity. The report was well-organised, with sections in a logical progression We liked its innovative customer segmentation framework, which includes categories like "Growth Champions" and "Frequent Shoppers."
• We all liked its analysis and felt it was comprehensive
• What we liked was its tailored recommendations for different customer segments

Problems

• There was nothing we thought was innovative, but it worked by the rules. It ignored the location, that we were in Australia, and the same problem we had in the previous test.

Overall

ChatGPT transformed customer data into strategically actionable segments that you can use in your marketing and sales approaches. It saved time but gave us little originality.

Grok (Score: 68/90)

Since it's now free, this is a brilliant AI. You should be delighted with it.

Strengths

• We notice that it is outstanding in its accuracy and attention to detail
• The report was an in-depth and comprehensive analysis
• We liked its comparative analysis of individual customers
• It came up with a category, and we liked the emerging high-value customers

Problems

• We thought that most of the insights were limited in actionability; it's nice to know something, but what is the point of telling us if you cannot use it?
• Also limited in creative solutions
• The report sections did not follow a logical order.

Overall

Grok provided an excellent analysis and identified some subtle patterns in customer behaviour. It would be good to investigate why, though you'll need to develop action plans based on its findings.

DEEPSEEK (Score: 67/90)

Strengths

• Excellent formatting and visual emphasis that make your information accessible
• We liked that it had specific, implementable recommendations tied to analysis findings.
• It was accurate in its data presentation, with correctly identified trends
• Effective customer segmentation approaches

Problems

• Did not give a detailed customer-by-customer examination
• Not that good in a specific Australian retail context
• Recommendations were sound but somewhat conventional

Overall

DEEPSEEK struck a good balance between analytical depth and practical recommendations.

QWEN (Score: 66/90)

Do not underestimate this AI. The only reason it did not win was that it required some advanced computer skills to use. It was not just a simple matter of using it. 

Strengths

• We liked its brevity, which offered highly actionable recommendations
• We liked its concise format, clear headings and bullet points
• It provided good creative thinking in recommendations for improving customer visits
• We liked its suggestion for improving a loyalty program and bundling.

Problems

Small report: Now, this may not be a problem for you. Some of us liked that it produced a good condensed report. They felt they did not want a book; the quicker it could be said, the better. I disagreed; I wanted to know as much as possible. Let me know your thoughts on this below. We thought it didn't consider that we were talking about retail.

Overall

Many people like QWEN's concise, action-oriented approach, which provides quick and practical guidance without requiring extensive analysis.

Claude (Score: 59/90)

It was a paid version, yet its score was bad. You expect it to be better if you pay, but you don't get what you pay for with AI.

Strengths

• It provided accurate data analysis throughout
• We did like its breakdowns of top customers and their performance changes
• It had clear section headings and a well-organised structure
• It identified key account growth opportunities
• It also identified at-risk relationships

Problems

• Overall, it lacked specific implementation strategies
• The segmentation of customer types was bad.
• Again, as with some others, not much is known about Australian retail
• Report sections varied in detail

Overall

Claude was solid but struggled to translate those insights into tailored, implementable recommendations.

Google AI (Score: 55/90)

Now, Google AI is a good AI. Last time, it came out the best, but here, it's the worst. Google changed the free version because it wants you to switch to the paid version.

Strengths

• Methodical approach to analysis
• Accurate calculations
• We thought that it produced logically sound conclusions
• It considered many factors

Problems

• It presented an analysis without any specific recommendations
• Little creative
• Minimal segmentation of customer types
• Limited adaptation to retail

Overall

The free Google AI fell short of providing the strategic interpretation and actionable guidance that retailers need.

Key Findings and Implications for Your Retail Business

Our evaluation revealed several important considerations for using AI:

Different tools excel at different retail tasks

It's all good to analyse, but an ideal AI solution should connect the dots between "what's happening," "why it's happening," and, most importantly, "what to do about it." Not all AI ChatBots are equal.

The significant shift in rankings between our pricing study, where Google AI dominated, and this customer analysis evaluation highlights the critical point that AI is not a one-size-fits-all approach. It also showed that suppliers are moving to a user-paid model.

Usability

Busy retailers need an AI that produces a clear organisation and logical flow.

Practical Recommendations for Australian Retailers

Your specific need

The reality is that different AI systems excel at other tasks. There's no way around it; you need to test which one works better in your circumstances.

Prioritise actionability

Choose AI marketing tools that connect analysis to specific actions you can take. Ask yourself: "What can I do tomorrow based on this information?" If the answer isn't clear, the tool may not be right for your needs.

Provide detailed context

We tested with more specific information about a business, location, and customer base. We did get better results, but that's outside of this test. I would include such information if I were doing it in a shop. Don't assume the AI knows your business environment; even if it does, it can use it.

Verify findings

We found that AI made errors and provided advice that didn't align with business reality. Always check.

Continue with a focused question.

These reports should be considered the start of your analysis. To get more insights, I would ask specific questions about the customer, the segments, loyalty patterns, or purchase frequency. For example, "Which customers decreased their visit frequency in the last quarter?" will yield more actionable results than "Analyse my customers."

Integrating AI Insights with Your POS System

For retailers using our POS systems, connecting AI analysis has tremendous potential. Exporting customer sales data in formats your AI can analyse is easy; you can do this in the report section. I will discuss this in a future post.

The Future of AI

This evaluation demonstrates that AI tools have already reached impressive capabilities. Using them, you can get free access to dedicated data analysts. They offer you access to sophisticated insights previously available only to large organisations.

My thoughts

While it's free, I recommend looking at Grok, our winner.

Written by:

Bernard Zimmermann is the founding director at POS Solutions, a leading point-of-sale system company with 45 years of industry experience. He consults to various organisations, from small businesses to large retailers and government institutions. Bernard is passionate about helping companies optimise their operations through innovative POS technology and enabling seamless customer experiences through effective software solutions.

A point-of-sale (POS) system allows your business to accept customer payments, track sales, and manage the shop.

The POS System

Hardware: The Physical Backbone

Every POS system includes hardware components that facilitate transactions. Common examples include:

• Terminals: Countertop units or mobile tablets are used to process sales.
• Barcode Scanners: Quickly identify products and prices.
• Receipt Printers: Generate paper or digital receipts for customers.
• Cash Drawers: Secure storage for cash transactions.
• EFTPOS Machines: Widely used in Australia to process card payments efficiently.

Software: The Brains of the Operation

The software component powers the functionality of a POS system:

Sales Processing

Inventory Control

Tracks stock in real time. This enables retailers to monitor their stock.

Customer Relationship Management (CRM)

Stores customer data to build loyalty programs.

Reporting and Analytics

Provides insights into sales trends and staff performance.

How POS Systems Transform Aussie Retail

Streamlined Operations

POS systems automate many manual tasks, allowing businesses to operate more efficiently:

• Automatically adjust stock levels after each sale.
• Generate detailed reports for financial tracking and decision-making.
• Process payments.

Data-Driven Decision Making

The POS management solution gives retailers information that helps them make better decisions:

• Identify top-selling products to optimise inventory.
• Identify dead stock. For example, a Melbourne newsagent discovered that 20% of his stock, using this insight from their POS system, was dead and not selling.
• Analyse peak trading hours for better staff scheduling.
• Track customer purchase behaviour to tailor promotions.

Enhanced Customer Experience

Modern POS systems improve the shopping experience by:

• Reducing queue times with faster checkouts.
• Offering personalised recommendations based on purchase history.
• Managing loyalty programs seamlessly.

Real-World Benefits from Our Users

The Future of POS in Australia

As we move forward, POS systems will become even more integral to retail success:

Omnichannel Integration

The shop will need to be connected to the internet

AI-Powered

AI is already investigating many aspects of the shop. We feed information from a POS System into AI to investigate improving shop layouts, inventory, marketing strategies, etc.

Cashless society

It is only a matter of time before Australia becomes a cashless society

Cryptocurrencies

With bank fees the way they are now, it is only a matter of time before we see a growing movement to crypto.

Conclusion: Empowering Australian Retail

A POS system is an investment in your future retail business.

Explore our top POS System, which has been used in thousands of stores Australia-wide for over 40 years.

Written by:

Bernard Zimmermann is the founding director at POS Solutions, a leading point-of-sale system company with 45 years of industry experience. He consults to various organisations, from small businesses to large retailers and government institutions. Bernard is passionate about helping companies optimise their operations through innovative POS technology and enabling seamless customer experiences through effective software solutions.

https://walterwrites.ai/

Update: I wrote this article a few weeks ago and was asked about the other free AI model, GWEN, that was recently released. So, I decided to test this one, too, and add it to the list. It's an excellent AI model. Also, for the sake of completeness, I decided to add Microsoft Copilot. So here is the updated list.

No one has talked about artificial intelligence (AI), and now it seems people are talking about little else. We have been actively involved in AI for several years now.

In retail, AI promises to boost sales and reduce operational costs in the POS system. Like everyone else in business, those leveraging AI will stay competitive in a rapidly evolving market. 

Comparison of AI Models

A good leaderboard of what AI models is available here.

But these are not measured on what our clients now use and the problems they encounter. So, to understand the current landscape of AI needs in retail, we compared several leading widely available AI models:

1) DeepSeek

2) Gemini

3) ChatGPT

4) Claude

5) Meta AI Facebook

6) Grok 2

7) GWEN

8) Microsoft Copilot

We tested these models on real-world scenarios that retailers encounter, such as product descriptions, inventory management, customer service, and sales forecasting. We then combined the answers, amended them by hand and came up with answers that we scored 40. We then compared each AI's answer to this score of 40. All of this took us a lot of work.

Our test results showed that Gemini (Google) was the top performer, scoring 39 out of 40. It also offered a comprehensive package with many additional benefits, making it an attractive choice for businesses seeking a robust AI-powered POS system.

Claude excelled in writing capabilities, scoring 37, which makes it most suitable for tasks requiring explicit and engaging content.

ChatGPT and Grok 2 scored 36, demonstrating their ability to handle various tasks effectively. What we liked about Grok 2's answers is that they contained advanced information on items the other AIs did not have. If, for example, a new game came out and you wanted to see what people thought about it, Grok 2 gave the best response. I cannot wait to see Grok 3, which is overdue now.

DeepSeek scored 35 despite being significantly cheaper. It offers impressive performance at a fraction of the cost of other models, making it ideal for businesses requiring API access.

GWEN scored 34, which is a bit lower than Deepseek's, but like Deepseek, it is free. We weren't that impressed with what the AI model could achieve compared to the other models mentioned; it also lacks an API, which could lead to issues in usage.

Microsoft Copilot scored 32, but like Deepseek, it is free and integrates well into Microsoft products that many of my clients use. Again, we weren't impressed with what the AI model could achieve, but if you use Microsoft products, it fits well into the suite. 

However, Meta AI (Facebook) struggled, scoring only 30, but was still included in the assessment due to its potential in specific use cases. Overall, I would not recommend it as your primary AI.

Recommendations

Gemini is likely the best choice if cost is not a concern due to its superior performance and additional features. Google's support and integration capabilities make it an excellent solution for businesses seeking a comprehensive AI-powered system.

However, DeepSeek presents a compelling option for those prioritising cost-effectiveness. At only 2% of the cost of ChatGPT, it delivers nearly comparable results, making it an attractive choice for businesses requiring API access.

Grok 2 is particularly noteworthy, especially with its upcoming update. Its integration with X (Twitter) offers access to a vast source of real-time data, which can be invaluable for businesses that must stay informed about the latest trends and news.

AI in POS Systems: Promises

English and spelling

Not everyone is good at English with AI lousy spelling, and people with bad grammar can communicate in writing better. It also allows them to communicate better with non-English speakers.

Marketing material

AI can be successfully used to write marketing material. A client wanted to create fancy names for their lotto syndicate, so they used AI to help them.

Real-time Predictive Analytics

AI analyses sales data and market trends to forecast demand, helping businesses optimise and prepare for busy seasons. For example, a retailer can use AI to predict a surge in demand. As trends overseas tend to come first before they hit us, they can tell us where the market is going.

Personalised Marketing

AI could provide tailored recommendations and promotions based on customer purchase history and preferences, fostering loyalty and boosting sales.

Dynamic Pricing Optimisation

We like that it can better set prices in real time based on demand. Companies dealing with marketing events often have goods that sell well in that season, but the demand for the product collapses as soon as it's over. We are hoping AI can help us with this, too.

Implementation Challenges

Implementing AI in POS systems can present challenges. The answers are often not as good as they look. They are often wrong, and it's hard to argue with it because they look so right.

The future

It is unclear where the AI market is going. Will consumers want a low-budget or medium-budget, or are they prepared to pay for an expensive system? One company told me they spend $200/month on ChatGPT, which is $2,400 annually. Will the consumer bear that?

The other issue is whether a business needs a car or a truck in AI. In the context of retail POS systems, AI is not just about speed or luxury; it's about finding a solution that can handle the workload efficiently. Businesses need a reliable truck rather than a sports car to carry a heavy load rather than speed.

I am sure there are privacy issues, too. Some AIs are specially built with that in mind. But this all would involve a deeper discussion of data privacy, security, and compliance (such as GDPR or Australian privacy laws) beyond the scope of this post. 

Some industry research shows that over 70% of retailers plan to adopt AI within the next two years. I would not be surprised if it will be closer to 100% in one year, as AI can enhance competitiveness and drive growth.

FAQ: Frequently asked questions

Q: What is the role of AI in POS systems?

A: AI in POS systems promotes boosting operational efficiency.

Q: Which AI models were compared in our tests?

A: The models tested included DeepSeek, Gemini, ChatGPT, Claude, Meta AI (Facebook), and Grok 2. These were evaluated in real-world scenarios such as product descriptions, inventory management, customer service, and sales forecasting.

Q: What were the results of the AI model comparison?

A: Gemini (Google) scored the highest at 39 out of 40, offering a comprehensive package with additional benefits. Claude excelled in writing capabilities, scoring 37. ChatGPT and Grok 2 scored 36, while DeepSeek scored 35 despite being significantly cheaper. Meta AI (Facebook) scored 30.

Q: Which AI model is recommended for businesses with no budget constraints?

A: Gemini is likely the best choice due to its superior performance and additional features. Google's support and integration capabilities make it an excellent solution for comprehensive AI-powered systems.

Q: What about cost-effective options?

A: DeepSeek is a compelling choice for businesses prioritising cost-effectiveness. It offers impressive performance at a fraction of the cost of other models, making it ideal for those requiring API access.

Q: How does AI improve communication in retail?

A: AI helps individuals with limited English proficiency communicate more effectively in writing. It also facilitates better communication with non-English speakers.

Q: Can AI assist with marketing tasks?

A: AI can be used to write marketing material, such as creating product names or promotions. It can also help generate engaging content.

Q: What are the benefits of AI in predictive analytics and personalised marketing?

A: AI analyses sales data and market trends to predict demand, assisting businesses in preparing for peak seasons. It also offers personalised recommendations and promotions based on customers' purchasing history, enhancing loyalty and driving sales.

Q: What challenges are associated with implementing AI in POS systems?

A: Utilising AI can present challenges, such as ensuring the accuracy of AI-generated responses and integrating AI with existing systems. Additionally, although AI responses may seem correct, they can still contain errors.

Q: What does the future hold for AI in retail?

A: The future of AI in retail appears promising, as over 70% of retailers plan to adopt AI within the next two years.

Q: How does the analogy of a "truck" apply to AI in POS systems?

A: In retail POS systems, AI is not just about speed or luxury; it's about finding a solution that can handle the workload efficiently. Businesses need a reliable "truck" rather than a sports car to carry a heavy load effectively.

Q: Are there privacy concerns with AI in POS systems?

A: Yes, very much so. Some AI systems are claimed to be designed with privacy in mind. It remains an essential consideration for businesses implementing AI solutions.

Q: Is a POS system AI?

A: A POS system itself isn’t AI but can be integrated with AI to enhance its capabilities.

Update: The federal and SA governments have blocked access to DeepSeek over its network and directed public servants to stop using and remove it from devices. More details are available here. There are security concerns over the product. 
 

Artificial Intelligence (AI) is now revolutionising the retail industry. It is already changing how businesses operate and engage with customers. I have witnessed firsthand the increasing impact of AI on our retail sector. This article investigates how we anticipate the latest generation of AI solutions will transform the brick-and-mortar retail in Australia.

The retail landscape is evolving rapidly, with AI leading the charge. From inventory management to customer service, AI promises to provide solutions once deemed impossible. 

The Focus Engine: Our Early AI Solution

Almost three decades ago, we created an AI solution that transformed stock ordering for our users. Using the Focus Engine, this system has been a pillar of our service offering and has stood the test of time. No one has been able to match it in our market space.

Key features of the Focus Engine include:

• Widespread adoption: Thousands of our clients have used this solution, many in their daily operations; it is a testimony to its effectiveness and reliability.
• Cost-effective: We've always offered this powerful tool free of charge, making advanced AI accessible to all our users.
• Tailored for specific needs: The Focus Engine was designed to address particular challenges in stock order and excels in this specific domain.

The most telling indicator of the Focus Engine's success is the feedback we've received from our long-standing users. One particular comment I liked by one of our users when talking about the latest update:

"You can update it however you like. Just make sure that it gives the same figures after the update."

It's hard to beat a dedicated AI specially built for one task. However, it does speak volumes about the trust and reliance our clients place on the consistency and accuracy of our AI solution.

ChatGPT in Retail: Limitations and Challenges

Recently, some of our clients have been using ChatGPT. Unfortunately, in tests, its application in retail has revealed some significant limitations:

• Cost concerns: A significant problem with ChatGPT for many retailers is that it's "not particularly affordable." This poses a significant barrier, particularly for small—to medium-sized businesses operating on tight margins.
• Weaknesses in retail-specific issues: Although versatile, ChatGPT frequently encounters the many nuanced challenges unique to the retail sector in Australia. Most of its information is form overseas. 
• Mathematical limitations: One significant flaw of ChatGPT is its struggle with maths and arithmetic, which are essential for numerous retail operations.
• Pattern recognition methods: ChatGPT's strength resides in pattern recognition rather than actual computations, which can pose a significant drawback for retailers requiring precise calculations.

These limitations highlight why solutions like our Focus Engine, designed specifically for retail requirements, remain valuable even against the backdrop of broader AI advancements.

Enter DeepSeek: A Game-Changer in AI

The AI landscape is undergoing a seismic shift with the arrival of DeepSeek, a Chinese AI model shaking up the status quo. It's making waves in the industry, and here's why:

• Unparalleled speed: DeepSeek operates twice as fast as competitors like ChatGPT, allowing quicker response times and increased productivity.
• Cost-effectiveness: Perhaps most importantly for retailers, DeepSeek costs around a tenth of the price of its competitors, making advanced AI more accessible than ever.
• Comparable power: Despite its lower cost, DeepSeek boasts comparable power to the best commercially available AI models.

Here is a table I constructed to show the difference, in particular checkout the costs.

Why DeepSeek Matters for Retailers

DeepSeek's capabilities are particularly well-suited to the retail sector:

• Mathematical prowess: Unlike some general-purpose AI models such as ChatGPT, DeepSeek excels in mathematical problem-solving, a crucial skill for inventory management, pricing strategies, and financial forecasting.
• Improved efficiency: The combination of speed and accuracy means retailers can make decisions faster and more confidently.
• Cost-effective hardware requirements: DeepSeek is less reliant on expensive Nvidia microchips, allowing it to run on much cheaper equipment. It significantly lowers the barrier to entry for retailers looking to implement AI solutions.

These advantages are already impacting the tech industry. Nvidia, a major player in AI hardware, has lost nearly $1 trillion in market value, indicating a shift in the AI landscape. Moreover, DeepSeek's popularity is soaring, becoming "one of the most downloaded apps in the world".

The Open-Source Advantage

One of DeepSeek's most significant features is that it's the "only powerful AI model in Open-source". This open-source nature brings several benefits:

• Public preference: Users and developers alike prefer open systems. They like to know that the systems they use are open for inspection.
• Wider deployment and development: An open-source model allows for broader deployment and faster development of new applications and improvements as developers can see what it is doing.

Speed and Processing Power

DeepSeek's high processing speed makes it particularly suitable for businesses that require quick, real-time decision-making - a common need in the fast-paced retail environment. No one wants to wait unnecessarily.

Privacy and Security Considerations

While DeepSeek offers many advantages, it's essential to address our privacy concerns:

There are worries about the Chinese government's potential data access. It is also an issue with most AIs, as wherever they are hosted, there is a government with potential data access.

Running DeepSeek locally can mitigate some of these concerns. For those concerned about data privacy, I recommend using DeepSeek "for personal or exploratory use only."

The Bigger Picture: AI Industry Disruption

DeepSeek's emergence is more than just a new product launch; it represents a significant shift in the AI industry:

• It challenges US dominance in AI development.
• It positions China as a strong competitor in the global AI race.
• This competition will drive further innovation and development in AI technologies.

Current Limitations and Strengths

While DeepSeek is powerful, it's essential to understand its current position:

• It is only text-based tasks.
• Its focus on these areas means it can provide better-targeted, efficient solutions for many retail operations.
• Its maths and arithmetic are better, but it does make plenty of mistakes.

Looking Ahead with its Cost-Effective AI retail solutions

The emergence of DeepSeek and similar AI models is set to revolutionise the retail industry. We predict that many more AI models will soon copy its approach, making AI increasingly more cost-efficient and accessible. This democratisation of AI technology levels the playing field, allowing smaller businesses to compete with larger retailers in terms of AI-driven capabilities.

Despite these advancements, there's uncertainty about fully leveraging generative AI capabilities in practical applications. However, the potential benefits for retailers are significant:

Enhanced Customer Experience

AI can dramatically improve customer interactions and satisfaction:

• Provide personalised shopping experiences with 24/7 customer support, handling inquiries and potentially leading to simple transactions.
• Use AI-powered recommendation engines to offer tailored product suggestions, mimicking the personalised service of knowledgeable salespeople.

Improved Inventory Management

AI can revolutionise how retailers manage their stock, particularly in predicting demand fluctuations, automating inventory management, reducing waste, and ensuring popular items remain in stock.

Marketing Optimisation

AI tools can significantly enhance marketing efforts:

• Target ideal customers more effectively, maximising marketing ROI.
• Analyse market trends and competitor pricing to optimise pricing strategies.
• Generate more engaging product descriptions and marketing content.
• Analyse foot traffic patterns in physical stores to improve layout and product placement.

What I particularly like about AI is its ability to scan social media to check out current public thoughts. If you haven't tried it, I suggest you do. You can use this feedback to analyse customer sentiment. I will write another article with a step-by-step approach to show how you can do it now in a few days.

This cost-effective AI implementation means that even small brick-and-mortar retailers in Australia can now access powerful tools. By leveraging these AI capabilities, you can streamline operations, enhance customer experiences, and make data-driven decisions to drive growth and profitability.

The Promise of Cost-Effective AI Implementation

The emergence of DeepSeek and similar AI models is set to revolutionise the retail industry. We predict that "Many more will soon copy its approach", leading to AI becoming increasingly cost-efficient and accessible. This democratisation of AI technology levels the playing field, allowing smaller businesses to compete with larger retailers in terms of AI-driven capabilities.

Despite these advancements, there's uncertainty about fully leveraging generative AI capabilities in practical applications. However, the potential benefits for retailers are significant:

Retail technology trends

The rapid advancements in AI technology will transform the retail landscape.

From our early Focus Engine, which has served thousands of clients for nearly three decades, to the latest advancements in AI, we have seen how these technologies can revolutionise stock ordering. Soon, they will move into customer service, inventory management, marketing strategies, etc. Who knows where they will end up?

One thing is for sure: DeepSeek and what I am sure will be similar AI models will represent a paradigm shift in the AI industry.

Its speed, cost-effectiveness, and open-source nature challenge the status quo.

By staying informed about these developments and thoughtfully integrating AI solutions, Australian retailers can boost their competitiveness, enhance customer experiences, and drive business growth.

As a programmer specialising in retail and Point of Sale (POS) systems, I recently embarked on an intriguing experiment: using ChatGPT to create a dashboard without relying on my programming skills. Much discussion has been about ChatGPT enabling non-programmers to write code, with dashboards often highlighted as a key example. I decided to test this claim, and the findings were illuminating.

What's a Dashboard, Anyway?

A dashboard is a visual display that displays important information, commonly called Key Performance Indicators (KPIs). These provide a quick visual overview of the current situation, helping us make informed decisions without the need to sift through large amounts of raw data.

For retailers, dashboards transform massive sales data into actionable insights in seconds.

The Experiment: Following a Non-Programmer's Guide

To simulate the experience of a non-programmer, I followed a YouTube tutorial that promised to teach dashboard creation using ChatGPT.

So, I selected this YouTube here. Please feel free to consider this article as my response article to it.

So, I started with data from our POS software's Sales Report, which has comprehensive insights.

The ChatGPT Experience: Not Quite as Advertised

Data Wrangling Woes

My first hurdle was getting the data into the correct format. While our POS system can export to JSON, I followed the tutorial's suggestion. Later, I found that I had made the correct decision as I would dive into Excel many times to manipulate the data. It became a recurring theme throughout the process.

Paid Account Required

Contrary to the tutorial's claims, I quickly discovered that a free ChatGPT account wouldn't cut it. The credits ran out faster than a sausage sizzle on a Saturday morning. The experiment would have ended if I had not had access to a paid account. Let me know if anyone wants a paid account, and I offer reasonable offers. So, I switched to the paid account to continue this experiment.

Dashboard Dilemmas

After multiple attempts, I managed to create a basic dashboard. However, getting it to look presentable was another story entirely. As any retailer trying to spruce up their shop window knows, making things look good is most of the work.

Real-World Retail Challenges

Then, I ran into the problem of using real-world retail data in an experiment. In business, things are not cut and dry. I would encounter these problems here.

Consignment Stock

Items on consignment threw off profit calculations, as they had no listed cost.

Gift Cards

These presented a similar challenge to consignment stock.

Payouts

While these transactions affect sales numbers, they don't contribute to profit.

I only discovered these issues through this exercise, and it took time to learn these problems each time. The solution was to return to Excel, adjust the data, and recreate the JSON file. It was like constantly restocking shelves but with numbers instead of products and then recreating the dashboard.

The Programming Plot Twist

By now, I had spent many hours. So, when trying to calculate the total profit, I hit another wall. After many attempts, I had enough, so I resolved this by going outside the tutorial's framework. I had to break character and lean on my programming expertise. I delved into the HTML code generated by ChatGPT to understand what was happening behind the scenes. Only then did I finally wrangle the dashboard into something usable!

Now I had this, I could select a department, and it would give me these figures and charts.

Now I had something, but were the figures correct? After five hours of this exercise, I did not check, so it was unusable. In programming and business, it's rarely worth it for one-off jobs. You need stuff that, once done, repeats. Here, you must massage the data extensively before using it. The Bottom Line

It was presented as a quick and easy project for someone with moderate computer skills but turned into a time-consuming ordeal that required the following:

• Over five (5) hours of work
• Extensive Excel manipulation
• The ability to read and understand HTML code
• A paid ChatGPT account

Even after all that, I hadn't yet verified the accuracy of the figures—a crucial step that would likely take many hours more if they were wrong.

Lessons 

While quickly creating custom dashboards is appealing, the reality is not yet here.

ChatGPT for Businesses 

Most of our clients are very progressive regarding technology and are as excited about ChatGPT as we are.  

What is ChatGPT

Its an AI chatbot. If you have yet tried out ChatGPT, click here. Make yourself an account, and then give it a try. Ask it some questions, ask it to translate some text into your language, give it some history questions, religious or theological questions, cooking questions, etc. You will be amazed at what it can do. 

This is why businesses today are paying attention to ChatGPT. It is an appealing option for businesses of all sizes looking at improving efficiency because it can save time and money. Exactly what it can do is still being determined.  

Fun fact

I asked ChatGPT to describe itself and put its description into a drawing program; this is how ChatGPT sees itself.

Competitors to ChatGPT

There are several rivals for these products. The most well-known is Bard by Google, but many others are into it; Vicuna is a Japanese product. 

Quality 

Quality is the most crucial point. If the product cannot do the job, what difference does anything else make? Here is a very rough test of the quality of several product results.

I wonder if most users will notice that much difference in quality. All have their strengths and weakness. 

You can check out the quality here and make up your mind.

I feel that the free version of ChatGPT is about as good as Vicuna. Overall I prefer Vicuna for business.

Price

The older ChatGPT is free, but the newer product is $20 per month. The others are all free for now. If you want to try the newer ChatGPT before paying for it, try the others first and the older version of ChatGPT so you will know what you need before jumping into it. One needs to learn to walk before one starts to run.

Availability

All except Bard are available now to an Australian. Bard is officially yet to be open to Australians. If you want to run Bard now in Australia, you need a VPN. 

Everyone is now waiting to see the Chinese product, but it has yet to be available in Australia.

Information

This is a big problem in business; Bard is the only one now with up-to-date information, and the rest are about two years old. Yet a businessperson needs current information. A person will come to a shop and generally wants to know about something recent. This puts significant limitations on its business use in Australia.

Outages

Even with paid services, users need help with using the product. It can be very frustrating. Also, many reports say that OpenAI has made ChatGPT stupider to get faster speeds. 

Accuracy

With a Google search, you know where the information comes from; this is not the case with these products often, and YES, the information they supply is often wrong. 

Since these often do not supply references, you must check the answers you get from these products. Be careful.

Political filter

Except for LLaMA, they all have political filters in place. These can drive you crazy as innocent questions can be refused to be answered as such. Heavy users of these products often will debate if Big Brother is watching them. 

Conclusion

Today we are all paying attention to this technology. It is an exciting technology that has the potential to cut costs and increase productivity. I am more than happy to discuss it if anyone wants. 

Executive summary

> These AI can answer a wide range of questions.
> Businesses are looking for them because of their potential to cut costs, save time, and increase efficiency.
> They all have their pluses and minuses. 
> You may not notice a significant difference in quality 
> These products' limited business applications may be due to outdated information.
> These products give incorrect answers, so you must check their accuracy.