6. Analysing sales and making decisions

Abebe runs a small electronics accessories shop in Merkato, Addis Ababa. Every day he sells screen protectors, phone cases, charging cables, earphones, and power banks. At the end of each month he looks at his cash and wonders: Did I make a profit? Which items should I restock? Should I expand into tablets?

Without analysing his sales, Abebe is guessing. He restocks items that feel popular rather than items that actually generate the most profit. He misses the fact that charging cables — cheap but high volume — are his biggest revenue driver, while bulky power banks tie up cash for weeks.

Sales analysis means looking at your numbers with a clear eye: Which products sell most? Which have the best profit margin? When do customers buy most — weekdays or weekends, mornings or evenings? Which months are slow?

In the past, this required a business degree or an accountant. Today, AI makes it possible for any shop owner to get these answers in minutes — by simply describing or pasting their sales data into a tool like ChatGPT and asking the right questions.

Before AI can help you, you need to give it something to work with. Your sales data does not have to be perfect — it just has to exist in a form you can describe or paste.

Here are three common starting points for Ethiopian small business owners:

1. A notebook or paper ledger — You write down what you sold each day and how much you received. This is enough. At the end of the week simply count up totals by product and type a short summary, for example: 'This week I sold 45 phone cases at 150 birr each, 120 charging cables at 80 birr each, and 12 power banks at 450 birr each.'

2. A WhatsApp order log — Many small businesses take orders by WhatsApp. Scroll back through a week of messages and count the orders per product. Paste that summary into ChatGPT.

3. Telebirr or CBE Birr transaction history — If customers pay digitally, your Telebirr or bank app keeps a record. Copy the list of amounts and dates and paste it into ChatGPT, noting what each payment was for.

The key habit is recording sales consistently. Even a five-minute daily note in your phone's notes app builds up into powerful data over time.

When you paste your sales data into ChatGPT and ask for analysis, it will look for patterns you may have missed. Here are the most valuable patterns for small business owners:

High-volume vs high-margin products — A product that sells 100 units a day at 20 birr profit each (2,000 birr) may be more valuable than one that sells 5 units at 200 birr profit each (1,000 birr). AI will help you calculate which contributes more to your bottom line.

Seasonal or day-of-week patterns — Sara's samosa shop sees 70% of its sales on Fridays, Saturdays, and public holidays. By asking ChatGPT to spot this pattern in her weekly data, she learns to prepare more stock before weekends and reduce waste on slow Tuesdays.

Customer spending habits — If you track individual customers (for example through repeat WhatsApp orders), AI can help you spot who your best customers are, how often they buy, and what they typically order together. A shop in Piassa discovered that customers who buy coffee beans almost always also buy a small sugar packet — and started bundling them.

Slow-moving stock — If a product has not sold in three weeks, it is tying up cash. AI will flag this pattern and suggest whether to discount, bundle, or stop stocking the item.

Sales analysis is not just about understanding the past — it is about making better decisions for the future. Here are three common decisions where AI can dramatically improve your thinking:

Decision 1: Should I stock more of this product?

Almaz sells fabric in Hawassa. Her data shows that Tilet and Shemane fabric both sell well, but Tilet sells out in three days while Shemane sits for two weeks. She asks ChatGPT: 'Tilet fabric sells out in 3 days and Shemane takes 14 days to sell the same quantity. Each costs me the same wholesale price and sells for the same margin. Which should I stock more of, and why?' AI explains clearly: Tilet has 4.7 times the sales velocity, so investing the same birr in Tilet generates nearly five times the profit per month.

Decision 2: Should I open on Sundays?

A coffee shop owner in Addis Ababa has Saturday data showing strong sales, but no Sunday data. He asks ChatGPT: 'My Saturday sales average 3,500 birr revenue. Fixed costs for opening one extra day are about 800 birr in wages and electricity. If Sunday sales are likely to be similar to Saturday, would it be profitable to open on Sunday?' AI walks through the math and helps him decide with numbers, not guesses.

Decision 3: Which customer group should I target more?

By reviewing Telebirr payment records, a mobile accessories seller notices that most large purchases come from small business owners buying in bulk, not individual retail customers. AI helps him recognise this segment and suggests creating a simple wholesale programme with bulk pricing — turning occasional large buyers into regular monthly accounts.

The most powerful use of AI for sales analysis is not a one-time exercise — it is a monthly habit. Here is a simple routine any small business owner can follow:

At the end of every month, spend 30 minutes doing this:

1. Tally your sales — Count up total sales per product or service for the month. If you have digital records (Telebirr, bank statements, or a simple spreadsheet), this is quick. If you use a notebook, add up the daily pages.

2. Compare to last month — Note which products sold more, which sold less, and what the total revenue was compared to the previous month.

3. Open ChatGPT and paste your summary — Use the prompt template you learned earlier in this lesson. Ask for the key patterns and one or two recommendations.

4. Write down one decision — Based on the AI analysis, commit to changing one thing next month. It could be stocking more of a fast-selling item, stopping orders of a slow one, adjusting a price, or offering a promotion during a predictably slow week.

5. Track the result — In the following month, look at whether your decision made a difference. This feedback loop is how you turn AI analysis into real business growth.

This monthly review keeps you from running your business on guesswork. Over a year, it builds a powerful picture of what drives your business — and turns small decisions into compounding improvements.