A shop owner in Aba opens a spreadsheet with 14 colourful charts, a pie chart of "customer mood" and a gauge that nobody can read. She still can't answer one question: did the shop make money this week? That is what a bad dashboard does. A good one answers three or four questions in under a minute, on a phone screen, and then you close it and go back to selling.
This guide shows you what to put on a small-shop dashboard, what to leave off, and how to build it from the sales records you probably already have. It also works as a service you can offer to shop owners, which we cover near the end.
What a dashboard is for (and what it isn't)
A dashboard is one page that shows the numbers an owner needs to make the next decision. Restock or not. Chase a debtor or not. Cut a slow item or not. If a chart doesn't change a decision, it's decoration.
It is not a replacement for your records. The dashboard reads from a clean sales sheet, so if your underlying data is messy, fix that first. Our guide on turning a messy WhatsApp order list into a clean sales report covers that step.
Start with the five questions an owner actually asks
- How much did I sell this week compared with last week?
- What did I actually keep after the cost of goods? (gross profit, not just sales)
- Which items bring most of the money?
- Which items are about to run out, or are sitting unsold?
- Who owes me, and for how long?
Each question becomes one block on the page. Five blocks is plenty. If a shop owner asks for a sixth, ask which decision it would change.
The data you need before you chart anything
You need one table, one row per sale line, with these columns:
- Date (a real date, not text like "Mon 3rd")
- Item name (spelled the same way every time)
- Quantity
- Selling price per unit
- Cost price per unit
- Payment type: cash, transfer, POS, or credit
- Customer name (only needed for credit sales)
- Amount paid so far, for credit sales
Cost price is the column most shops skip, and it's the one that makes profit visible. If the owner doesn't know the cost price of every item, start with the top 20 items by sales and add the rest later.
If transfers and mobile money are mixed into the records, match them to sales first using the method in reconciling mobile money and bank transfers with your sales sheet. A dashboard built on unmatched payments will show sales that never arrived.
What to chart: the five blocks
1. Weekly sales and gross profit (a simple column chart)
Show the last 8 weeks, with two columns per week: total sales and gross profit. Eight weeks is long enough to see a trend and short enough to read on a phone. Add a "sales per day" figure for the current week as a plain number above the chart.
2. Top 10 items by gross profit (a bar chart, sorted)
Rank by profit, not by units. A shop that sells many cheap sachets may find that two slower items bring more money. Sorted horizontal bars are easy to read when item names are long.
3. Stock alert list (a table, not a chart)
A short list of items below the reorder level, with the quantity left. Colour the rows red with conditional formatting. This is where our stock tracker in Google Sheets plugs in; the dashboard just displays its output.
4. Who owes me (a table sorted by age)
Customer, amount outstanding, days since the sale. Sort the oldest first. Add a total at the top. For many small shops this one block is worth more than all the charts combined, because unpaid credit quietly eats working capital.
5. Payment mix (one small chart, optional)
Cash, transfer, POS and credit as a share of sales. Use it only if the owner is deciding something about it, such as POS charges or too much credit. Otherwise skip it.
What to skip
| Common chart | Why to skip it | Use instead |
|---|---|---|
| 3D or pie chart with more than 4 slices | Slices are hard to compare, labels overlap on a phone | Sorted bar chart |
| Daily sales line for a full year | Too noisy; one bad power day hides the pattern | Weekly columns, last 8 weeks |
| Total sales only | Sales can rise while profit falls | Sales and gross profit together |
| Chart of every item | Hundreds of bars nobody reads | Top 10, plus a slow-mover list |
| Gauges and speedometers | They take space and show one number | A big plain number |
| Customer "ranking" for walk-in buyers | Most are unnamed, so the data is thin | Only track named credit customers |
A worked example (hypothetical numbers)
Say a provision shop in Ibadan sold ₦640,000 last week and ₦590,000 the week before. The owner sees sales up and feels good. The dashboard's gross profit column tells a different story: cost of goods was ₦520,000 last week against ₦440,000 the week before, so gross profit fell from ₦150,000 to ₦120,000.
Why? The top-10 profit chart shows that a fast-selling item had a supplier price increase, but the shop kept the old selling price. The fix is a price change on that item, not more advertising.
The "who owes me" table shows ₦86,000 in credit, with ₦52,000 of it older than 21 days from two customers. That's more than a week's profit sitting outside the till. The owner now has two phone calls to make today. That is a dashboard doing its job.
Build it step by step
- Keep raw data on one tab and the dashboard on another. Never type on the dashboard tab.
- Add helper columns in the data tab: revenue (quantity × selling price), cost (quantity × cost price), profit (revenue − cost), and week number or week start date.
- Make a summary table per week using sum-by-condition formulas, or a pivot table if you're comfortable with them.
- Make the top-10 table by summing profit per item and sorting it largest first.
- Build the debt table by filtering credit rows where amount paid is less than the total, then computing days since the sale with today's date minus the sale date.
- Insert charts from those summary tables onto the dashboard tab. Give each a plain title that states the question, such as "Are we making more than last week?".
- Test on a phone. If you have to zoom or scroll sideways, shrink the layout to one column.
An AI chat assistant can help with the formulas. Describe your column names and ask for the formula in plain words, then test it on five rows you can check by hand. Don't paste customer names or phone numbers into a public AI tool; swap them for codes first. Our post on using AI at work without leaking customer data explains how.
Common mistakes
- Text that looks like numbers. "₦1,200" typed with the symbol or a space can break sums. Store plain numbers and format the currency.
- Item names that vary. "Indomie", "indomie " and "Indomie chicken" become three items. Use a dropdown list for item names.
- Mixing sales and money received. A credit sale is a sale today and cash later. Track both columns.
- Charts with truncated axes. A bar chart starting at ₦500,000 makes a small change look huge. Start at zero.
- Building it once and never updating. Agree a weekly routine, such as ten minutes on Sunday night, or the dashboard dies in a month.
- Ignoring power and data. If the owner works on a phone, keep the file small and make sure it can be viewed offline, or share a weekly screenshot or PDF on WhatsApp.
Turning this into paid work
Many shop owners will never build this themselves but will pay someone to set it up and maintain it. A reasonable package is: clean the existing records, set up the five blocks, and send a one-page weekly summary. Keep the offer small and specific, such as "I'll show you who owes you money and which items make you the most profit."
For how to set a fair fee, read how to price a spreadsheet cleanup job. Charge separately for the setup and for any weekly upkeep, and agree in writing who owns the file and who can see the sales data.
How it changes by type of shop
- Pharmacy or provision store: add expiry dates to the stock alert list, since expired stock is a direct loss.
- Food seller or restaurant: track waste and ingredient cost per plate; sales by item matter less than margin per plate.
- Fashion or tailoring: replace stock with orders in progress and deposits received against balances due.
- Online seller: add delivery cost and returns, because they often decide whether a sale made money.
Frequently asked questions
Do I need paid software?
No. A free spreadsheet app is enough for everything above. Paid dashboard tools only make sense when the business has several branches or thousands of rows a day.
How many items should the top list show?
Ten. If the owner sells fewer than ten products, show them all.
Should I include net profit?
Only if the owner records rent, transport, wages, electricity and fuel for the generator regularly. Otherwise a made-up net figure misleads. Show gross profit and add a note listing the costs that aren't counted.
Can AI build the dashboard for me?
It can suggest layouts and write formulas, but it can't know your shop's records. Always check its output against a few rows you've calculated yourself.
Your next step
Take last week's sales, put them in the eight-column table above, and build only the "who owes me" block first. It takes under an hour, and it's the part most likely to put money back in the owner's hand this week.
Results from any side hustle or online work vary widely, and nothing here is a promise of income. Be wary of anyone who asks you to pay upfront to start earning.