Which tool to choose
The tool is the conversational assistant to read and interpret the data, and the spreadsheet for the exact figures and polished charts. You paste or upload the sales data and ask the AI for the trends; for the totals and precise percentages, have the spreadsheet do the math. If your assistant generates charts, use them to see trends at a glance. The interpretation part — why sales dropped in March, what made that product grow — stays yours: AI sees the curve, but doesn't know what happened in your market and your company.
How to do it
- Prepare the sales data in an orderly way and paste or upload it, with the labels.
- Ask for the trends: what's growing, what's falling, when there are peaks or drops.
- Verify the important numbers by having the spreadsheet calculate them, not trusting the chat's math.
- Interpret the results yourself in light of what you know: promotions, seasonality, events that explain the trends.
A concrete example
Sara had the sales data for her online store but saw only a sprawl of numbers. She pasted them into the AI asking for the main trends. The assistant showed her that one product was growing steadily while another, once strong, had been falling for months. Sara verified the numbers in the spreadsheet: they checked out. Then she applied her own head: the declining product had been overtaken by a competitor's new release, something the AI couldn't know. The assistant had found the trend; the why, and what to do about it, she supplied, because she knew her market.
When it does NOT work (and how to fix it)
If the numbers don't add up
AI can get calculations wrong on a lot of data. Have it find the trends and read the patterns, but the totals and percentages have the spreadsheet calculate or verify. A business decision made on a wrong number is a serious problem.
If it mistakes a coincidence for a cause
AI can notice that two things move together and suggest that one causes the other, but correlation isn't cause. Take its prompts as hypotheses to verify with what you know, not as certain explanations. The why of a trend requires your context.
If the data is too much or disorderly
Enormous or poorly structured tables confuse the AI. Work on portions, or first give it the structure of the data (what each column contains). Orderly data in gives reliable analysis out.
A tip from someone who really uses it
Let AI find the what, and keep the why for yourself. The assistant is brilliant at bringing out the patterns hidden in a mass of numbers: that product in a slow decline, that seasonal peak, that channel that yields more than the others. It's work that, on your own in front of a dense sheet, is hard to see. But finding a trend is only half: the other half, the one that counts for deciding, is understanding why it happens, and there AI is blind, because it doesn't know what's going on in your business, among your clients, in your market. That piece you supply. Use the assistant as a radar that flags where to look, and then bring your own knowledge to interpret what you've found: a radar without a pilot leads nowhere.
Frequently asked questions
Can I trust the calculations on sales?
For spotting trends and patterns yes, for the exact numbers verify: AI can get sums and percentages wrong. Have it read the data, but have the spreadsheet calculate the precise totals.
Can AI tell me why sales dropped?
It can propose hypotheses, but it doesn't really know: it doesn't know what happened in your business and your market. It sees the trend; the why you interpret, with your context. Take its prompts as leads, not as certain explanations.
Is it worth having it make the charts too?
If your assistant generates them, they're useful for seeing trends at a glance; for something polished build them in the spreadsheet. Either way, verify that the data shown is yours.
If AI analyzes sales, do I know what to do to improve them?
No, and it's the leap that leads to wrong decisions. AI shows you what happened in the data, but what to do depends on why it happened and on your context, which it doesn't know: the same dip can call for opposite responses depending on the cause. Treating the analysis as a recipe of actions, without interpreting the results with what you know of your market, is the most common way to react to the wrong symptom. The assistant tells you where to look; deciding what to do stays your choice, informed by your knowledge of the business, not just by the curve.