Imagine this: you are presenting competitor research. The table is organized, the colors look good and the conclusions include a convincing paragraph about your advantage. Then someone asks a small question: “Where did that number come from?” You start searching through tabs, browser history and a long AI conversation. The number was here somewhere. It looked very credible when you read it last night.
In my market research guide, I wrote about recording sources alongside findings. AI’s ability to produce research text quickly makes that habit even more useful. Getting something that sounds professional is easy. We still need to understand what supports it.
Separate three different things
Suppose a competitor’s website says its product saves a team time. That is a company claim, and we can record how it presents the product. To know how much time it really saves, for whom and under which conditions, we need more information. The published sentence does not answer all those questions.
If we open the pricing page and see a particular plan with a particular allowance, we have information observed at a source on a given date. We should still read the conditions. The price might require annual billing, apply to a different country or be part of an offer ending tomorrow.
Then comes our interpretation: perhaps the plan seems more suitable for large teams. That may be a useful hypothesis if we explain how we reached it. I suggest keeping observed information, company claims and our conclusions distinguishable. Otherwise, all three enter the same spreadsheet cell and emerge as a “fact.”
What would the accountant like you to keep?
Every search does not need to become an audit. But you should be able to return to a finding next week without repeating the entire search. For an important claim, keep:
- A link to the specific page, rather than just the homepage.
- The check date and the relevant product or plan name.
- A short passage showing what supports your wording.
- A note explaining what remains missing or unclear.
A screenshot can help when a page changes. Before saving or sharing it, check permissions and avoid unnecessary personal or confidential information. We are collecting useful evidence, rather than everything we can find.
Two sources, two answers. What now?
One page says a feature is available. An old article says it is planned. The AI answer makes it sound as though it has always existed. Before choosing whichever version fits our table best, check dates, product versions, countries and whether the sources describe the same use case.
If the conflict remains, show it. You can explain what each source says and mark the disagreement for clarification. That is a useful finding because we now know what to investigate. Confident wording will not resolve the conflict for us.
You are allowed to leave a cell empty
I know a full table looks better. Even so, “unknown” can be the most professional cell in it when that reflects the available information. A guess may improve the spreadsheet’s appearance while weakening the decision we make from it.
AI can help suggest directions, summarize and interpret. When a finding affects a significant decision, open the source and check that it still supports your wording. Especially when the answer is exactly what you hoped to find.
Before you send the presentation
Choose three central findings and try explaining them to someone else. Open the links, show the supporting information and identify where the source ends and your interpretation begins. If that is difficult, strengthen the research before the meeting.
In Mikud.AI, sources sit beside competitors and your ratings remain central, with a separate AI assessment to identify gaps. My aim is to help you move faster and stand behind what you present. When someone asks where the number came from, it would be nice to simply open a link.