Stop Researching AI Tools in Spreadsheets — There's a Better Way

The Spreadsheet Problem

Here's how most teams evaluate a new AI tool today:

1. Someone mentions a tool in Slack. Someone else says "we should look into that."
2. An ops lead opens a Google Sheet and creates columns: Name, Pricing, Features, Pros, Cons, Score.
3. Over the next week, 2-3 people sporadically fill in cells between meetings. Half the data is from the vendor's marketing site. The other half is from a single G2 review.
4. Two weeks later, someone asks "did we ever decide on that tool?" The spreadsheet is 40% complete. Nobody remembers who was supposed to finish it.
5. The team picks the tool that the loudest person recommended, not the one with the best evaluation.

Sound familiar? You're not alone. We've talked to hundreds of ops teams, and this is the default process at nearly every company under 500 employees.

Why Manual Research Fails

The core problem isn't laziness — it's that manual tool research doesn't scale.

It's inconsistent. Different people research different tools with different criteria. One person checks pricing thoroughly but ignores security. Another reads Reddit but skips the official docs. There's no standard.

It's slow. A thorough evaluation of a single tool takes 4-8 hours. Multiply that by the 5-10 tools a growing team evaluates per quarter, and you've burned an entire person-week on research.

It's biased. The person doing the research has an opinion before they start. They unconsciously cherry-pick evidence that confirms their gut feeling. The spreadsheet becomes a post-hoc justification, not an objective evaluation.

It goes stale immediately. AI tools ship updates weekly. The pricing you researched last month has changed. The feature gap you identified was closed. Your spreadsheet is a snapshot of a moving target.

What Good Tool Research Looks Like

Good research has three properties: it's consistent (same criteria every time), fast (minutes, not days), and shareable (the whole team sees the same data).

That's the problem automated research agents solve. Instead of assigning a human to open 15 browser tabs, an agent can:

• Scrape the official product site for current features, pricing, and positioning
• Pull review data from G2, Capterra, and TrustRadius for aggregated user sentiment
• Scan Reddit and community forums for unfiltered opinions from real users
• Run competitive analysis by comparing the tool against known alternatives
• Score everything on consistent dimensions so tools are directly comparable

The output isn't a half-filled spreadsheet. It's a scored research report that anyone on the team can read in 5 minutes and have a real conversation about.

The Time Math

Let's do the math on a typical quarter:

• Manual process: 8 tools evaluated x 6 hours each = 48 hours = $2,400 at $50/hr
• Automated process: 8 tools evaluated x 2 minutes each = 16 minutes = effectively $0

That's not a marginal improvement. That's eliminating an entire category of busywork.

More importantly, when research takes 2 minutes instead of 2 days, teams actually do it. They evaluate more tools. They make better decisions. They catch redundancies before signing annual contracts.

Stop Spreadsheet-ing. Start Researching.

Your team deserves a real research process, not a shared Google Sheet that everyone feels guilty about not updating.

Trackr gives you that process. Submit any tool URL. Get a scored research report in under 2 minutes. Share it with your team. Make a decision based on data, not gut feelings.

Try Trackr free — research your first AI tool in under 2 minutes. No credit card required.