How to Run a Fair Bake-Off Between Two AI Meeting Notes Tools
Running two AI meeting notes tools for a week each and picking the one that felt better is not a comparison. Here is how to set up a bake-off that actually tells you which tool is stronger.
A week with each tool is not a comparison
The most common way a team compares two AI meeting notes tools is to run one for a week, switch to the other for the next week, and then decide based on which one felt better. It looks like a fair test because both tools got equal time. It is not a fair test, because the two weeks were never equal to begin with.
Week one might have carried a quiet stretch of easy syncs, while week two happened to land a rescheduled call, a five-person cross-functional meeting, and a stretch where whoever was judging the output was simply busier and paying less attention. By the time a decision gets made, the comparison is really between two different sets of meetings scored from memory a week apart, not between two tools on equal footing.
Write the scorecard before either tool touches a meeting
Guidance written for enterprise vendor bake-offs is consistent on this point: write down what a good result looks like, and how much each part of it counts, before any tool has a chance to make a first impression. If note quality, action item accuracy, and how easily a decision can be found again later all matter, decide how much each one matters in advance, not after seeing which tool happens to be stronger on one of them.
This matters more than it sounds like it should, because a strong first demo or a single impressive note from either tool can quietly move the goalposts. A team that has not written its criteria down tends to reach for whichever criteria the better-performing tool happens to satisfy, and calls that the deciding factor after the fact.
Run both tools on the same meetings, not different ones
A real bake-off tests both candidates against the same conditions at the same time, so that a single hard meeting or a single easy one does not swing the whole result. For meeting notes tools specifically, this is usually more achievable than it sounds. A tool that works from screen and audio context rather than joining as a separate bot participant can often run alongside a second tool on the identical call without either one interfering with the other.
That makes it possible to point both finalists at the same string of meetings across the same days: the same recurring standup, the same customer call, the same messy planning session. Whatever difference shows up in the output is then a difference between the tools, not a difference between which week each one happened to draw.
Score the output blind, and get more than one person to look
Once both tools have produced notes from the same meetings, strip the tool name before anyone judges the result. Put the two sets of notes for a given meeting side by side, unlabeled, and have someone read them without knowing which tool wrote which. This one step removes most of the brand loyalty and first-impression bias that otherwise decides these comparisons before the actual notes get read closely.
It also helps to have more than one person score. A single evaluator's judgment, even a careful one, is one data point shaped by that person's own working style and blind spots. Two or three people scoring the same blind pairs and comparing notes catches disagreements worth discussing instead of letting one person's preference stand in for the whole team's decision.
Set an end date before you start, not after
Bake-offs that drag on tend to end not because enough evidence has accumulated, but because someone finally gets tired of running two tools at once. Pick a fixed window, typically one to two weeks of real meetings, and a specific date the decision gets made. Announce the date at the start, not once one tool is already pulling ahead.
A dedicated, time-boxed comparison also keeps the exercise from quietly turning into permanent double coverage, where a team keeps both tools running for months because nobody wants to be the one who commits to dropping either. The scorecard exists to make that call once, on schedule, using evidence gathered under matched conditions rather than a slow drift toward whichever tool nobody got around to canceling.
Sources
- How to make vendor technology bakeoffs work, including narrowing to two finalists first and defining measurable, objective criteria before testing begins - InformationWeek
- How to run a fair vendor bake-off: writing and weighting criteria before any demo, testing every candidate against the identical conditions, and scoring measurement separately from final judgment - Coval
FAQ
Is it worth comparing more than two tools at once?
No. Vendor bake-off practice generally narrows the field to two finalists before the head-to-head starts, using a lighter first pass to eliminate weaker options. Running three or more tools in parallel on the same meetings adds coordination overhead without adding much signal, since the real decision usually comes down to two close contenders anyway.
What if one tool needs to join the call and the other does not?
Run the bot-based tool as it normally would and let the botless tool observe the same call in the background. The difference in how each tool captures the meeting is itself useful information, not a reason to disqualify the comparison, as long as both are working from the same actual meeting rather than separate ones.
Who should do the blind scoring if the team is small?
Even two people works better than one. Have whoever ran the trial remove the tool names before a colleague, or the founder, reads both sets of notes. If the team is genuinely one person, wait a day or two between running the meeting and scoring the notes, so the memory of which tool produced which output has faded enough to judge the text on its own.
What breaks a bake-off even when the process is followed?
Letting one especially good or bad meeting decide the outcome. A single strong or weak result should move the score for that meeting, not overturn the whole comparison. That is why the scorecard runs across several meetings and a fixed window, so one outlier gets averaged against the rest rather than becoming the whole verdict.