Analytics tools earn attention with big projected dollar figures. We think that habit is why operators stopped trusting analytics tools. Alfredo is built the opposite way: when the data is not there, the number is not there either. This page is the whole rule, in public, so you can hold us to it.
Every dollar amount traces back to your own transactions. If we cannot trace it, you do not see it. That includes our marketing: the example board on our homepage is labeled as a sample, and no invented figure is ever presented as a real result.
Thin data shows as "needs more data," never as a confident guess dressed up with decimals. Review scores hide until enough customers have actually said something. Cost figures wait for real cost data.
A finished trial can say exactly three things: worked, no effect, or backfired. When it backfires, the board says backfired. A recommendation engine that cannot admit a miss cannot be trusted on a hit.
While a trial is running, the dashboard shows no interim results. Checking mid trial inflates false positives, so Alfredo does not let anyone peek. Including us.
There are tools that report, tools that account, and tools that forecast. There was nothing that recommends, tests, and admits when it is wrong. So we built it.
When Alfredo suggested a cross promotion to one of our operators, it attached this label to its own idea:
"Very low confidence. Consider an A/B test."
An engine that flags its own weak ideas is the only kind whose strong ideas mean anything.
The same rule applies when the data itself is wrong. On day one with a real client's cost data, Alfredo flagged a 1,370 times data entry error.
"Flagged for review. Confirm or dismiss."
It asked the operator instead of silently fixing it. Data that gets quietly corrected is data you can no longer trust.
Run Alfredo on your own data and judge it by its verdicts. That is the whole point.