Published research
When a proof article quotes a stat about response time, follow-up, reviews, or local-service conversion, it should trace back to a real study or benchmark report.
Proof Methodology
How Avo builds trust without pretending results exist when they do not.
Avo should feel credible, not padded. So the proof layer is built from real published studies, reputable benchmark reports, and clearly labeled modeled projections instead of unsupported customer claims or made-up ROI stories.
Modeled projections
If we estimate upside, it should be labeled as a projection based on benchmarks and assumptions, not presented as a client result.
Live demo proof
The strongest thing Avo can show right now is the actual system experience. The demo is the proof-of-feel layer that sits on top of the research layer.
What We Use
The proof stack that works right now.
Without a mature client roster yet, the best trust strategy is to make the buyer feel two things: the problems are real, and Avo is built for the exact places those problems show up.
Evidence buyers can respect
These are the assets that help a skeptical buyer lean in instead of dismissing the offer.
Research-backed insight posts with clear sources
Benchmark summaries tied to local-service operators
Relevant quotes from established publications
Simple, labeled projection math based on realistic assumptions
Things we should not invent
These might create short-term excitement, but they damage trust fast if a buyer pushes deeper.
Invented client names and invented wins
Made-up reviews, ratings, or review counts
Guaranteed ROI or booked-job claims without proof
--Live metrics-- from systems that are not actually live
The Rules
The 4 rules behind every proof page on this site.
These rules keep the site persuasive without crossing into slippery claims you cannot defend later.
Show real published findings before showing projections.
Label modeled scenarios as modeled scenarios, not customer outcomes.
Use the instant demo to prove experience, not unsupported numbers.
Replace shallow social proof with better argument quality and stronger sourcing.
Next Step
Let the research build confidence, then let the demo close the gap.
That combination is what makes Avo believable right now: the buyer sees the numbers, understands the problem, and then experiences the system directly.
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