For real estate
More viewings, and the proof it was Avarto.
Buyers and renters scan listings at midnight. Avarto answers on the spot and books the viewing while intent is hot.
What the assistant does on a real estate site
Instant answers across every listing
Books viewings & captures qualified enquiries
Filters by budget, beds & area
See which experiments moved viewings
Each experiment runs against a randomized holdout. The bar is the 95% confidence interval — never a bare point estimate. Green helped, red hurt, slate isn’t yet significant, and a sample too small to trust is labelled “not enough data” instead of a confident wrong number.
Viewings lift vs holdout, by experiment
The bar is the 95% confidence interval; the dot is the point estimate; the line at zero is the holdout baseline. A “✓” marks a statistically significant result.
Illustrative — based on the demo store, not a real customer result.
The campaign loop: a ratchet, not a one-off test
Optimisation isn’t a single A/B test — it’s a programme that compounds. Inside each shaded experiment band the line wobbles as variants win and lose; when the experiment ends you apply the winners as normal site behaviour and the line settles and holds. Run a second experiment and the cycle repeats — even dipping while a losing idea is live — but its learnings push the metric to a new high, above where the first round left it. The holdout line shows what viewings would have done with no experiments at all; the gap is the illustrative lift Avarto adds.
Viewings vs holdout, across two campaigns
The shaded area is viewings with Avarto; the dashed line is the holdout (no experiments), held flat at the baseline index of 100. The dashed-edge bands mark each live experiment period (“begin ┄ end”) — where the line wobbles; between them the winning learnings are applied and the line holds, then climbs.
Illustrative — based on the demo store, not a real customer result.
- 1
Hold-out
A randomized slice of visitors never sees an experiment. That flat line is your true baseline — the counterfactual every later gain is measured against.
- 2
Experiment period
Inside the shaded band the line wobbles week to week — some variants win, some lose. That noise is the programme working, not failing: you're learning what actually moves the metric.
- 3
Learnings applied
When the experiment ends, the proven winners become permanent site behaviour. The wobble stops and the line settles — and the lift holds instead of snapping back to baseline.
- 4
Repeat — and climb
The next experiment period wobbles again (sometimes it even dips while a losing idea is live), but once its learnings are applied the line steps up to a new high — above where the last round left it.
What moved
Illustrative — based on the demo store, not a real customer result.
Grounded answers, measured causally
Answers are grounded in your own content, and a holdout group never sees the assistant — so you measure the viewings it actually added, not the ones it happened to sit near.
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