How HoneyBook doubled
its high value customers per campaign with LTV predictions?
It was challenging to optimize the campaign based on trials and to measure campaign success early
Long funnel - can take months to convert
Limited metrics to evaluate user's quality
Scarce number of conversions within first 30 days
Using short term proxies to optimize towards high value users - showed limited results
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1
Voyantis created custom prediction models to generate value prediction based on HoneyBook anonymized data
Voyantis created custom prediction models to generate value prediction based on Honeybook data
2
These predictions were fed to Meta and Google using CAPI and Server’s API to optimize campaigns
New data of users was imputed to the models that yielded the predictions
3
Ad spend shifted to optimize according to Voyantis event, no change was done to the creative and audience
These value predictions were fed to the ads managers to optimize campaigns
4
Google: tCPA-trial changed to Value-Based Bidding with the Voyantis’ predictive value per user
Meta: trial-event changed to custom event 20/50/80% top LTV
Meta: trial-event changed to custom event 20/50/80% top LTV
Ad spend shifted to optimize according to Voyantis event
80%
Of ad spend was optimized according to Voyantis event
“Partnering with Voyantis allowed us to acquire higher-value users at a lower cost. Voyantis predictions are being used as a key decision metric in our day-to-daydecision-making.”
Shai Brumer
Sr. Director, Data & Scale @ HoneyBook
93%
Model
Accuracy
Accuracy
53%
Lower high-value segment CAC
2.1x
High-Value User Conversions
3x
More accurate than proxy used before by Honeybook
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Your demo request has been received successfully. Get ready to explore the possibilities with Voyantis.
Our team will reach out shortly to schedule the demo at your convenience.
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