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Read a case studyHoneybook gets 3.5X VIP paying customers with LTV predictions
Highlights
Honeybook's Business: Specializes in end-to-end business management, from booking to payment processing. Earns additional revenue when customers also use their payment services, categorizing these users as high-value.
Early Detection Challenge: With a complex acquisition funnel, initially, only 2% of high-value customers were pinpointed within the first 30 days.
Prior Strategy: Honeybook used trial start as a proxy KPI due to a lack of deeper funnel insights.
Enter Voyantis': Offered forecasts on the probability of users becoming high-value customers or VIPs through payment service usage
Strategic A/B Testing: Implemented A/B testing on Meta (tCPA) and Google (tROAS) platforms, applying Value-Based Bidding and Voyantis predictions to target high-value conversions.
Remarkable Results: Secured a 3.5x surge in high-value customer acquisition and slashed CAC by 50%, all thanks to Voyantis' predictive insights.
“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-day decision-making”.
The Challenge
Your funnel without Voyantis
Your funnel with Voyantis
Early Funnel Value Uncertainty - Honeybook provides a 7-day free trial, followed by a subscription model. Among subscribers, a portion adopts advanced services like payments. However, within the first 30 days, only 2% of these valuable users are successfully identified.
The Gap - Honeybook didn’t have enough signals to clearly identify those VIP customers, who will also use the payment services, early on.
A Short-Term Proxy Used - Since something is better than nothing, Honeybook optimized their campaigns by using free-trial signups, as a Proxy target metric.
The Pilot
1. To evaluate Voyantis' effectiveness, Honeybook conducted experiments on Google and Meta campaigns, utilizing Voyantis' predictions and targeting a US audience.
2. Google: Both groups were optimized for tROAS. The control used a proxy goal (free trial), while the experiment group used Voyantis’ prediction of the likelihood of becoming a paying and activated user (using the payments service).
3. Meta: The control group optimized for tCPA (free trial) while the test group optimized for the likelihood of becoming an activated user (process payments), based on Voyantis’ models.
4. On Meta, Honeybook could further refine targeting to the customer percentiles - for example, the top 50% of the VIP segment and only the top 10% of the non-VIP segment.
How does it work
Data Processing & AI prediction model
Voyantis' AI engine learned the unique nature of Honeybook's users, and the value they will generate over time, differentiated between Honeybook's distinct segments (VIP and non-VIP), and created a custom prediction model tailored to Honeybook.
Privacy First
Voyantis created accurate prediction models using Honeybook's engagement, transactions, and attribution data, all strictly anonymized. We never used personally identifiable information (PII) for predictions, ensuring our clients' data is secure.
Google and Meta Orchestration
We customize the prediction feed for each platform based on their unique network algorithm setup. For Google, we optimize for value-based bidding and send values through the Server's API. On the Meta feed, we used CAPI to optimize for custom events of a 20/50/80% likelihood of converting to an activated user.
Quality Verification
The model is constantly tested and adjusted when needed to provide the most accurate predictions (93% accuracy) and continuous improvements.
The Impact
The results of the pilot clearly indicate the advantage using value predictions for improving campaigns outcomes.
ROAS Uplift
Growth Improvements
3.5X more high-value VIP customers: Not only did Voyantis help Honybook score more VIP paying customers that also use the paying service, Honeybook was able to reduce its CAC by 50%.
Scalable
Google’s Ad engine preferred Voyantis’ targets: after Voyantis predictions were fed back to Google, the engine shifted to optimized almost only according to Voyantis events (95% of the ad spend).
Accuracy
Highly accurate predictions: the predictions that Voyantis generated were 14X more accurate than the proxy that was used by Honeybook with 93% accuracy when compared to actual results.
