Bango has released new data enrichment features to its machine learning algorithm that analyzes the in-app purchases processed by the Bango Payment Platform. Applied to a Large Payment Model (LPM), which analyzes source payment data across thousands of apps, these enhancements have led to a significant increase in the performance of Bango Audiences, the market-leading purchase behavior targeting technology.
New, advanced machine learning techniques applied to a massive payments data set identifies additional buying patterns and optimizes audiences to target specific purchase profiles. Called the Bango Buyographics Data Modeler (BDM), the algorithm analyzes billions of in-app payments to enhance the data intelligence, increasing the effectiveness of Bango Audiences. In trials, app developers have gained an average of 25% increase in Return On Ad Spend (ROAS) from their UA campaigns using these evolved audiences.
This evolution of Bango Audiences delivers app developers:
Supreme UA performance
Enhanced audience creation from a deeper set of proven purchase signals, and more granular and detailed segmentation of purchase behavior data, is driving higher conversion rates, with an average increase of over 25% ROAS. App developer clients targeting their social ad campaigns with Bango Audiences are reaching new audiences with the strongest purchase intent signals for their apps, providing greater confidence in UA spend.
60% bigger in-app purchase data set
In the last year, the Bango Payments Platform has scaled its payment processing transaction volume by over 60%. This expanded, global in-app payments data set generates billions of additional purchase signals for audience creation optimizations. App developers can leverage this vast in-app payments data set to target new paying users on social ad platforms by specific purchase behavior and campaign KPI’s.
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Actionable purchase behavior-based competitive intelligence
Machine learning analysis of industry-wide payment behavior within apps, categories and geos provides a unique source of competitive analysis and insights. App developers can discover:
- App specific segments with the highest propensity to spend
- Categories with the highest crossover of paying users
- Industry average KPI metrics
- Categories that generate the highest revenue per country
- Lookalike percentages that best deliver against KPIs, and more.
Greater control over user acquisition
In an era where automation and low quality data impedes targeting specificity and the data feedback loop, marketers using Bango Audiences to target segments with specific purchase behaviors gain valuable first-party data into the characteristics of acquired payers. Key intel to identify, inform and prioritize marketing, product development and growth strategies.
Less wasted spend
Shorten the learning phase to reach new paying users when launching new features, products and geos. Purchase signals derived from real purchase data feed the social ad platform’s learning algorithm with the strongest data to optimize towards. You can get specific with targeting without compromising on results. Get the right message, to the right users, at the right time, even in new markets.
Take back control of your user acquisition targeting - Join the (R)Evolution !
