wappier
Going beyond Typical Marketing Automation, Bringing AI in Mobile Gaming

How did wappier start off back in 2015? It was a team of five—the team is rapidly growing with a headcount of 30 at the moment—that realized a gap in the mobile app market. It is the first time in history we see 20 or 50 people companies trying to manage millions of consumers. Typical marketing segmentation and workflows are insufficient, while live operations fail to operationalize marketing and optimize revenue generated from their global audience. An automated, personalized, closed-loop AI Technology is needed to achieve Revenue and Retention Optimization for each individual consumer and this is exactly what wappier is trying to build.

With its Intelligent Revenue Management & Optimization Technology, bringing the course of change is a U.S.-based firm, wappier Inc. The company is building a cloud-based platform that uses machine learning and AI to optimize in-app purchase revenue, retention, and user lifetime value for mobile apps in general and games in particular. The company’s solutions are Automated Loyalty & Retention (creating a native automated rewarding scheme that makes users come back to the game) and Dynamic 1-1 Pricing (finding the optimal price point for the right user at the right time) through machine learning, predictive analytics, and deep data pooling.

Since 2015, wappier has been one of the market leaders of Intelligent Revenue Management & Optimization Technology by leveraging AI in mobile gaming. The company substitutes the human element with machine learning and AI to automate revenue management and marketing personalization. We interviewed Alex Moukas, the Founder and CEO of wappier, to see how wappier is building the AI Technology that mobile app publishers need to better monetize through the existing users of their apps and fulfill their need to provide every single user out there with the optimal price and reward.

What are the primary pain-points that wappier is solving?

Revenue optimization is all about making money above and beyond the core product. Although the typical mobile app publisher is very systematic and sophisticated in terms of new customer acquisition, once a user downloads the app, there is no seamless and systematic approach for managing revenue from IAPs (In-App Purchases) and marketing outside the core product. For the app publishers out there that don't have a dedicated function within their organization for revenue optimization and marketing automation (and most of them lack resources, tools or both), wappier doesn't only provide automation, but also closes the revenue and marketing loop, and takes specific actions on a per consumer basis.

Can you elaborate on the benefits that you deliver to mobile app publishers?

Using machine learning and AI helps us create next-best action recommendations for our clients’ clients, the end users. We focus on optimizing the LTV (lifetime value) of a consumer with every opportunity we have to interact with them through the mobile app. Our solution falls under two over-arching categories: (1) automated loyalty, engagement, and retention systems, and (2) dynamic pricing and bundling of negatively correlated goods to optimize IAP revenue and maximize consumer LTV. Numerous case studies and live customer projects show that using our technology can result in ARPDAU (Average Revenue per Daily Active User) uplifts of 120 percent, while boosting User Retention by 30-50 percent!

Could you please shed more light on wappier’s two solutions: automated loyalty and retention systems, and dynamic 1-1 pricing and bundling?

What we offer as a company is a complete automated solution that uses machine learning on the back-end and is integrated within the app at the front-end to serve publishers and their customers in an efficient and real-time way.

We process more than one billion data facts every day. This gathered knowledge is used to solve different sub-problems revolving around the type and behavior of each user. We help our clients understand:

a) Their app’s optimal loyalty and marketing system: whether their users are engaged, what is the bottleneck of user churn and which is the optimal loyalty program that they should implement for each user.

b) Their app’s optimal pricing strategy: what drives user spending, what is the typical user journey of a payer, what is the right price point they should be charging each user with ? to increase spending.

We combine wappier’s deep integration data— including location, device, time spent, level progress, average time for first IAP , F2B (free-to-billed) conversion, etc.—with third- party data pools for unique customer view and personalized customer management.

How has the past six months been for wappier?

We have grown at a stupendous rate. When we first started, we were a team of 5, we are now 30, and are planning to be 45 by the end of 2018. We are hiring software engineers and data scientists very aggressively to deliver to the traction that we have received in the U.S. and other markets.

Last year our revenue grew by 6x, while in the first half of the 2018 we have further doubled our revenue as a company. With that in mind and having recently secured our first round of financing by a top-tier U.S. VC, we feel ready to bring the mobile app market revolution!

How would you position your company for the next 12-18 months to come?

wappier will be coming up with new solutions that will ensure we cover different types of mobile apps and new verticals, a $6 trillion market on mobile. Since our inception three years ago, wappier’s algorithmic performance has increased more than 300 percent, and we continue to optimize it every day. We invest a lot of time and effort optimizing our algorithms and data models which help us roll out solutions that can predict consumer behavior in the most optimal way and across different verticals.