Days of Poker

Transforming an idea of a Poker app into a market-fit product through data-driven software engineering & engagement

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Days of Poker is a non-gambling, open-face Chinese poker app that offers 6 different OFC poker games in 4 different game types and aims to introduce a new concept to the social gaming industry.


The Situation

Days of poker app adds a new twist to the conventional game of poker.

Their creators, who come from a non-tech background, were looking for a technological partner that could grasp their concept and turn it into a fully functional mobile app. In terms of intricacy and scalability, developing an app based on the OFC Pineapple game concept is difficult.

Team Unthinkable recommended building the app using their in-house library of reusable components after recognizing the project’s needs, complexity, and deadline. Early go-to-market was a significant aspect for the Days of Poker team, hence the use of reusable components was proposed to save development and testing time.

  • Building a Gaming Engine: To ensure that all aspects of the game, i.e. the rules, and special rules like fantasyland are covered, a new gaming engine was developed. This was done in a way that does not hamper the speed of the app.
  • Shuffling Cards: A loophole in shuffling can make the users guess the next card. This increases the probability of a gamer cheating the system and winning. There have been several instances in an industry where the companies had flak from users due to improper shuffling.

The Solution

By utilizing our in-house library of reusable components, a native mobile app for Android and iOS platforms was developed. Since the reusable components were tested for their stability and efficiency, it accelerated the app development cycle and immensely reduced the overall time for app testing as well. For example, The Chat and Push Notification components for the app were built in 1/3 of the usual development time.

Server-side CRUD APIs development was done in 60% of the usual time because of the reusable libraries. The server in this case needed to be stable while there could have been a lot of changes in the user interface. Thus, we picked the reusable modules from our server library to ensure fast yet smooth delivery of work. To keep a check on the app usability when there is load variation, we used in-memory session management with failsafe hardware so that the sessions are not lost and users do not need to wait for a long time on any requests.

Data-driven software engineering

The Unthinkable team developed the solution architecture, defined the data structure, designed the user interface, and delivered an MVP in close collaboration with the product owner and the key developers of the app. The team started with an in-depth analysis of the business idea to Days of Poker define a clear product vision and prioritize the scope.


The process of data-driven software engineering works on a consumer-first approach that involves tracking the consumer behavior analytics and making design iterations based on the user behavior insights making it progressively easier for the client to achieve the intended goal of the product.

Data-driven user engagement

The next stage of the development process was to meaningfully engage the users with the game and make them understand the unique proposition. Firstly, our user engagement team segmented the clients into various categories based on their behavior such as active users, engaged users, dormant users, purchasers, about-to-uninstall users, and many more. The behavioral insights were drawn from the data they received through CleverTap, which is a customer engagement and retention platform that provides the functionality to integrate app analytics and marketing to draw user insights. Once the segmentation was done, workflows were created for each segment to get them to re-engage with the app. An example of this would be a strategy to send push notifications to non-active app users in order to get them to re-engage with the app. Through CleverTap, the user engagement team could draw out the details about non-active users along with their demographic details and send push notifications recommending a question or product based on their interests or requirements.

After testing out multiple workflows, custom funnels were made for each user segment as per the user responsiveness for all the workflows. For instance, when a user abandons a recommendation before submitting it, CleverTap creates a separate segment of such users, and a custom workflow is created which for instance sends a notification alerting the user to take further action on the abandonment issue and complete the recommendation process. These user funnels were regularly monitored and modified as per the user behavior and consisted of different channels of communication for each segment.