Apptica Talks. Episode #2 S2. AI in Mobile Marketing with James Crabb from Gamelight

In this episode Apptica Talks about AI in Mobile Marketing  with James Crabb, Director of Business Development at Gamelight.

Gamelight - Revolutionary AI Platform for Mobile Games Marketing

What we have talked about:

• Current state and future of AI
• Gamelight's AI algorithm
• Risks, challenges, and ethical implications of using AI

Key Takeaways:

1.AI is beginning to muscle in on many stages of the game development process, including:

• Game design: with AI supporting the creation and adaptation of gameplay mechanics
• Game testing: with the use of AI powered testing systems and machine learning algorithms that can pick up patterns and anomalies in vast amounts of data.
• Game Art
• Programming
• Marketing: AI is supporting marketing teams to create written and visual content and now there are tools to help gather user sentiment and improve player feedback loops. Now it is even possible to run and optimize ad campaigns using AI.

2. AI can play a significant role in identifying and targeting high-value users for mobile apps. For example:

• User Profiling: Analyzing user data to create detailed profiles, identifying high-value users based on behavior and preferences.
• Predictive Analytics: predicting future high-value users by analyzing patterns in data, enabling targeted marketing efforts.
• Personalized Recommendations: individualized suggestions to users based on preferences, increasing engagement and encouraging high-value behaviors.
• Dynamic Pricing and Offers: AI optimizes pricing strategies and personalized offers based on user data, attracting and retaining high-value users.
• Customer Segmentation: AI segments users into groups for targeted marketing campaigns and personalized communication.
• Churn Prediction and Retention: AI predicts user churn and enables proactive measures to retain high-value users through interventions and tailored offers.

3. Having access to as much data as possible is crucial. Therefore, it is important to let machine learning take place. Machine learning algorithms have a much easier time to read and analyze massive volumes of data and deliver desirable outcomes based on that.

4. The biggest challenge among mobile marketers is explaining that no rule fits for every user. It is hard to explain those ‘what if’ questions. The algorithm is driven by the goal of maximizing ARPU, LTV and ROAS and will constantly analyze data and user patterns to achieve better results. So, there is an element of trusting the algorithm to deliver, and not trying to influence the results with unnecessary and restrictive targeting.

5. Aside from the usual ethical concerns and while we are striving to bring efficiencies to mobile marketing, there is a concern that AI will do the job of humans much better, and this is true. But if AI can do one job then it allows humans to focus on other areas and, therefore, increases the overall output of marketing teams.

You can learn more about Gamelight on the website and get more insights in its blog.

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