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In a compelling session led by Propel's co-founder Jas and Brainforge.ai’s CEO Uttam Kumaran, the duo dove deep into the often-overlooked power of dormant users and how businesses can utilize data-driven strategies to revive engagement and maximize retention. If you missed on the session, here is the full recording below:
Here's a breakdown of their discussion on leveraging data for lifecycle marketing success:
Jas kicked off the webinar by sharing staggering insights into user inactivity: over 90% of users in typical apps go dormant. However, with the right strategy, reactivating just 5% of these dormant users can increase your customer base by up to 35-40%. Propel’s research emphasizes that identifying where businesses lose engagement and re-engaging users can be a highly efficient way to drive growth, especially when combined with the right data insights.
Key Insight: Don’t give up on dormant users—many of them are just waiting to be re-engaged.
Uttam highlighted the importance of having a solid data infrastructure to run effective lifecycle marketing campaigns. He emphasized that businesses need to first consolidate their data, moving away from spreadsheets and basic dashboards to more comprehensive systems. For brands with revenues between $20M to $100M, a well-structured data stack including ETL tools, data lakes like BigQuery, and BI tools like Snowflake is essential to setting up a foundation for accurate decision-making.
Key Insight: Investing in the right data tools from the start ensures that your lifecycle marketing efforts can scale effectively.
One of the recurring themes in the discussion was the need for marketers to build empathy and understanding with their data teams. Marketers often face challenges in effectively communicating their needs to data teams, leading to delayed timelines and misaligned expectations. Uttam shared that marketers can bridge this gap by framing data requests around business problems instead of narrowly asking for specific data points. This approach allows data teams to suggest the best solutions and avoid simply creating a one-off solution for each request.
Key Insight: Empathy and collaboration between marketing and data teams are key to driving faster results and avoiding misunderstandings.
A major takeaway from the webinar was the evolving role of AI in the lifecycle marketing process. Uttam spoke about how AI is being integrated into the decision-making process, particularly in terms of predictive analytics, content automation, and workflow optimization. However, while AI can make processes more efficient, it’s not a substitute for human creativity and oversight. AI can help marketers make decisions faster, but human insight is essential for ensuring the final decisions align with brand values and goals.
Key Insight: AI can make life cycle marketing decisions faster and more accurate, but it still needs human creativity and oversight.
As AI continues to evolve in marketing, building trust in its decisions is critical. Uttam emphasized that AI’s accuracy depends on the quality and depth of the data it is trained on. He shared how Brainforge builds a "golden data set" by working closely with clients to establish key questions and answers that guide AI decision-making. Through iterative feedback and scoring systems, businesses can ensure that AI-backed insights are trustworthy and actionable.
Key Insight: AI-driven decisions must be continuously validated with real-world data and feedback loops to ensure accuracy and relevance.
Looking to the future, both Jas and Uttam discussed how data engineering roles will evolve with AI advancements. AI tools, such as text-to-SQL agents, are already improving the efficiency of data querying. However, as Uttam pointed out, understanding the basics of SQL is still valuable for marketers to ensure they can critically assess AI outputs and collaborate more effectively with data teams. While AI will reduce the manual workload, the need for skilled professionals who understand both the business and data context will remain.
Key Insight: While AI will automate many aspects of data engineering, understanding data basics like SQL will remain crucial for marketers to collaborate effectively.
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