This episode explores how AI data agents promise to unlock speed, autonomy, and strategic clarity that lifecycle marketing teams have been waiting for — by removing their biggest blocker: access to usable, contextual data.

Through a conversation with Ishan Rakshit (Co-founder @ Sortment), we dive into how AI is shifting from being a creative assistant to becoming a deeply integrated data teammate — helping CRM teams move from ticket requests to instant, insight-driven execution.

I honestly feel this is one of the most insightful episode of my podcast so far. Some of the key topics we discussed here:

• Why does personalization still feel broken in 2025?: A honest look at why lifecycle marketing hasn’t evolved fast enough — and what’s kept us stuck.
• How AI is changing the way CRM professionals think — not just how fast they move. What are the AI native use-cases for lifecycle marketers?: Things that weren't possible until we had this technology. AI enables teams to ask more questions, explore more strategies, and think out loud without friction.
• What can an AI data agent actually do?: Real examples: from asking vague brainstorming prompts to deploying live segments into your ESP — in minutes, not weeks.
• Why the future marketing tech stack will be built around your data warehouse — not your ESP": A must-hear for Heads of CRM and Growth Leaders thinking about the next 12–24 months of their CRM & Martech tooling.
• "How to get your team (and data team) ready for AI-first workflows": Tangible advice on change management, adoption blockers, and the mindset shifts required to truly benefit from AI tools.

You can check out Sortment here.

Cognitive biases shape how users make decisions, but how do you apply them strategically in product, CRM, and growth—without relying on gimmicks? How do you choose and prioritise which biases can help your users?

In this episode of LTV Talks, I sit down with Angele Lenglemetz, Senior Product Manager at Cleo AI, to explore the right (and wrong) ways to use cognitive biases in your work. Angele shares how she evolved from using psychological tricks as quick wins to systematically integrating behavioral science into product strategy.

We cover:
✅ How to choose the right cognitive bias for the right problem✅ Why loss aversion, anchoring, and social proof work—and when they don’t✅ How Cleo applied biases in financial behavior change (and what backfired)✅ The 3B framework for systematically applying biases to product & CRM✅ When overusing biases hurts trust and long-term retention

Whether you’re a product manager, lifecycle marketer, or growth expert, this episode will give you a clearer, more structured approach to applying behavioral science in your daily work.

In this conversation, I speak with Dr. Tim Wiegels explore the intricacies of CRM data, focusing on effective measurement strategies, common pitfalls in CRM teams, and the importance of understanding the broader business context.

Tim shares his journey from academia to data leadership, emphasizing the need for CRM teams to align their metrics with overall business goals and to avoid siloed thinking. The discussion also touches on the challenges of managing control groups and the potential overload of CRM tools, advocating for a more strategic approach to data utilization.

In this conversation, wel discuss the challenges and strategies surrounding CRM tools, customer data management, and the importance of understanding customer lifetime value. The emphasis for teams to define their strategies, leverage AI for data analysis, and focus on retention in the evolving landscape of marketing.

The discussion also highlights the significance of data literacy and the future of CRM in a data-driven world.takeaways

• Understanding ROI on CRM tools is crucial.
• Teams often focus too narrowly on their KPIs.
• A holistic view of the funnel is essential.
• Vouchers can lead to revenue loss if mismanaged.
• CRM goals should align with overall business objectives.
• Control groups need regular refreshing to remain valid.
• Data teams must communicate effectively with management.
• Incrementality and uplift modeling are key measurement strategies.
• Headspace is necessary for effective data analysis.
• Freelancing allows for more focused project work. CRM teams often rely too heavily on tools without understanding their full capabilities.
• It's crucial to segment customer data effectively to drive better marketing strategies.
• Defining a clear strategy is essential for CRM teams to succeed.
• Customer lifetime value is complex and requires a deep understanding of customer behavior.
• AI can significantly enhance data analysis and decision-making processes.
• Teams should focus on retention strategies as acquisition becomes more challenging.
• Data literacy is vital for marketing teams to manipulate and understand data effectively.
• Using AI tools can streamline processes and improve efficiency in data handling.
• Understanding the value segments of customers can help in targeted marketing efforts.
• Effective communication and collaboration between teams are key to successful CRM implementation.

Tim's Linkedin: https://www.linkedin.com/in/timwiegels/

Tim's Podcast: https://tr.ee/DCtUqUirY_

Enjoy this conversation!