Episode 51 - Agentic AI Part 2: Retention Use Cases

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📰 Top Story: Agentic AI part 2 - Customer Retention Use Cases

In the first part of this 3 part series, we explored what agentic AI is, and expected growth. If you didn’t catch that episode you can catch up here. 

For those short on time heres a quick 72-word summary:  

Agentic AI isn’t AI that helps you be better at retention, as a co-pilot. Agentic AI is AI that runs retention for you. Agentic AI acts autonomously: it takes goals, then defines tasks, learns from experience, adapts in real-time, and collaborates with other AI agents across your business and outside your business.  This is a market that is projected to 10x in the next 5 years. 

To learn more read episode 50. 

10 Agentic AI Retention Use Cases

1. Proactive Churn Prevention 

In episode 41 I wrote about how most churn models dont work and how it is always much better to use the insight from those churn models to address churn early warning signs. Agentic AI will be able to continuously monitor customer behaviour and proactively identify customers at risk of churn later. The AI will be able to execute personalised retention intervention strategies based on the specific customer profile and engagement history.

2. Intelligent Chatbots 

Most chatbots today are driven by AI, but invariably they find it difficult to deal with questions that are much more complex than those already available in your FAQs. Agentic AI will be able to provide much richer experiences, examining your previous interaction history, while sourcing data from multiple internal and external data sources.  Agentic AI systems will manage the entire support journey, deciding when to escalate issues, choosing the appropriate human agent based on expertise and rapport history, preparing comprehensive case summaries, and following up after resolution to ensure satisfaction.

3. Dynamic Loyalty Program Management

While loyalty communications customers receive can be personalised, most loyalty programs are one-size fits all. Spend X, get Y, for everyone. With agentic AI, rather than static tier and points systems, agentic AI will continuously optimise each customer's loyalty program, adjusting rewards, perks, and challenges based on individual preferences and spending patterns, all while analysing and optimising against competitor offerings that might tempt customers away.

4. Retention-Focused Pricing Optimisation

Instead of blanket pricing strategies, agentic AI will be able to identify price-sensitive customers and autonomously provide personalised pricing adjustments, contract extensions, or value-added service bundles to retain customers and maximise revenues. 

5. Digital Twin Customer Account Manager 

With agentic AI, brands will be able to provide each customer a virtual account manager, either an AI version of their own real human account manager (available 24/7) OR an entirely AI driven virtual account manager. This digital twin will continuously advocate for the customers needs within your organisation. The agent will identify friction points, suggest product improvements specific to the customer, and coordinate cross-departmental efforts to enhance the customers experience. 

6. Competitive Intelligence Shield 

Agentic AI will be deployed to monitor competitor content amd promotions and autonomously implement defensive strategies – such as timely education about your unique value propositions or preemptive outreach with retention offers.

7. Customer Success Autopilot

Particularly relevant in the B2B SaaS space, agentic AI will drive customer success initiatives by identifying optimal product usage patterns, autonomously creating customised adoption pathways, and guiding customers toward their goals with infinite personalisation. For more on retention in B2B SaaS, check out the latest episode of my podcast: the Customer Retention Show.   

8. Relationship Health Management

AI Agents will be able to build and maintain a comprehensive "health score" for each customer relationship, considering not just usage metrics but sentiment analysis, competitive environment,  macroeconomic factors and more. Similar to proactive churn intervention, the agent will then orchestrate multifaceted interventions across touchpoints. 

9. Cross-Organisational Retention Intelligence

Agentic systems will be deployed that identify retention risks emerging from adjacent departments (billing issues, product bugs, service delays) and will orchestrate preemptive measures before customers become aware of problems or it will suggest holistic changes to customer or product management.

10. Hyper personalised contextually evolving experiences 

In episode 11, we explored how generative AI is already reshaping retention marketing - from enabling personalised content creation at scale to laying the groundwork for AI agents that can autonomously build entire lifecycle journeys. While most brands are still using genAI in basic, decentralised ways, the next wave will see AI agents orchestrating deeply personalised, emotionally resonant experiences across the entire martech stack, making decisions on content, tone and journeys based on pre-defined parameters (e.g. brand guidelines), but without human intervention. 

I cover the impact of AI on retention marketing in my course, CRM Strategy 2.0 and to celebrate 1 year of the Retention Blueprint Newsletter (the anniversary is next week 🎂), for a short time I am offering $25 off, find out more here and use the coupon code BLUEPRINTBIRTHDAY at checkout to access the discount. 

Final Thoughts

Of course all of this change wont come without organisational challenges and thats what we explore in part 3 of this series, in episode 53 of this newsletter dropping on Friday June 13th. 

Until next week, 

Tom

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