Episode 11 - Generative AI and Retention Marketing

Welcome to episode eleven of the Retention Blueprint. This newsletter promises to transform your retention impact in just 5 minutes per week, providing digestible retention content that adds value every time. This episode focuses on the impact of generative AI on retention marketing. 

Future newsletters will cover the impact on other aspects of the retention experience, including the impact of AI on customer support and data-driven predictive AI.   

Generative AI & the Story So Far

While AI has been conceptualized for over 70 years and work on it underway since then, it is only since the launch of ChatGPT that the world awoke to its transformational power (although AI has been present in many tools we use everyday for 20+ years). There is a lot of talk about AI and its likely impact on many aspects of our lives and it's sure to change many aspects of how we live and work. Customer retention is no different. Whilst we are still in the midst of working through this paradigm shift, what is true is that in retention the ability to leverage AI is already starting to fundamentally alter digital customer interactions.  

Generative AI & Its Potential

The ability to create micro-segments using martech tools has existed for over 20 years. The challenge has always been to execute creatively and with tailored content against different audiences across the lifecycle. Most brands just didn't have the resources to execute. 

Grocers, fashion retailers, streamers, and a few others were exceptions in that they have been able to map vast inventory to audience preferences, in some cases for a couple of decades. However, the difficulty has always been creating emotionally relevant content around that vast inventory; there simply wasn't the copywriting or design capacity to do that.  

AI allows us to leverage both an understanding of not only what, but why a customer is likely to be interested in a specific piece of inventory and tailor messaging to the audience in ways that engage emotionally to improve usage, conversion and retention. 

However, despite the fact that nearly all leading martech vendors now have inbuilt generative AI capabilities, it is currently under-deployed in most organisations. Even where it is being used, deployment is relatively unsophisticated.  Essentially, users work with generative AI tools to create ad hoc copy and imagery, often in a relatively decentralised way, drop that into their digital asset and carry on as before. 

The future will see a much more automated, centralised and more personalised approach to digital asset production and the retention marketing customer experience.  

AI Agents Operating Across the Stack

This new future will be one powered by AI Agents working across the martech stack, empowered by API’s. Users will be able to submit a prompt, and the AI Agent will build an entire retention marketing lifecycle journey across all elements of a brand's martech stack, think emails, push messages, product notifications, landing pages and much more. The journeys AI Agents build will contain a multitude of different permutations at different moments of truth for different customer cohorts. AI Agents will connect to different customer cohorts' preferences emotionally across vast inventory and create personalised content that resonates at scale. 

For example, in the customer onboarding stage, the key is to identify factors predictive of long-term value (e.g. usage of particular features, services, no. of products brought, no. of billing periods) and aim to get customers to undertake those activities within the first 90 days (See Retention Blueprint episode 4 for more details on this). Generative and predictive AI working together across the stack will be able to identify behavioural triggers, how they vary by customer cohort, and what you need to do to get cohorts of customers to undertake new behaviours. It will then build bespoke journeys for those different customer cohorts, with some customers encouraged to undertake action A, while others are encouraged to undertake action B, with different journeys for different sub-cohorts according to channel preference, engagement history and potential value. 

This is not a long way away. AI agents are already being tested in workflow automation tools, and very soon, we will see them widespread throughout the martech stack. 

One great example of how a single tool combines predictive AI and generative AI to drive value comes from a start-up in Denmark called Subsets. They have built a solution that leverages predictive AI to identify cohorts of customers at high risk of churn. Then, via generative AI, the tool provides high-performing CRM marketing interventions that are proven to reduce churn propensity.  

What's Next  

Sam Altman (CEO of OpenAI) believes that Artificial General Intelligence is not far from reality and that in perhaps 5 years, maybe slightly longer: 

“95% of what marketers use agencies, strategists, and creative professionals for today will easily, nearly instantly and at almost no cost be handled by the AI … images, videos, campaign ideas…no problem”

However the proliferation of AI agents across the Martech will happen before this, perhaps in 1-2 years from now.  This is a hugely exciting time for Retention, CRM and Product Marketers. In a future where you are submitting a prompt to build an entire lifecycle journey, key skills will be prompt engineering and strategy, since your ability to write a prompt to meet your needs will determine how efficiently you are able to work, while your strategy skills will determine how well you are able to vet the AI’s output. 

Final thoughts

While we are not there yet, AI will very soon create emotionally engaging, highly personalised content at scale, drastically enhancing customer engagement and retention. Very soon, AI Agents will automate and centralize the entire customer journey, crafting personalized experiences across all touchpoints. AI Agents will identify key customer behaviours and tailor interactions accordingly. As a retention marketer, honing skills in prompt engineering and strategy will be essential to fully leverage AI's potential.

Stay tuned for future episodes as we explore AI's impact on customer support and predictive analytics.