Episode 32 - Personalisation, Growth and AI

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📰 Top Story: Personalisation, Growth & AI

Why Is Personalisation Important?

The number one reason brands fail to retain customers is because they don't feel you are a brand for them.

Sometimes, your value proposition may not align with their needs. But, one unforgivable reason is forgetting to personalise the experience for the customer.

There is loads of data demonstrating why personalisation is so important. For example, McKinsey shows that 71% of customers expect brands to understand their preferences and tailor their experiences accordingly. 

And that is the crux of it. 

Customers expect you to provide relevant information that helps them achieve their goals because, ultimately, the key to customer retention is helping them achieve their desired outcomes.

So, if you share uncurated experiences or irrelevant information, in the best case, the customer will ignore it, and some will opt out. In the worst case, customers will start to feel that you are not a fit for their needs. 

Key Personalisation Dimensions

There are four dimensions to personalisation: content, timing, channels, and frequency. 

Content Personalisation 

When most people talk about personalisation, they talk about content. 

There are essentially three key elements to content personalisation:  

• Cohorts: What you know about customers' interests, preferences, habits and lifestage.  

• How to execute personalisation content leveraging content feeds and tailored emotionally resonant messaging. 

• Moments of Truth: What you know about the customer’s likely journey outside and inside of interaction with your brand.  

There are key principles that help you to respond effectively at key moments of truth; some of these have been covered before in previous episodes of this newsletter, but what makes a critical difference at moments like onboarding, usage declines, or the cancel journey is personalisation.

Timing Personalisation 

Rather than operate to your business's desired cadence (e.g. regular Tuesday email), it can be highly effective to leverage customer-level data to ensure messages arrive at the most relevant time for each customer.  

This, of course, overlaps directly with moments of truth since it's about ensuring you drive the right content to the right customer at the right time to help the customer achieve their desired outcomes. 

Data inputs to send time personalisation can include: 

1. Historical behavioural analysis of previous engagements by the customer. However, if you have typically operated standard send times, you may need to conduct some timing tests to identify this accurately.  

2. Historical analysis of customer behaviours: when does the customer typically engage with what you wish to promote or undertake the action you want the customer to take? Does a specific e-commerce cohort usually buy on Saturday afternoon, or does a streaming customer cohort typically watch on the weekends? 

Channel personalisation 

If a customer doesn't open your emails, click on your push notes, or engage in your in-app messages, it is potentially not a channel they wish to engage with.  

The benefit of excluding a customer from a channel is to protect against any future all channel opt-outs.  

But it takes time to assess this, and exclusion of a customer cohort from a specific channel should only occur once you have a high degree of confidence that they are unlikely ever to engage.  

Frequency Personalisation

In some sectors (e.g. gambling or e-commerce), the more messages you send to each customer, the more sales/engagements you get. 

Hence, some brands bombard their audiences with messaging to maximise short-term revenues.  

However, while more messages drive increased sales and engagement, it will also increase unsubscribes.  

The key is establishing engagement frequency models to identify the maximum number of messages per cohort by period and optimise frequency accordingly. 

When you do this, you will often find specific cohorts require less communication while others need more. In most cases, this will result in a net increase in total communication send volume and associated impact. 

Personalisation & AI

The dream of one-to-one personalisation has been around for a couple of decades. While brands like Amazon, Tesco, Netflix, HBO, and DAZN have set the benchmark for delivering hyper-relevant content to audiences, this has typically been based on flat content modules that are merely descriptive. 

With generative AI, brands can create their LLMs from their master content, which includes everything they know about their business, products, and customer motivations. Then, leveraging AI Agents, brands can create content that is relevant, emotionally engaging, and hyper-personalised at scale. 

All while delivering the most appropriate frequency, timing and channel priorities according to predicted customer behaviours at an individual customer level. 

Think dynamic, hyper-relevant, emotionally engaging journeys built just for you.   

I have seen brands demo CRM Marketing journeys delivered with a prompt (see Airship, Netcore cloud) while others have built AI-driven decisioning (see Optimove, High-Touch). 

Case studies

Doom scrolling is a big issue for Netflix, which is why they put so much effort into personalisation. Netflix's personalisation strategy focuses on delighting customers through highly relevant personalised content recommendations, including trending and most popular content. This is executed within the product and across CRM Marketing. 

HBO Max found that most customers watch movies on the weekends and series during the week. However, one segment does the opposite, and HBO Max tailors product content according to customer behaviour and content preferences. 

Final Thoughts 

Personalisation is a key differentiator for effective retention. By tailoring content, timing, channels, and frequency to align with customers' needs, you can maximise your chances of helping them achieve their desired outcomes. 

Focus must be placed on moments of truth to maximise customer and commercial outcomes.  

As we enter an era in which generative AI takes personalisation to unprecedented heights, brands that invest in understanding their customers and deliver hyper-relevant experiences will gain a competitive advantage.

Watch or listen to my conversation with Rasmus Houlind for the Hello $Firstname podcast to explore some of these concepts in more detail. Also if you want to dive deeper into personalisation, I recommend following Rasmus for personalisation strategy and Frans for AI & technology strategy. They have also produced a brilliant book.

Until Next week, 

Tom

Do you need help with Customer Retention?

When you are ready, contact me to discuss consulting, my fast-track retention accelerator, courses, and training. Or if you are interested in sponsoring this newsletter, get in touch via [email protected]