In a recent panel webinar event hosted by InPublishing, Acrotrend CTO, Shailesh Mallya, shared his insight into how companies can use data to optimise subscriber retention. He’s spent the last five years helping large media and publishing companies work with their customer’s data, technology & people to help them acquire, retain & engage with their customers. Here’s what he had to say:

Can you give us one example of a data driven insight that helped drive retention?

We’ve devised an affordability score primarily for the customers who are about to churn and created an affordability matrix, so you can select customers to target effectively and have a better shot at retaining them.

Using data to better understand churn

What are the things publishers need to put in place to be in a position where they can use their data to improve their understanding of churn?

There are three things publishers can do. The first point I’d say is creating all necessary checkpoints and capturing the relevant data in the customer journey. Next, monitoring your engagement metrics based on your relevant digital channels within an engagement health dashboard. Finally visualizing with a simple dashboard customer renewal and retention rates at a cohort / segment level to take specific actions.

Can you give us a top tip for how publishers can use data better to understand churn?

Focus on how customers interact with your product across your key channels to understand their content engagement pattern to give you a better view on why they are about to churn. The latest unresolved customer service issues are some of the hints indicating what could have possibly led to churn.

Organising data to spot (and predict) changing customer behaviours.

In terms of how publishers organise and manage their data, what should publishers be trying to do?

One area that is often neglected is definition and agreement on data. In other words, data literacy. I am often surprised by the different answers I have got when I’ve asked a simple question – can you define your customer? The key definitions must be agreed by the key stakeholders, and then you’ll need to educate teams who will utilise that data.

The same is true with your metrics and KPIs. The calculations must be consistent and agreed between different functions.

Structure and model your data appropriately. I usually recommend focusing on customer centric data models, so all data is ‘centred’ around your customer.

There is a range of data that can be collected, and we often hear teams complaining there is too much data for them to manage. It is imperative to identify and focus on data that is relevant for your high-value use cases.

Can you give us a top tip on how publishers can use their insight into customer behaviour to improve retention?

Look at engagement patterns with your content in terms of RFD (recency/frequency/duration). This can give your tremendous insight into improving retention by providing the right actions.

The role of data in the end-to-end journey in subscriber retention

Subscriber profiles are typically built by stitching various data sources together. What can publishers do to ensure the dots are properly joined?

We understand the shortcomings of not having third party data at our disposal, so it is important to enhance the first party data strategy by capturing data consistently through the customer journey, right from the time a customer might be unknown or a registered user or a prospect.

But, first party will not be enough, so that must be enriched with third party data. There are techniques and technologies available to enrich your first party data securely keeping GDPR in mind of course!

Can you give us a top tip on how publishers can use customer journey insights to boost retention?

Insights are one part of the solution. Once you have them – the question is now what? What do you do with those insights? This is where actions come into play. It is essential to define the actions throughout the customer journey wherever you derive an insight or a set of insights.

Segmenting subscribers to quickly personalise journeys and prevent churn

Once a publisher has created a set of subscriber segments, how should they then manage, fine-tune and evolve them?

Customer segmentation is an evolving process, and it is the bedrock of personalisation. It is simple in the sense that is a cycle. The more we engage with customer based on segmentation, the more relevant data we collect. And we understand the customer in depth and personalize their experience.

You will end up collecting behavioural and psychographic data for customer segmentation.

And the key to effective evolution is to frequently test, measure & optimise value of your segments.

Can you give us a top tip on how publishers can best use segmentation to improve retention?

Personalise and test your offers, proactively where you know customers are about to churn and personalise content based on their interests and categories.

Making tech and data work together to deliver better insight

How can artificial intelligence / machine learning be used to optimise retention performance?

One area where AI / ML can be effective is pre-emptive churn mitigation. This is where you can use models whereby you can know if the customer is about to churn and why they would do so even before the customer knows it. Of course, to make this a reality, besides AI/ML, it typically requires your first party data to be potentially enriched with third party data.

And then there are other possibilities placing personalised content or trying out new content with the subscribers. In the current economic scenario, optimising the price for subscribers who may be price sensitive.

In our view, the sky is the limit when you combine AI/ML with the data.

Can you each give us a top tip on how publishers can organise themselves better to improve retention?

Given the opportunities publishers have with their content, my top tip would be to create of strong collaborative teams especially to retain customers. I often recommend creating cross functional teams to target the high value retention use cases. Set up the right set of processes to enable the relevant people with tech & data. Have access to the right retention metrics and KPIs for the teams to take informed decisions.