Personalisation as a Process

Customer centricity and personalisation are heavily discussed these days, more so than ever before. But most organisations work round internal structures rather than customer needs, so how can we change that? 

When it comes to customer centricity, it can be split into: 

  • The Reality (of being commercially focused) 
  • The Holy Grail (truly putting customers at the heart of your CRM strategy) 

Most organisations are firmly in reality, so if you’ve not reached Holy Grail stage – you’re not alone! Most companies have pockets of customer actions that are captured and multiple data systems driving different parts of the CRM Strategy – and you’ll often find that they rarely work together! 

In e-commerce, for example, I still see there’s a commercial focus rather than a customer centric focus in CRM strategy. CRM stakeholders work in silos, usually focussed on channel performance, promoting certain products and focussed on one-to-many, week-to-week campaigns. 

The biggest challenge this will cause is that KPI’s become insular and result in internal commercial competition, rather than external collaboration for the benefit of the customer. 

There may well be areas of CRM optimisation and good practice in journeys across acquisition, retention and win-back etc., but by not treating personalisation as a process, these journeys will always be inconsistent. Inconsistency is the antithesis of personalisation. 

To gain a greater control of consistency, the focus should be on becoming best in class when it comes to being truly customer centric in personalised CRM. 

So how do you define the steps in the personalisation process? 

There are four core categories of strategic capability that are needed to enable truly customer centric personalisation: 

  1. CRM Data Application 

Action Capture 

Allows you to capture actions from each touchpoint so it can be attributed to an identifiable person. This will create an understanding of the attributable motivation for the engagement; if a call to action leads to engagement, what the action related to, how long the interaction lasted, which content is it related to, etc. 

Content Engagement Attribution and Delivery 

Let’s you track and serve messages and brand experiences that support all customers and provide experiences they would recommend to others.  

  1. Customer Journey Execution 


Testing different variations of content, messaging and CTAs allows you to see what influences the next best action. This gives you the ability to select the best performing combination and apply it to all subsequent relevant engagement. 

Customer Journey Orchestration 

This will allow you to define customer contact rules that connect all technology and systems enabling you to provide personalised customers experiences wherever they are in their journey, across all devices, in sequence. 

Next Best Action Strategy 

This will let you define rules to determine the most appropriate action to take for a specific customer, selecting the right message, personalisation or experience from all the possible options. 

One-to-Many Segmentation 

Use logic to allocate records to specific journey groups or target communications/experiences. For example, “Any customers who have transacted in between 31 days and 60 days ago, spending between £50 and £150, who have not transacted since” – this micro segment could then be used to allocate them to certain communications, personalisation, or automated journeys to try to influence specific cohort engagement. 

  1. Data Science 

Analysis that Curates Actionable Insight 

By building diagnostic and predictive analytical models you can clearly show why an action or engagement occurred. (For example, a recommended personalised product failing to create an engaged action from the segment it was targeted at). Use that insight to be able to predict what’s most likely to happen next based on previous data – this is insight that is actionable in its truest form. 

One-to-One Segmentation 

By using data science to attribute against the singular customer view (SCV) to overarching groups/cohorts you can bring together people with similar characteristics based on the data held about them. For example, where customers are allocated to high, medium or low life time value segments based on their anticipated value to the brand. 

  1. Customer Data Strategy 

Unified Person Record 

Assembling your data into a single view of the person by applying matching and merging processes that can be optimised through gathering learnt, asked and given data. Allowing you to personalise a customer’s experience, in the most meaningful and timely way. 

CRM Data Enablement and Alignment 

By combining a deeper understanding of customer needs, behaviors, and value with tech, you can communicate with customers with the right message, at the right time across all touch points. 

Customer Centricity in CRM, in Summary 

Personalisation should be a process that captures every customer interaction; where every new journey is optimised through an automated personalised next best action – either unified in one platform or shared across separate martech applications. The next best action should be the next best action for the customer and the business, with the customers needs coming first. 

By aiming for this “North Star” of dual-purpose next best actions, the process starts to become an organic, in-built, organisational customer centric focus that dictates customer journey design.  

Measurement frameworks can be created to reinforce an obsession with cross-organisational, unified customer centric experiences. Put simply, I mean showing what journeys are working and having a clear understanding of why they are working – then having a crystal-clear, data driven methodology of how to do more of it!  

This is what CRM strategists like me mean by moving from one-to-many, to one-too-few to one-to-one CRM. 

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