Why a customer data strategy will help you outperform competitors



Creating a competitive customer data strategy helps you understand and retain your customers by enabling you to offer a better service and a more engaging experience. No surprise then, that companies focussed on effectively using data to deliver ‘better’ and ‘more engaging’ are more likely to outperform the market.


Companies with extensive use of customer analytics outperform their competitors.


How to get Started

Creating and implementing a customer data strategy can seem complex, but if you stick to these principles, you’re on the right road.

  1. “If you don’t know where you are going, any road can get you there”, so start by defining what the business objective is. What are the key challenges you want to solve with data insights; retention, growth, acquisition? It helps to define the desired future state for your enterprise; best customer retention, highest lifetime customer value…

  2. Break your vision into steppingstones – smaller initiatives, one at a time. This lets you flex your strategy as new capabilities emerge.

  3. Focus on key pathways and stakeholders, this includes CX, operations and systems. People, culture, and processes all need to evolve together.

  4. Start by differentiating High Value, Medium Value and Low Value customers, and their respective behaviours to deliver impactful ‘Quick Wins’ such as onboarding; frequency / seasonality; spend stretch.

  5. Incorporate the characteristics of your business category to understand customer clustering and department preferences. Test potential for cross-sell e.g., category-specific offers vs. cross-sell offers.

  6. Develop a richer view of the customer with additional data, segmentation, incorporate qualitative (demographic, attitudinal) and quantitative (value, share of wallet) inputs, and potential enrichment with data from external sources.

The Key Skill for Success…

In our white paper ‘the critical skill for a data led culture’ we discussed the 5 stage journey companies typically go on when implementing their data strategy. We also pointed out that the key skill to be successful is storytelling.

Storytellers are critical employees on this journey – we recommend you develop team members to become great storytellers or hire them into your team. We call these people 'boundary-spanners', people with a foot in both the tech and management domains who can make each relevant to the other. A summary of the 5 stages;


1. Sprouting

Interest in data analytics often comes from junior management who demonstrate to the Executive team that a data-driven approach to marketing could be profitable. Storytelling and education are required for these sprouts to take root, a balance of raw knowledge and enthusiasm with experience and perspective of the wider business makes for the best storytelling.


2. Recognition

Increase the intensity of data-led storytelling – painting the picture of ‘what good looks like’ but this time based on facts from your own experiences and testing new activity. Move the stories from conjecture and the hypothetical to ‘we found this and therefore can project…’ to rally support for the cultural changes that are yet to come.


3. Commitment

At this stage, management has ‘got it’ and demonstrates strong support for data initiatives, funding data warehouses and staffing that includes analytics professionals and consultants. The ‘proof of concept’ phase is over, and management can see the returns on offer. This is also the stage where data analysis becomes an organisation-wide priority, not a project in Marketing.


4. Culture Shift

If the organisation has an appreciation of analytics and its potential, the final step is a cultural change1, highlighted by the shift of data analytics from descriptive to predictive, and the presence of Data Scientists in the team. There is a word of warning at this stage; do not forget the importance of your brand in the relentless drive for short term ROI and do not succumb to the ‘Street Light Effect’2 where analysis is limited to areas where you already have good data.


5. Data-driven Marketing

Is achieved when ‘customer equity faithfulness’ is achieved; that is, each customer is treated according to their profit potential. To outperform your competitors, neither culture nor technology is enough on its own. The combination of technological capabilities with robust underlying processes and skilled human resources will ensure you are on your way.


At the heart of any customer data strategy should be Customer Science®, Ellipsis’ proprietary methods and data-driven insights to grow customer value and optimise performance. Customer Science® uses data and insight to identify your customers’ changing needs, creating real value and measurable results.


We are Ellipsis, the Loyalty Experts. We help you measure, manage and grow customer loyalty​. We’re here to help, please get in touch



  1. ‘How to build a data-driven company’ Sara Brown. September 4, 2020
  2. Named after the joke where the drunk is looking for his keys at night and is asked, ‘did you lose them here?’. He answers, ‘No, I lost them over there, but the light is better here by the streetlight’.
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