Tackle customer strategy through data: 7 key steps to drive growth

In a competitive landscape, customer analytics and customer centricity are vital for driving growth and enhancing experiences. Yet, many brands limit analytics to marketing or email campaigns, missing broader opportunities.

By leveraging customer lifetime value (LTV) and focusing on data-driven strategies, brands can move beyond narrow metrics to make impactful decisions. This paper presents a step-by-step approach to embedding analytics into business strategy, unlocking sustainable growth through actionable insights and optimized customer experiences.

1. Dive into your customer data…

…to begin your customer understanding. This is the first step to building your customer analytics maturity and allows you to start making sense of who your customers are – e.g. where and how they shop, what makes them loyal, or not. You may be able to build an initial ‘actionable segmentation’ from the outset. An actionable segmentation uses existing known attributes to describe the differences between segments.

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2. Identify and prioritize your use cases…

…to drive the strategy forward. Involve vertical experts and cross-functional teams to consider use cases from awareness to acquisition, retention to advocacy. With your current understanding and direction of travel, you can design a program to implement a customer-centric approach.

3. Design customer strategies…

…aligned to your brand promise and the opportunities identified through your data. Ask ‘what type of customer should we be acquiring?’, ‘what experience of your brand should you give them throughout their journey?’, ‘what perception do you want to leave them with?’.

4. Set the data foundations…

…to facilitate the deployment of analytics capabilities and strategic use cases. Think about data capture, structure and governance; building up these capabilities in a way which supports your long-term vision is essential. To fast-track this process, make use of tech accelerators.

5. Advance your customer intelligence…

…to enable optimized and anticipatory outreach; longer-term thinking to build on the potential of your client base is essential to the deployment of next best experience. For example, propensity and behavioral scoring models can be used to understand and predict a customer’s likelihood of buying a product, returning a product, leaving to competition, basket size and more.

6. Industrialize your approach…

…with live and dynamic model outputs. By moving to always on scoring and optimization, with data visualization to bring customer data to life, you can both automate and animate customer analytics. With the sheer quantity of datain play, advanced analytics and machine learning can support automation.

7. Democratize insights

It’s essential to onboard all teams, from the concept of customer centricity to sharing the insights that are relevant to them achieving it. Gain their trust through transparency in how the models are built and the value of the resulting actionable analysis in driving high-level strategies. Dashboards will help to standardize and make accessible the basis for decisions for colleagues from finance, to supply chain, marketing and analytics.

Discover how to unlock the full potential of customer analytics and drive growth. Explore our expertise here: Customer Analytic Solutions.