At the heart of every customer-centric organisation lies a solid data foundation. This foundation, often a combination of tools, processes, and strategies, allows businesses to capture, store, and analyse data effectively. It drives strategic decision-making and enables advanced personalisation, optimised targeting, and cross-channel customer experiences, to name a few.
Today, with abundant information flowing in real time from multiple touchpoints such as mobile phones, in-store point-of-sale (POS), and e-commerce, it is clear why every modern business wants to capture and analyse data more effectively than ever before. But now, with all this data on hand, how can companies leverage it?
In this blog, we delve into the success stories of Halfords, M&S International, and Crew Clothing. We explore how they strategically built and leveraged their data foundations through a “use case by use case” approach, leading to them achieving remarkable outcomes.
Want to learn how to fix your customer data issues for good? Check out our guide for marketing leaders.
Halfords
Use case: Data-driven personalisation
Halfords engages with its customers both online and in-store as an omnichannel retailer. Hence, for their marketing team to drive engagement and sales with real-time omnichannel personalisation, they needed to have a strong foundation of unified and accessible data in place.
This foundation allows marketers to deliver hyper-relevant personalisation exactly when (and where) it matters most and create outstanding customer experiences that keep shoppers returning for more.
To achieve this, Halfords assessed a few specific factors within their data foundations, such as their brand’s requirements, audiences, and data capabilities—from data breadth to data depth and from integration to latency. By having a robust foundation of unified customer data and the right technology to leverage data to their advantage, Halfords successfully delivers consistent and personalised messages to all its customers—even at the till. So, let’s uncover how they achieve this by looking at some of the essential requirements that make up their robust data foundations.
With customers expecting seamless and tailored experiences across numerous channels (email, e-commerce, apps and more), having a comprehensive view of your customers is crucial. Failing to deliver these experiences will likely cause your customers to seek brands that provide a better experience. Halfords had to ensure they designed their data foundations into centralised data points from various sources, from behavioural to transactional and online to offline. By mapping out all of their data sources, their marketing team could assess different areas of interest like customer profiles (demographics and contact information), transactional data (online and in-store), channel behaviour, including website and app behaviour (both known and anonymous) and more, giving them better insights and analysis for real-time web personalisation.
With all available data matched to a profile and flowing into a connected view, Halfords’ next step was to ensure their data foundation had the power to capture intent signals as they occurred and orchestrate experiences based on those signals. Intent data enables them to analyse real-time activity and tailor product recommendations to thousands of customers each week.
Coming to resource management, thanks to Unilyze, our AI-optimised, real-time data platform that supports flexible, low-effort configuration, Halfords could bring in data in its raw format, allowing teams to ingest their data from multiple sources without the requirement for manual transformation.
Overall, this success story demonstrates the power of unified data in delivering personalised, omnichannel experiences. By building a robust, fit-for-purpose, and future-proofed data foundation, Halfords not only improved the shopping experience but also empowered employees to provide informed assistance at each step of the customer journey, resulting in increased engagement and sales.
Read the complete case study for more details.
M&S International
Use case: Campaign targeting and optimisation
M&S International wanted to assess its promotional strategies, providing its customers with the best offers that incentivise them to make a purchase. The goal was to leverage all of its customer data to create actionable insights and enable its marketing team to tailor campaigns more effectively, which begins with having a solid foundation of unified and accessible data in place. Let’s discuss this approach in more detail, considering the critical considerations within M&S International’s data foundations.
M&S International began by unifying its customer data into a single source of truth, which involved mapping out all its data sources, such as customer profiles, demographics and contact information, transactional data (online and in-store), website behaviour, promotion uptake, and more. Its data foundation also allowed for data depth, which provided its teams with a full historical view of each customer. With this large data storage capacity, M&S International was able to utilise as much data as possible to train predictive models and AI, identify unique lifecycles between the targeted segments and build on their retention strategy. Furthermore, having the right data matching capabilities allowed marketers to match that data to known customers across the targeted segments, giving them insights into the best offers that drive the highest purchase frequency.
With data unified and accessible, all it required was some analysis. We deployed our Future Value Model (FVM), to predict a customer’s future value based on their past behaviour and interactions with the brand. It allowed M&S International’s marketing team to ensure their promotions were driving the highest incremental spend across different value segments, increasing the value of their lower value customers whilst maintaining high value customer trajectories without overspending.
A solid data foundation ultimately enabled their marketing team to develop a forward-looking, actionable, holistic, and nuanced view of the customer. This allowed them to tailor promotions effectively across customer segments and drive incremental value across the board.
Read the complete case study for more details.
Crew Clothing
Use case: Self-serve insight and analysis
Crew Clothing wanted to use real-time data collection to gain insights into customer behaviour during Black Friday. However, to easily access and analyse customer data when required, it was critical for them to have the right foundations in place.
Like Halfords and M&S International, Crew Clothing needed the right foundational platform and had to consider key data requirements within its data foundations. First, it had to combine customer data from all sources — no matter how disparate and no matter what format—into a continuously updated Single Customer View (SCV). By doing so, teams could gain a comprehensive and unified view of each customer in one place, setting the foundations for extracting customer insights quickly.
However, while collecting, storing, and matching customer data is vital to building a solid data foundation, data’s value is only impactful if teams across the business can act on it. Therefore, data accessibility was a key requirement for Crew Clothing. With practical, real-time data such as spend by channel, average sale value, sales by category, and more displayed throughout the day on intuitive dashboards and reports, the business could make quick, informed decisions and leverage the data and insights to their fullest.
Furthermore, given that “proving the value of customer marketing” is the top cause of stress for senior marketers, it was great to see how the CRM and marketing teams could now prove channel impact and monitor category spending, enabling them to optimise their campaigns even further to achieve the best results and impact the overall business strategy.
Read the complete case study for more details.
Conclusion
The success stories of Halfords, M&S International, and Crew Clothing underscore the transformative power of establishing robust data foundations.
In the end, it comes down to understanding that each business has different data requirements and use cases. For instance, Halfords, with its abundance of in-store and online data, prioritised low-latency updates to deliver real-time experiences which allowed them to swiftly implement tailored product recommendations to thousands of customers. For M&S, their priority was to optimise promotional spend whilst boosting projected future spend across customer segments. Crew Clothing prioritised robust matching capabilities to ensure online and in-store behaviour can be linked to individual customers, allowing them to make data-driven decisions on the fly.
When considering which use cases will have the most significant impact on the brand (both immediately and in the future), marketers can focus on the most essential requirements for their data foundation. Ultimately, these cases show how harnessing the potential of data integration, real-time analytics, and predictive modelling can optimise operational efficiency and elevate customer experiences, all achieved when your core data foundations are in place.
If you are still trying to figure out where to begin with your brand’s transformation to becoming customer-first or want to embark on a similar journey of data-driven success and fix your customer data foundations for good, check out our latest guide or get in touch with our solutions experts today.
