Every little helps: Tesco's big data-driven strategy

The poster-child of data-driven retail experience

Tesco initially was a down-market, whose strategy primarily focused on cost leadership. However, this all changed after the firm realized that through the integration of data-based assessments into their everyday decision-making, they can open a new route for differentiation strategy. In this case, differentiation occurred in comparison to their own products, not to their competitors.

The first inductor was the introduction of Clubcard, which was mostly used as a loyalty scheme, a product similar to the ones offered by Tesco’s competitors. It was not valued highly on the market, but Tesco realized that by using their Clubcards customers were emitting rich data about their purchasing behavior. This made two-thirds of the customer’s shopping baskets transparent for Tesco.

After realizing the potential in the application of big data, Tesco slowly started to integrate it into every field of their business. To create a stable basis for their data collection, Tesco had to find a place to store them. The solution Tesco chose was the Hadoop framework, which is a cloud-based data repository. It allowed efficient and organized data storage in large volumes, moreover, it was easily accessible for all departments.

Source: BBC.co.uk

Achieving operational efficiency through big data

Big data appeared on many levels within Tesco. The first segment, on their operational fields. By establishing Internet of Things (IoT) sensors around the stores, Tesco managed to increase the efficiency of energy consumption, through the continuous monitoring of the heating and lighting. Moreover, sensors enabled the company to monitor which unit of in-store fixed asset needs potential service or replacement.

Customer understanding and purchasing behavior prediction

The second segment, which was heavily affected by big data, was the pattern recognition of customer behavior. Through analyzing historical data Tesco could forecast the prospective months based on last month’s purchasing behavior, the seasonal trends, and the weather. In certain regions, they could precisely predict that the percentage of sales of barbecue meat, lettuce, and coleslaw would go up depending on changes in temperature and weather. An essential tool, when managers wish to plan the supply of goods in order to minimize the bullwhip effect.

Customer segmentation as never seen before

The third segment, where Tesco successfully integrated big data, was in the field of customer segmentation. Through data analytics, Tesco regrouped its customer base and could offer new products for the newly formed clusters. Up until this technological innovation, Tesco utilized the traditional modes of segmentation, such as demography, geography, and behavioral traits of the customers, which was vague and overly simplistic. By utilizing big data, the company could unfold layers of customers with niche demands within their original segmentation. For instance, the upmarket with their Tesco Finest product line or health-conscious customers with the Tesco Healthy Living product line. Tesco also introduce loyalty programs providing the customers an experience that made the visit to Tesco’s stores more engaging.

So, what went wrong?

Despite the pioneering adaptation of data analytics into their daily operation, Tesco’s success faced a downturn and a halved market capitalization sourcing from three different challenges that Tesco failed to overcome. The first challenge was that new discount stores such as Lidl and Aldi convinced the price-sensitive customer layer of Tesco to switch from the well-known brand. Even the second to none data analytics could not stave off the competitive advantage of slightly lower prices. The second challenge was the inefficient communication of their newly introduced programs causing complex customer journeys and deteriorating brand perception. The third challenge Tesco failed to tackle was the effective utilization of the customer data. They lacked the imagination and innovation to truly grasp the merits of data-driven customer segmentation resulting in a stagnating share. A sword is only as good as the man who wields it.