SimIT Web in action: strategic use cases
The following use cases demonstrate how simit Web transforms raw shopper data into strategic insights that drive tangible growth. Whether from the viewpoint of a retailer or a brand, these examples show how behavioral data can uncover hidden potential and guide smarter decision-making. Each case illustrates a distinct challenge and how it was addressed through precise, data-informed strategies.
Use case 1: Retailer Perspective Hot Beverages at Retailer X
Retailer X, operating in a competitive grocery market, sought to expand its Hot Beverages category. Traditional sales metrics painted a static or even declining picture for several subcategories, particularly Instant Coffee and Tea. At first glance, roasted coffee appeared to be the only bright spot, showing significant year-over-year growth. However, Retailer X’s category managers wanted to ensure they were not simply chasing yesterday’s success but were instead identifying where tomorrow’s growth could be found.
Enter SimIT Web. By analyzing shopper data, the tool uncovered a counterintuitive insight: while roasted coffee had grown rapidly, there was still room to grow further, particularly through capsules, a subcategory that showed lower sales performance but high behavioral indicators for future potential. The data showed that capsules were being purchased by a segment of older consumers, Empty Nesters and Pensioners, who were underrepresented in Retailer X’s capsule category sales. These households had a high affinity for capsule formats, including both Nespresso-compatible and non-compatible varieties, and represented a gap of approximately €1.3 million in potential revenue.
Empty-Nesters and Pensioners are the key to capsule growth — Nespresso and beyond.
Additional Value at Retailer X by household type and capsule format
Value Potential in Euros (x 1,000)
Young Households w/o Children
Middle Aged Households w/o Children
Families
Empty nesters
Pensioners
⬤ Nespresso Incl. NCC (Capsules) ⬤ Not Nespresso-Compatible Total (Capsules)
What Retailer X discovered was a classic case of misalignment between sales trends and shopper potential. Capsules were not underperforming due to a lack of interest but because the retailer had not effectively converted or activated the most promising shopper segments. This revelation enabled Retailer X to refocus its strategy: remerchandise the capsule offering, target marketing to older households, and prioritize brands that resonated with these consumers — such as Nescafé, l’Or, and Jacobs. This move positioned Retailer X not only to protect its gains in roasted coffee but to expand them by pulling adjacent categories up alongside.
Use Case 2: Brand Perspective — Coffee Brand A at Retailer Z
In the second scenario, a leading coffee brand, referred to here as Brand A, was confronting uneven performance across its retail partners. At Retailer Z, Brand A had experienced a decline in espresso sales, prompting concerns among its category team. Sales figures alone suggested that Retailer Z might no longer be a viable growth partner for espresso. But Simit Web told a different story.
Shopper data revealed that the issue wasn’t a lack of demand but rather a loss of access. A partial delisting of Brand A’s espresso line at Retailer Z had led many loyal shoppers to purchase their espresso elsewhere. Interestingly, these customers did not abandon Brand A, they simply found it at other retailers. This indicated a resilient shopper base with unmet demand within the Retailer Z ecosystem.
Further analysis highlighted that the core segment behind this untapped demand was older households without children, the same group driving capsule growth in the previous use case. The data showed that Retailer Z’s strategic cutbacks had improved loyalty and value potential among remaining espresso buyers, but left significant money on the table. Specifically, there was an estimated €0.6 million in unrealized value, representing a missed opportunity for both Brand A and Retailer Z.
The espresso gap at Retailer Z = €0.6 million in untapped value.
Matching Roasted Coffee’s performance unlocks major revenue upside.
⬤ Value in store (000 EUR) ⬤ Additional value in % ⬤ Possible total value in store (000EUR)
Armed with this insight, Brand A could re-approach Retailer Z not with a generic push to increase shelf space, but with a data-driven proposal. This included reintroducing espresso formats tailored to older shoppers, repositioning promotional efforts, and optimizing the in-store experience. Importantly, Brand A could also quantify the “size of the prize,” presenting a compelling business case for renewed collaboration.
These two use cases illustrate how simit Web allows stakeholders to move beyond reactive, surface-level analysis. It empowers them to uncover nuanced, behavior-based opportunities; whether it’s finding white space in an existing category or recovering lost ground through strategic realignment.