Strategy
Most product selectors are built around what a machine does. Rika's view was that the more useful question was who the customer was. Someone who doesn't yet know the difference between a bean-to-cup and a manual espresso machine can't answer a question about technical features meaningfully. But they can tell you whether their mornings are rushed or relaxed, and whether they want coffee that feels made for them or coffee they take pride in making themselves.
Emotional and lifestyle questions came first, coffee preference, morning routine, personal interests, before budget or features. The result felt like a recommendation from someone who understood the user, not an algorithm that had processed their inputs.
Underneath, a decision matrix upweighted and eliminated machines based on cumulative answers until an optimal result emerged. The tool surfaced a primary recommendation alongside alternatives, giving users enough choice to feel in control without undermining the confidence of the result.
Insights
De'Longhi's own purchase decision data showed that appearance and brand reputation outranked price and technical characteristics among buyers. People were making an emotional decision and then justifying it rationally. The tools available to them, including the existing selector, were built the other way around. Asking someone what kind of coffee drinker they are before asking what they want a machine to do produces a more honest answer, and a more accurate recommendation.
Approach
Decision matrix and question design. Rika developed the logic engine first, using the Pugh Decision Matrix as the basis for mapping eight questions against six core machines and twelve alternatives. The matrix upweighted and eliminated options based on each answer, designed to reach a confident recommendation regardless of the path taken through the quiz.
Microsite. The tool launched on a dedicated microsite, delonghicoffee.com, with a results page designed to give users what they needed to move forward: a clear recommendation, the reasoning behind it, and a direct route to the product page or further information.
Facebook and Instagram app. The tool was adapted as a Facebook and Instagram app, extending the experience to audiences who weren't actively searching for a machine. Where the microsite captured people already in the market, social reached people at the point of interest rather than purchase intent.
Paid media. Google Search and Display drove traffic to the microsite, while the Facebook campaign supported the app. A top-of-funnel campaign built around novelty coffee drinks, Cold Brew, Flat White, Nitro Coffee, proved particularly effective, meeting people at their interest in coffee culture before introducing the range.
Creative theme
Choosing a coffee machine isn’t simple however we framed the decision around a simple question: do you want coffee made for you, or made by you? This became the foundation of the experience, shaping the journey and guiding users towards the right machine.
Deliverables
- Selector Tool UX & Interaction Design: Design of the full user journey, including question flow, decision logic, and results experience to guide users towards a clear recommendation.
- Decision Matrix & Scoring Logic: Development of the underlying model mapping user responses to machines, weighting and eliminating options to produce a credible outcome.
- Microsite Design & Build: Creation of a dedicated, responsive experience with tailored results pages and clear routes to product exploration and purchase.
- Social App Adaptation: Adaptation of the tool for Facebook and Instagram to extend reach and engage users earlier in the decision process.
- Paid Media Campaign Delivery: Planning and execution of Search, Display and Social activity to drive traffic and engagement across all touchpoints.
