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CoffeeHQ

Coffee-maker selector methodology

The coffee-maker selector is a fixed, rule-based scoring system — not an AI model, not machine learning, and not a black box. Every point added or subtracted comes from an explicit rule comparing your answers to a coffee maker's own published attributes (convenience level, cleaning burden, space requirement, and so on).

How scoring works

Each candidate starts at zero. Your answers about budget, priority (manual control vs. convenience), cleaning tolerance, counter space, noise sensitivity, speed needs, bean format, drink preference, household size and portability each add or subtract a fixed number of points from candidates that match or conflict with that answer. A close-but-not- exact match (for example, a coffee maker one budget band away from yours) scores a smaller bonus than an exact match, rather than being excluded outright. The candidate with the highest total is the top pick; the next two highest become the alternatives shown alongside it.

Every match is explained

Alongside its score, every candidate accumulates a list of matched reasons (why it scored well against your answers) and tradeoffs (where it falls short of what you asked for). Both lists are shown in the results — the recommendation is never presented as a bare verdict without the reasoning behind it.

Deterministic and reproducible

The same answers always produce the same recommendation. Where two candidates score exactly equally, the tie is broken by a fixed, consistent ordering rather than left to chance, so results don't reshuffle between visits.

When there isn't a strong match

If even the top-scoring candidate scores low, the selector says so explicitly rather than presenting a mediocre match with false confidence. That usually means your answers describe a combination of priorities (for example, wanting maximum manual control and maximum speed at once) that no single coffee-maker category satisfies well.

What this deliberately does not do