1. Lighthouse

Level 1 · Frame the slow movers question

The request

From Thomas Whitaker, Head of Merchandising

“Debra in the warehouse says we're full of stock that barely moves. Before the spring range review I want a shortlist of active products we should think about dropping. Which ones barely sell? I need it by the end of the month.”

Your goal

Choose the version of the question you would agree with Thomas before touching the data.

Which framing of Thomas's request is the one to analyse?

Pick one answer, then check it.

The lesson

Why framing comes first

“Which products barely sell?” sounds simple, and the first instinct is to sort by units sold. Try that on a home goods catalogue and the bottom of the list is all furniture, because a dining chair can cost twenty times as much as a cushion. Before you write a query, agree what “barely sells” means. The checklist most analysts use is SMART:

  • Specific: which products. Active products that were on sale for the whole period. Retired products are already gone, and a product launched in the autumn has not had time to sell.
  • Measurable: which number. Net revenue in the period, with units next to it, expressed as a share of the product’s own category.
  • Achievable: can the data answer it? Yes: order lines carry quantity, price paid and discount, and products holds the category, the launch date and whether the product is active.
  • Relevant: what decision does it feed? Thomas will decide which products to review or drop at the spring range review.
  • Time-bound: calendar 2025, the latest full year, answer before the review.

Compared with what?

Three choices make the list fair:

  • Within the category. A product is slow if it sells little for its kind of product. Its share of the category’s revenue answers that; a ranking inside each category does too.
  • A full year. Outdoor products sell mostly from April to July; Decor, Kitchen and Textiles peak in November and December. Any window shorter than a year favours one category over another.
  • Like-for-like products. Only products launched before January 1, 2025, so each was on sale for all twelve months.

What the plan looks like

Step What you do Output
Check Count established, new and retired products, what sold in 2025, missing costs a 3-row table
Analyse Each product’s share of its category’s 2025 revenue; the weakest three per category an 18-row list
Size How much of each category the weakest three bring in a 6-row table
Show One chart: share of category revenue from the weakest three a column chart
Recommend A shortlist with caveats three or four sentences

Interview note

“How would you find underperforming products?” is a common merchandising and retail analytics question. A strong answer picks a fair period (a full year or the same season), compares within a category or price band, sets aside new launches, and says what is missing: margin, stock on hand, and whether a product earns its place by completing a range rather than by its own sales.

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