Case 4 · 3 levels
Did the price rise hurt sales?
Harbor & Pine raised prices on 29 products in March 2025. Frame the question, confirm the change in the data, compare like for like against last year and products that kept their price, and write the recommendation.
StartIn March 2025 Merchandising put prices up by about 6% on 29 products. Six months later the question lands on your desk: did it cost us sales? It is one of the most common questions an analyst gets, and one of the easiest to answer badly, because sales move for many reasons at once: the season, new products, marketing, the economy.
This case is the whole job, the way you would do it at work:
- Frame the question so it can be answered: which products, which measure, which period, compared with what, and what decision it feeds.
- Check the data: find the products whose price changed and confirm the change happened when Merchandising says it did.
- Analyse like for like, in SQL, pandas or Excel, whichever you prefer: the same months a year earlier, next to products whose price did not change.
- Recommend: pick the conclusion you would send, with the numbers and the caveats.
The case is open from the start. It uses joins, conditional sums and a CTE (or merge and
groupby in pandas, or formulas on a prepared sheet in Excel); the lessons walk through each.
Levels
- Frame the price question
from Thomas Whitaker, Head of Merchandising
smart goal, problem framing, control group, like for like
- Check and compare the price rise
from Thomas Whitaker, Head of Merchandising
data validation, having, cte, conditional aggregation, like for like, control group, yoy
- Recommend: keep, roll back or extend?
from Thomas Whitaker, Head of Merchandising
recommendation, caveats, causation, control group, data storytelling