# Machine-learning interview question: predict client purchases from transaction data

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Source: https://www.aced.io/questions/553/build-classification-algorithm-client-purchases
Source observed: 2026-11-05T00:30:13.226Z
Last checked: 2026-11-05T00:30:13.226+00:00
Indexed: 2026-11-07T00:47:45.959+00:00

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# Use a transaction dataset to build a classification algorithm predicting client purchases in the next 3 months.

We publish interview questions and preparation resources through Aced, formerly Exponent. This question concerns building and evaluating a classification model from transaction data. It is associated with [BCG Gamma](https://www.aced.io/questions?company=bcg-gamma), and its category is [Technical](https://www.aced.io/questions?type=technical).

## Interview details

- **Format:** Interview
- **Last asked:** 5 years ago
- **Question number:** 553

## Questions to answer

1. From the data—transaction date, client ID, color of item, and amount—what features would you create to build the model?
2. You train a model and get a “too good to be true” accuracy. What could have happened?
3. You build an SVC model and its accuracy is not very good. What could you do to improve the model?

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