Research in practice

Ask about the decision, then listen.

Product and marketing teams need specific observations they can distinguish from their own interpretation.

“Would you use this?” often produces a more encouraging answer than a useful account of what somebody actually does. Customer Research Review focuses on questions and observations that reveal the circumstances behind a decision. Its material includes interviews, task walkthroughs and research notes that preserve uncertainty. The aim is to understand a problem before a preferred solution shapes every conversation about it, especially when a small team has only a limited number of opportunities to speak with customers.

Ask about a recent occasion

Invite someone to describe the last time they encountered the problem: what started it, what they tried and what happened next. Follow their sequence before introducing your own explanation. Ask for clarification when a broad label such as “difficult” could refer to several different obstacles. Avoid making approval of a proposed feature the purpose of the interview. A concrete account can expose tools, workarounds and constraints that a prediction about future behaviour leaves out. Respect the participant’s time and obtain appropriate permission before recording.

Keep observation separate from interpretation

Write down what the participant said or did, then distinguish the inference you draw from it. If a person pauses at a form field, the observation is the pause; the cause may still require a question or another example. Remove unnecessary identifying information from shared notes. Include enough context to explain the task without distributing private customer material. When several people review the research, compare interpretations against the original evidence rather than allowing the most memorable quotation to settle the whole discussion.

State the limits of what you learned

A handful of interviews can raise a strong question without establishing how common the issue is across all customers. Note who participated, which circumstances were represented and which were absent. Use disagreements to guide further investigation rather than smoothing them into an artificial consensus. The articles here connect interview craft, observed behaviour and research records. Useful research gives a team a clearer basis for its next decision while preserving the distinction between an observed example, a recurring pattern and a claim that still needs checking.

From the working notebook

Latest published articles

Energy-Aware AI Infrastructure: Why Power Planning Matters in 2027

Artificial intelligence strategy is increasingly connected with energy strategy. Training and operating AI systems require data-centre capacity, computing hardware, cooling, networks, and reliable electricity. Even companies that do not own…

Energy-Aware AI Infrastructure: Why Power Planning Matters in 2027

Artificial intelligence strategy is increasingly connected with energy strategy. Training and operating AI systems require data-centre capacity, computing hardware, cooling, networks, and reliable electricity. Even companies that do not own…

Physical AI and Robotics: A Practical Business Strategy for 2026

Artificial intelligence is moving beyond screens and software workflows. In manufacturing, warehousing, logistics, inspection, and service environments, AI is being combined with robots, cameras, sensors, and connected equipment. This development…

Scaling Account Reviews for Growing Service Companies

Scaling account reviews requires more than asking employees to handle a larger volume of the same work. For service teams managing a growing customer base, the process keeps long-term customer…

Scaling Service Scope for Growing Service Companies

Scaling service scope requires more than asking employees to handle a larger volume of the same work. For service teams managing a growing customer base, the process defines what the…

Scaling Quality Checks for Growing Service Companies

Scaling quality checks requires more than asking employees to handle a larger volume of the same work. For service teams managing a growing customer base, the process prevents important errors…