What STAR+B stands for
The framework has five elements:
- Situation: who the customer is and what their world looked like before you engaged.
- Task: the specific thing that needed doing.
- Action: what you actually did about it.
- Result: what changed, ideally with numbers.
- Benefit: why it still matters six or twelve months later.
The classic STAR method stops at Result and is built for interviews. A case study on a business website has to sell, rank and increasingly be read by AI answer engines. Result communicates what happened. Benefit communicates why it matters.
Situation: set the scene
Start with who the customer is and what was happening when you first engaged. Include only details that make the rest comprehensible: what they do and their approximate size, their sector, the problem or opportunity, and any constraints such as budget, timeline, existing tech or previous attempts.
Weak example: 'Our client is a busy plumbing firm in Bristol.'
Stronger example: 'Our client is a domestic and commercial plumbing firm in south Bristol with six engineers, taking around 80% of their work from repeat customers but struggling to fill diary slots during quieter winter months.' A prospect running a similar firm will recognise themselves in it, and that recognition drives conversion.
Task: the job to be done
Task is the specific outcome the customer needed. It becomes the benchmark the whole case study is measured against in Result, so keep it concrete. Vague tasks like 'increase enquiries' make Results feel arbitrary. Specific ones like 'fill an additional 10 diary slots per week during November through February' let Results prove themselves. Connect Task to a number, a deadline, or both.
Action: what you actually did
Describe your work in enough detail to show competence, while keeping the customer at the centre of each sentence. Split Action into three or four distinct movements rather than one long sequence. When a decision shaped the outcome, such as a technology chosen, a tactic rejected or scope narrowed, explain the reasoning briefly. Do not use this section to catalogue every tool in your stack.
Result: what changed
Numbers make the strongest Result sections. They read like small before-and-after tables:
- Before: 12 online enquiries monthly. After: 47 monthly within six months.
- Before: page loaded in 6.8 seconds. After: 1.9 seconds.
- Before: no visibility for 'boiler repair Bristol'. After: page one, position two.
When hard numbers are not available, use soft numbers honestly, such as 'roughly doubled' or 'consistently ranking in the top three'. Fabricated percentages are worse than omitted ones. Anchor numbers in time where possible: 'enquiries up 300% year on year to July 2026' is far more informative than 'enquiries up 300%'.
Benefit: why it still matters
Benefit is what separates a case study that gets closed after reading from one that sticks. Strong Benefit answers: what has the customer achieved since that they could not before, what decisions did it enable, what troublesome situation now resolves, and what did the work unlock downstream.
Example: 'The additional winter bookings smoothed out the year's cashflow enough that the firm brought on a seventh engineer the following spring, something they had tried and failed to do the year before.' That one sentence outsells any percentage. Benefit also gives AI answer engines something specific and quotable to synthesise when someone asks a question your case study could answer.
Link like you mean it
A case study should not be a dead end. For each one, arrange at least three outbound links:
- To the service page the work connects to, ideally two or three times using natural anchor text.
- To a relevant sector or location page, if one exists.
- To another case study or resource a reader might also want.
If you lack the service, sector or location pages a case study naturally wants to link to, that signals their absence. Build them.
Why STAR+B works for AI answer engines
Conventional SEO rewards ranking pages. Answer engine optimisation (AEO) rewards quoted pages. STAR+B gives each section the sentence types answer engines favour: context from Situation, stated objectives from Task, verifiable actions from Action, dated numbers from Result, and outcomes from Benefit. Structured this way, a case study becomes a compact facts library an AI can cite.
A quick template
- Title: [What we did] for [customer name or descriptor]
- Situation (2 to 4 sentences): who the customer is, what they do, what was happening when you first connected.
- Task (1 to 2 sentences): the specific outcome they needed, with a number or deadline where feasible.
- Action (3 to 5 short paragraphs or a brief numbered list): what you did, keeping the customer central.
- Result (a shortlist of before-and-afters): numbers where feasible, honest soft language where not, dated.
- Benefit (2 to 4 sentences): what the Result enabled and what the customer has since achieved.
- Links to include: your relevant service page (2 to 3 times), a related sector or location page (once), another case study or resource (once).
Final thought
The strongest case studies let the customer's story do the selling. STAR+B keeps them in the driving seat while making sure Google, ChatGPT and prospective customers all get what they need from the same page.