A customer interview can produce strong copy quickly: “Our team became more efficient,” “Customers understood the material faster,” or “Follow-up became easier.” Add an impressive number, and the first draft can look convincing before anyone has checked what the claims actually mean.
The publication review needs a different set of questions. What was measured, and against which baseline? How did the customer use the product? Did the customer confirm the statement, or did the vendor add that interpretation? More quotes and numbers do not create a credible story unless the evidence trail is visible.
Write the sequence of change before declaring success
A useful case study does not need a dramatic structure. Begin with the situation before adoption, narrow the problem, and describe the features and operating practices the customer actually used. Then separate the observed change, the customer’s assessment, and the conditions that still apply.
“The team improved proposal operations” says much less than “Several account owners repeatedly sent the same introduction deck and could not tell whether it had been reviewed.” From there, explain what changed in the document, how it was distributed, and which records from which period were compared.
That sequence allows the reader to follow the path from problem to action to result instead of being asked to accept a success claim on trust.
Sort the draft into five types of statement
During editorial review, label each sentence as one of the following. Unsupported or overstated language becomes much easier to spot.
- Product fact: a capability that was available at the time and actually used by the customer
- General guidance: editorial advice that may apply elsewhere but is not a result from this customer
- Customer statement: an assessment the customer confirmed in an interview or approval round
- Outcome claim: a change supported by a metric or an observation record
- Legal or comparative language: claims of being first, unique, complete, or certain that require separate review
Even “Customers understood us more easily” changes category depending on its source. If the customer said it in an interview, it is a customer statement. If the writer inferred it from longer viewing time, it is an interpretation. Those two statements should not appear as the same kind of fact.
Treat every metric as a bundle of measurement conditions
An outcome metric needs a time period, baseline, scope, and definition. For a before-and-after comparison, identify the document versions and time windows. For an average, state which documents and viewing sessions were included. A change on a few pages should not be expanded into a claim about the performance of the entire document.
Causal attribution also needs restraint. If the team changed the document structure, added a demo video, and introduced a contact link at the same time, the evidence shows a change after several interventions. It does not isolate the effect of the video or the contact link without a separate test.
When the numbers are not ready, a qualitative case study can still be useful. Describe the original problem, the operational change, and the difference people noticed in their conversations. A precise account with clear limits is stronger than a prominent percentage with an unclear basis.
Use FeatPaper to connect evidence with the next question
Once the case study has passed review, it can be shared as a FeatPaper link. For material created with the Figma plugin, the documented workflow can connect supported video, external forms, or scheduling widgets so that a product workflow and the next action sit close to the supporting context.
Interaction does not replace evidence. Adding a video does not grant permission to publish a customer statement, and a longer viewing time does not validate the case study’s claims. Visit counts, page-level viewing time, revisited pages, and link clicks are observations about reading behavior.
If readers return to one section, do not conclude that it was especially persuasive. It may have been important, or it may have been unclear. Use the record to ask a more specific question in the next conversation. Viewing data belongs in the follow-up workflow, not in an engagement score for the reader.
Approval covers the disclosure scope, not just the wording
The final review should address the customer name and logo, the speaker’s name and title, direct quotations, outcome metrics, and product screenshots separately. An anonymous case study may still reveal the customer through its industry, size, location, or project name.
Record how each metric was calculated and who approved it. State the date or product period the story represents, and define what should be checked again if the product or the customer’s circumstances change. Approval is not a single sign-off on a document; it aligns each published element with the exact scope of the supporting evidence.
Final checklist before publication
- Does the story move from problem to action to observed change in a clear sequence?
- Are product facts, customer statements, outcome claims, and editorial interpretation distinct?
- Does every metric include a period, baseline, scope, and definition?
- Have multiple interventions been kept separate from claims about one feature’s effect?
- Were names, logos, quotations, metrics, and screenshots approved individually?
- Is viewing data being used to shape the next question rather than prove the outcome?
A strong case study does not fill every gap with a success claim. It separates verified facts from customer assessments, observed outcomes from vendor interpretation, and evidence from the limits around it. The goal is not to promise readers the same result. It is to help them judge what is similar—and what is different—in their own situation.