Research can be accurate and still leave a client unsure what to do. A market map, interview synthesis, or company dataset becomes useful advice only when it is connected to a clear decision, credible options, and the tradeoffs between them.

Strawberry keeps that path connected. Your companion can work from the engagement brief and existing research, fill material gaps in the visible browser, and carry the reviewed evidence into a recommendation and client artifact. You can inspect where a claim came from instead of accepting a polished conclusion on trust.

Start with the decision

The same evidence can support different answers depending on the decision owner, time horizon, constraints, and appetite for risk. Strawberry first establishes what the client must decide, which criteria matter, what would change the answer, and how the recommendation will be used.

If the request is still to map a market or collect comparable company data, the work stays with the relevant research workflow. The recommendation begins when the client needs a point of view rather than another pile of findings.

Want to try it?

Ask your Strawberry companion: “Use the available client research and engagement context to compare credible options, recommend a path, and create the right decision-ready memo, deck, workshop artifact, or supporting sheet.”

Skill

Turn research into a client recommendation

Turn the evidence for one client decision into credible options, a recommendation, and the right decision-ready artifact.

Fill only the gaps that matter

Client evidence often sits in several forms: meeting records, interview notes, internal files, prior analysis, source links, and logged-in research sites. Strawberry can use those sources together while keeping the browser work visible, so the consultant can correct a category, inspect a source, or take over when a site needs judgment or access.

Before expanding the research, your companion identifies the gaps that could actually change the options or recommendation. A broad new run is unnecessary when the existing evidence is enough. When scale is needed, repeated fields across many pages belong in a validated dataset, with a small varied sample reviewed before the run expands.

Skill

Build a client-ready market map

Define the market, categories, and relationships when the landscape itself is still unclear.

Skill

Research hundreds of companies into a spreadsheet

Collect and validate repeated fields across many companies or pages when the evidence needs scale.

Show the path from evidence to advice

A defensible recommendation makes its reasoning inspectable. Strawberry separates observed facts, client statements, calculations, and consultant inference; reconciles definitions; and keeps contradictions or stale evidence visible. It then compares credible options against the agreed criteria.

The result should explain why one path is recommended, the strongest alternative, the tradeoffs and dependencies, and what new evidence would change the answer. If the evidence is thin, a bounded recommendation or a focused next research step is more useful than manufactured certainty.

Choose the artifact the decision needs

A memo suits a decision that needs detailed reasoning. A deck works for a client readout. A workshop artifact helps a group weigh options together, while a supporting spreadsheet keeps comparisons and calculations transparent. Large datasets remain the evidence layer rather than becoming the recommendation by default.

Because the artifact is built from the same reviewed evidence and criteria, the consultant does not have to rebrief a separate presentation or spreadsheet tool. Sources, assumptions, and formulas can stay traceable while the client-facing result becomes concise and polished.

Skill

Create a polished client presentation

Turn the accepted recommendation into a polished client readout when a presentation is the right format.

Review before the recommendation travels

Before delivery, Strawberry checks material claims against their sources and looks for counterevidence, inconsistent definitions, unsupported calculations, feasibility constraints, and facts that may have changed. The consultant still owns the judgment and the client decides what to do.

Internal review, client delivery, public sharing, CRM changes, and implementation are separate actions. Strawberry establishes who should see the artifact, what access they need, and where it belongs before suggesting a sharing path. Client-specific evidence stays with that engagement.

Once the method is trusted, your companion can preserve the accepted sources, criteria, artifact structure, and review behavior as a custom skill. A stable evidence refresh can become a draft-first Routine, but it should stop when sources conflict, access changes, calculations cannot be reproduced, or the client decision has moved on.

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Official Strawberry skill
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turn-client-research-into-recommendations
description
Turn client research, interviews, data, and engagement context into evidence-backed options, a defensible recommendation, and a decision-ready memo, deck, workshop artifact, or supporting spreadsheet. Use when a consultant or internal advisory team needs to move from findings to what the client should do.

Turn Client Research into Recommendations

Help the client make a decision from the available evidence. This skill owns the move from findings to credible options and a recommendation; it does not replace the research skills that collect or structure the underlying evidence. Follow an existing consulting method when the user has one.

1. Frame the decision

Identify the client, decision, intended audience, decision owner, stakes, time horizon, constraints, criteria, deadline, and useful output. Clarify what is already known, what would change the decision, and whether the user wants a recommendation, help choosing between options, or a neutral set of options.

If the request is only to collect, map, or compare information, route to the appropriate research skill instead of forcing the work into a recommendation.

2. Choose the right evidence path

Start with the accepted engagement brief, prior research, meeting records, client data, source links, files, visible tabs, connected apps, and relevant client-specific memory. Keep every client's sources, calculations, artifacts, permissions, and learned context separate.

Use existing research skills for the work they already own:

  • strawberry/research-analysis/map-a-market for a landscape, taxonomy, or relationship map;
  • strawberry/research-analysis/extract-web-data for repeated fields across many rows, including large company-research runs;
  • strawberry/research-analysis/research-a-company for a sourced brief on one company;
  • strawberry/research-analysis/create-beautiful-slide-deck when accepted research should become a visual presentation;
  • strawberry/sales/research-an-account when the company matters as a commercial relationship.

Strawberry can combine this work with material in visible logged-in browser sessions and connected sources while keeping the supporting evidence inspectable. Propose the sources, depth, likely time or cost, and a useful first review point before filling gaps. Do not start a broad research run when the existing evidence already supports the decision.

3. Build a trustworthy evidence base

Organize the material around the decision rather than the order in which it was found. Keep observed facts, client statements, calculations, and consultant inference distinct. Preserve source links and relevant dates, reconcile definitions, and flag stale evidence, contradictions, missing data, and important limitations.

When the classification, research depth, or output structure is subjective, review a representative sample with the user before scaling. Ask only for gaps whose answer could change the options or recommendation.

4. Move from findings to a recommendation

Explain the decision-relevant patterns and implications. Compare credible options against the accepted criteria, then recommend a path when the evidence supports one. Show the rationale, tradeoffs, risks, reversibility, dependencies, and remaining uncertainty. Include the strongest alternative and explain what evidence or event would make it preferable.

Do not turn a client claim into an established fact, hide a logical leap, invent a calculation, or present confidence the evidence does not support. When evidence is thin, provide a partial recommendation, bounded options, or the highest-value next research step rather than manufacturing certainty.

5. Create the decision-ready artifact

Propose the structure before producing the polished version. A useful default includes an executive recommendation, the decision and criteria, key evidence, credible options, rationale, risks and assumptions, next steps, and traceable sources.

Choose the simplest format that fits the decision:

  • a memo for a detailed written recommendation;
  • a deck for a client readout, using strawberry/research-analysis/create-beautiful-slide-deck for production;
  • a workshop artifact when stakeholders need to evaluate options together;
  • a supporting spreadsheet when comparisons or calculations need transparent inputs, formulas, assumptions, and source notes, using the internal strawberry/general/spreadsheets capability.

Use a dataset or CSV as the evidence layer for a large research run, not as a substitute for the recommendation the client needs. Do not allow visual polish to obscure weak evidence or unsupported calculations.

6. Review before sharing or action

Test each material claim against its source and check the path from evidence to conclusion. Look for counterevidence, inconsistent definitions, feasibility constraints, client-voice problems, and facts that may have changed. Surface the remaining decisions and recommend answers where possible.

Establish the audience, access model, and destination before recommending a sharing path. Confirm that client confidentiality, personal data, source permissions, and visual examples are appropriate for that audience. Internal review, client delivery, public sharing, sending, publishing, CRM changes, and implementation are different approval states; do not treat approval of the analysis as approval for any of them.

7. Preserve the accepted method

After the approach works, offer to save the accepted questions, sources, evidence standards, decision criteria, artifact structure, voice, and review behavior as a custom skill. For boutique teams, preserve only the reusable method unless the team has explicitly agreed access to the client context and destination.

A draft-first Routine can refresh a trusted recommendation when the source set, cadence, output, and review owner are stable. Define its permissions, notification behavior, and approval boundary. Stop when a material source is unavailable, sources conflict, access changes, calculations cannot be reproduced, or the underlying client decision has changed.

Suggested outcome

Deliver a decision-ready recommendation with inspectable evidence, credible alternatives, explicit risks and assumptions, and a polished memo, deck, workshop artifact, or supporting spreadsheet that fits the audience and decision.