Honestly
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Honestly for research & development

Build the roadmap from what people value.

Honestly turns scattered product conversations into structured, source-linked evidence. Compare products by customer-valued attributes, surface recurring strengths and objections, and carry the original language into requirements.

Compare your products or market Read the anonymized study

Opinion evidence describes the reviewed corpus. It does not establish market share, product causation, or future demand.

Product evidence map Illustrative interface
Comparison set9 products
Shared vocabulary25 attributes
Customer-valued feature groupsDelivered-study structure
  1. 01Camera
  2. 02AI
  3. 03Performance
  4. 04Display
  5. 05Battery
Requirement inputOriginal language + product context

Source record and evidence count remain attached.

Display rulen≥10

A fixed, reviewable base

The denominator belongs beside the decision.

The anonymized delivered smartphone study used one fixed corpus for coverage, feature comparisons, and reviewer context. Every displayed metric carried its sample size; headline leaderboards required at least ten tagged mentions.

Products
9
Compared in the delivered report
Attributes
25
Organized into five feature groups
Reviewer cards
796
Attribute-tagged records in the base
Attribute mentions
2,569
Retained for analysis
Source types
6
YouTube, TikTok, and four review domains

Four product decisions

Do more than count requests.

Product teams need to know what experience sits behind a request, how often it appears in the reviewed evidence, which products it affects, and where the language came from.

  1. 01

    Compare value

    See which attributes matter in each product context.

    Organize opinions around a shared vocabulary, then compare strengths, tradeoffs, and objections product by product instead of flattening them into one portfolio score.

    Working viewProduct × attribute
  2. 02

    Review issues

    Bring recurring objections into roadmap review.

    Separate an isolated complaint from a repeated experience, then open the underlying reviewer language before deciding whether the issue deserves research, design, or engineering attention.

    Working viewPattern × source context
  3. 03

    Prioritize carefully

    Keep sample size attached to every signal.

    A strong ratio built from a small base should not carry the same weight as a pattern supported by substantial volume. Honestly keeps the denominator visible while your team applies judgment.

    Working viewSignal × evidence count
  4. 04

    Write the requirement

    Carry customer language into the handoff.

    Attach the excerpt, product, attribute, source, and available context to the requirement so design and engineering can inspect the experience—not just a rewritten summary.

    Working viewRequirement × provenance

From language to roadmap

A requirement should be traceable to the experience behind it.

Honestly structures the evidence without pretending the system made the product decision. The research record stays separate from the team's interpretation and priority.

  1. 01
    Public sourceCapture the original language.

    Keep the product, post, excerpt, and available timestamp together.

  2. 02
    Structured evidenceAssign product, attribute, and sentiment.

    Use one vocabulary across the comparison set while preserving the source wording.

  3. 03
    Comparative signalRead direction with the denominator.

    Review volume and source context before promoting a finding.

  4. 04
    Human decisionChoose research, requirement, or watchlist.

    Your team decides what the evidence means for the roadmap.

Requirement evidence Illustrative workflow
Customer-valued attribute Preserve context across products
Comparison
Product by product
Signal
Direction + sample size
Evidence
Original language attached
Status
Human review
“The source excerpt belongs beside the requirement, not inside a separate research folder.”

Illustrative operating principle, not a quote from the anonymized client.

Anonymized delivered work

Nine products. One vocabulary. Every figure in context.

The delivered smartphone study compared 25 customer-experience attributes across nine products. Its 796 reviewer cards yielded 2,569 attribute mentions across five feature groups and six source types.

Study disclosure. The client and product-family names are withheld. Percentages in the case study describe the fixed report corpus, not current market share or a live market estimate.

Read the anonymized case study
Delivered research systemFixed corpus
2,569attribute mentions
Products
9
Attributes
25
Reviewer cards
796
Minimum for displayed headline metricsn≥10
  1. Camera
  2. AI
  3. Performance
  4. Display
  5. Battery

Evidence boundaries

Know what the research can support.

Clear labels make the work more useful. The source record, structured finding, and product decision are related—but they are not interchangeable.

Measured in the corpus
In-scope products, tagged attributes, evidence counts, sentiment direction, and available source context.
Interpreted by Honestly
Whether a pattern looks like a supported strength, an objection to inspect, or a question that needs more collection.
Decided by your team
Research priority, requirement, sequencing, and investment—using product strategy, feasibility, and other first-party evidence.
Not established by opinion data alone
Market share, causal product impact, revenue, or future demand. Those conclusions require additional evidence.

Honestly for research & development

Put the customer experience inside the roadmap.

Bring a product portfolio, competitive set, or market. Honestly will show you the source-linked opinion layer underneath it.

Compare your products or market