Honestly
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Brand & campaign

See how the campaign actually landed.

Honestly reads the earned conversation about a brand or campaign across social video, communities, and reviews, then organizes it by theme, sentiment, region, and source, so brand teams can see how it was received and what to do next.

Request a demo See the anonymized deep dive

Earned-conversation evidence describes the reviewed corpus. It does not measure reach, impressions, or sales, which need your first-party campaign data. Region is derived from language and post signals, not verified location.

Campaign reception map Illustrative interface
Source lensEarned vs owned
Break down byRegion & language
Themes in earned conversationIllustrative structure
  1. 01Product experience
  2. 02Sponsorship & event fit
  3. 03Regional response
  4. 04Competitor comparison
  5. 05Creative reception
Region signalDerived from language and post signals

Sample size stays attached to every rollup.

EvidenceLinked

Three capabilities

Owned reach is not reception.

Reach and impressions describe what you paid to distribute. Earned conversation shows how people received the brand or campaign in their own words, and where that reception splits by place and by competitor.

  1. 01

    Collect the earned signal

    See how a campaign landed in earned conversation, not just owned reach.

    Honestly collects product and brand opinions across social video, communities, and reviews, ingests public community threads and forums under consent-gated rules, then labels each record with an earned-vs-owned source classifier so paid placements are not read as organic reception.

    Working viewEarned vs owned × source
  2. 02

    Read it by place

    Break reception down by region and language, with sample size attached.

    A region rollup groups the conversation by where it appears to come from, and multilingual capture keeps every opinion in its original language before localizing it. Each regional read carries its sample size, so a loud pocket never reads like a whole market.

    Working viewRegion × language × n
  3. 03

    Compare the field

    Benchmark the brand against competitors on the attributes people actually raise.

    A competitive comparison view lines the brand up against named competitors, and the subject-and-attribute opinion model organizes what people say around a shared set of attributes, so the comparison rests on the themes the audience raises rather than the ones the brief assumed.

    Working viewBrand × attribute

From conversation to decision

A reception read should trace back to the post behind it.

Honestly structures the earned conversation without pretending the system made the call. The source record stays separate from Honestly's reading and from what the brand team decides to do.

  1. 01
    Public sourceCapture the original post.

    Keep the platform, author context, excerpt, and available timestamp together, consent-first for community sources.

  2. 02
    Structured evidenceAssign subject, attribute, sentiment, and region.

    Use one attribute lens across the brand and its competitors while preserving the source language.

  3. 03
    Reception signalRead direction with the sample size.

    Weigh volume, region, and earned-vs-owned source before promoting a finding.

  4. 04
    Human decisionChoose message, market, or watchlist.

    Your brand team decides what the reception means for the next move.

Reception evidence Illustrative workflow
Earned-conversation finding Keep region and sample beside the read
Source lens
Earned vs owned
Signal
Direction + sample size
Region
Language-derived
Status
Human review
“The post belongs beside the finding, not inside a separate slide.”

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

Anonymized delivered work

Every finding stays tied to its source.

A global brand's world-championship campaign: earned community conversation collected consent-first from public community channels plus YouTube, Reddit, and X, geo-tagged and scored on a shared attribute lens, every finding source-linked.

For public, inspectable scale and attribute depth, a live smartphone deep dive reads 35,107 opinions from 6,804 opinion-bearing posts across 11 platforms, each opinion tied to its sample and source.

Study disclosure. The brand, campaign, and community names are withheld. The smartphone figures describe that public deep dive's live corpus, not the world-championship campaign and not a reach, impression, or sales estimate.

See the public deep dive
Public product deep diveLive corpus
35,107opinions read
Opinion posts
6,804
Platforms
11
Sourcing
Linked
Every read stays tied to its sample and sourcen shown
  1. AI
  2. Display
  3. Value

Evidence boundaries

Know what earned conversation can support.

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

Measured in the corpus
In-scope brands and competitors, tagged attributes, opinion counts, sentiment direction, language-derived region, and available source context.
Interpreted by Honestly
Whether a pattern looks like a supported strength, an objection to inspect, or a regional split that needs more collection.
Decided by your team
Message, market focus, sponsorship read, and spend, using brand strategy and your first-party campaign data.
Not established by opinion data alone
Reach, impressions, and sales. Those outcomes need your first-party campaign and commerce data.

Honestly for brand & campaign

See how the brand and the campaign landed.

Bring a brand, a campaign, or a competitive set. Honestly will show you the source-linked earned conversation underneath it.

Request a demo