Trackers give numbers without explanations
Awareness ticked up four points. Sentiment dropped from 72 to 68. Why? Trackers can't tell you, and by the time you commission qual to find out, the moment has passed.
Brand perception with the why attached.
Brand-tracker dashboards tell you awareness is up two points and sentiment is "neutral-positive". They never tell you why. Diaform runs AI-led brand conversations at scale so every score comes with the language, emotion, and reasoning behind it.
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Why brand research keeps falling short
Agency-led brand studies are slow and expensive
A traditional brand health study runs six to ten weeks and burns a six-figure budget. You get a beautiful deck once a year, not a research instrument you can run whenever a campaign lands.
Single-question NPS-style asks miss the brand story
"Rate this brand from 1 to 10" gives you a number, not a narrative. The actual brand associations, the words, metaphors, and feelings, never make it into the data.
How Diaform runs brand research differently
01
AI conducts open-ended brand conversations
Instead of attribute scales, the AI asks respondents to describe your brand in their own words, and probes when an answer is vague, generic, or surprising.
02
Voice captures emotional language
Respondents can speak their answers. Voice surfaces the adjectives, hesitations, and tone that reveal real brand feeling, the stuff that never appears in a checkbox.
03
Structured analysis for every respondent
Every conversation is auto-tagged. You see which associations are dominant, which are emerging, and which are unique to specific segments, without coding a single transcript.
04
Sentiment per brand attribute
Sentiment isn't one number for the brand. It's broken down per attribute, quality, trust, innovation, value, so you know exactly which dimensions are strong and which are slipping.
05
Multilingual native research
Run the same brand study in supported languages. Respondents can speak or type naturally, and each completed conversation stays available with its transcript and structured response.
06
Plug into your existing tracker
Add relevant tracker findings as written context or a supported PDF or DOCX file. The AI can reference that context while it conducts the conversation.
How a brand research study runs
- 01
Define the brand questions to probe
Pick the dimensions that matter, awareness, associations, positioning, message recall, competitive perception, and the segments you want to compare.
- 02
Upload competitive context
Drop in your brand book, latest campaign assets, and competitor list. The AI uses them to ask sharper follow-ups and to recognize when respondents reference a competitor unprompted.
- 03
Run conversations via one link
Share a single link with your panel, customer list, or market sample. Every respondent gets their own AI-led brand conversation, in their language, on any device.
- 04
Review brand sentiment and responses
Per-attribute sentiment, dominant associations, competitor mentions, and the verbatim quotes worth screenshotting for the next leadership review, all generated automatically.
What brand teams use it for
Annual brand health study
Replace or augment the once-a-year agency study with a continuous research instrument. Same dimensions, fraction of the cost, qualitative depth attached.
Post-rebrand perception check
After a visual or verbal identity refresh, find out what actually shifted in customers' minds, and whether the new positioning is being heard the way you intended.
Competitive positioning research
Map how customers describe you versus the alternatives. Find which attributes your competitors own, where you're interchangeable, and where you have unique territory.
Message resonance testing
Test new taglines, value props, or campaign messaging against real audiences. The AI probes for what the message implied, not just whether they liked it.
New-market brand awareness
Entering a new geography or segment? Measure unaided awareness, associations, and trust signals in the local language before you commit to a launch.
Post-campaign brand lift
Run a brand-lift study within days of a campaign wrapping. Catch what landed, what was misremembered, and which messages drove genuine perception change.
Traditional brand trackers vs. Diaform
Traditional brand tracker
- Closed-ended scales only
- No qualitative depth behind the scores
- Slow agency-led turnaround
- Expensive panel and analyst fees
- Single-language fielding by default
Diaform
- Open-ended brand probing on every dimension
- Voice captures the emotional language behind sentiment
- Per-response summaries, sentiment, confidence, and optional quotes
- Multilingual native research in 30+ languages
- Days, not weeks, run a study whenever the campaign demands one
Frequently asked questions.
The practical details behind setting up, running, and scaling this kind of research with Diaform.
Diaform is designed to complement, not replace, your quantitative tracker. Add the relevant findings as written context or a supported PDF or DOCX so the researcher can reference them when probing. Keep the tracker for measurement and use the conversation responses for the explanation layer.
More conversations your team can run.
Explore the other ways Diaform can turn a static request for feedback into a useful conversation.
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