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DAGENO / AI VISIBILITY
Narrative Shaping
Continuously calibrate brand perception in AI answers
Observe how AI summarizes the brand, associates differentiators, and explains strengths and limitations. Find perception gaps and missing evidence, then validate changes with consistent facts, content, and sources.
Definition
Narrative Shaping is the Dageno Visibility brand-perception workflow. It continuously compares brand descriptions, attribute associations, evidence sources, and changes over time in AI answers.
NARRATIVE EVIDENCEDageno Visibility solution
Define scope
Brand facts and differentiatorsTarget scenarios and audiencesModels, regions, and languages
Dageno Visibility
Brand descriptionsStrength and limitation contextCited sources and competitors
Deliver reviewable results
Perception baselineNarrative deviationsEvidence reinforcement list
This page illustrates the analysis structure only. Actual scope, model responses, and data availability depend on project configuration.
Trace narrative sources
Observe changes over time
Solution capabilities
Turn narrative shaping into an actionable workflow.
Start with the business question, preserve the answer, context, and visible sources, then give the evidence to the teams responsible for action.
Define the target narrative
Turn brand facts, differentiators, target scenarios, and misconceptions to avoid into a monitorable question scope.
Compare perception and evidence
Analyze how AI summarizes the brand, which attributes it associates, and how visible sources and competitor differences support those descriptions.
Calibrate perception continuously
Connect perception gaps to owned, earned, community, and knowledge content, then monitor change with consistent questions.
Narrative Shaping
Questions this page helps answer.
How does AI currently summarize the brand, and which differentiators, scenarios, and audiences does it associate?
Which descriptions are factually wrong, incomplete, or consistently occupied by competitors?
Did perception and recommendation reasons change after brand content and sources were updated?
Narrative Shaping
Reviewable outputs your team receives.
Brand-perception baseline
Narrative deviation list
Differentiator evidence gaps
Perception-change record
Narrative Shaping
What the data can answer—and what it cannot represent.
Brand perception comes from configured questions and sampled answers. It is not complete user perception, total online share of voice, or internal model knowledge.
Visible citations help review narrative sources but cannot prove that one page directly caused a model to form or change a perception.
Dageno monitors externally observable changes. It cannot guarantee control of model answers or a target narrative within a fixed period.
Narrative Shaping
A clear three-step workflow.
Establish the narrative baseline
Confirm the target perception, brand facts, priority differentiators, and user questions to monitor.
Identify gaps and sources
Review incorrect, missing, or competitor-owned narratives and trace visible citations and content evidence.
Align expression and validate
Coordinate brand, content, and PR assets, then compare answer context and attribute associations after updates.
Narrative Shaping
Explore other Visibility solutions.
Choose the workflow closest to your current question across brand risk, competitive position, launches, content, and perception.
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Brand Crisis Management
Continuously monitor incorrect claims, negative context, and unusual changes in AI answers. Find the affected questions, models, and sources, then give brand, PR, and content teams a reviewable order of action.
Competitive Positioning
Compare brand descriptions, attribute associations, competitor co-occurrence, and recommendation context in AI answers. Identify established positions, missing differentiation, and perception gaps across models and markets.
Content Strategy
Start with user questions, brand absence, competitor presence, and cited sources. Find the topics worth creating, updating, or reinforcing while preserving the answer and source evidence behind each recommendation.
Product Launch
Create a launch baseline around the product name, market questions, core differentiators, and alternatives. Monitor whether AI recognizes the product, how it describes and compares it, and which sources support recommendations.
Frequently asked questions.
Notes on page scope, data methodology, and usage.
No. Brands cannot directly control model output. Dageno helps teams see current perception, trace evidence, and validate changes after content and communication work, enabling better-informed calibration of public information.
Narrative Shaping / READY
Build a reviewable monitoring and action path for narrative shaping with real questions.
Confirm the brand, competitors, questions, models, and target markets. The Dageno team will demonstrate the complete workflow with relevant samples.
Brand-perception baseline
Narrative deviation list
Differentiator evidence gaps