Brand Understanding and Narrative Building
Define the questions that matter, what a correct answer should say, and where the brand needs to earn authority across key audiences.
Be present, accurate, and influential when AI shapes the answer. When HCPs, patients, caregivers, or payers turn to AI, brands need to be easy to find, accurately represented, and supported by credible evidence.
Indegene helps improve AI visibility across the sources and platforms that shape those answers. We measure the outcome as Share of Algorithm.
230M+
weekly health questions on ChatGPT
81%
of physicians use AI professionally
0.6%
click-through with an AI Overview
Across many brands, the pattern is similar. Institutional sources dominate citations, class-level language can crowd out brand names, and owned sites often earn little citation share when content is not structured for retrieval. Even when a brand appears, the evidence that differentiates it may be missing.
This creates an evidence-visibility paradox: the brand is present, but the evidence needed to build clinical confidence is not. Traditional traffic metrics do not show whether the brand is retrieved, represented accurately, or prominent when AI shapes the treatment shortlist.
Today, humans read the answer. Soon, the HCP's AI will rank it first, with EHR agents following. Each step moves the decisive moment from your website to the answer.
Healthcare has the highest reported AI Overview trigger rate of any industry, at 89%.
AI answers will overtake traditional search around 2028 and reach about two-thirds of monthly visits by 2030.
This single metric will track Presence, Precision, and Prominence to show whether a brand is visible, accurate, cited, and competitive in AI answers.
Every shift rewards the same discipline: science engineered for retrieval, structured for citation, and monitored daily. Own the narrative in the answer itself.
Define the questions that matter, what a correct answer should say, and where the brand needs to earn authority across key audiences.
Daily tracking feeds weekly engineering. Every citation compounds, at no cost per impression.
Proof
40%
increase in AI visibility across priority brands
30%
reduction in time to assess and optimize each additional brand
2x
increase in priority narrative coverage before launch
Understand the roles of generative engine optimization, answer engine optimization, and large language model optimization as discovery shifts from links to answers.
Learn how schema markup and structured data can make pharma content easier for search engines and AI systems to interpret.
Explore how connected data, content, activation, and measurement can create a stronger foundation as AI changes how healthcare professionals find information.
A market- and persona-specific baseline of Share of Algorithm, narrative accuracy, citations, source influence, and priority gaps.
A narrative architecture connecting strategic priorities, evidence, competitive context, and the answer components that matter most.
An intent-based prompt universe tied to brand strategy, evidence, audience needs, market, and language.
Priority websites and digital assets restructured to improve retrieval, interpretation, and citation.
A prioritized plan for credible external sources that validate approved information and strengthen source confidence.
Trial data, publications, and medical evidence structured so clinical AI platforms can find, interpret, and cite them accurately.
Selective paid distribution to reinforce approved narratives and support the broader owned, earned, and clinical ecosystem.
Consistent tracking of Presence, Precision, and Prominence across relevant engines, competitors, audiences, markets, and languages.
Detection, evidence-based triage, and medical, legal, and regulatory-aligned action when AI answers misstate or omit important information.
Share of Algorithm measures a brand across Presence, Precision, and Prominence: whether it appears, whether the information is accurate and cited, and how it ranks against competitors.
Generative engine optimization improves how approved brand content and clinical evidence are found, interpreted, cited, and repeated by AI platforms across owned, earned, clinical, and paid sources.
It defines the approved narrative, evidence hierarchy, competitive frame, and audience needs that optimization must preserve.
It maps the questions HCPs, patients, caregivers, and payers ask to brand strategy, evidence, market, and language, keeping monitoring focused on real intent.
Consumer and clinical AI use different information environments but shape the same brand narrative. Commercial teams improve discovery, while Medical Affairs protects evidence depth and scientific accuracy.
The operating model remains consistent while prompts, approved evidence, sources, language, and governance adapt to each market and regulatory context.
Give us your priority brands, markets, and audiences. We will establish a Share of Algorithm baseline, show which sources and narratives shape the answer today, and define the priority actions across owned, earned, clinical, and paid channels.