Large Language Models have changed the way brands are discovered, evaluated, told. BIKMA is the framework — developed with the University of Pisa, cited at The Web Conference 2019 — that measures how your brand appears to generative models. The Light version of the analysis is free.
Until three years ago, the brand discovery funnel went through Google and landed on your site. Today a growing share of that funnel never sees your site. It sees an answer generated by ChatGPT, Perplexity, Gemini, Claude — an answer that talks about your brand, describes its products and values, compares it with competitors.
You did not write that answer. It was composed by the models, drawing from dozens of sources: your official content, third parties, news, reviews, social, structured data. The LLM selects, summarises, synthesises. And in synthesising it may say things that do not match your truth.
For most brands we meet, this is a complete blind spot: no one measures what the machines say about them, no one knows their generative Share of Voice, no one checks whether LLMs are citing the brand accurately.
It is a gap that can be closed — and this is the right moment, before it becomes a structural cost.
BIKMA Light is the entry version of the Brand Insight Knowledge Mapping Analytics framework. We measure six dimensions of your brand’s presence in generative models on a defined scope, collect the data, build the assessment, and return the results in a call.
No commitment. No commercial follow-up unless you ask for it.
We map explicit demand (what is actively searched for) and latent demand (what would be searched if the topics were already articulated). It is the starting point for understanding where your brand should be visible and is not yet.
Behavioural clusters and segments behind demand. Who they are, what stage of the journey they are in, what they are really looking for — beyond the literal wording of the query.
We measure your brand’s presence in LLM responses for a set of key queries, against a defined competitive set. How often you are cited, in what narrative position, with what weight relative to competitors.
We identify the sources that feed LLMs about your brand. Are they your official content, or third-party sources, news, social, reviews, retailers, trade publications? The generative knowledge graph becomes explicit and mappable.
Tone of the responses. Positive, neutral, critical, and which specific attributes the model’s judgement focuses on — price, quality, ethics, innovation, sustainability. It is the public face of your brand filtered through the machines.
How much what LLMs say about your brand coincides with what the brand officially states on its own site. It measures the risk of generative misinformation — an increasingly critical issue for pharma, regulated food, finance.
BIKMA — Brand Insight Knowledge Mapping Analytics — is the result of eight years of research collaboration with the University of Pisa. In 2019 the paper describing the model was selected and cited at The Web Conference of San Francisco — the leading international scientific conference on the Web. We update it every year together with the university research: the extension that measures visibility in LLMs is the most recent output from our teams.
So far we have applied it to over 200 enterprise projects for brands in pharma, food, luxury, manufacturing and banking. The analysis you receive with BIKMA Light is not a sales demo: it is a contained version of what we do for Bayer, Lactalis, Chiesi, Barilla. Same method, tighter scope.
Repositioning post-mergerAfter a merger or acquisition, the brand needs to know how it is being read by the machines and which knowledge sources are feeding the LLMs. BIKMA Light gives a sharp first picture.Entry into a new category
Regulated sectors
Every year the CMO must decide where to invest content, SEO, PR, digital. BIKMA Light is the briefing material that prevents starting the plan from old assumptions. 07 · After the analysis
If the analysis surfaces a real opportunity and you want to act on it, we open a full BIKMA project . We extend the perimeter, add the missing dimensions, build the activation roadmap. Typically 8–12 weeks of work, with concrete deliverables and senior management of the project.
An Italian FMCG brand in the food sector had a generative Share of Voice of 12% against a direct competitor at 31%, despite higher market share. BIKMA analysis revealed that the competitor owned nine key sources — trade publications, nutrition blogs, retailer product pages — that the brand was not treating as central in its editorial plan.
An Italian luxury brand was cited with 78% positive sentiment in LLMs, but with a significant narrative drift: the heritage of the brand was systematically associated with a city where the company had never operated. It was a chain of third-party citations consolidated on a Wikipedia entry that had never been corrected. A correction realigned the knowledge graph in eight weeks.
At the end of the readout call you have three paths open. None implies a commitment to us.
If the results that emerge call for an articulated action plan — content strategy, SEO/GEO, knowledge graph management, relations with third-party sources, continuous fact alignment — we can build a tailored project. It’s the path most enterprise brands choose.
If you prefer to manage continuous monitoring in-house and use the platform autonomously, BIKMA is available in self-serve on bikma.ai. Monthly subscription, real-time data, integration with your marketing and content systems.
If BIKMA Light gave you the awareness you were looking for and you prefer to move without external partners, that is fine too. We leave you the report, the methodology explained, our contacts for any future questions. No commercial follow-up.
Free. No commitment. Five business days. Readout with a senior consultant.