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From SEO to GEO – Exploring Generative Search Readiness

  • by LB Forsikring (Danemark)

Objectives

The overall purpose is to explore how traditional SEO practices need to evolve towards GEO (Generative Engine Optimization) in a context where users increasingly search, compare and get recommendations through AI‑driven and generative interfaces (e.g. LLMs).

Key objectives are:

  • Understanding how LB’s products, services and advisory content can remain discoverable and accurately represented in generative search experiences
  • Identifying how authoritative, compliant and member‑oriented insurance content can be surfaced and referenced by LLMs
  • Assessing implications for content strategy, technical SEO, structured data and brand authority

Building internal knowledge to support future decisions on tooling, processes and investments

Progress status

Under development
  • Exploratory phase since Q4 2025. No fixed end date.
  • Currently in an investigation and capability-building phase, with the aim of defining a clear GEO approach and roadmap during first half of 2026.

Work team

  • Developed in house with external support.
  • Project Management: Project Mgt: owned by the Marketing & Digital Strategy / Digital Sales (MDS) team, with primarily strong involvement from our SEO/Content Specialist as well as our Copywriter
  • External partner/team: External partners: A performance marketing agency (S360) supporting SEO/GEO-strategy and analysis. An external copywriter producing content based on internally defined briefs

Work carried out to date

  • Conceptual clarification of SEO vs. GEO and how generative search differs from traditional search engines
  • Mapping potential use cases and risks for an insurance company operating in a highly regulated domain
  • Internal knowledge sharing and presentations to align stakeholders around why GEO is becoming relevant
  • Initial analysis of how existing content types (guides, product explanations, advisory content) might perform in generative contexts
  • Technical implementation is planned to be carried out in Q2

First Results & Lessons learnt

Early learnings include:

  • GEO is less about short‑term optimization tactics and more about content quality, authority, clarity and consistency
  • Strong alignment between brand trust, subject‑matter expertise and structured information seems critical in generative environments
  • Many existing SEO best practices remain relevant, but need to be reframed to support AI‑driven interpretation rather than rankings alone
  • Cross‑functional collaboration (SEO, content, legal/compliance, digital strategy) will be essential

Difficulties encountered & Remainng Challenges

Key challenges and open questions include:

  • Limited transparency into how generative engines select, weight and present sources
  • Measuring impact and defining relevant KPIs for GEO compared to traditional SEO
  • Ensuring compliance, accuracy and controlled messaging when content is interpreted by third‑party AI systems
  • Deciding where to draw the line between experimentation and scalable, operational processes
  • Understanding how other insurance companies are approaching GEO and what organizational models work best.