Generative Engine Optimisation Use Case · Data Innovators Exchange

Apr 15 • General

Generative Engine Optimisation Use Case

In this week's datapro.news we present a playbook for Data Engineers on adapting to the new age of Search. Here is an example of how a leading UK Financial Services firm recently transformed their data architecture to support GEO, resulting in a 35% increase in visibility within AI-generated responses for financial planning queries.

Their approach included:

Entity-Relationship Modelling: They restructured their product data around financial planning concepts rather than product categories, creating clear relationships between financial goals, life events, and appropriate products.
Authoritative Citations: They integrated regulatory guidance and market data directly into their data models, with proper citations and timestamps, increasing the likelihood of being referenced in AI responses.
Real-Time Data Pipelines: They implemented streaming data pipelines that ensured rate information and product details were updated in near real-time, addressing a key weakness in their previous batch-oriented approach.
Cross-Functional Data Teams: They created hybrid teams combining data engineers, financial experts, and content specialists to ensure data structures aligned with both technical requirements and user needs.

The result was not only improved visibility in AI search but also a 22% increase in qualified leads from digital channels as customers received more relevant, contextual information about their services.

Check out the in-depth guide on GEO here https://www.perplexity.ai/page/the-generative-engine-search-r-Y9_1tFJwQCCMAVF1MvNRgQ

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