How to integrate GEO tactics within your existing B2B marketing strategy

Getting a brand, product, or service to surface in today’s search queries requires a change in strategy. The good news is, Google has lost its monopolisation on discoverability. The bad news is, your marketing strategy needs to evolve with user search behaviour.  

It’s now necessary to look beyond search engine optimisation (SEO) and think tactically about generative engine optimisation (GEO). This means making your brand more visible to large language models (LLMs) such as ChatGPT, Gemini, and Perplexity.  

Don’t worry, it’s not a case of ripping up the rulebook. Most of the tactics you’re already following for SEO are applicable for GEO. It’s just important to understand the nuances, find out what your current AI visibility is like, and implement adjustments to maximise reach in this AI era.   

Whether your prospect is using their favourite Gen AI platform or their favourite search engine, if their query is relevant to your business, your brand should be surfaced.

Our step-by-step guide to implementing a GEO strategy.

Stage 1: Market research and analysis.

Effective market research and analysis – in the context of GEO – involves deeply integrating an understanding of generative AI usage within your initial strategy.  

1. Determine your ‘core query set’: identify the specific industry-related questions that your target audience frequently asks. This doesn’t need to be queries that have come from LLMs, but ones that prospects are likely to ask LLMs in the future. Actually, the best way to curate this list is by using your CRM data or speaking with your sales team. It’s important you note the language prospects use. So, analyse sales calls scripts and build your understanding of what they want to know – and when. This should give you crucial insights into buyer intent and conversational patterns. In turn, it’ll allow you to structure your content and messaging in a way that mirrors your prospects AI queries.  
2. Competitor analysis: conduct a comprehensive competitor visibility analysis to gauge how well others are already performing within these generative AI environments. Identify competitors who regularly appear within LLM-generated responses and explore why their content or brand resonates with AI algorithms. This competitor analysis will help you pinpoint what GEO strategies and tactics are already working, providing a robust foundation for your GEO efforts.

Stage 2: Positioning and messaging.

Developing effective positioning and messaging within the GEO framework involves crafting content explicitly designed for conversational interactions typical of LLM queries. 

1. LLM-ready messaging: Your positioning statements and key messages should naturally fit question-and-answer formats, aligning seamlessly with user expectation. 
2. Keyword and phrase alignment: incorporate exact-match conversational phrases that your audience frequently uses, ensuring your messaging closely aligns with real-world user interactions. This careful linguistic synergy boosts your visibility in AI-generated responses.

Stage 3: Content and asset development. 

To excel in GEO, content creation must focus on developing educational, authoritative, and comprehensive assets that directly answer essential buyer questions. 

1. GEO-aligned content creation: Prioritise content formats that are clearly structured, such as detailed FAQs, how-to guides, and insight-rich thought leadership articles. These formats – not coincidently – align well with your users’ needs and the content preferences of generative AI. These content types will enhance your chances of being surfaced and cited in LLM responses. 
2. Strategic use of data: Embed unique, original statistics and insights into your content to encourage citation and enhance brand SOM. 

Stage 4: Channel strategy and distribution. 

User-generated and organic content is regularly cited in LLMs. In fact, many favour this type of content. So, it’s important you get your valuable content shared as far and wide as possible. Inviting additional commentary from partners or colleagues will give you a boost too.  

1. Content syndication and PR: Ensure your core thought leadership and educational assets are shared across influential industry platforms, authoritative third-party websites, and high-visibility media channels.  
2. Forum and community engagement: If relevant, actively engage in professional communities such as LinkedIn, Stack Overflow, Quora, and Reddit. Getting involved in these communities helps seed your content in areas commonly referenced by generative AI models.  

Stage 5: Measurement and optimisation. 

From choosing your tools and metrics to working out your routine for monitoring and optimisation, it’s important to regularly review your content.   

1. GEO monitoring tools: Utilise specialised monitoring tools to continuously measure your brand’s ‘Share of Model’ (SOM) and sentiment across various LLM platforms.  
2. Iterative improvement: Regular analysis of these metrics allows you to identify visibility gaps and areas for improvement. Use these insights to iterate and refine your content and distribution approaches. This ongoing optimisation ensures your GEO strategy remains effective, adaptive, and consistently aligned with evolving generative AI algorithms and user behaviours.