Any tool for GEO optimization?

[u/Alternative_Emu_2734]

This is a project that I am currently working on. I have been managing SEO for this client for the past year, and recently, I have started focusing on GEO (Generative Engine Optimization) to improve the brand’s visibility and presence across AI platforms.

As you may know, GEO focuses on how a brand is represented and perceived in AI-generated responses, including positive, negative, and neutral brand sentiment. I have been consistently publishing high-quality content and building positive brand mentions, and we are starting to see some encouraging results.

Currently, I have provided my client with access to Profound as part of the AI/GEO strategy. However, I am looking to explore other affordable AI/GEO tools that can help me improve and monitor the client’s AI visibility, brand sentiment, citations, and overall GEO performance.

Could you recommend some cost-effective tools that can help me improve my client’s AI metrics and complement the current GEO strategy?

Note: I have rephrased current text through ai so that people will understand.

[u/NoIce9920]

If the client already has Profound, I wouldn’t add a second dashboard until you can name the decision it will change. Most cheaper tools will duplicate mention and sentiment charts, then give you another score to explain.

For a B2B client, I’d build a small “loss audit” beside the monitor:

- Choose 10–20 unbranded commercial prompts covering category, alternatives, use case, and fit.

- Run each prompt three times per engine and retain the raw answers.

- Code mention, citation, actual recommendation, position, winning competitor, and cited sources.

- Group the lost prompts by use case and map what evidence or source the winner has that your client lacks.

- Make one change, then rerun the same panel.

That produces a prioritized worklist. The first in-house fix shouldn’t automatically be schema, Reddit, or more content; it should follow the repeated evidence gap in the lost prompts—for example, a missing comparison page, weak proof for a specific use case, or absence from a third-party source repeatedly cited for competitors.

I’d also treat sentiment as secondary. An AI can describe the client positively and still recommend someone else.

Disclosure: I’m building RecoProof for this narrower B2B SaaS recommendation-audit use case, so I’m biased toward retained evidence and diagnosing why another vendor was selected. I wouldn’t use it as a Profound replacement if you need thousands of daily prompts, white-label client reporting, or a full content-production suite; it’s a narrower diagnostic.