Unlock scalable organic growth with AI search optimization

Q: How do I design effective prompts for LLMs?

Use clear, specific, and context-rich instructions, and test variations to identify what generates the best results.

Q: What is the role of training data in influencing LLM behavior?

Training data shapes the knowledge and biases of an LLM. When AI search platforms have access to curated datasets, it can help refine outputs to better align with desired goals.

Q: Can I customize LLM outputs for my business needs?

Yes, however due to the novelty of the technology and its evolution, it is unclear how to directly guide and alter LLM outputs. That’s why Previsible is experimenting to discover which methods are most effective for fine-tuning AI models and impacting results.

Q: What tools can help optimize LLM outputs?

Tools like prompt optimization platforms, observability frameworks, and LLM monitoring solutions can improve output quality and reliability.

Q: How to optimize for Google AI Overview?

Leverage E-E-A-T principles (Expertise, Experience, Authoritativeness, Trustworthiness), create helpful and engaging content, and utilize structured data to align with Google's AI understanding of content.

Drive AI search results with impactful experiments tailored to your business.

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The rise of generative AI search

The increasing use of AI search tools like ChatGPT creates new challenges for businesses trying to maintain visibility and track brand sentiment effectively. The way people search is changing—businesses need to change with it. Unlike traditional search engines, there are no clear guidelines outlining how to optimize for AI, so we’re setting out to discover how to best adapt digital marketing and SEO strategies to this new form of search.

To do this, Previsible is teaming up with clients to run experiments that test out unique optimization strategies and measure their impact on brand perception and the information that is presented to searchers through LLM outputs.

Navigating the AI landscape

Previsible is partnering to help brands navigate the complexities of AI-driven search landscapes. We want to help companies better understand their brand’s AI visibility and provide a clear, actionable roadmap for improvement.

90%

For the first time in years, Google’s market share of search has dropped below 90% (AI Study).

25%

If current growth rates hold, what’s currently 0.25% of total traffic from LLMs could become 25% of the overall traffic by 2026 (Gartner).

37%

Perplexity and ChatGPT each command about 37% of LLM referral traffic (AI Study).

AI search optimization

AI search optimization is a scalable solution designed to enhance your organic presence in AI search by leveraging content investments that improve visibility and accuracy in AI outputs. As AI search evolves and numerous LLMs jockey for position in the market, it’s clear that no single AI strategy will work for every business. By implementing targeted experiments across different platforms, we will identify the most effective way to integrate content into AI search outputs, large language models (LLM), and AI-driven experiences to increase visibility and unlock new opportunities for growth. This offering is focused on gaining a deeper understanding of how discovery is changing for consumers and generating effective, scalable solutions to compete in this emerging search landscape.

Step 1

Market Sentiment Analysis

To start, we will analyze how your business is showing up in AI search outputs—how is your brand perceived? How do you compare to competitors in the market? What AI-generated information about your business is inaccurate or irrelevant? Through this analysis, we will identify personalized, data-driven insights into existing strengths and weaknesses, as well as opportunities for improving brand awareness and sentiment.

Step 2

Custom Experimentation

Using the market sentiment analysis, we will build a customized strategy to generate targeted content, brand awareness, discoverability, and out-of-the-box ideas that will impact and influence LLM results. This may include:

Improving digital PR and brand authority through internal and external channels.
Creating intentionally-structured, LLM-focused content.
Investing in activities that will generate marketing buzz and customer advocacy.

Step 3

Visibility Tracking

We will monitor each experiment's performance, tracking LLM outputs and creating sentiment reports to evaluate its effectiveness and make necessary adjustments.

Run LLM experiments with Previsible

Take part in our multi-phased experiments and discover what generative AI will bring to your business.

Feature

Pilot Program

Annual Retainer

# of Experiments

Timeline

6 months

1 year

Word/Content Limit

Up to 30,000 words

Up to 90,000 words

Ongoing Revisions

Customized Prompt Testing

15 Prompts

60 Prompts

Reporting

Monthly Reporting

Monthly Reporting & In-depth Analysis

LLM Prioritization (ChatGPT, Perplexity, Gemini, etc)

Limited

Customized

Web Publishing

Dedicated Support

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Got questions? We’ve got answers!

Still can’t find what you’re searching for? Our Frequently Asked Questions section may hold the answers you need.

How can AI improve search?

AI enhances search by providing personalized results, understanding user intent, enabling semantic search, and improving voice and image-based searches. It can also benefit website owners by providing a new way to direct relevant traffic to their sites via source links included in AI outputs.

How do I design effective prompts for LLMs?

What is the role of training data in influencing LLM behavior?

How to optimize for AI results?

Presently, there is still little known about how to optimize for AI results. However, initial research has shown that SEO best practices such as utilizing structured data markups, optimizing for voice and conversational queries, creating well-organized content, and implementing schema to help AI understand your content not only help with search bots, but also indicate to LLM bots the quality of a site/page. Previsible’s experiments aim to further uncover which elements are prioritized by AI search engines and develop strategies to optimize them.

Can I customize LLM outputs for my business needs?

What tools can help optimize LLM outputs?

How to optimize for Google AI Overview?

Why do LLM outputs sometimes include irrelevant or outdated information?

LLM outputs depend on the model's training data, which can sometimes be irrelevant or out of date, which can affect the accuracy of the outputs. Having inconsistent information across different sources (for example, a brand's website, social media accounts, press releases, external resources mentioning and linking to site, etc.) can confuse LLMs, leading to inaccurate or irrelevant information in the outputs. That is why it's important for any brand to ensure that their information is uniform and up to date across every digital channel they can control, providing the most accurate, unified, and relevant signals to the AI model.