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- Marketers, Ready for LLM-O?
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IN THIS ISSUE
Marketers, Are You Ready for LLM-O?
AI Poses Serious Risks And Needs to Be Supervised
Perplexity Enters Enterprise Search
TOP PICKS
Marketers, Are You Ready for LLM-O?
LLM-O: Search Engine Optimization for Large Language Models
Users can now get direct answers to their queries when they use LLM apps such as Perplexity, Google AI Overview, or ChatGPT. This is a better search experience than the traditional search results.
Marketers will be required to present their brands for relevant prompts and conversations, accurately.
WHY THIS MATTERS?
The biggest difference between LLM search experience -vs web-browser experience is: LLMs answer queries with answers.
Not links, unlike traditional web browsers.
Customers will converse with the LLM to learn about products and brands. It will be a conversational and consultative process.
Marketers will need to learn, anticipate, and prepare for this information pipeline to ensure their brands are presented by the LLM for appropriate prompts and questions.
If the LLM does not mention the brand at this stage, the user may never consider your brand in their journey.
LLMs operate differently than traditional search algorithms
The traditional search algorithms promote links that are seen as authoritative, comprehensive, and relevant. High-ranking websites emphasized metadata, keyword density, and backlinks.
LLMs are optimized to compile an accurate, compelling answer. They pull content from text, images, videos, reviews, brand site content, and user-generated content to create the answer. The LLM replies are all implicitly aware of where the user is in the buying process.
What should Marketers do?
Marketers need to think strategically about the various sources from which an LLM is likely to pull information.
Measure and monitor whether their brands appear in LLM output, and when this is most likely to happen
Monitor how favorably their brands are represented, and what negatives are attributed to their products
Monitor the visibility of their products and brands, as compared to their competition, across highly relevant prompts.
Doing so will require marketers to test and develop relevant metrics. They will also develop new workflows to manage the added complexity.
Monetization
There are 2 options, as of now: the subscription model and the ad monetization model
There will be multiple LLM options to choose from unlike a single, dominant player like today. This will open up new opportunities within LLMO.
The Career Path
LLMO professionals, traditionally SEO professionals, need to stay current with the dynamic and evolving LLM industry.
They will be required to manage the brand across multiple LLM platforms and learn new optimization methods while experimenting with new techniques.
AI Poses Serious Risks And Needs to Be Supervised
But, whistleblowers from OpenAI say that this is being overlooked.
The AI industry will surpass $1 Trillion in revenue by the end of this decade. Companies are in a race to claim the largest share of this pie. In the process, they are turning a blind eye to the serious risks, not in the public domain but well-known to the AI companies, that this technology poses.
WHY THIS MATTERS?
OpenAI employees released a letter stating "AI companies have strong financial incentives to avoid effective oversight, and we do not believe bespoke structures of corporate governance are sufficient to change this,”.
The employees believe that there is substantial information on the risks of AI tech and the harm that it can cause to mankind. But, the safety measures put in place are inadequate to contain it. AI companies are ‘weakly’ obligated to share the risks and safety information with governments and civil society. They will not share this voluntarily.
Inadequate Whistleblower Protection
Employees who may want to share this outside of the company may be at legal risk. They are not adequately protected by the current whistleblower laws as the AI industry is not as regulated as others.
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Perplexity Enters Enterprise Search
Slowly Emerging as a Google Challenger
Perplexity launched the subscription model Enterprise Pro to enhance enterprise search. It now serves both, regular users and enterprise users.
WHY THIS MATTERS?
Enterprise Efficiency: Perplexity’s AI search can significantly improve productivity within organizations. By providing accurate and relevant results, employees can find information faster, streamline workflows, and make informed decisions. This efficiency boost directly impacts business outcomes.
User Experience: As AI search becomes more prevalent in everyday apps and platforms, users expect seamless experiences. Perplexity’s approach ensures that consumers find what they need quickly, enhancing satisfaction and engagement.
Market Competition: Perplexity’s success could disrupt the search market dominated by giants like Google. If it delivers on its promise, other companies may adopt similar AI-driven search solutions, leading to innovation and increased competition.
What About Ads in Search Results?
Ads will come in the near future. But, without distorting the user search experience.
They may appear as 'related questions' giving marketers the opportunity to drive the conversation toward their brand. The goal will be to drive brand consideration and not necessarily an action.
Who Wins?
The one with more outcome data and a better feedback loop.
But, other than Microsoft, Apple, and Google, no other company has a significant data moat. By going the enterprise route or partnering with these companies in the future, Perplexity may be able to address this challenge.
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