GPT Store and SEO for GPTs

OpenAI announced the GPT Store today and it has the potential to become as busy a marketplace as Apple’s App Store and very fast. What this means for developers of specific GPTs is that they need to think about ranking in this store because the store will be a type of search engine. – there’s a familiar challenge: getting found. GPT Store and SEO for GPTs will become a serious issue. Just as the advent of the App Store revolutionized mobile software, the GPT Store promises to be a playground for creatives and developers alike, offering tailored AI experiences through a plethora of specialized GPTs.

For your custom GPT to succeed, it’s not just about how intelligent or advanced it is; it’s also about how visible it will be in the GPT Store. This is where the concept of ‘GPT Store Optimization’ (GSO) might come into play, mirroring the well-established practice of App Store Optimization (ASO) for mobile apps.

The premise is simple yet critical: When users search the GPT Store, they should be able to find your GPT easily, and your creation should rank well within its category. But how?

Understanding GPT Store Algorithms

The announcement from OpenAI suggests that GPTs will be searchable and may “climb the leaderboards.” This implies an algorithmic ranking, possibly akin to search engines and app stores, where factors such as relevance, user engagement, and quality drive visibility.

Relevance and Keyword Optimization

Your GPT must be meticulously tailored to your target audience’s needs. Like optimizing web content for Google or an app for the App Store, choosing the right keywords for your GPT’s description and metadata is crucial. Understand the language and terms potential users will employ when seeking out the functionality your GPT offers. At the moment we don’t have any information about how GPTs are going to be defined, labelled, categorised etc. but there will have to be some sort of taxonomy and labelling.

User Engagement and Reviews

High engagement levels are likely to influence your GPT’s visibility positively. These market places are nothing if not Darwinian. So getting users to interact with your GPT frequently and for longer sessions will probably benefit your ranking. Reviews will undoubtedly play a significant role, too—stellar feedback may boost your standings on leaderboards, while negative reviews could do the opposite.

Quality and Retention

The announcement hints at the possibility of monetization based on usage. This means retention could be a vital metric. Quality will be a cornerstone here; if your GPT is not only unique but also provides value, users will return, and new users will find it through recommendations and higher rankings.

Categories and Leaderboards

It’s essential to place your GPT in the correct category to ensure it reaches the right audience. Being a top performer in a niche category can be more beneficial than being lost in a sea of generalists. Climbing the leaderboard in your category will require understanding the nuances of what the GPT Store algorithm values most.

Spotlights: The Role of OpenAI’s Curation

The mention of spotlighting “the most useful and delightful GPTs” suggests that OpenAI will curate content, much like featured apps on the App Store. Gaining such a spotlight could significantly enhance your GPT’s visibility. This could involve networking within the OpenAI community and ensuring your creation stands out in utility and innovation.

The launch of the GPT Store marks a significant milestone in the evolution of AI tools and services. It will democratise and dramatically accelerate the process of app development so to succeed, builders must adapt and apply robust SEO strategies to ensure their custom GPTs are not only useful and innovative but also discoverable. With the right approach, the opportunities for visibility and monetization are boundless. Keep these factors in mind, and you may just find your GPT leading its category, one search at a time. The GPT Store and SEO for GPTs is the new marketing challenge.

Impact of Grok AI on Business

Elon Musk’s X.ai is launching its own LLM called Grok that will have the currently unique feature of having access to the live Twitter / X data stream. This means it will be able to answer questions about near real time events, thoughts, controversies, ideas and, tediously, celebrity news too no doubt. So what will be the impact of Grok AI on business?

It’s far too early to know at the moment but as a first attempt I asked ChatGPT the following question.

“Suppose a new LLM had access to up to the second information via the Twitter platform, what would be the implications for business and how might one utilise the tool?”

<STARTS>

If a new Language Model (LLM) had access to up-to-the-second information via Twitter / X, it could have significant implications for businesses in various ways, particularly in the areas of market intelligence, customer service, and real-time decision-making. Here’s how businesses might utilize such a tool:

Market Intelligence and Trends Analysis:

Real-time Monitoring: Companies could monitor real-time public opinion and reaction to events, products, or services, allowing them to adjust marketing strategies promptly.

Trend Spotting: The LLM could identify emerging trends by analyzing the velocity and sentiment of tweets on particular topics, providing businesses with early insights into consumer interests and market shifts.

Customer Service and Engagement:

Instant Response: By integrating the LLM with their customer service platforms, businesses could provide instant responses to customer queries on Twitter, improving customer experience.

Sentiment Analysis: The LLM could assess customer sentiment in real-time, allowing businesses to address complaints or issues before they escalate.

Personalization: By analyzing tweets, businesses could tailor their communication to individual customers, enhancing engagement and loyalty.

Crisis Management:

Issue Detection: The LLM could quickly identify negative trends or potential crises related to the company, enabling faster response and mitigation efforts.

Communication Assistance: It could help draft real-time responses and communication strategies to manage public perception during a crisis.

Competitive Analysis:

  • Competitor Monitoring: Businesses could use the LLM to keep track of competitors’ activities, announcements, and customer feedback, providing insights into their strengths and weaknesses.
  • Benchmarking: It could help in analyzing how competitors’ events or product launches are being received by the market.

Content Creation and Curation:

  • Content Ideas: The tool could generate content ideas that are currently trending or likely to resonate with the audience.
  • Automated Posting: Businesses could use it to create and post Twitter content in real-time, reacting to ongoing discussions or events.

Financial Markets:

  • Market Sentiment: In financial services, the LLM could gauge market sentiment on financial products, stocks, or cryptocurrencies, potentially influencing trading decisions.
  • Event-Driven Trading: Traders might use insights from Twitter to inform event-driven trading strategies.

Product Development:

  • Feedback Analysis: Real-time analysis of feedback on products could inform product development and improvement.
  • Idea Generation: The tool could identify gaps in the market or consumer pain points that could lead to new product ideas.

Risk Management:

  • Reputation Monitoring: Constant monitoring of the brand’s perception on Twitter could help in assessing and managing reputational risks.
  • Compliance and Governance: The LLM could detect discussions related to regulatory compliance, potentially identifying risks or required actions.

Strategic Planning:

  • Data-Driven Decisions: Insights gleaned from Twitter data could be incorporated into strategic business decisions, making them more responsive to current events and trends.

Advertising and Promotions:

Targeted Campaigns: Analysis of Twitter could help in creating targeted ad campaigns that align with current discussions and user interests.

Influencer Identification: It could identify key influencers and opinion leaders in real time, providing opportunities for partnerships or endorsements.

Challenges and Considerations:

  • Data Privacy: Businesses must navigate privacy concerns and adhere to regulations regarding the use of public data from social platforms.
  • Information Overload: The sheer volume of data might require sophisticated filtering to avoid analysis paralysis.
  • Misinformation: The tool would need to be capable of distinguishing between credible information and rumors or fake news.
  • Contextual Understanding: Tweets are often nuanced and filled with slang, humor, and sarcasm, requiring advanced understanding to interpret correctly.

Overall, a real-time LLM with Twitter access would be a powerful tool for businesses, provided it is used responsibly and in compliance with data protection laws and ethical guidelines. The key would be integrating the insights into the decision-making process in a meaningful way that enhances, rather than overwhelms, business intelligence functions.

<ENDS>

Impact of Grok AI on Business

The impact of Grok AI on business is likely to be profound both directly and indirectly. Accessing real time data will be increasingly important as the competitive environment becomes all the more intense and nimble businesses that respond to events fastest could gain competitive advantage. Consider a situation where an influencer tweets about your product or service. You could automatically respond with a tweet offering a special one-day only offer to capitalise on the publicity. Clearly a social media manager could do the same but most businesses don’t have the resources to employ a dedicated social media manager.

Indirectly, X.ai giving Grok AI access to the twitter feed will put considerably pressure on other LLM suppliers like OpenAI, Google, Microsoft and others to make up to date information available to their LLMs too. However, at the moment, those suppliers don’t have access to anything like the up to date information fire hose that Twitter / X has and it seems unlikely that Elon Musk and X.ai will want to release it in a hurry either. Why would they?