At www.AIsapiens.net, we help brands understand and shape how Artificial Intelligence (AI) perceives and presents them to the world. In today’s rapidly evolving digital landscape, what AI “thinks” about your brand is increasingly critical. This article will explore how you can influence AI training data to positively impact your brand perception.

The Growing Importance of AI in Brand Perception

AI chatbots, like those powered by OpenAI’s models, are rapidly becoming a primary source of information for consumers. As of December 2024, OpenAI reported over 300 million weekly users. This number is only expected to grow. People are using AI to research products, compare services, and make purchasing decisions. This means that the information AI provides about your brand directly influences consumer behavior and, ultimately, your bottom line.

Traditional Search Engine Optimization (SEO) is no longer enough. While optimizing for search engines remains important, AI chat is quickly becoming the preferred method for many users to gather information. This represents a paradigm shift. Instead of solely focusing on keywords and backlinks, brands must now consider AI Optimization – ensuring that AI models have a positive and accurate understanding of their brand.

Furthermore, the rise of AI agents is on the horizon. These agents will act on behalf of users, making purchasing decisions and recommendations. This makes the opinion of AI models even more crucial, as they will directly influence the choices AI agents make for consumers.

Understanding AI Training Data: The Foundation of AI Perception

To influence how AI perceives your brand, you need to understand how AI models are trained. Most large language models (LLMs) are trained on massive datasets scraped from the internet. These datasets, often referred to as “corpora,” include:

  • Web Pages: Everything from news articles and blog posts to product reviews and forum discussions.
  • Books: Digitized books provide a vast source of information and writing styles.
  • Code Repositories: Sites like GitHub contribute to the AI’s understanding of programming languages and technical concepts.
  • Social Media: While often filtered, social media content can still influence the model’s understanding of trends and public sentiment.
  • Wikipedia: Wikipedia’s structured text and encyclopedic entries give large language models a basic understanding of countless topics. https://en.wikipedia.org/wiki/Main_Page
  • Common Crawl: Common Crawl contains petabytes of data collected since 2007. It contains raw web page data, extracted metadata and text extractions. https://commoncrawl.org/

The sheer volume of this data is staggering. For example, the Common Crawl dataset, a publicly available web crawl, contains petabytes of information. Datasets like C4 (Colossal Clean Crawled Corpus), used in training some models, are derived from Common Crawl and are carefully filtered to improve quality.

The problem is that this data isn’t always accurate, unbiased, or up-to-date. It can contain:

  • Outdated Information: Your brand may have undergone significant changes (rebranding, new product lines, etc.) that aren’t reflected in older online content.
  • Negative Reviews: A few negative reviews, even if outliers, can disproportionately influence the AI’s perception.
  • Misinformation: Incorrect or misleading information about your brand can spread online and be absorbed by AI models.
  • Competitor Bias: Content promoting competitors might overshadow your brand’s positive attributes.
  • Bias from News Sources: An LLM’s perception may be influenced by the biases of the new sources it scrapes. https://www.allsides.com/blog/study-confirms-media-bias-chart-accurately-rates-news-sources

Strategies to Influence AI Training Data

While you can’t directly edit the training data of proprietary models like those from OpenAI or Google, you can influence the information available online, which will, in turn, impact future AI model training iterations. Here are key strategies:

  1. Content Creation and Optimization:
    • High-Quality Content: Create authoritative, accurate, and comprehensive content about your brand, products, and services. This includes blog posts, articles, white papers, case studies, and FAQs.
    • Schema Markup: Use schema markup (structured data) on your website to help search engines (and AI crawlers) understand the context of your content. This makes it easier for AI to extract key information about your brand. https://schema.org/
    • Knowledge Graphs: Consider creating a knowledge graph for your brand. This is a structured representation of your brand’s key entities, attributes, and relationships. While not directly fed into LLMs, it can improve your visibility in search results, which indirectly influences AI.
    • Regular Updates: Keep your website content fresh and updated. Outdated information can negatively impact AI perception.
  2. Online Reputation Management:
    • Monitor Online Mentions: Use tools to track mentions of your brand across the web, including news sites, blogs, forums, and social media.
    • Address Negative Reviews: Respond professionally and constructively to negative reviews. Demonstrate that you are actively addressing customer concerns.
    • Encourage Positive Reviews: Encourage satisfied customers to leave positive reviews on relevant platforms.
    • Fact-Checking and Correction: If you find inaccurate information about your brand online, attempt to have it corrected. Contact website owners or publishers directly.
  3. Public Relations and Media Outreach:
    • Press Releases: Issue press releases about significant company news, product launches, and achievements.
    • Media Coverage: Secure positive media coverage in reputable publications. This can significantly influence AI’s perception of your brand.
    • Thought Leadership: Position your company’s leaders as experts in your industry. This can be achieved through speaking engagements, articles, and interviews.
  4. Leveraging AI Measurement and Explanation Tools:
    • Understand Current AI Perception: Use our platform at www.AIsapiens.net to measure what AI models are currently saying about your brand. We provide detailed analytics across 30 key features for your industry, broken down by country and demographic group.
    • Identify Root Causes: We help you explain why AI models are conveying specific things about your brand. Our platform analyzes petabytes of training data to pinpoint the sources influencing AI perception.
    • Targeted Content Gaps: Identify areas where your brand’s online presence is weaker than competitors’. Focus on creating content that fills these gaps.
  5. AI Optimization (Our Approach):
    • Custom Projects: We offer custom AI Optimization projects. This involves a targeted approach to the URLs mentioning your brand and addressing content gaps compared to your competitors.
    • Data-Driven Strategy: Our approach is based on a deep understanding of the training data used by LLMs. We leverage access to petabytes of open-source training datasets, with over 100TB added monthly.

Our Platform: AIsapiens.net

Our platform, www.AIsapiens.net, provides a comprehensive suite of tools to measure, explain, and influence AI’s perception of your brand. Here’s how we can help:

  • Comprehensive Coverage: We cover over 12,874 consumer brands and 3,712 software brands, with the ability to add niche verticals upon request.
  • Deep Expertise: We possess deep expertise in LLMs and AI models in general.
  • Vast Datasets: We have access to billions of pages and hundreds of terabytes of data, representing a significant portion of the data LLMs are trained on.
  • Monthly Brand Index: We provide a proprietary Brand Index for each industry, consolidating 30 attributes into a single score to track your brand’s progress.
  • AI Customer Personas: Simulate focus groups with 10 typical customer personas for your brand. Ask them questions about upcoming campaigns or design changes to get instant, authentic feedback.
  • AI-Powered Insights: Our built-in AI assistant provides instant insights on every data chart and table, saving you time and ensuring you don’t miss key information.
  • Brand Coherence Tools: Upload documents and images to receive AI feedback on how to better align them with your brand guidelines.
  • Compare Brands: Compare your brands with others on different markets and demographics.

The Future of Brand Perception

The influence of AI on brand perception will only continue to grow. Brands that proactively address this challenge will be better positioned for success in the future. By understanding how AI models are trained and implementing strategies to influence the available online information, you can shape a positive and accurate AI perception of your brand.

Conclusion

Influencing AI training data is a long-term, ongoing process. It requires a combination of content creation, online reputation management, public relations, and a deep understanding of how AI models work. Our platform, www.AIsapiens.net, provides the tools and expertise you need to navigate this new landscape and ensure that AI is telling the right story about your brand. Don’t let AI’s perception of your brand be shaped by outdated information or competitor bias. Take control of your narrative and start influencing AI today. We have 600+ clients that have trusted our AI platforms of our company which also include Productcategorization.com, WebsiteCategorizationapi.com, LeadsQuantum.com.

Many studies demonstrate the link between brand perception and different key performance metrics. For instance, studies from Harvard show that positive brand perceptions correlate with increased customer lifetime value, https://hbr.org/2015/11/calculating-customer-lifetime-value-isnt-easy-but-its-worth-it and stronger purchase intention. https://scholar.harvard.edu/files/johanquelch/files/brand_equity_measurement.pdf

Start Learning about How AI talks to your customers about your brand / company. Check our plans and pricing on AIsapiens.net.