AI Search For Scaling Brands: Trends and Strategies

The rapid advancement of artificial intelligence (AI) is revolutionizing the world of search engine optimization (SEO), reshaping how businesses approach their online presence and interact with search engines.  

As AI becomes more sophisticated, it is transforming the way search engines operate, making them more efficient, accurate, and user-centric. Constant innovations from the Web2 to Web3 model, which has made sources of information more decentralized, has opened up the space for innovations at an unprecedented scale. With advanced data-analytics and LLMs at work, AI has revolutionized the tech spaces as well as how we look at businesses. 

AI-powered search: How traditional boundaries have been dismantled by great innovations

Traditional search engines have long relied on algorithms that analyse keywords, backlinks, and other on-page factors to determine search rankings. However, the integration of AI has revolutionized this process, introduced more sophisticated methods of understanding and delivering search results. AI-powered search engines utilize machine learning algorithms, natural language processing (NLP), and neural networks to:

1. Interpret user intent more accurately

2. Provide more personalized search results

3. Understand context and semantics beyond simple keyword matching

4. Continuously learn and improve from user interactions 

With these algorithmic advancements, the way we have practiced traditional SEO has changed dramatically. The shift has significant implications for SEO practitioners, who should learn these optimization techniques for AI-driven search behaviours rather than solely focusing on traditional ranking factors.

How engagement is shaping adoption of AI searches?

The adoption of AI technologies, including AI-powered searches, has been rapidly increasing across various sectors. As of 2023, more than 80% of global companies reported adopting AI to improve their business operations. However, when it comes to AI-powered search platforms specifically, the adoption rate is still in its early stages compared to traditional search engines. In May 2024, only 16.45% of traditional search engine users also used an AI platform, indicating that while AI search technologies are gaining traction, traditional methods still enjoy a lion share of the market.

AI-powered search engines have shown a marked increase in user satisfaction compared to traditional search methods. Users report a 30% increase in satisfaction when using AI-enhanced search features. This higher satisfaction rate can be attributed to several factors, including personalization, efficiency, and enhanced user experience.

Improved Search Algorithms and Accuracy

One of the most significant ways AI is impacting SEO is through the enhancement of search algorithms. AI-powered algorithms, such as Google's BERT, utilize natural language processing (NLP) to better understand the context and intent behind search queries.

This enables search engines to deliver more relevant and accurate results to users, prioritizing content that effectively addresses their needs. As a result, businesses must optimize their content to match the specific context and intent of their target audience, ensuring that their pages are deemed valuable and relevant by AI-driven search engines.

The Rise of AI in Search Engines

AI has introduced sophisticated methods of understanding and delivering search results. Modern search engines now utilize machine learning algorithms, natural language processing (NLP), and neural networks to interpret user intent more accurately, provide personalized search results, understand context and semantics beyond simple keyword matching, and continuously learn and improve from user interactions.

AI Overviews Dominating Search Results

One of the most notable changes brought about by AI in search engines is the prominence of AI Overviews. According to a study by Advanced Web Ranking (AWR), AI Overviews appear in 12.4% of analysed keywords, indicating a significant presence in search results. These AI-generated summaries provide quick answers to search queries by gathering information from various online sources, potentially reducing the need for users to click through to websites. Key findings from the AWR study include:

• AI Overviews contain an average of 7.2 links when expanded.

• 46.5% of the URLs included in AI Overviews rank outside the top 50 organic results, indicating that AI Overviews can feature content that is not necessarily highly ranked organically.

• The average AI Overview is 169 words and 912 pixels long, which can push organic results further down the page.

How Generative AI is transforming the way we search on internet? 

Generative AI is poised to have a significant economic impact across various industries. It is expected to add between $2.6 trillion to $4.4 trillion annually to the global economy across 63 use cases, ranking it as the third-largest economy if it were a country (McKinsey & Company, 2023). As of 2024, 72% of organizations worldwide report using AI technologies, up from about 50% in previous years (BCG, 2024). In the United States, nearly 40% of the population aged 18 to 64 reported using generative AI, with usage more prevalent at work than at home (Pew Research Center, 2024).

How Gen-AI is significantly impacting Revenue Generation

2.1 Dynamic Pricing and Promotions

Generative AI allows businesses to implement dynamic pricing strategies by analysing real-time data on market conditions, competitor pricing, and customer demand.

Retailers using AI-driven dynamic pricing have reported a 25% increase in gross profits. 60% of e-commerce businesses adopting AI for pricing achieved higher profitability. Airlines utilizing dynamic pricing algorithms have seen revenue increases of up to 10%.

2.2 Cross-Selling and Upselling

AI-driven recommendations identify optimal products to suggest to customers, enhancing cross-selling and upselling efforts.

Personalized product recommendations can drive 10-30% of revenue. Businesses have observed a 20% increase in sales through AI-driven upselling. 35% of Amazon's sales are generated by its recommendation engine.

3. Conversion Rate Optimization

AI optimizes website layouts, product placements, and checkout processes based on user behaviour analytics. Websites employing AI personalization have seen conversion rates increase by up to 15%.

57% of consumers are willing to share personal data for a better shopping experience. AI-driven chatbots can improve conversion rates by up to 45% through instant engagement.

3.1 Personalized Experiences

AI personalizes browsing experiences by utilizing data from past interactions and purchases.

80% of consumers are more likely to purchase from brands offering personalized experiences. Personalization can reduce acquisition costs by as much as 50%.

74% of marketers believe targeted personalization increases customer engagement.

3.2 Predictive Customer Service

AI predicts potential customer issues, allowing proactive solutions and enhancing satisfaction.

Predictive analytics can increase customer retention rates by 10–15%. Companies using AI for customer service report a 30% reduction in service costs. 83% of customers expect immediate engagement when contacting a company.

3.3 Loyalty Programs

AI manages and personalizes loyalty programs with targeted rewards and incentives.

77% of consumers participate in a retail loyalty program. AI-driven loyalty programs have increased customer retention rates by 27%. Personalized rewards can boost loyalty program engagement by 80%.

4. Click-Through Rate (CTR) Enhancement

Generative AI improves CTR through targeted advertising, content optimization, and A/B testing.

1. Targeted Advertising

AI analyses user data to create highly targeted ad campaigns. AI-driven advertising can result in a 50% higher CTR than non-targeted ads. Personalized ads lead to a 6x increase in transaction rates. 63% of consumers are annoyed by generic ad blasts.

2. Content Optimization

AI optimizes titles, meta descriptions, and content for SEO, improving search rankings. Companies using AI for content optimization have seen organic traffic increase by up to 30%.60% of marketers believe AI can improve SEO strategy. AI-optimized content can improve search rankings within 6 months.

4.3 A/B Testing

AI automates A/B testing of web pages or ads to identify the most effective versions.

AI-powered A/B testing can increase conversion rates by up to 20%. 71% of companies run more than two A/B tests monthly using AI. Reducing testing time by 50% allows faster strategy implementation.

Sector-Specific Adoption

The fintech, software, and banking sectors have the highest concentration of AI leaders, with fintech leading at 49% (BCG, 2024). Over half of manufacturers have adopted AI tools, and generative AI is widely used in about three-quarters of marketing departments (Vena Solutions, 2024).

From Keyword Matching to Understanding Intent

Traditional search engines relied heavily on keyword matching to deliver results. However, AI-powered searches use advanced techniques such as machine learning and natural language processing to understand the context and intent behind user queries. This shift requires content creators to focus on creating in-depth, authoritative, and relevant content that thoroughly addresses the user's intent, rather than solely optimizing for specific keywords.

Emergence of AI-Powered SERP Features

AI Overviews now dominate search results, appearing in more than one in four searches. These overviews are integrated into Google's search experience and cannot be turned off, highlighting the need to adapt SEO strategies accordingly.
AI has seen significant adoption in the marketing sector. Approximately 75.7% of digital marketers are now using AI tools in their work, indicating a strong integration of AI into marketing workflows. This widespread adoption is further supported by the fact that 69% of marketers are using ChatGPT, a popular AI tool, for various tasks such as content creation and customer interaction.

Key SEO Trends Shaped by AI Searches

1. Emphasis on High-Quality, Relevant Content: 

AI algorithms prioritize content that is comprehensive, credible, and directly relevant to the user's query. To rank well in AI search results, businesses must create content that provides in-depth analysis, demonstrates expertise and credibility, and directly answers the user's query.

AI is heavily utilized for content creation in marketing. A significant 85.1% of AI users employ the technology for blog content creation. This highlights the reliance on AI to accelerate content production and maintain a competitive edge in content marketing.

2. Enhanced User Experience (UX): 

AI is playing a crucial role in enhancing user experience by personalizing interactions on websites. AI-driven analytics can dynamically alter content to match individual user preferences, improving engagement and satisfaction.

3. Voice Search Optimization: 

With the rise of AI-powered voice assistants, optimizing for voice search has become increasingly important. This involves focusing on conversational keywords and natural language phrases, creating FAQ-style content to address common voice queries, and ensuring local SEO is robust for "near me" queries.

4. AI-Powered Content Creation and Optimization: 

AI tools like GPT-4 and Jasper are revolutionizing content creation by generating text that is relevant, engaging, and contextually appropriate. These tools help automate keyword research, content formatting, meta descriptions and title tag generation, and content ideation.

There is a growing belief in the quality of AI-generated content. About 65.8% of people think AI content is equal to or better than human writing. This perception is crucial as it influences the extent to which marketers are willing to rely on AI for content creation.

5. E-E-A-T Principles in the Age of AI: 

Experience, Expertise, Authoritativeness, and Trustworthiness (E-E-A-T) have become increasingly important in the age of AI-powered search. SEO strategies now must prioritize demonstrating author expertise, building site authority, ensuring content accuracy, and providing comprehensive coverage of topics.

6. Predictive Analytics and SEO: 

AI enhances predictive analytics by automating the process of identifying patterns and insights from data. This allows businesses to adjust their SEO strategies proactively, optimizing content for anticipated trends and improving search rankings.

AI is recognized for its ability to improve productivity. About 40% of employees believe AI improves productivity, which is a testament to its role in streamlining marketing tasks and enhancing overall efficiency.

The adoption of AI technologies, including generative AI, is rapidly accelerating across industries. As of 2023, 73% of U.S. companies have integrated AI into some aspect of their operations, indicating a widespread embrace of these technologies.

The adoption is not limited to specific sectors; while Information and Professional, Scientific, and Technical Services lead with 18% and 12% adoption rates respectively, even traditionally slower-adopting sectors like Agriculture and Construction are beginning to implement AI solutions.

AI technologies are significantly impacting productivity and task automation:

Organizations report that 34% of all business-related tasks are currently performed by machines, showcasing AI's role in automating routine processes. AI is projected to boost labor productivity growth by 1.5 percentage points over the next decade.

In advanced economies, about 60% of jobs may be impacted by AI, with roughly half benefiting from AI integration through enhanced productivity.

7. Competitive Advantage:
   
   AI is seen as a significant competitive advantage. A large majority, 87% of organizations, believe AI will give them a competitive edge. This belief underscores the strategic importance of AI in maintaining and enhancing market positions.

AI is revolutionizing marketing and sales strategies:

37% of advertising and marketing professionals in the U.S. are utilizing AI tools in 2023. 44% of businesses are using AI tools to generate content, indicating a shift towards automated content production to meet marketing needs.

AI-powered platforms, such as Coca-Cola's Albert, help optimize marketing strategies by analysing data and automating marketing tasks, leading to more efficient and targeted campaigns.

8. Impact on E-commerce and Online Shopping Trends

AI-powered searches have had a profound impact on e-commerce and online shopping trends, revolutionizing how consumers discover and purchase products. AI search technologies have significantly improved product discovery, leading to higher conversion rates in e-commerce. These technologies enable more accurate and personalized product recommendations, which can boost sales by up to 50%.

AI Search Revolution in B2B, B2C, and D2C Shopping

B2B Sector

AI-powered search is addressing unique challenges in the B2B sector:

• AI leverages machine learning and data analysis to provide more relevant and personalized search results for B2B buyers (Webriq, 2024).

• Companies like Walmart Business use AI to tailor the B2B shopping experience based on customer behavior and past interactions (Bloomreach, 2024).

• AI search enhances the efficiency of product discovery and purchase processes, crucial for B2B transactions involving bulk orders and complex specifications (Intershop, 2024).

B2C Sector

In the B2C sector, AI search is enhancing the shopping experience through:

• AI analyzes customer data, including browsing history and purchasing behavior, to provide tailored product suggestions (Webcreta, 2024).

• AI enables more intuitive product discovery through visual and voice search capabilities (Webcreta, 2024).

• Platforms like Zoovu and Shopware integrate AI-powered solutions to create hyper-personalized ecommerce experiences, significantly increasing conversion rates and average order values (DigitalOcean, 2024)

D2C Sector

Direct-to-consumer brands are leveraging AI search to:

• AI helps analyze customer data to deliver personalized marketing messages and product recommendations (Bloomreach, 2024).

• The adoption of conversational commerce, where AI chatbots provide 24/7 customer support and personalized shopping assistance, is improving customer experience and streamlining operations (Shopify, 2024).

• AI search capabilities help D2C brands manage inventory more effectively and predict demand patterns (Webriq, 2024).

Several other companies who have successfully implemented generative AI in their business models:

• Mastercard: Integrated AI chatbots for customer service and fraud prevention, providing quick, personalized responses and enhancing security (InData Labs, 2024).

• Microsoft: Pioneered AI integration in products like Bing and Windows 11, enhancing search capabilities and user assistance (InData Labs, 2024).

• Walmart: Implemented AI chatbots for customer and employee queries, resulting in cost savings and improved efficiency (LinkedIn, 2024a).

• Sutter Health: Utilized generative AI to improve doctor-patient interactions by creating detailed summaries and instructions from patient conversations (LinkedIn, 2024b)

Impact on Consumer Behaviour

The integration of AI-powered search is leading to significant changes in consumer behaviour:

• Increased Expectations: Consumers now expect more personalized and efficient shopping experiences, with AI-driven search engines providing quick and relevant results (LinkedIn, 2024c).

• Shift in Search Patterns: Businesses are seeing a decline in traditional search volume and a rise in engagement with AI-enhanced search interfaces (LinkedIn, 2024c).

• Trust in AI Recommendations: There's an increasing reliance on AI-generated recommendations, reducing dependence on traditional search methods (LinkedIn, 2024c).

Case studies of two of our clients: Saas and D2C

1. Visily: Understanding Key Metrics in the Context of B2C SaaS

• Engagement Rate: For B2C SaaS clients, engagement rate reflects how relevant and compelling the platform is to users. High engagement from sources like Bing, Google, and ChatGPT.com shows these channels attract a quality audience.

• Average Engagement Time: Understanding this metric is a strong indicator of user satisfaction and depth of interaction with the product. Sources like Bing and ChatGPT.com demonstrate extended user interaction, suggesting that users from these sources find the product highly engaging.

• Events Per Session: A high number of events per session, as seen with Bing and ChatGPT.com users, shows a willingness to explore the platform's features which indicates these audiences are more likely to convert into loyal customers.

• Key Events: The volume of key events from Google and Direct Link reinforces their critical role in driving meaningful actions (e.g., sign-ups, feature utilization).

1. Direct Link has the highest percentage of key events (3.41%), suggesting that users coming through specific links are more likely to perform significant actions.

2. ChatGPT.com also shows a strong percentage of key events (2.24%), highlighting the potential of AI-driven sources to encourage meaningful interactions.

3. Bing and Google have relatively lower percentages (1.88% and 1.82%, respectively) but make up for it with their high volume of events, still contributing significantly to overall key actions.

4. Direct Traffic has a slightly higher key events percentage (1.87%) than Google, which indicates room for improving engagement strategies tailored to this audience.

2. How AI Searches Are Making Huge Strides:

AI-powered searches like those from ChatGPT.com, AI chat platforms, and perplexity.ai are revolutionizing B2C engagement in significant ways:

• Personalization: AI search tools are highly adept at understanding user intent and delivering hyper-personalized results. For Visily, this means targeting these platforms brings in users who are already aligned with their product's value proposition.

• Proactive Interaction: Platforms like ChatGPT.com and AI chat interfaces deliver conversational and engaging user experiences, encouraging deeper interaction. The high engagement rates from these sources suggest that AI search platforms are fostering trust and curiosity about SaaS tools like Visily.

• High-Quality Traffic: The audience from AI-driven sources tends to be tech-savvy and goal-oriented, as indicated by higher engagement times and events per session.

Vitality:

1. Key Metrics Overview

Key Insights

1. AI-Driven Sources Deliver Higher Engagement per Session

Gemini.google.com (Google's AI-powered product):

• Leads with the highest events per session (17.5%) and average engagement time per session (20%).

• These metrics signify that AI-enhanced search channels foster deeper user interactions and longer sessions, suggesting a higher likelihood of conversions or meaningful engagements.

ChatGPT.com:

• While its average engagement time is moderate, it generates a high event count, indicating that users guided by generative AI engage in multiple actions or touchpoints on the site.

AI panel and Perplexity.ai:

• These platforms also show above-average engagement times and events per session, further underscoring the role of generative AI in initiating productive user journeys

2. Traditional Channels Retain Volume but Are Rivalled by AI

• Google (Search) and Direct Traffic:

These sources maintain the highest share of key events (22.65% and 22.85%) and event counts (~77%), reflecting their continued dominance in driving traffic volume.

• Bing:

Lags behind Google in user engagement, but as Microsoft integrates more AI capabilities (e.g., Bing Chat), there is potential for improved performance in the future.

• AI-Driven Competition:

Emerging AI tools, like Gemini.google.com and ChatGPT, are closing the gap in engagement, offering Vitality an opportunity to capitalize on a growing shift toward conversational and generative search.

2. AI Sources Foster "Stickiness"

• Higher Engagement and Events per Session:

Users entering via AI-driven channels demonstrate "stickier" behaviour, as evidenced by higher key events and time spent on-site. This indicates that AI referrals are more likely to result in meaningful interactions, such as content exploration, sign-ups, or purchases.

• Implications for Brand Strategy:

AI-driven traffic sources are particularly valuable for campaigns that prioritize user engagement over sheer volume.

What future holds for the booming AI market and changing shopping behaviour: 

Looking ahead, several key trends are expected to shape the future of generative AI and AI search in business and e-commerce:

• Generative AI will enable even more tailored shopping experiences, enhancing customer satisfaction and loyalty (McKinsey & Company, 2023). Hyper-personalisation has caused a major disruption in the market, and this might lead to a newer range of price discovery and analytics. 

• Improvements in AI-driven search engines will lead to more accurate and relevant search results, directly impacting consumer behaviour across B2B, B2C, and D2C environments (LinkedIn, 2024c). AI-powered search engine enhancements are the game changer on how we look at B2B, D2C and B2C businesses. Over time these growth patterns can help scaling niche products and wider market adoption strategies for your unique business model. 

• The market for AI chatbots is projected to grow significantly, reaching nearly $47 billion by 2029, up from $16 billion in 2024 (Shopify, 2024). Chatbots provide a new personalization avenue for brands that want to dive deeper into customer retention and better product sales. 

• adoption of customized generative AI models in large enterprises is expected to rise from 1% in 2023 to 50% by 2027 (Neurond, 2024). Generative AI is anticipated to drive innovation and create new business opportunities, reshaping the competitive landscape across various sectors (McKinsey & Company, 2023).

Challenges and Limitations for adapting to the changing AI spaces

Despite the promising outlook, there are several challenges and limitations to consider:

• Data Dependency and Quality: The performance of AI models heavily depends on the quality and diversity of training datasets, which can be a challenge in sectors with scarce or highly regulated data (FTC, 2023).

• Computational Resources: The substantial computational requirements for generative AI models can be a barrier for smaller companies or startups (Codiste, 2024).

• Talent Scarcity: The need for specialized skills in machine learning and AI can limit companies' ability to innovate and compete effectively (BCG, 2024).

• Ethical and Privacy Concerns: The use of personal data and the potential for misuse of AI-generated content raise significant ethical and privacy issues (Harvard Online, 2024).

• Market Competition and Control: The concentration of essential AI inputs (data and computational resources) among a few dominant firms could hinder innovation and limit the broader benefits of AI technologies (FTC, 2023).

• Integration and Adoption Challenges: Companies may face difficulties in adapting their workflows to effectively incorporate AI technologies (Shopify, 2024).

Influence on SEO strategies with the wider market space

The rise of AI in search has transformed digital marketing strategies, forcing marketers to adapt their approaches to align with new technologies and user behaviours. AI-powered search technologies enable marketers to deliver highly personalized experiences by analysing vast amounts of data on consumer behaviour and preferences. 

AI searches facilitate predictive analytics, allowing marketers to anticipate customer needs and trends. AI tools automate various marketing tasks, such as content creation, email marketing, and ad placement. AI's ability to process and analyse large datasets in real-time allows marketers to make informed decisions quickly. 

In conclusion, the AI revolution in SEO is fundamentally reshaping how businesses approach their online presence and interact with customers. As AI continues to advance, it's crucial for businesses to adapt their strategies, invest in AI capabilities, and navigate the challenges to stay competitive in the rapidly evolving digital landscape.

References: 

1. BCG. (2024). New BCG Research on AI Adoption in 2024. Retrieved from https://www.bcg.com/press/24october2024-ai-adoption-in-2024-74-of-companies-struggle-to-achieve-and-scale-value 

2. Bloomreach. (2023). The Future of D2C Marketing: How AI and Automation Are Changing the Game. Retrieved from https://www.bloomreach.com/en/blog/the-future-of-d2c-marketing-how-ai-and-automation-are-changing-the-game 

3. Codiste. (2023). Economic Impact of Generative AI. Retrieved from https://www.codiste.com/economic-impact-of-generative-ai 

4. DigitalOcean. (2023). AI in E-commerce. Retrieved from https://www.digitalocean.com/resources/articles/ai-ecommerce 

5. Elagra, J. (2023). The Future of E-commerce: AI Trends and Insights. LinkedIn. Retrieved from https://www.linkedin.com/pulse/future-e-commerce-ai-trends-insights-jamal-elagra-dbosf 

6. Exploding Topics. (2023). Generative AI Statistics. Retrieved from https://explodingtopics.com/blog/generative-ai-stats 

7. FTC. (2023a). Generative AI Raises Competition Concerns. Federal Trade Commission. Retrieved from https://www.ftc.gov/policy/advocacy-research/tech-at-ftc/2023/06/generative-ai-raises-competition-concerns 

8. Harvard Online. (2023). Benefits and Limitations of Generative AI. Retrieved from https://www.harvardonline.harvard.edu/blog/benefits-limitations-generative-ai 

9. InData Labs. (2023a). Companies Using Generative AI: Mastercard. Retrieved from https://indatalabs.com/blog/companies-using-generative-ai 

10. InData Labs. (2023b). Companies Using Generative AI: Microsoft. Retrieved from https://indatalabs.com/blog/companies-using-generative-ai 

11. Intershop. (2023). The Transformative Power of Generative AI in B2B E-commerce. Retrieved from https://blog.intershop.com/en/the-transformative-power-of-generative-ai-in-b2b-e-commerce 

12. McKinsey & Company. (2023a). The Economic Potential of Generative AI: The Next Productivity Frontier. Retrieved from https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/the-economic-potential-of-generative-ai-the-next-productivity-frontier 

13. McKinsey & Company. (2023b). Generative AI's Impact on Marketing and Sales. Retrieved from https://www.mckinsey.com/capabilities/marketing-and-sales/our-insights/generative-ai 

14. Neurond. (2023). The Future of Generative AI. Retrieved from https://www.neurond.com/blog/future-of-generative-ai 

15. Perley, K. (2023). The Big Shift: How AI-Driven Search Is Changing Consumer Behavior and What Marketers Need to Do About It. LinkedIn. Retrieved from https://www.linkedin.com/pulse/big-shift-how-ai-driven-search-changing-consumer-what-kathleen-perley-iygic 

16. Shopify. (2023). AI Predictions for 2024 and beyond. Retrieved from https://www.shopify.com/blog/ai-predictions  

17. Techstack Ltd. (2023a). Case Studies: Successful Generative AI Adoption - Walmart. LinkedIn. Retrieved from https://www.linkedin.com/pulse/case-studies-successful-generative-ai-adoption-techstack-limited-0u8nf 

18. Techstack Ltd. (2023b). Case Studies: Successful Generative AI Adoption - Sutter Health. LinkedIn. Retrieved from https://www.linkedin.com/pulse/case-studies-successful-generative-ai-adoption-techstack-limited-0u8nf 

19. Vena Solutions. (2024). AI Statistics: AI in Business. Retrieved from https://www.venasolutions.com/blog/ai-statistics 

20. Webcreta. (2023). How AI and Machine Learning Transform B2B and B2C E-commerce. Retrieved from https://www.webcreta.com/how-ai-and-machine-learning-transform-b2b-and-b2c-ecommerce 

21. Webriq. (2023). The Importance of AI Search in B2B E-commerce. Retrieved from https://www.webriq.com/the-importance-of-ai-search-in-b2b-ecommerceAdvanced  Web Ranking. (n.d.). Google AI Overview. Retrieved December 27, 2024, from https://www.advancedwebranking.com/free-seo-tools/google-ai-overview 

22. Advanced Web Ranking. (n.d.). AI Overview Study. Retrieved December 27, 2024, from https://www.advancedwebranking.com/blog/ai-overview-study 

23. Advanced Web Ranking. (n.d.). How RBBI uses AWR data to manage top brands: Case study. Retrieved December 27, 2024, from https://www.advancedwebranking.com/case-studies/how-rbbi-uses-awr-data-to-manage-top-brands-case-study 

24. Advanced Web Ranking. (n.d.). Organic visibility data: Case study with Feelgood Contacts. Retrieved December 27, 2024, from https://www.advancedwebranking.com/case-studies/organic-visibility-data-case-study-with-feelgood-contacts 

25. Content Whale. (2024). How AI affects SEO in 2024. Retrieved December 27, 2024, from https://content-whale.com/us/blog/how-ai-affects-seo-2024/ 

26. Cotinga. (n.d.). AI search engines vs traditional search engines: What's the difference? Retrieved December 27, 2024, from https://cotinga.io/blog/ai-search-engines-vs-traditional-search-engines-whats-the-difference/ 

27. Dorik. (n.d.). AI search engines vs traditional search engines. Retrieved December 27, 2024, from https://dorik.com/blog/ai-search-engines-vs-traditional-search-engines 

28. Herrmann Global. (2024, December 6). Traditional vs AI-driven search engines. Retrieved December 27, 2024, from https://herrmannglobal.com/2024/12/06/traditional-vs-ai-driven-search-engines/ 

29. Matthew Edgar. (n.d.). Generative AI vs traditional search: Technical differences. Retrieved December 27, 2024, from https://www.matthewedgar.net/generative-ai-vs-traditional-search-technical-differences/ 

30. Nestify. (n.d.). Traditional search vs AI-powered search. Retrieved December 27, 2024, from https://nestify.io/blog/traditional-search-vs-ai-powered-search/  

31. Noble Desktop. (n.d.). SEO trends for 2024: What to watch for. Retrieved December 27, 2024, from https://www.nobledesktop.com/learn/seo/seo-trends-for-2024-what-to-watch-for 

32. Originality.ai. (n.d.). How AI SEO content affects optimization. Retrieved December 27, 2024, from https://originality.ai/blog/how-ai-seo-content-affects-optimization 

33. Perplexity AI. (n.d.). AI search engines vs traditional search engines. Retrieved December 27, 2024, from https://www.perplexity.ai/page/ai-search-engines-vs-tradition-eYTfUTD2Qxyjay76eBJE1w 

34. Prerender. (n.d.). Traditional search vs AI-powered search explained. Retrieved December 27, 2024, from https://prerender.io/blog/traditional-search-vs-ai-powered-search-explained/ 

35. Restack. (n.d.). AI-powered search engines: Answer AI vs traditional search algorithms 2024. Retrieved December 27, 2024, from https://www.restack.io/p/ai-powered-search-engines-answer-ai-vs-traditional-search-algorithms-2024-cat-ai 

36. ResultFirst. (n.d.). Types of featured snippets that can boost your website traffic. Retrieved December 27, 2024, from https://www.resultfirst.com/blog/seo-basics/types-of-featured-snippets-that-can-boost-your-website-traffic/ 

37. The Ad Firm. (n.d.). SEO trends for 2024: How AI and E-E-A-T are redefining search. Retrieved December 27, 2024, from https://www.theadfirm.net/seo-trends-for-2024-how-ai-and-e-e-a-t-are-redefining-search/ 

38. WSI World. (n.d.). SEO in the age of AI. Retrieved December 27, 2024, from https://www.wsiworld.com/blog/seo-in-the-age-of-ai 

39. Xponent21. (n.d.). What are E-E-A-T principles and why are they important for AI SEO? Retrieved December 27, 2024, from https://xponent21.com/insights/faq/what-are-e-e-a-t-principles-and-why-are-they-important-for-ai-seo/ 

40. Exploding Topics. (n.d.). The future of AI: 10 trends to watch in 2023 and beyond. https://explodingtopics.com/blog/future-of-aiFinn , G. (2023, June 8). 

41. Study: Google AI overviews appear in 47% of search results. Search Engine Journal. https://www.searchenginejournal.com/study-google-ai-overviews-appear-in-47-of-search-results/535096/MIT  Sloan Management Review.  (2023). 

42. Five key trends in AI and data science for 2024. https://sloanreview.mit.edu/article/five-key-trends-in-ai-and-data-science-for-2024/Statista . (n.d.). 

43. AI-powered online search. https://www.statista.com/topics/10825/ai-powered-online-search/Statista . (2023a). 

44. Generative AI market growth worldwide from 2022 to 2030. https://www.statista.com/forecasts/1449870/generative-ai-market-growth-globalStatista . (2023b). 

45. Generative AI market size worldwide from 2022 to 2030. https://www.statista.com/forecasts/1449838/generative-ai-market-size-worldwideStatista . (2023c). 

46. Market growth of AI robots worldwide from 2022 to 2030. https://www.statista.com/forecasts/1449873/market-growth-ai-robots-globalStatista . (2023d). 

47. Natural language processing (NLP) market size worldwide from 2022 to 2030. https://www.statista.com/forecasts/1449869/nlp-market-size-worldStatista . (2023e). 

48. Online searches for "AI" and "artificial intelligence" in the United States as of March 2023. https://www.statista.com/statistics/1384280/online-searches-ai-artificial-intelligence-united-states/Thorbecke , C. (2023, March 15). 

49. 35 key artificial intelligence statistics for 2023, Forbes Advisor. https://www.forbes.com/advisor/business/ai-statistics/Exploding  

50. Topics. (n.d.). 25 AI statistics that will blow your mind. https://explodingtopics.com/blog/ai-statisticsSynthesia

51. (2023, March 15). 35 AI statistics for 2023: Adoption, growth & more. https://www.synthesia.io/post/ai-statistic.

52. Authority Hacker. (2023, April 11). 35+ AI statistics 2023 - Facts about artificial intelligence. https://www.authorityhacker.com/ai-statistics/Semrush.  

53. (2022, December 12). 35 artificial intelligence statistics for 2023. https://www.semrush.com/blog/artificial-intelligence-stats/

54. NTT DATA. (2023, April 6). Navigating the future of generative AI: Ethical, regulatory and governance challenges. https://www.nttdata.com/global/en/insights/focus/navigating-the-future-of-generative-ai-ethical-regulatory-and-governance-challenges 

55. https://www.gartner.com/en/newsroom/press-releases/2023-08-30-gartner-reveals-three-technologies-that-will-transform-customer-service-and-support-by-2028 

56. Google Cloud. (2024). Google Cloud Shares New Research on 2024 Outlook on Generative AI in Retail. PR Newswire. Retrieved from https://www.prnewswire.com/news-releases/google-cloud-shares-new-research-on-2024-outlook-on-generative-ai-in-retail-302032042.html

57. McKinsey & Company. (2023). The value of getting personalization right—or wrong—is multiplying. Retrieved from https://www.mckinsey.com/capabilities/growth-marketing-and-sales/our-insights/the-value-of-getting-personalization-right-or-wrong-is-multiplying

58. NVIDIA. (2024). State of AI in Retail and CPG. Retrieved from https://www.nvidia.com/en-us/lp/industries/state-of-ai-in-retail-and-cpg/

59. Shopify. (2023). AI Statistics: The Future of Generative AI. Retrieved from https://www.shopify.com/blog/ai-statistics

60. MarketsandMarkets. (2020). Artificial Intelligence Market Report.

61. Grand View Research. (2021). Generative AI Market Size & Share Report.

62. MIT Sloan Management Review. (2020). Artificial Intelligence Global Executive Study.

63. McKinsey & Company. (2018). How Artificial Intelligence Boosts Revenue in D2C Businesses.

64. Deloitte. (2019). Dynamic Pricing in Retail.

65. Accenture. (2020). AI in Pricing Strategies Report.

66. IATA. (2018). The Future of Airline Revenue Management.

67. Forrester Research. (2017). Personalized Marketing Effectiveness.

68. Gartner. (2019). AI in Upselling Strategies.

69. McKinsey & Company. (2013). Big Data: The Next Frontier for Innovation.

70. Epsilon. (2018). The Power of Personalization in Marketing.

71. Salesforce. (2019). State of the Connected Customer.

72. Juniper Research. (2017). Chatbots: Retail, eCommerce, Banking & Healthcare.

73. Epsilon. (2018). The Power of Me: The Impact of Personalization.

74. Boston Consulting Group. (2017). Retail's Personalization Imperative.

75. Evergage. (2019). Trends in Personalization Survey Report.

76. Bain & Company. (2018). Predictive Analytics in Customer Retention.

77. Oracle. (2019). AI in Customer Service.

78. HubSpot. (2018). Customer Expectations Survey.

79. Nielsen. (2016). The Loyalty Divide.

80. Capgemini. (2018). Loyalty Deciphered—How Emotions Drive Genuine Engagement.

81. Bond Brand Loyalty. (2019). Loyalty Report.

82. Digital Marketing Institute. (2019). AI and Personalized Advertising.

83. CMO by Adobe. (2018). The ROI of Personalized Advertising.

84. SmarterHQ. (2019). Privacy & Personalization Report.

85. BrightEdge. (2019). The Future of SEO.

86. Conductor. (2018). Artificial Intelligence in SEO.

87. MOZ. (2020). How AI is Changing SEO.

88. Optimizely. (2018). The State of Experimentation.

89. VentureBeat. (2019). AI in A/B Testing.

90. Gartner. (2020). Accelerating Marketing Strategies with AI.