Gartner’s “Predicts 2024: How GenAI Will Reshape Tech Marketing” claims as GenAI (Generative AI) evolves, traditional search engine volumes are poised to undergo a remarkable shift. Alan Antin, Vice President Analyst at Gartner, underscores this paradigm shift, noting GenAI solutions are swiftly assuming the role of substitute answer engines, usurping user queries traditionally executed within conventional search engines. As this trend gains momentum, businesses need to recalibrate their strategies through a lens of customer-centricity, acknowledging the omnipresence of GenAI across all facets of the enterprise. The ripples caused by the increased usage of GenAI will affect website traffic, user intent, and other key measures.
Ravi Sen, Associate Professor, Management Information Systems, Mays Business School, Texas A&M University, says, “as the quality of AI-generated answers improves, users will have less incentive to browse through search result listings.” This leads us to ask three questions:
- What can your company start doing now leverage GenAI?
- What measures provide insights the effectiveness of your efforts?
- How can you use GenAI to improve customer-centricity?
To answer these questions, we must first understand how AI is changing the way people search.
Targeted Queries Unlock Invaluable Customer Data
People ask all kinds of questions. In the world of search these questions are known as queries. In addition to providing answers to questions, queries are also a valuable source of user data. Queries help us gain insight into user patterns and user intent, which refers to the underlying motivation or goal behind a user’s search query, website visit, or online interaction.
It serves as a guiding principle for businesses seeking to tailor their content, products, and services to meet the specific needs and preferences of their customers.
Dirk Lewandowski’s book, “Understanding Search Engines” explores the different kinds of queries that reflect user intent. These are three query categories almost every business needs to understand.
- Informational queries: In this instance, people are searching for knowledge, answers, and instructions. For example, if you’re looking for a new CRM platform, you might seek information about important features to consider. Your query might be, “What are the essential functionalities a CRM system should offer?” or “Provide a comprehensive guide or checklist of key features to look for when evaluating CRM solutions.”
- Navigational queries: A navigational query indicates the user has a clear destination in mind. For example, a query to go to specific pages for an online demo of a specific platform and its features, functionality, and pricing.
- Transactional queries: Transactional queries indicate the user is ready to act, such as make a purchase, request a quote, subscribe, etc. In this example, a transactional query might be to schedule a proof-of-concept demo.
Each type of intent represents a different stage in the user’s journey and requires a tailored approach.
Customer-Centricity Can Soar — With Help From GenAI
GenAI represents a paradigm shift in how search engines understand and process user queries. Because GenAI leverages machine learning and natural language to understand the nuances of user queries, it can deliver highly relevant results. This capability makes GenAI well-suited to answer informational and transactional queries.
Familiar measures, such as search queries, website interactions, bounce rate, click-through rates, and call-to-action (CTA) conversion rates are key indicators of user intent. By analyzing these measures, you can gain a deeper understanding of user intent and tailor your customer-centric strategies accordingly.
Let’s see how we might apply this concept.
A high conversion rate on CTAs, such as “Buy Now” buttons or subscription forms, indicates strong transactional intent among users. It would suggest these users are actively interested in making a purchase or taking a specific action, such as subscribing to a service or downloading a resource. Here’s how a business can capitalize on this transactional intent:
- Prominently feature CTAs.
- Offer incentives or discounts to encourage immediate action.
- Streamline the checkout or signup process to reduce customer effort.
A low bounce rate serves as another example.
It indicates users are spending significant time on the website and exploring multiple pages, suggesting high user engagement and informational intent. Here’s how a business can leverage informational intent:
- Create in-depth guides, tutorials, case studies, or blogposts that address common questions or pain points within the industry.
- Focus on content quality and relevance to reflect an authoritative source of information.
- Analyze user behavior patterns and content consumption data to gain insight into the topics and formats that resonate most with users.
Use GenAI in 4 Ways to Elevate Your Customer-Centricity
The above examples provide some insight into how you can use GenAI to analyze and leverage user intent data. Understanding user intent is a key way to elevate customer-centricity, which emphasizes the importance of prioritizing customer needs and preferences in all aspects of your business operations. By aligning your customer-centric strategies with user intent, you can create more relevant and personalized experiences that resonate with your target customers.
This customer-centric approach fosters loyalty, trust, and satisfaction, leading to improved brand reputation, brand preference, and long-term customer value.
There are four broad areas where every organization can use GenAI to be more customer-centric:
- Analyze user queries: By analyzing user queries and interactions, businesses can use GenAI to extract valuable insights into user intent and preferences. For example, GenAI can analyze the language used in customer reviews, social media posts, and support tickets to identify common themes, sentiments, and pain points.
- Make personalized recommendations: Use GenAI to analyze user behavior and historical data to develop personalized recommendation systems that suggest relevant products, content, or services based on user intent and preferences. For example, an e-commerce retailer can use GenAI to recommend products based on a user’s browsing history, purchase history, and demographic information.
- Create engaging content: By analyzing user queries and search trends, GenAI models can generate content ideas, headlines, and descriptions that are tailored to meet the specific needs and interests of your target market. For example, a content marketing team can use GenAI to generate blog post ideas, optimize headlines for search engine visibility, and create compelling meta descriptions that attract clicks and engagement.
- Forecast future behavior: With enough historical data, GenAI models can be developed to measure and predict how users are likely to behave in the future and anticipate their needs and preferences.For example, a predictive analytics model powered by GenAI can forecast which products are likely to be popular during the annual planning season.
As businesses navigate GenAI, the concept of customer-centricity emerges as a guiding principle, emphasizing the importance of prioritizing customer needs and preferences across all facets of operations. By embracing GenAI and aligning strategies with user intent, businesses can craft personalized experiences that resonate deeply with their customers, fostering loyalty, trust, and long-term customer value. Elevate your customer-centricity and your measures with our free white paper, “Bring Your A-Game to a Customer Empowered Market” and our “CustomerDNA” Infographic.
FAQ:
A1: As GenAI improves, users increasingly get complete answers without clicking through traditional search results. That shift reduces the incentive to browse listings, which will likely change search volumes, website traffic patterns, and how intent signals show up. The strategic implication is not “SEO is dead.” It is that customer acquisition and engagement will depend more on how well your organization shows up in AI-mediated discovery and how effectively you convert intent when users do engage.
A2: Start with actions that strengthen customer-centricity and reduce friction across the journey:
- Instrument and organize intent data: Consolidate query data, on-site behavior, content engagement, and conversion paths so you can see intent signals clearly.
- Build an AI-ready content system: Create authoritative, structured content that answers informational and transactional questions cleanly (guides, FAQs, comparisons, proof points, case studies).
- Deploy GenAI where it improves speed and relevance: Use it to accelerate insight extraction, content production workflows, and personalization—while keeping human oversight for accuracy, differentiation, and brand voice.
- Pilot use cases tied to measurable outcomes: Choose 1–2 high-value journeys (e.g., demo requests, assessments, advisory inquiries) and use GenAI to improve conversion and customer effort.
A3: Continue tracking familiar intent measures, but interpret them through a “search-to-answer” lens:
- Search query themes and intent mix (informational vs. navigational vs. transactional)
- Website engagement quality: time on page, pages per session, return visits, content depth
- Bounce rate and exit rate (paired with page intent—low bounce is not always “good,” high bounce is not always “bad”)
- CTR and CTA conversion rates (especially on high-intent offers like demos, trials, assessments, advisory inquiries)
- Customer effort indicators: steps to convert, form completion rate, time-to-value, support deflection with satisfaction
The key is to connect these measures to outcomes: pipeline contribution, retention, share of wallet, and customer lifetime value.
A4: Query intent is a direct expression of what customers are trying to accomplish. When you align content, offers, and experiences to intent, you reduce friction and increase relevance—two prerequisites for trust and loyalty. Informational intent requires education and authority; navigational intent requires speed and clarity; transactional intent requires confidence, proof, and low-effort conversion paths.
A5: Four broad applications consistently improve relevance and responsiveness:
- Analyze user queries and interactions: Extract themes, sentiment, and pain points from reviews, social posts, and support tickets to inform strategy and experience design.
- Make personalized recommendations: Use behavior and history to suggest relevant content, products, or next steps based on intent.
- Create engaging, intent-aligned content: Generate and optimize topics, headlines, and descriptions that match what customers are actually asking—then refine with human expertise.
- Forecast future behavior: Use historical patterns to anticipate needs (seasonality, churn risk, product demand) and proactively serve customers.
A6: GenAI is changing discovery and compressing the path from question to answer. The winners will be customer-centric organizations that treat intent data as a strategic asset, build authoritative content ecosystems, and use GenAI to improve relevance, personalization, and speed—while measuring outcomes that matter, not just traffic.
FAQ:
A1: As GenAI improves, users increasingly get complete answers without clicking through traditional search results. That shift reduces the incentive to browse listings, which will likely change search volumes, website traffic patterns, and how intent signals show up. The strategic implication is not “SEO is dead.” It is that customer acquisition and engagement will depend more on how well your organization shows up in AI-mediated discovery and how effectively you convert intent when users do engage.
A2: Start with actions that strengthen customer-centricity and reduce friction across the journey:
- Instrument and organize intent data: Consolidate query data, on-site behavior, content engagement, and conversion paths so you can see intent signals clearly.
- Build an AI-ready content system: Create authoritative, structured content that answers informational and transactional questions cleanly (guides, FAQs, comparisons, proof points, case studies).
- Deploy GenAI where it improves speed and relevance: Use it to accelerate insight extraction, content production workflows, and personalization—while keeping human oversight for accuracy, differentiation, and brand voice.
- Pilot use cases tied to measurable outcomes: Choose 1–2 high-value journeys (e.g., demo requests, assessments, advisory inquiries) and use GenAI to improve conversion and customer effort.
A3: Continue tracking familiar intent measures, but interpret them through a “search-to-answer” lens:
- Search query themes and intent mix (informational vs. navigational vs. transactional)
- Website engagement quality: time on page, pages per session, return visits, content depth
- Bounce rate and exit rate (paired with page intent—low bounce is not always “good,” high bounce is not always “bad”)
- CTR and CTA conversion rates (especially on high-intent offers like demos, trials, assessments, advisory inquiries)
- Customer effort indicators: steps to convert, form completion rate, time-to-value, support deflection with satisfaction
The key is to connect these measures to outcomes: pipeline contribution, retention, share of wallet, and customer lifetime value.
A4: Query intent is a direct expression of what customers are trying to accomplish. When you align content, offers, and experiences to intent, you reduce friction and increase relevance—two prerequisites for trust and loyalty. Informational intent requires education and authority; navigational intent requires speed and clarity; transactional intent requires confidence, proof, and low-effort conversion paths.
A5: Four broad applications consistently improve relevance and responsiveness:
- Analyze user queries and interactions: Extract themes, sentiment, and pain points from reviews, social posts, and support tickets to inform strategy and experience design.
- Make personalized recommendations: Use behavior and history to suggest relevant content, products, or next steps based on intent.
- Create engaging, intent-aligned content: Generate and optimize topics, headlines, and descriptions that match what customers are actually asking—then refine with human expertise.
- Forecast future behavior: Use historical patterns to anticipate needs (seasonality, churn risk, product demand) and proactively serve customers.
A6: GenAI is changing discovery and compressing the path from question to answer. The winners will be customer-centric organizations that treat intent data as a strategic asset, build authoritative content ecosystems, and use GenAI to improve relevance, personalization, and speed—while measuring outcomes that matter, not just traffic.
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