We asked thirteen CEOs and marketing directors how AI has revolutionized their approach to customer segmentation. From enabling personalized messaging to analyzing client data, discover how these leaders leverage AI to enhance their marketing strategies.
- Enables Personalized Messaging
- Powers Micro-Segmentation
- Drives Behavioral Segmentation
- Identifies Customer Intent
- Aligns Responsive Messaging
- Uncovers Hidden Patterns
- Predicts Lead Conversion
- Discovers Upselling Opportunities
- Matches Customers with Product or Services
- Gives Actionable Insights
- Creates Dynamic Segmentation
- Identifies Niche Markets
- Provides Accurate Client Analysis
Enables Personalized Messaging
AI has revolutionized our customer segmentation by allowing us to analyze behavioral patterns in ways we couldn’t before, going far beyond basic demographics. By delving into how each user interacts with our tools—whether they’re favoring Toggl Track over Toggl Plan, or how often they engage—we can craft marketing messages that resonate on a deeply personal level. It’s like we’re able to have individualized conversations with thousands of users simultaneously—something that was merely a dream before AI came into play.
Absolutely, we discovered through AI analysis that a significant number of our users were logging hours late at night, suggesting they might be freelancers or teams in different time-zones. Recognizing this, we adjusted our marketing to highlight features that support flexible scheduling and international collaboration, which resonated strongly with this group. The result was a noticeable increase in engagement and satisfaction among these users, simply by acknowledging their unique work patterns.
Alari Aho
CEO and Founder, Toggl Inc
Powers Micro-Segmentation
AI tools have helped us segment our customers into micro-segments that previously were not available. With that, we can personalize our marketing efforts toward them. The main beneficiary of this system has been our content-marketing campaigns.
We’ve managed to create more targeted content based on customer segments we’ve discovered through analyzing customer sentiment and feedback about our products and services.
Whereas previously we created and published blog posts that focused broadly on different customer segments and industries, now we have content tailored for e-commerce businesses, logistics service providers, and other organizations that need shipment tracking.
This strategy has led to increased traffic to our main website and a boost in conversion rates.
Clooney Wang
CEO, TrackingMore
Drives Behavioral Segmentation
AI has enabled us to move beyond traditional demographic and psychographic segmentation to a more dynamic behavioral-segmentation approach. By leveraging machine-learning algorithms, we can now analyze customer actions in real time, anticipate their preferences, and respond to their behavior changes faster than ever before. This shift has allowed us to create highly personalized marketing campaigns that resonate more deeply with each segment. The predictive power of AI helps us not only understand what customers want now but also what they might want in the future, making our marketing efforts not just responsive but also proactive.
For instance, we used AI-driven tools for an e-commerce client specializing in outdoor gear to segment their customers based on purchasing behavior, frequency, and preferred product categories. The AI algorithms identified a significant segment of customers who frequently purchased hiking gear but showed interest in seasonal camping equipment. Based on this insight, we tailored email marketing campaigns offering special deals on new camping-gear arrivals around the start of the camping season, which resulted in a 30% increase in sales for that category. This campaign’s success underscored the effectiveness of AI in uncovering hidden opportunities within our customer base.
Marc Bishop
Director, Wytlabs
Identifies Customer Intent
AI has transformed how we handle customer segmentation by enabling real-time segmentation based on intent. Instead of waiting for long-term data to accumulate, we now use AI to identify customer intent based on real-time actions on websites. For instance, when a visitor engages deeply with our SEO tools but hasn’t converted, we create a segment of users who may be on-the-fence and deploy highly personalized emails to address their specific needs or concerns.
This approach led to a 20% increase in trial sign-ups for our platform within a few weeks. The ability to respond to intent-driven behaviors has made our marketing strategy more agile and responsive, maximizing our chances of converting leads.
Sahil Kakkar
CEO & Founder, RankWatch
Aligns Responsive Messaging
AI has significantly changed the way I approach customer segmentation by enabling more precise, data-driven insights into customer behavior and preferences. Rather than relying solely on traditional demographic data like age, location, or job title, AI allows me to leverage behavioral data, purchase history, and predictive analytics to create highly granular segments. This means I can target specific customer groups based on patterns in their behavior, such as how frequently they engage with content, the type of content they prefer, or where they are in the buying journey.
For example, when working with a self-storage client, we used AI to segment customers not just by basic factors like location, but by their predicted intent and life-cycle stage. By analyzing data on how users interacted with the website—such as browsing certain storage unit sizes or reading specific blog posts—we were able to group them into segments like “price-sensitive shoppers” or “long-term renters.” AI-powered tools helped predict which users were likely to convert soon based on past behaviors and allowed us to send tailored messaging. For the “price-sensitive shoppers,” we delivered a targeted offer, while the “long-term renters” received information on flexible rental terms and security features.
This more advanced level of segmentation increased engagement and conversions because the messaging was aligned with what each segment needed at that moment. AI has essentially made customer segmentation more dynamic and responsive, allowing me to adjust strategies in real time and create more personalized, effective marketing campaigns.
John Reinesch
Founder, John Reinesch Consulting
Uncovers Hidden Patterns
AI has revolutionized how we approach customer segmentation at Rail Trip Strategies by allowing us to analyze vast amounts of data and uncover patterns we might not have seen before. With AI, we can go beyond basic demographic segmentation and dive into more sophisticated behavioral, psychographic, and intent-based groupings. This level of granularity enables us to target prospects with highly tailored content and offers that align perfectly with their needs and buying stage.
For example, we used AI to segment a large pool of digital marketing agencies based on their engagement with our previous outreach campaigns, website interactions, and content consumption. The AI tool analyzed patterns in how different agencies interacted with our case studies, blog posts, and emails. It identified segments like “high-engagement agencies” that frequently consumed our educational content but hadn’t yet become clients, and “transactional buyers” who were more likely to convert after seeing a direct offer.
We then tailored our messaging to these segments: for high-engagement agencies, we sent value-driven, educational emails to nurture their interest further, while the transactional buyers received more targeted, offer-based messaging. The result was a marked improvement in conversion rates across both groups, with a 30% increase in engagement from high-engagement agencies and a 20% boost in conversions from the transactional buyers.
AI has helped us refine our customer segmentation, making our campaigns more effective by delivering the right message to the right people at the right time.
Reed Daniels
Owner, Rail Trip Strategies
Predicts Lead Conversion
We utilize AI to conduct predictive lead scoring, which evaluates potential customers based on their likelihood to convert. This approach prioritizes resources towards high-potential segments and tailors interactions to match their specific stage in the buying journey, significantly improving conversion rates.
In deploying predictive lead scoring for a B2B SaaS client, we focused our efforts on segments identified as high-value based on their engagement patterns, leading to a 35% increase in ROI by concentrating resources on likely converters.
Jason Hennessey
CEO, Hennessey Digital
Discovers Upselling Opportunities
AI has significantly transformed our approach to customer segmentation in our marketing strategy, making it more data-driven and precise.
Before implementing AI, our segmentation was based largely on broad categories like company size or industry. AI enables us to use behavioral data to create dynamic, hyper-targeted segments. For example, we use AI to analyze customer behavior patterns—such as platform-usage frequency, interaction with specific features, and even response times to support queries. This allows us to segment users not just by demographics but by how engaged they are with our platform.
One concrete example is our upsell strategy. Using AI to segment customers based on usage patterns, we identified a group of users underutilizing certain features. We then created personalized campaigns, highlighting the value of those features and offering tailored guidance.
Liudas Kanapienis
CEO, Ondato
Matches Customers with Product or Services
AI has transformed how we segment our customers at Edumentors. We use machine-learning to analyze student performance data and preferences, allowing us to match them with tutors who best fit their academic goals.
Recently, we grouped students aiming for Oxbridge prep and created targeted content showcasing success stories of similar students. This personalization led to a 35% increase in bookings for Oxbridge-focused sessions. AI helps us tailor our offerings, ensuring we meet the unique needs of each student more effectively.
Tornike Asatiani
CEO, Edumentors
Gives Actionable Insights
The integration of AI into our marketing strategies at our organization has been a game-changer, particularly in understanding customer lifecycle stages and behaviors. Through predictive analytics, AI gives us insights into which customers are most likely to engage, convert, or churn, allowing us to tailor our outreach efforts to maximize retention and growth. It’s like having a futuristic crystal ball that provides actionable insights, not just data, driving smarter decisions and better outcomes.
A recent success story involved using AI to segment and target users in the hospitality industry who showed a tendency towards tech-savvy solutions for customer engagement. We designed a specific campaign that highlighted interactive digital signage as a tool for enhancing guest experiences, and by targeting this AI-identified segment, we achieved a 50% higher response rate compared to general market campaigns. This precision marketing effort not only boosted our sales but also reinforced the effectiveness of AI in identifying and capitalizing on niche markets.
Mark McDermott
CEO & Co-Founder, ScreenCloud
Creates Dynamic Segmentation
AI has significantly changed how I approach customer segmentation in our marketing strategy. Before AI, we mainly relied on traditional methods, like demographic data, geographic location, and basic buyer personas. These were useful but often too broad. Now, AI enables us to analyze more complex data points, like customer behavior, real-time interactions, and even predictive insights. It helps us move from static to dynamic segmentation.
One example is when we integrated AI into our CRM to optimize our email marketing. The AI system grouped customers based on their previous interactions with our emails—who opened them, who clicked, and who didn’t engage at all. Using this data, it automatically segmented users into highly-targeted groups, allowing us to create personalized email campaigns. The results were impressive: open rates increased by 35%, and click-through rates nearly doubled.
AI is a game-changer in processing huge amounts of data and continuously customizing parts based on real-time behavior. It allows us to focus on creating more meaningful experiences for the right customers at the right time, instead of just casting a wide net and hoping for the best.
Vikrant Bhalodia
Head of Marketing & People Ops, WeblineIndia, A Custom Software Development Company
Identifies Niche Markets
AI has revolutionized my approach towards customer segmentation, enabling me to deliver personalized marketing strategies at Relyir Artificial Grass. With AI tools and algorithms, I can auto-analyze large datasets, uncovering patterns and segments that would be arduous to identify manually.
A prime example is our recent marketing campaign, where we applied AI to segregate our global customer base. The segmentation identified several niche markets, including pet owners who needed our products for dog runs. We subsequently tailor-made our campaigns to cater to this newly identified segment, resulting in a 20% rise in website visits and improved customer engagement compared to non-AI-driven strategies.
AI’s predictive capabilities have also been invaluable, helping us foresee customer behaviors based on past behavioral data, thereby optimizing future marketing efforts and realizing tangible business outcomes.
Sarah Mitchell
Marketing Director, Relyir
Provides Accurate Client Analysis
AI has fundamentally transformed the way we approach customer segmentation at TruBridge by allowing us to analyze vast amounts of data more efficiently and accurately. Traditional segmentation methods, which often relied on basic demographic or behavioral data, were limited in their ability to capture the nuances of our diverse client base. With AI, we can now analyze multiple data points—such as client interactions, purchasing patterns, and even content engagement—to create highly refined and dynamic customer segments.
One example of this in action is how we used AI to improve segmentation for our healthcare-focused marketing campaigns. Previously, we segmented clients based on the size of their organization or the type of healthcare facility they managed. However, with AI, we went a step further by analyzing historical data to identify more specific behavioral patterns and preferences. For instance, we discovered that certain clients were more responsive to messaging about automation and efficiency, while others prioritized insights on compliance and regulatory updates.
By using AI-driven insights, we were able to create more personalized and targeted campaigns for each segment. For example, we developed two separate content tracks—one focused on simplifying operations through automation for time-strapped facilities and another addressing regulatory concerns for larger, more compliance-driven organizations. This level of segmentation resulted in a significant increase in engagement, with higher open rates and click-through rates for each tailored campaign.
AI not only enhanced the granularity of our customer segmentation but also enabled us to continuously update and refine those segments based on real-time data. This dynamic approach allows us to respond to shifting customer needs more effectively and deliver content that resonates, driving stronger results in both lead generation and customer retention. The ability to harness AI for segmentation has truly transformed our marketing strategy, allowing us to be more precise and impactful in our outreach.
Sandra Stoughton
Director, Marketing Operations, TruBridge
