Personalizing Customer Interactions Through Tech

Every delightful customer interaction begins with the marketer, and it can only be as powerful as the #CRM and #metadata underpinning it. With agents supporting them at every step of the customer journey creation process, marketers and #customerengagement teams can now create superior experiences shaped by intelligent and emotionally resonant conversations. At a cognitive level, the human brain no longer perceives AI as a “chatbot.” It perceives a relationship. This emotional shift fundamentally changes how consumers relate to brands, fostering deeper loyalty and trust. When customers interact with agents in a way that feels natural, their engagement deepens. The implications go far beyond engagement. Every AI-driven interaction generates a wealth of contextual data, far richer than what brands could ever collect from a single web form or survey. In one conversation, an agent can gather insights about a customer’s preferences, behaviors, and intent, building a more complete, dynamic customer profile. This continuous intelligence loop allows brands to maximize the value of every interaction. Let’s bring this to life with an example... Imagine Melanie, one of your many potential customers. She’s been thinking about joining Posh Fitness, a popular gym chain in her city. Instead of filling out a form, she decides to engage with the agent on their website. As they chat, it quickly feels more like a friendly exchange than a transaction. Melanie shares her fitness goals, whether she wants to lose weight, gain muscle, or improve flexibility, and the agent listens closely, asking the right questions to understand her needs and intent. The agent gathers valuable insights through this conversation that a simple web form could never capture. Melanie mentions her dietary restrictions, her preference for a supportive personal trainer style, and that she loves outdoor workouts but needs a flexible schedule due to her busy life. In just a few minutes, the agent collects a wealth of data about Melanie: her goals, preferences, and availability—all essential to crafting a personalized experience. And because the conversation feels human-like and emotionally resonant, it creates an immediate connection to Posh Fitness. By collecting this richer data early in the relationship, Posh Fitness can offer tailored recommendations and build Melanie’s loyalty well before she signs up. This isn’t just about closing a sale. It’s about building trust and delivering personalized experiences that evoke emotions and feel deeply human. Brands that will thrive in the era of #Agentic #AI are those that recognize the shift from transactional interactions to relationship-driven engagement. This isn’t just about personalization; it’s about creating experiences and dialogues that feel alive—where AI and marketers co-create journeys that adapt in real time, amplifying the impact of every customer moment.

This is the way we've always done it. Those words will cost dealerships millions in 2025. Here's why based on how I see it. While you're running your store the same way you did in 2023, your customers have evolved. They're interacting with AI daily - from Netflix recommendations to Amazon shopping to their iPhone's predictive text. They expect the same intelligence from their car buying experience. Here are 3 simple, high-impact AI implementations any dealership can deploy in 2025: Intelligent Service Follow-Up Stop sending generic "14-day service follow-up" emails. Use AI to analyze repair orders, vehicle history, and customer behavior to send personalized follow-ups that actually drive value: - Predictive maintenance recommendations based on driving patterns - Custom offers based on repair history - Targeted trade-in opportunities based on service costs → Impact: 40%+ increase in service retention Data-Driven Customer Intelligence Stop treating every lead the same. Use AI to understand your customer before the first interaction: - Calculate true purchase propensity using behavioral patterns - Analyze website engagement depth and frequency - Assess affordability based on customer cohort data - Understand similar customer purchase patterns - Track digital body language across all touchpoints This intelligence helps you instantly distinguish between ready-to-buy customers, early-stage shoppers, and tire kickers - allowing your team to customize their approach and maximize every interaction. → Impact: 2-3x improvement in lead conversion rates Unified Customer Insight for Sales Transform how your sales team understands customers. Create a single, AI-powered view that brings together: - Complete vehicle ownership history - Service interaction patterns - Communication preferences - Family vehicle needs - Recent life events - Website browsing patterns - Current vehicle equity position This enables your team to have meaningful, personalized conversations from the first interaction - no more generic "what brings you in today?" → Impact: 30%+ reduction in sales cycle time, 25% improvement in customer satisfaction The beauty? These aren't massive technology overhauls. They're practical implementations that work alongside your existing systems. The cost of maintaining "the way we've always done it" isn't just measured in missed opportunities - it's measured in customers who choose to shop elsewhere. What "always done it" processes are you ready to evolve? #QoreAI #Automotive #AI #Innovation #DealershipOperations #DigitalTransformation

For years, companies have been leveraging artificial intelligence (AI) and machine learning to provide personalized customer experiences. One widespread use case is showing product recommendations based on previous data. But there's so much more potential in AI that we're just scratching the surface. One of the most important things for any company is anticipating each customer's needs and delivering predictive personalization. Understanding customer intent is critical to shaping predictive personalization strategies. This involves interpreting signals from customers’ current and past behaviors to infer what they are likely to need or do next, and then dynamically surfacing that through a platform of their choice. Here’s how: 1. Customer Journey Mapping: Understanding the various stages a customer goes through, from awareness to purchase and beyond. This helps in identifying key moments where personalization can have the most impact. This doesn't have to be an exercise on a whiteboard; in fact, I would counsel against that. Journey analytics software can get you there quickly and keep journeys "alive" in real time, changing dynamically as customer needs evolve. 2. Behavioral Analysis: Examining how customers interact with your brand, including what they click on, how long they spend on certain pages, and what they search for. You will need analytical resources here, and hopefully you have them on your team. If not, find them in your organization; my experience has been that they find this type of exercise interesting and will want to help. 3. Sentiment Analysis: Using natural language processing to understand customer sentiment expressed in feedback, reviews, social media, or even case notes. This provides insights into how customers feel about your brand or products. As in journey analytics, technology and analytical resources will be important here. 4. Predictive Analytics: Employing advanced analytics to forecast future customer behavior based on current data. This can involve machine learning models that evolve and improve over time. 5. Feedback Loops: Continuously incorporate customer signals (not just survey feedback) to refine and enhance personalization strategies. Set these up through your analytics team. Predictive personalization is not just about selling more; it’s about enhancing the customer experience by making interactions more relevant, timely, and personalized. This customer-led approach leads to increased revenue and reduced cost-to-serve. How is your organization thinking about personalization in 2024? DM me if you want to talk it through. #customerexperience #artificialintelligence #ai #personalization #technology #ceo

When you think AI, you probably think of chatbots replacing human interaction, right? 🤖 But that’s not how innovative companies like Feast & Fettle and Wildgrain are using AI. They’re doing the opposite—using AI to enhance the human connection, not replace it. 🤝 Take Wildgrain, for example. They use the AI capabilities of Island enterprise browser - which we install on all Peak Support computers - to help customer support agents read between the lines. The AI doesn’t interact with customers directly but instead helps agents pick up on subtle cues they might have missed. Wildgrain’s CEO, Ismael Salhi, puts it this way: “We don’t use it to interact directly with customers because AI is not there yet, and I don’t know if it will be there, ever. We use it to help agents not miss an ask.” 🧠 That means more thoughtful, personalized responses. At Feast & Fettle, they’re using AI to support agents by streamlining processes and workflows. This frees up time for agents to focus on deep, active listening with customers. The company is also exploring AI to customize meals for customers. Imagine if you always remove tomatoes from your salad order—AI could recognize this and adjust your meal automatically each week, creating a seamless, tailored experience without you even needing to ask. 💡 So, it’s not about reducing human touch—it’s about enhancing it through technology. Follow me to see how AI and other tools can work for your CX team, creating deeper, more meaningful customer relationships 👇