Analyzing Customer Behavior To Improve Service Delivery

If your CX Program simply consists of surveys, it's like trying to understand the whole movie by watching a single frame. You have to integrate data, insights, and actions if you want to understand how the movie ends, and ultimately be able to write the sequel. But integrating multiple customer signals isn't easy. In fact, it can be overwhelming. I know because I successfully did this in the past, and counsel clients on it today. So, here's a 5-step plan on how to ensure that the integration of diverse customer signals remains insightful and not overwhelming: 1. Set Clear Objectives: Define specific goals for what you want to achieve. Having clear objectives helps in filtering relevant data from the noise. While your goals may be as simple as understanding behavior, think about these objectives in an outcome-based way. For example, 'Reduce Call Volume' or some other business metric is important to consider here. 2. Segment Data Thoughtfully: Break down data into manageable categories based on customer demographics, behavior, or interaction type. This helps in analyzing specific aspects of the customer journey without getting lost in the vastness of data. 3. Prioritize Data Based on Relevance: Not all data is equally important. Based on Step 1, prioritize based on what’s most relevant to your business goals. For example, this might involve focusing more on behavioral data vs demographic data, depending on objectives. 4. Use Smart Data Aggregation Tools: Invest in advanced data aggregation platforms that can collect, sort, and analyze data from various sources. These tools use AI and machine learning to identify patterns and key insights, reducing the noise and complexity. 5. Regular Reviews and Adjustments: Continuously monitor and review the data integration process. Be ready to adjust strategies, tools, or objectives as needed to keep the data manageable and insightful. This isn't a "set-it-and-forget-it" strategy! How are you thinking about integrating data and insights in order to drive meaningful change in your business? Hit me up if you want to chat about it. #customerexperience #data #insights #surveys #ceo #coo #ai

Your churned customers will show 5 warning signs months before leaving. While writing latest book, Behind The Click, I analyzed 15+ years of optimization efforts at The Good for Fortune 500 brands like Adobe, Nike, and The Economist. It pointed to one key theme: → Most companies look at conversion rates and revenue *after* the damage is done. But digital experience issues often show warning signs long before customers leave. Here are the 5 key metrics that signal customer dissatisfaction: 1. Path Efficiency Issues When customers take longer paths to complete basic tasks, it increases cognitive load and frustration. Don't make customers hunt through your navigation to find basic product information. 2. Search Behavior Changes Large volumes of search queries for basic information indicate a broken digital journey. Easy wins are often found in your on-site search data. 3. Mobile Experience Friction Only 34% of US customers prefer shopping on mobile. But 62% are less likely to purchase again after a negative mobile experience. So, focus your mobile experience around product research tasks, knowing they'll likely convert later on desktop. 4. Cart Abandonment Patterns 17% of visitors abandon due to lack of trust. Trust signals also impact retention. Security badges are too often used as a bandaid for trust issues. Research and fix the underlying issues. 5. Customer Service Escalations Digital experience issues create support burden. Is your customer service flooded with questions your site isn't answering? Surface those questions, then provide the answers in your site content. 🪄 Boom! More conversions, less support overhead killing your margins. The most successful enterprise brands don't wait for churn. They proactively optimize their digital experience using customer behavior data and research-backed improvements. Don't let your customers slip away.

I remember years ago working with a coffee brand, and we discovered some fascinating insights from analyzing customer buying behavior. We had two types of purchases: subscriptions and one-time buys. When we dug into the data, we found a significant pattern. Only 18% of one-time buyers made a second purchase. But if they did, there was an 85% chance they’d order a third time, and the repeat order rate stayed high after that. This showed us a major bottleneck. The founder initially wanted to focus all incentives on attracting first-time buyers, but the data told a different story. We saw the value in driving that crucial second purchase. So, we overhauled our approach: 1. Revamped Fulfillment Kits: The first order kit included incentives for a second purchase. 2. Updated Email Campaigns: Emails were tailored to encourage a second buy. The results? We boosted the second purchase rate to nearly 30%, leading to a significant increase in overall sales and customer lifetime value (LTV). Even with pushing more people into that second order, we only saw a small dip in the number of people who went from a 2nd to a 3rd order, moving from 85% to 83%. This experience shows the power of slicing your data by cohorts to uncover bottlenecks and then addressing them directly. Sometimes, the biggest gains come from focusing on the steps beyond the initial sale.