Using Customer Data to Improve User Experience

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

Track customer UX metrics during design to improve business results. Relying only on analytics to guide your design decisions is a missed opportunity to truly understand your customers. Analytics only show what customers did, not why they did it. Tracking customer interactions throughout the product lifecycle helps businesses measure and understand how customers engage with their products before and after launch. The goal is to ensure the design meets customer needs and achieves desired outcomes before building. By dividing the process into three key stages—customer understanding (attitudinal metrics), customer behavior (behavioral metrics), and customer activity (performance metrics)—you get a clearer picture of customer needs and how your design addresses them. → Customer Understanding In the pre-market phase, gathering insights about how well customers get your product’s value guides your design decisions. Attitudinal metrics collected through surveys or interviews help gauge preferences, needs, and expectations. The goal is to understand how potential customers feel about the product concept. → Customer Behavior Tracking how customers interact with prototype screens or products shows whether the design is effective. Behavioral metrics like click-through rates and session times provide insights into how users engage with the design. This phase bridges the pre-market and post-market stages and helps identify any friction points in the design. →  Customer Activity After launch, post-market performance metrics like task completion and error rates measure how customers use the product in real-world scenarios. These insights help determine if the product meets its goals and how well it supports user needs. Designers should take a data-informed approach by collecting and analyzing data at each stage to make sure the product continues evolving to meet customer needs and business goals. #productdesign #productdiscovery #userresearch #uxresearch

Wondering how to design a Scaled Customer Success motion? Leverage your data and reverse engineer what your customers need. Take the customers that you already know are successful, and look at their data to identify what a successful customer journey looks like. We keep the customer at the center, and use the data we have available to better understand our customers en masse. As you look at the data, you might find information that surprises you. Doing a regression analysis across customer data will tell you surprising things around signals that indicate growth potential as well as risk. You might find that the feature you thought was most "sticky" isn't actually used all that much by your growing and successful customers. You might find that the data that correlates to successful business outcomes for customers isn't at all what you would have guessed. After you've looked at this data and put on your detective hat and asked it good questions, you're ready to begin mapping out how to achieve those results at Scale. Start with what channel you're going to use. You can decide what is best delivered via digital channels vs human channels so that customers can grow and better accomplish their goals. You can identify where your CSMs can best spend their time in strategic human intervention as risk mitigation or growth acceleration as they help customers achieve their desired outcomes. You keep customers at the center by listening to what they're telling you: both in what they say and what they DO. That's what data can help you understand: what it is that your customers are actually doing. And then as you build out this Scaled motion, constantly go back to the data and get a better understanding if what you're doing is accomplishing the goals you're looking for. Don't make assumptions, be willing to look at the data and see the results. Because the only thing worse than not having data you need, is ignoring the data you have because you're too comfortable with what you're already doing. #CustomerSuccess #SaaS #Data #DigitalCS

Subscription services need strong analytics to build smarter & strategically strong plans. 🚀 Subscription models aren’t just a trend anymore—they’re shaping the future of eCommerce. 🛍 But are you leveraging data & analytics sufficiently, to iteratively build your strategy, & have your customers coming back? Here’s why you should make data analytics an integral part of your business approach: 🎯 Customer Retention Isn’t a Guessing Game Many eCommerce businesses still rely on gut feeling & high level market trends when deciding what keeps their subscribers happy. What if you could make smarter, data-driven decisions instead? Here’s how: 1️⃣ Understand User Behavior at a Granular Level Accurate analytics helps you spot patterns in how your subscribers behave. 👉 For example, a fitness app found that users who completed daily workouts stayed subscribed longer. With this insight, the app focused on features that encourage consistent engagement, boosting retention. 2️⃣ Personalize the Experience Analytics isn’t just about numbers—it’s about the people behind them. By segmenting your customers based on their behavior & psychographics, you can create personalized experiences that drive loyalty. 👉 Example: Netflix tailors its show and movie recommendations at a segment of one level, making subscribers feel seen and valued, while also making their life easier! 3️⃣ Track Key Metrics Keep an eye on crucial metrics such as Churn Rate, Average Order Value (AOV), & Customer Lifetime Value (CLTV). These metrics tell you what’s working, & where you need to pivot. 👉 For instance, a music app discovered that users who created personalized playlists were less likely to churn. Now they focus on promoting playlist creation to keep users engaged. 4️⃣ Leverage Predictive Analytics Want to predict churn before it happens? Predictive analytics can highlight warning signs of disengagement so you can take action before your subscribers leave. 👉 Takeaway: With predictive analytics you can send personalized reminders, special incentives, or tips to at-risk users, keeping them engaged. 5️⃣ Test, Learn, Optimize Don’t settle for your first plan. A/B testing helps you experiment with different subscription models, pricing, & features to arrive at the best. 👉 Example: A video streaming service can test different pricing structures & tiers, & find the best pricing plans that maximize sign-ups, market share, & retention. Bottom line: Subscription analytics give you the insights you need to understand, retain, & grow your subscriber base. Embracing smart data, & analyzing it while keeping the people behind it in your mind can create more personalized, engaging, & profitable subscription model. At Appstle Inc. there are 30,000+ eCommerce businesses that hands-on use our granular analytics to make impactful data driven customer retention strategies. The analytics are an integral part of Appstle Subscriptions. Because there is no better way to profitably scale!

Creating a customer journey map? You don't have to guess what your customers need. The data is right there. Using CRM tools like HubSpot can streamline the process. By capturing the right insights, you can anticipate customer needs, personalize interactions, and create a seamless experience. Start with these steps: 1. Develop your customer profile. Understand who your customers are by analyzing data from surveys, interactions, and social media. 2. Chart the customer lifecycle. Map out the journey from awareness to purchase, identifying key stages and what drives your customers at each point. 3. Sync goals with customer expectations. Align your strategies with what your customers aim to achieve, ensuring their needs are met throughout their journey. 4. Identify key touchpoints. Determine where and how customers interact with your brand, ensuring these touchpoints are optimized for engagement. 5. Evaluate goal fulfillment. Regularly assess whether your strategies are helping customers reach their goals, and adjust as needed. HubSpot’s lead scoring updates can give your sales and marketing teams a unified view of lead quality, enhancing alignment and efficiency. How are you using data to understand your customers better? #hubspot #crm #data