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20 October 2021

The Data Science Of Customer Success: 4 Steps To Successfully Leverage Data For Deeper Customer Understanding

by Emily Ryan Reading time: 6 mins
manage customer data

Are You Making The Most Of Your Customer Data?

In enterprise organizations, Customer Success Managers (CSMs) interact with dozens of customers every day, with each interaction holding valuable information. The sheer volume of these interactions and their subsequent data points alone makes efficient data collection and analysis a key business imperative. This is why 86% of enterprises agree that data governance is either important or very important to meeting their financial and growth goals (ObservePoint, 2020). 

So, how can you empower your Customer Success Organization with the right approach to customer data management? To be successful, your organization must be able to formulate new ways to improve customer satisfaction and drive value. With a proper plan in place to manage customer data, your organization will be empowered to drive growth for both your company and your customers. 

In this article, we outline 4 meaningful steps to help you effectively leverage your data to better understand your customers and maximize value delivery across the customer journey.

1. Start With A Customer Journey Map

A complete and thorough customer journey is crucial to understanding your customers and delivering optimal value. By performing a customer journey mapping workshop with all of your cross-functional teams, you can identify each of the important touchpoints and moments that are going to drive them toward value. This will allow you to create a smooth and unified experience that moves the customer from acquisition through expansion seamlessly. 

When completing this exercise and thinking about how best to engage with customers, think about your customers  in broad categories. Often, businesses get hung up on how different all of their customers are instead of acknowledging the big ways in which they are the same. Utilize the data in your cross-functional ecosystem to uncover the important differentiators that help put your customers into the correct cohorts to enable you to optimize your scoring, automation and outreach.

2. Collect & Leverage Data Based On Your Customer’s Journey

The way you collect, use and manage customer data needs to map to your customers and where they are on their journey. Without this, you’re at higher risk for misinterpreting your customer data and potentially misstepping with your digital automation efforts. 

Early on in a customer’s lifecycle, customers don’t necessarily derive a lot of tangible value right away. At the beginning, they’re turning on the technology, implementing it, figuring out how to use and scale it and how to operationalize it. At this stage, your customers  aren’t going to have much in the way of qualitative data, so you’re going to need to maximize your quantitative data. We strongly encourage you to collect product usage measures such as login frequency and active users, as well as other indicators of “lights being turned on” and use these to determine how best to interact with your customers. 

As your customers move through their usage phase and start to adopt and operationalize your product, you can introduce more qualitative and experience measures. This includes metrics and scores such as: responses to an onboarding survey, use case readiness pulse checks, professional services satisfaction and consumption of education and external resources, like engagement with your adoption resources.

Once your customers deepen their adoption of your product, their data and usage is going to plateau. This is a good sign because this indicates that these customers are using the product consistently, and ideally, this doesn’t change much month over month. In this stage, you’re going to start seeing more qualitative insights and these will be your leading drivers for understanding your customers. Metrics like customer sentiment, customer engagement, use case completion, and customer satisfaction from support interactions will be easier to obtain and are extra important at this stage.

The final stage that you want all of your customers to reach is advocacy. This stage is almost entirely qualitative – you can’t see customer advocacy coming through product data, but you can gauge this sentiment during executive meetings with their C-level leaders and through their  willingness to provide case studies, participate in conferences or Customer Advisory Boards (CAB) and refer customer-qualified leads.

3. Analyze Thoughtfully & Strategically

While there are many ways to analyze data, the most strategic organizations begin with a hypothesis about different insights that may indicate whether a customer is healthy or unhealthy. Your hypothesis will be the starting point and Northstar that guides your organization as you analyze data and determine if there is a statistically significant difference between a customer who is likely to churn and a customer who is likely to stay. 

To create a strategic and meaningful hypothesis, ask yourself; what do my customers care about? What drives value and truly moves the needle for them? For instance, if you hypothesize that your customers care heavily about dashboards, you can look into how often users log in and look at dashboards, analyze that data and compare it between customers that you think are doing really well, customers who have expanded or renewed, and customers who have churned. Repeat this process for multiple data points and customer engagement metrics to determine which data produces insights and which data is not relevant one way or the other. 

This exercise provides a helpful benchmark to determine where your customers are in comparison to their peers, how you can better serve them, and how you can effectively collect and manage customer data moving forward. But, be cautious not to take these results at face value. You need to be critical and thoughtful in your analysis in order to determine if a negative metric is a direct result of the issue you’re solving for or symptomatic of something else entirely.

4. Develop Frameworks That Enable Actionable Insights

Once you have the data and insights necessary to understand your customers, you need to translate them into frameworks that everyone in your organization can access and use. This step is crucial to developing actionable insights that can focus your value-driving activities where they are needed most, helping to scale the organization. Customer scorecards and easy-to-use dashboards are examples of digestible customer insights that everyone in your organization can use. These can be broken down by customer segment or product category, or they can span your entire customer base to spot patterns and opportunities to ensure optimal value delivery among all of your segments.

Manage Customer Data To Master Growth

The most successful Customer Success organizations are the ones that are able to master customer data collection, measurement and analysis. By developing strategic and tactical data policies, CSMs can garner insights that help your organization define customer best practices, identify patterns for meaningful interactions and expansion opportunities, and create customer advocates that drive new customer acquisition.

Driving the greatest impact for your customers and your business is contingent upon creating and implementing the perfect segmentation model. Read our recent article about how to scale through segmentation and drive industry-leading customer growth.

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Emily Ryan

Emily has nearly 15 years’ experience coordinating teams across Sales, Post-Sales and Product/Delivery to ensure successful customer interactions. Her unique expertise applying Customer Success Strategy to effectively establish, analyze and scale great customer-centric teams means her impact is not only to corporate revenue and retention, but to the health and productivity of the teams she empowers.