To many in the technology industry, customer success and customer experience are viewed as the same teams. However, TSIA’s research shows that customer success and customer experience are two separate departments with different roles and responsibilities.One of those key roles, which sometimes lands in the customer experience department, is the customer success data scientist. Too often, customer success executives are not aware of how to leverage this resource and do not understand the benefits that a customer success data scientist can bring to the organization to advance its digital capabilities. In a previous position as Global Vice President of Customer Success, I saw first hand the importance of having well-defined teams with clear delineations of roles and responsibilities, including the incorporation of data scientists. Let’s take a moment to understand the value the customer success data scientist brings in your journey for digital transformation. Understanding the Value of the Customer Success Data Scientist Role Customer success data scientists come in many different forms, shapes, and titles. Some of the titles that we’ve seen are Customer Success Analyst, CS Data Analyst, Customer Experience Manager, Business Intelligence Analyst, Data Scientist, CS Business Analyst, and the list goes on. When the Customer Success Data Scientist role sits outside of Customer Success, many times it is because it’s a shared resource. We sometimes see this shared role sitting in Marketing or Sales. This is common for smaller companies or smaller organizations that have limited resources. However, when we engage with larger organizations, this is no longer a shared resource but a dedicated resource that plays a great role in preparing the field for information awareness, workflow automation, improvements in the customer experience, and advancements in digital transformation. Many organizations may leverage the Customer Success Data Scientist but may not be focused on how to use this resource to prepare their organization for greater digital capabilities.
Sorting Through the Data to Find That “One Thing”
In the movie City Slickers, the character Curly Washburn (played by Jack Palance) tells Mitch Robbins (played by Billy Crystal) that the secret to life is about that “one thing.” The same is true for customer success. The secret to understanding if your customer health is strong is to find that “one metric” that shows the correlation between whether that customer will stay with you and grow with you–or whether they will likely churn. Customer Success Managers and Customer Success Executives typically do not have the cycles to sift through the data to find these correlations. It takes a seasoned Customer Success Data Scientist to decipher the data and identify trends that lead to expansion with a 90% or greater likelihood. Additionally, Customer Success Data Scientists can identify trends that will lead to renewals. During one of our conferences, a member shared that their data scientist found that “one thing” correlation for their organization, and it was conference attendance. They found that when their customers sent three or more members to their user conference, there was a 99% likelihood that they would renew. Guess what that member did? You got it–they focused on getting every customer to send at least three attendees. While this may not be the “one thing” that most companies are looking for, it illustrates that there may be key metrics that are not top of mind for Customer Success leaders that will have a significant impact on retention and expansion. Your “one thing” metric could be something completely different, but the Customer Success Data Scientist will know how to create the pivot tables and run the correlations to find the metrics that will be the “one thing” that you are looking for to give you greater predictive analytics.
Preparing Your Customer Success Team for Automation
A significant goal for scaling your Customer Success organization is to automate activities that do not require a human touchpoint by your team. What are the processes, actions, steps that can be automated? In many organizations, the Customer Success Data Scientist plays a pivotal role in identifying areas in the customer journey to leverage technology to create automation. This will give back additional time to the CSM team for more important “moments that matter.” When CSMs are spending 25% to 50% of their time on administrative items or non-operational activities, that is time not spent on “moments that matter” for the customer. Leverage the Customer Success Data Scientist to find times in the customer journey map where automation is possible and when it is important for a CSM touchpoint. Using Customer Health Scores are a way to have greater insights into the disposition of your customer and understand when is the right time to engage. Additionally, customer health scores play a key role in predictive capabilities such as outcome achievement, retention, and expansion. When organizations build an adoption framework as outlined by TSIA, knowing when a customer has low, high, or effective adoption is key for using it as a weighted metric in the customer health score. The next logical step is having the Customer Success Data Scientist build the automation behind the metrics to help with descriptive analytics, predictive analytics, and predictive outcomes.56% of organizations that have a dedicated Customer Success Data Scientist have fully-automated health scores, compared to 43% of organizations without the position. Additionally, organizations with a dedicated Customer Success Data Scientist have 28% more CSM workflow automation established compared to organizations that do not have this dedicated role.
Validating the Customer Feedback Loop
Customer Success is the central repository for customer data. CSMs bring the intelligence collected on their customers, however, the customer still needs a place for direct feedback. This is where Net Promoter Scores (NPS), Customer Satisfaction Scores (CSAT), and Customer Effort Scores (CES) are so incredibly important. Sifting through the data and aligning the customer feedback against additional data correlations is critical for understanding customer health. The Customer Success Data Scientist plays a key role in bringing this information back to the Executive Oversight Committee to report customer themes across the voice of the customer metrics. Organizations that leverage the Customer Success Data Scientist see a +4 point improvement on their NPS and approximately a 1/4 point increase in their CSAT scores.
To Put It Simply
The Customer Success community has many talented resources to help make your company successful. Don’t confuse customer success managers, whose primary role is to focus on customer adoption, to be the resource that can help automate and prepare your organization for going deeper into the digital realm. Let the CSM’s continue to focus on Adoption, Retention, and Expansion. As you make efforts to transform your organization for more digital capabilities, strongly consider the investment in a dedicated Customer Success Data Scientist.