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The Impact of Data and Operations on Customer Success
Data is integral to the field of customer success. This is not a controversial point of view. However, making data rise to its full potential in customer success is a serious challenge for many companies. Senior business leaders understand what they must do, but it’s hard to make data work in customer success and revenue operations (RevOps). This article, based on a podcast interview with Nick Mehta, CEO of Gainsight, the customer success innovator, looks at some of the underlying causes of this problem and suggests a practical, viable solution approach.

About Nick Mehta and Gainsight

Nick is CEO of Gainsight, a company whose products help businesses improve customer retention and accelerate expansion. The Gainsight Platform turns customer success into a major competitive advantage. It enables the achievement of this goal by interpreting the nuances of customer relationships and surfacing customer insights. He leads a 700-person team who refer to themselves as “Gainsters.”

Software Report has named Nick one of the Top SaaS CEOs three years in a row. The company itself holds one of highest Glassdoor approval ratings for CEOs. He is co-author of “Customer Success: How Innovative Companies Are Reducing Churn and Growing Recurring Revenue,” considered an authoritative book on the subject. Nick is also passionate about family, football, philosophy, physics, fashion and feminism. These details are worthy of mention because they provide context and give some weight to Nick’s insights about data and customer success.

Customer Success: A Brief Overview of the Category

Customer Success is a subject that most people intuitively understand. A business needs happy, successful customers in order to thrive and grow. However, today, Customer Success embodies a distinct set of practices and objectives.

The advent of Software-as-a-Service (SaaS) businesses like Salesforce.com was the driving force behind this evolution. With SaaS, customers have to make a conscious choice to renew their subscriptions every year. Unless the customer is extremely pleased with his or her success, there may not be a full renewal. This led to a concerted focus on ensuring that customers reached that high level of satisfaction.

The Customer Success team, along with the technologies that support its work, are responsible for managing the customer lifecycle. They drive adoption and renewals. They present up-sell opportunities and facilitate customer advocacy. Customer Success offers a new model of customer management—a field of business that is becoming more of a movement than a job description or an org chart box. It’s part of the bigger RevOps picture: the alignment of sales, marketing and customer support to drive better customer outcome and revenue growth.

How data fits into customer success

According to Nick, data is the wellspring of success with Customer Success. If a client is not getting great outcomes with a product, for instance, the Customer Success process and supporting platform should reveal this finding. But, how will the Customer Success team know there’s a problem in the first place? Such trends are easy to miss. That’s a matter of data.

Data will show that a customer is not using the product as much as it should be used. Data can indicate if there are customer support issues that are unresolved, a situation that can lead to disappointment and reduced chances of renewal. However, in order for this data to play its part in Customer Success, someone has to see it, understand it and take action. This is where many companies struggle.

The Unfortunate Reality

Nick related a type of conversation he has had many times with CEOs. He asks a CEO about her business and she replies, “Oh my God, we’re so innovative. We’re changing everything and shipping all this stuff. There were so many challenges. We fought through them.” Then, Nick asks about culture, and she responds, “We have this awesome culture and we have so much connection and blogging.” The CEO then brags about her great sales process. But then, when Nick says, “Tell me about your data,” she’ll get all sheepish and admit that data is a major challenge, a real struggle right now…

For Nick, this is a disappointing but very familiar situation. As he put it, “It’s 2020 and data is critical to running your business. Are we really going to be like this 10 or 20 years from now? We’ll have flying cars and like artificially sentient beings—but managing and analyzing data will still be a project that can never get done? If data is not your strength, you’re being a JV company. It’s inexcusable.”

Making Data Part of Customer Success

Data can fuel Customer Success, but first, the Customer Success team and its platform has to get the data together. That’s the first level of making data part of customer success. As Nick has seen, the location of data usually isn’t a big mystery. However, getting it into a manageable, accessible place can be a challenge without the right tools and processes.

Data from multiple sources has to be pulled into a single Customer Success data repository. This takes data integration and normalization. Integration gets the data into the same place, but it is normalization that makes it workable. Normalized data has uniform formatting and schemas, so the Customer Success platform can analyze it on an “apples to apples” basis.

Level two involves turning that data into useful insights. Nick used the example of whether it pays to quote pricing on the first call versus holding back that information until later in the sales and renewal processes. “Which approach is generating higher renewal rates, higher expansion in my business?” He asked.

From there, the third level is about turning insights into action. In his experience, the insight itself is valuable, but ultimately meaningless if no one turns it into a practical, customer-facing tactic. Continuing with the example of quoting price on the first call, if the finding is that one should never quote price at that point in the sales process, then someone has to make that a policy. “You have to make sure people do something about that,” he adds, “That’s what customers success is all about. If you learn something from analyzing the data, it has to go into the playbook so it becomes an ongoing factor in Customer Success strategy.”

Data orchestration has a role to play in making data a contributing part of Customer Success. The process normalizes data, for one thing. Data orchestration also takes care of de-duplicating data and removing errors and bad data from the Customer Success data set. Poor quality data will not serve the needs of Customer Success, and in fact may corrupt the analytics that make it work. Data orchestration can also perform enrichment on customer data. This makes it possible to get an enhanced view of the customer experience, e.g., by adding geographic information to account records to show patterns of usage that may be hard to spot otherwise.

Conclusion

Nick Mehta is in a position to offer great insights into Customer Success and the role of data in the realization of this important area of business operations. In SaaS, as well as in the broader business world, success comes to companies who work the hardest on achieving great customer outcomes. This is an inherently data-driven type of work. The data is there, but it needs to be organized, managed and analyzed. Data turns into Customer Success insights and then, ideally, actions. Data orchestration helps make it all happen.