This guide will help you build a data-driven customer success team and enhance your chances of team success.
At the center of customer success is data. Without it, you can’t maximize your customer’s potential with your product.
But having access to it is pointless if you don’t have a data-driven team that’ll use the data to get your customers and organization results. In this post, we’ll provide you with tips and best practices you can use to build the data-driven customer success team you need.
Hiring the right people with the right mindset is important to influence behavior. Your first step is to recruit people who know and understand the significance of being data-driven.
Most people from data-based companies are naturally oriented to embrace and interpret data. They understand the importance of data-driven processes and have experience measuring success. If you’re scarce on resources and can’t hire additional help, you can bring sales, product, and support teams together to improve customer success and fine-tune collaboration.
Hiring data-driven people alone isn’t enough. You need to ensure that they’re empowered to use that data. By doing this, you’ll be providing relevant information about customers to the right people to help them succeed. You should also suggest common workflows to identify potential issues and share available resources.
Facilitate data literacy by ensuring team members are well trained and understand data complexities by investing in training. Building a data-driven culture doesn’t happen overnight. It needs to be improved at a granular, cultural level and be a part of your organization’s DNA.
It’s not simply gathering data. You need to see how well the company embraces data and makes it part of the company culture.
You need to keep your data accessible by consolidating it in one place. You can do this by utilizing a data warehouse or customer success solution that’ll track events and help desk information and extract data from CRM and production databases.
Once you’ve found the right product for your team, you need to ensure that everyone’s on the same page and using the same terms. Standard terms and their metrics like churn rate, revenue rate, and active users are known universally. But, for others, it’s essential to use the same one across teams to avoid miscommunication and irregular tracking.
Building your team is the first step to ensuring they’re data-driven. The next is to measure individual, team, and company performance and optimize your team based on the data collected.
One way you can do this is by setting metrics and KPIs to measure performance and productivity. Measuring their performance is vital for understanding if your data-driven insights are working. And KPIs can track data and offer better reports. This can mean operations metrics, conversations metrics, total conversations metrics, and more. Information like time to first response, time to close, conversation rating, net promoter score, user metrics, number of active users, length of user sessions, and number of user sessions needs to be kept in mind.
As previously mentioned, if teams in other departments aren’t familiar with customer-success data processes, this can lead to misunderstandings and inaccurate tracking. You can help improve cross-departmental communication by attaching descriptions to data, highlighting guidelines, and establishing better-streamlined processes.
Plus, by improving communication across teams, everyone will be on the same page and can grasp the data’s importance. This can lead to better conversations, informed decisions, and discussions about health, adoption, and customer success.
In today’s businesses, the core idea is to make customers successful. And the rise in subscription-based business models has made it essential to see customers benefit from these products.
This is why businesses need to build a data-driven customer success culture. It’ll impact customer churn, loyalty, revenue, and more. A data-oriented CS team can enable your company to scale alongside your customers. And with the right people, processes, and tools, over time, it’s possible.