What is Data-Driven CS (and How Do You Do It Properly?)
Learn about data-driven CS and how you can apply it to your organization
A Customer Success tech stack is a marvel of services, tools, and manpower coming together in service of the customer. A robust and well-executed CS tech stack is the engine that drives an effective Customer Success organization.
But if the tech stack is the engine, then the data is the fuel. The right fuel can drive your team forward and power them to new heights.
So how can you ensure that your CS department is data-driven? And more to the point, how do you ensure that it’s powered by the right data?
We discussed all this and more in No Fluff: What is Data-Driven CS?, a webinar featuring Veronica Dasovich, Senior Director of Customer Success at Heap, Tobin Bennion from Snowflake Data Warehouse, and our very own Edward Chiu, CEO and co-founder of Catalyst.
In this blog post, we will recap the following topics:
- What is data-driven CS and what does it mean?
- What kind of data do you need?
- What are the vital components of a data-driven CS tech stack?
Let’s get down to it!
What does it mean to be data-driven in Customer Success?
The concept of being data-driven as a customer-centric organization can be broken down into three levels:
- Customer level
- Team level
- Company level
Data is used at the Customer level to understand how a company is taking care of its customers. It answers valuable questions about their health, and helps establish any proactive steps that can be taken to ensure the customers enjoy great success.
Data-driven CS at the Team level is concerned with things like capacity planning, segmentation, and NDR forecasting. It even covers whether or not a company is in a position to expand their CS team and support staff.
Lastly, the Company level is when you’re using data to understand your Go-To-Market motion. The data affects your Ideal Customer Profile and ensures you have proper customer alignment.
Data is also used at the company level to assess and, if necessary, realign the product roadmap. You need to lean in on building features that align with the needs of healthy customers that fit your ICP.
What kind of data do you need?
Being data-driven only works if you leverage the right data. And the thing about finding the right data is it depends on what you’re going to be using it for.
For this blog post, we’re going to focus on three specific use cases: one for each level of Customer, Team, and Company.
Proactive CSM plays (Customer level)
While Customer Success can often be reactive based on a customer’s situation, being proactive can help head off problems and further cement strong relationships. Proper data can help inform CSMs on when it is the right time to act.
The data you need to create proactive CSM plays includes:
- Product usage data
- Support data
NDR forecasting (Team level)
Your organization needs to know how much money you can expect per quarter in order to properly plan your business strategy. This means that you need to know for certain which customers are renewing, and which will probably churn.
For this use case, you will need data like:
- Contract value
- Renewal date
- Health score
Product roadmap (Company level)
A customer-centric organization will align their product roadmap to the needs of their healthiest and best fitting-customers. In order to achieve this alignment, the organization would be best served by the following data points:
- CRM Data
- Customer health score
- NPS
- Customer meeting notes (created by CSM)
As you can see, it’s very important to establish what you’re trying to achieve first. This helps focus your data collection and analysis and ensures that all of the data you’re using is relevant and valuable.
What are the vital components of a data-driven CS tech stack?
Tech stacks are a tricky subject to discuss at the best of times. Every business is so unique in how they operate and that no two CS tech stacks are ever identical.
Having said that, many businesses follow the same general framework. For example, there always has to be a CRM, a Data Warehouse, and a Backend Infrastructure.
In this post (and during the talk), we will be speaking about three major components in particular:
- Event tracking
- Data warehouse
- Customer Success Platform
Event tracking
“The purpose of event tracking is to keep a system of record of what your customers are actually doing in your website or mobile app product,” says Veronica.
Digital analytics platforms like Heap can track the following actions or events:
- Button clicks
- Pageviews
- Form fills
- Swipes
- And more
All of these events can then be associated with specific users and time stamps, which give you great visibility into how users are interacting with your product, what paths they take, and whether different customers use the product in different ways.
Further analysis can give you greater insights into which user actions predict churn, and which predict retention. They can tell you what kind of assistance users might need from your CS team, and which they can learn and master on their own.
They’re pretty simple to set up, too. All you have to do is insert a snippet of code into your website or app SDK. No additional installations or setup required.
Data warehouse
A data warehouse is a system used for reporting and data analysis. Data warehouses often serve as a central repository for data collected by disparate areas of the business across different tools and data sources.
“The pros of a data warehouse are that the data is very structured and defined for high-performance reasons. You know what’s coming in, you know where it is, and it’s easy to make calculations,” Tobin says.
“Data warehouses are also known as ‘analytical databases,’ where data is grouped in columns instead of rows. This means that they’re much more efficient at calculating across many different pieces of data. For instance, calculating the average ACV of all of my customers.”
Data warehouses are themselves built from different components, such as storage and a query engine.
Customer Success Platform
A Customer Success Platform is where all of the different components of your tech stack coalesce. It ingests all of the data compiled by the different components of your tech stack and aggregates them into a usable format.
According to Edward, “The point of a Customer Success Platform is to make sure that your CS organization has a tool that empowers them to be proactive rather than reactive. And the number one way to be proactive is being able to see all of your relevant information in a singular view, instead of in multiple tabs.”
When you’re being data-driven in your Customer Success approach, CS platforms like Catalyst allow you to access important information like:
- 360-degree customer views
- Customer health
- Deeper customer segmentation
- Lifecycle tracking
- Product usage
None of this would be possible without event tracking solutions like Heap providing valuable, real-time behavioral intelligence and data warehouses like Snowflake organizing and analyzing the data.
Watch the full webinar for the complete webinar (including a sneak peek at Heap’s tech stack.)
We’ve also created a free, downloadable worksheet to help you strategize your data-driven initiatives that will drive the most value to your customers and team.
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