5 strategies for having a more data-driven Customer Success
Customer Success uses health scores, NPS, and product data to act before churn. 5 practical data-driven strategies every CS team should monitor.
Have you ever stopped to think about what your company would be without your customers? Let's be honest... Having an incredible and complete solution is useless if your end user cannot extract value and see utility in it. That is why Customer Success has become increasingly present within companies, and a more data-driven Customer Success team can achieve truly transformative results.
There is still a lot of confusion around this topic, especially regarding what this professional does and how they can be a key player in your data strategy. This is true even though companies today understand the need to combat churn, put customer needs at the center of the business, and establish the right metrics so the department doesn't end up being just support with a different name.
That's why we are bringing you an overview of what Customer Success is and how your company can build a more Data-Driven Customer Success operation.
What is Customer Success
Having successful sales and marketing teams is extremely important to win the market, expand opportunities, and build your company's success story. But these departments alone are no longer enough to guarantee business stability, ensure predictable recurring revenue, and sustain constant growth. The truth is that how companies sell has changed, and so has how people buy.
Consumer relationships are no longer one-sided: someone sells, someone buys, and that's the end of it...
With businesses becoming increasingly digital and the rise of companies focused on service and subscription models, the responsibility of maintaining customer loyalty is higher, especially in a dynamic market ripe with competitors. According to Gartner's glossary, customer success is a methodology to ensure customers achieve their desired outcomes while using your products and solutions, motivating them to continue buying or consuming from your brand.
In other words: it is about all the effort your company invests in the success your customer experiences with your solutions. A common scenario in CS teams is when, in addition to customer onboarding, they are also responsible for technical support. This is a mistake, as it limits the department's capacity to generate and leverage vital business data.
Therefore, your CS department shouldn't be confused with other customer-facing roles like account management, support, and growth. Some data and insights that can be gathered when the team is focused strictly on the customer experience include:
Your company's customer journey;
The user's time-to-value with the solution;
The main challenges and advantages of your tool or service;
Understanding the customer's post-acquisition sales funnel;
The main reasons customers choose not to buy or decide to cancel contracts.
Additionally, a high-performing Customer Success department increases the likelihood of users championing and recommending your company, improving cash flow through both new customer acquisition and expansions.
5 strategies for a more Data-Driven Customer Success operation
Now that you understand what Customer Success is and the importance of having a dedicated department for it, let's talk about the 5 key strategies to make your Customer Success Data-Driven.
1) Invest in data-driven people
An important point in building a data-driven department (and company) is what we call data literacy: your team's ability to read, write, and analyze data to make it actionable within their daily scope of work.
Finding the right people with well-developed analytical skills is a major challenge in the job market. When building your team, the ideal is to look for professionals who are already data-driven, or at least data-aware (meaning they understand the importance of leveraging data within the organization).
You don't need to find ultra-specialized professionals, but it is important to count on those who are eager to learn and who believe in a data-centric approach. They will be the right allies on your data-driven journey!
2) Design clear processes
A Data-Driven Customer Success department relies on processes built for acquiring, interpreting, and generating insights from data. Since CS professionals are constantly in contact with your customers, they are the best-positioned people to collect useful feedback to guide your business decisions.
One way to ensure this is by designing processes focused on data collection and analysis to generate actionable insights. Encourage documenting client interactions and every step of their onboarding process to implement highly effective action points and identify key drop-off risks in their journey with your solution.
3) Train your team
Data literacy across an organization is a continuous process of enablement, reinforcement, and training to ensure a data culture remains embedded in your team's daily routine. That's why you should never overlook regular training, especially for your Customer Success team.
Some useful training topics for the team, besides product and industry domain knowledge, include:
Data applications for Customer Success;
Data collection and basic modeling;
How to improve customer journey documentation.
4) Identify the department's biggest challenges (and document them!)
You might believe your team has areas for improvement, but what are you actually using to track this right now? This is an important question for any department: knowing exactly what data highlights bottlenecks or drives decisions.
In a customer-facing role, this becomes vital. Therefore, understand your team's main bottlenecks and tackle them with data-backed solutions.
5) Define clear metrics
Lastly, implement Customer Success metrics that are clear and align with your department's reality and the goals you want to achieve. Remember to maintain a detailed historical log of each metric to make data analysis possible. The essential Customer Success metrics are:
Health Score
The Customer Health Score indicates the health level of your company's accounts, categorizing them into: poor (churn risk), medium (potential renewal), or good (renewal and expansion opportunities). This metric helps predict customer behavior based on the analysis of variables such as:
Usage frequency: How often are customers using your product, and what is their dependency on your solution?
Breadth: How many users within an account are actually active on your product?
Depth: How deeply are users adopting your product features? Which features are being leveraged and what can be optimized?
Support: How satisfied is the customer with the support and interactions they receive when contacting your team?
The ideal Customer Health Score will depend heavily on your company's profile, product type, customer segment, and solution features.
Expansion
This metric is critical for businesses with multiple revenue streams, indicating expansion, up-selling, and cross-selling on top of the original purchase. It usually shows that the customer is so satisfied with the solution that they want to scale their usage or unlock more features.
From a customer's budget perspective, this indicates they are seeing so much value and ROI that it makes sense to invest even more. This metric is heavily influenced by your CS team's performance; the better the onboarding and success outcomes, the more trust and value the customer associates with the partnership.
Activation
The concept of activation is straightforward: how long it takes for your customers to adopt key features and start extracting value from them (time-to-value). Activation metrics depend on mapping your product's usage milestones, which varies from business to business.
For example: if your company provides financial software, there is a minimum set of setups required before the customer can successfully run the tool and see its impact. Mapping these paths based on features used or ignored helps pinpoint user friction points, allowing your CS team to intervene proactively.
Some of these checkpoints could include: the number of actions within your platform, logins, session duration, data ingested, or touchpoints with your team. To define the right activation criteria, map out a customer journey that makes sense based on the data your CS team generates!
NPS
Net Promoter Score is a metric that measures overall customer satisfaction and loyalty. This methodology identifies whether your customers are promoters, passives, or detractors based on periodic surveys, placing them into three distinct groups:
If on a scale of 0 to 10, a customer rates their experience between 0 and 6, they are classified as a detractor: an unhappy customer who is unlikely to recommend your product and might even discourage potential buyers.
If they rate it a 7 or 8, they are considered passive: they are satisfied but not enthusiastic enough to recommend your brand. If their score is 9 or 10, the customer is a promoter: they are highly satisfied and will actively advocate for your company. To calculate your NPS, subtract the percentage of detractors from the percentage of promoters, resulting in a score from -100 to +100.
Churn
Generally speaking, this metric tracks when a customer decides to cancel their subscription or service. It reflects overall satisfaction with the entire experience, not just CS or support interactions. This metric has an exponential impact, and over the long run, heavily dictates business growth. You can measure it in two ways: customer churn (the percentage of lost logos) or revenue churn (Net or Gross Revenue Churn, calculating the ARR/MRR lost).
While tracked as a CS metric, churn usually reflects company-wide performance, as multiple factors lead a customer to cancel. Pro-tip: once you leverage your data, you will understand exactly how to proactively reduce churn.
Conclusion
A data-driven Customer Success team is about having a department capable of generating, analyzing, and acting on customer data. Therefore, building a data-driven department requires people trained in data literacy, backed by processes and metrics that support this culture.
Customer-facing teams are essential for collecting useful data points that guide more assertive decision-making for your company's overall strategy and planning.
Remember: being data-driven is not just about collecting data, but knowing how to generate insights and use them to transform your business. In this mission, companies like Erathos can help—providing everything from the support needed to implement your data infrastructure to building BI dashboards, analytics, and leveraging AI to predict scenarios and guide decision-making.
Want to learn more about how Erathos can help your company become data-driven in less time? Click on the WhatsApp icon on the side and get in touch with us today!
Have you ever stopped to think about what your company would be without your customers? Let's be honest... Having an incredible and complete solution is useless if your end user cannot extract value and see utility in it. That is why Customer Success has become increasingly present within companies, and a more data-driven Customer Success team can achieve truly transformative results.
There is still a lot of confusion around this topic, especially regarding what this professional does and how they can be a key player in your data strategy. This is true even though companies today understand the need to combat churn, put customer needs at the center of the business, and establish the right metrics so the department doesn't end up being just support with a different name.
That's why we are bringing you an overview of what Customer Success is and how your company can build a more Data-Driven Customer Success operation.
What is Customer Success
Having successful sales and marketing teams is extremely important to win the market, expand opportunities, and build your company's success story. But these departments alone are no longer enough to guarantee business stability, ensure predictable recurring revenue, and sustain constant growth. The truth is that how companies sell has changed, and so has how people buy.
Consumer relationships are no longer one-sided: someone sells, someone buys, and that's the end of it...
With businesses becoming increasingly digital and the rise of companies focused on service and subscription models, the responsibility of maintaining customer loyalty is higher, especially in a dynamic market ripe with competitors. According to Gartner's glossary, customer success is a methodology to ensure customers achieve their desired outcomes while using your products and solutions, motivating them to continue buying or consuming from your brand.
In other words: it is about all the effort your company invests in the success your customer experiences with your solutions. A common scenario in CS teams is when, in addition to customer onboarding, they are also responsible for technical support. This is a mistake, as it limits the department's capacity to generate and leverage vital business data.
Therefore, your CS department shouldn't be confused with other customer-facing roles like account management, support, and growth. Some data and insights that can be gathered when the team is focused strictly on the customer experience include:
Your company's customer journey;
The user's time-to-value with the solution;
The main challenges and advantages of your tool or service;
Understanding the customer's post-acquisition sales funnel;
The main reasons customers choose not to buy or decide to cancel contracts.
Additionally, a high-performing Customer Success department increases the likelihood of users championing and recommending your company, improving cash flow through both new customer acquisition and expansions.
5 strategies for a more Data-Driven Customer Success operation
Now that you understand what Customer Success is and the importance of having a dedicated department for it, let's talk about the 5 key strategies to make your Customer Success Data-Driven.
1) Invest in data-driven people
An important point in building a data-driven department (and company) is what we call data literacy: your team's ability to read, write, and analyze data to make it actionable within their daily scope of work.
Finding the right people with well-developed analytical skills is a major challenge in the job market. When building your team, the ideal is to look for professionals who are already data-driven, or at least data-aware (meaning they understand the importance of leveraging data within the organization).
You don't need to find ultra-specialized professionals, but it is important to count on those who are eager to learn and who believe in a data-centric approach. They will be the right allies on your data-driven journey!
2) Design clear processes
A Data-Driven Customer Success department relies on processes built for acquiring, interpreting, and generating insights from data. Since CS professionals are constantly in contact with your customers, they are the best-positioned people to collect useful feedback to guide your business decisions.
One way to ensure this is by designing processes focused on data collection and analysis to generate actionable insights. Encourage documenting client interactions and every step of their onboarding process to implement highly effective action points and identify key drop-off risks in their journey with your solution.
3) Train your team
Data literacy across an organization is a continuous process of enablement, reinforcement, and training to ensure a data culture remains embedded in your team's daily routine. That's why you should never overlook regular training, especially for your Customer Success team.
Some useful training topics for the team, besides product and industry domain knowledge, include:
Data applications for Customer Success;
Data collection and basic modeling;
How to improve customer journey documentation.
4) Identify the department's biggest challenges (and document them!)
You might believe your team has areas for improvement, but what are you actually using to track this right now? This is an important question for any department: knowing exactly what data highlights bottlenecks or drives decisions.
In a customer-facing role, this becomes vital. Therefore, understand your team's main bottlenecks and tackle them with data-backed solutions.
5) Define clear metrics
Lastly, implement Customer Success metrics that are clear and align with your department's reality and the goals you want to achieve. Remember to maintain a detailed historical log of each metric to make data analysis possible. The essential Customer Success metrics are:
Health Score
The Customer Health Score indicates the health level of your company's accounts, categorizing them into: poor (churn risk), medium (potential renewal), or good (renewal and expansion opportunities). This metric helps predict customer behavior based on the analysis of variables such as:
Usage frequency: How often are customers using your product, and what is their dependency on your solution?
Breadth: How many users within an account are actually active on your product?
Depth: How deeply are users adopting your product features? Which features are being leveraged and what can be optimized?
Support: How satisfied is the customer with the support and interactions they receive when contacting your team?
The ideal Customer Health Score will depend heavily on your company's profile, product type, customer segment, and solution features.
Expansion
This metric is critical for businesses with multiple revenue streams, indicating expansion, up-selling, and cross-selling on top of the original purchase. It usually shows that the customer is so satisfied with the solution that they want to scale their usage or unlock more features.
From a customer's budget perspective, this indicates they are seeing so much value and ROI that it makes sense to invest even more. This metric is heavily influenced by your CS team's performance; the better the onboarding and success outcomes, the more trust and value the customer associates with the partnership.
Activation
The concept of activation is straightforward: how long it takes for your customers to adopt key features and start extracting value from them (time-to-value). Activation metrics depend on mapping your product's usage milestones, which varies from business to business.
For example: if your company provides financial software, there is a minimum set of setups required before the customer can successfully run the tool and see its impact. Mapping these paths based on features used or ignored helps pinpoint user friction points, allowing your CS team to intervene proactively.
Some of these checkpoints could include: the number of actions within your platform, logins, session duration, data ingested, or touchpoints with your team. To define the right activation criteria, map out a customer journey that makes sense based on the data your CS team generates!
NPS
Net Promoter Score is a metric that measures overall customer satisfaction and loyalty. This methodology identifies whether your customers are promoters, passives, or detractors based on periodic surveys, placing them into three distinct groups:
If on a scale of 0 to 10, a customer rates their experience between 0 and 6, they are classified as a detractor: an unhappy customer who is unlikely to recommend your product and might even discourage potential buyers.
If they rate it a 7 or 8, they are considered passive: they are satisfied but not enthusiastic enough to recommend your brand. If their score is 9 or 10, the customer is a promoter: they are highly satisfied and will actively advocate for your company. To calculate your NPS, subtract the percentage of detractors from the percentage of promoters, resulting in a score from -100 to +100.
Churn
Generally speaking, this metric tracks when a customer decides to cancel their subscription or service. It reflects overall satisfaction with the entire experience, not just CS or support interactions. This metric has an exponential impact, and over the long run, heavily dictates business growth. You can measure it in two ways: customer churn (the percentage of lost logos) or revenue churn (Net or Gross Revenue Churn, calculating the ARR/MRR lost).
While tracked as a CS metric, churn usually reflects company-wide performance, as multiple factors lead a customer to cancel. Pro-tip: once you leverage your data, you will understand exactly how to proactively reduce churn.
Conclusion
A data-driven Customer Success team is about having a department capable of generating, analyzing, and acting on customer data. Therefore, building a data-driven department requires people trained in data literacy, backed by processes and metrics that support this culture.
Customer-facing teams are essential for collecting useful data points that guide more assertive decision-making for your company's overall strategy and planning.
Remember: being data-driven is not just about collecting data, but knowing how to generate insights and use them to transform your business. In this mission, companies like Erathos can help—providing everything from the support needed to implement your data infrastructure to building BI dashboards, analytics, and leveraging AI to predict scenarios and guide decision-making.
Want to learn more about how Erathos can help your company become data-driven in less time? Click on the WhatsApp icon on the side and get in touch with us today!