How to Build a Data Driven Customer Success Program That Drives Growth

Are you looking to build a data-driven customer success program that drives growth? Manasij Ganguli, a two-time SaaS founder, and CEO of ZapScale, knows that retaining customers is critical for success. 

After four years of trial and error, he found the most important aspects of a customer’s health that indicate churn, adoption, retention, and expansion. He wants to help others avoid the same hassle that he and his team went through, and he has developed a care metrics analysis system to do just that. 

In this post, I’ll outline how Manasij Ganguli did it in detail and how you can use it to boost growth with a data-driven customer success program.

About Manasij Ganguli

Manasij Ganguli is the founder and CEO of Zap Scale, a company that helps B2B SaaS companies retain their customers, drive engagement, and increase upsells. Manasij has a wealth of experience with customer success operations, having developed customer health metrics and customer service playbooks in his own business. 

He has now dedicated himself to helping others streamline the customer success process, allowing them to reach the same level of success without having to go through the same trial and error he experienced. With his deep understanding of customer success, Manasij will be able to provide valuable insight into how to improve customer health and customer retention.

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Why is it important to build a data-driven customer success program that drives growth?

A data-driven customer success program is essential to any successful B2B SaaS business. Businesses can create targeted customer success initiatives that drive growth by leveraging data to understand customer needs and behaviors better. A data-driven customer success program also allows companies to identify potential areas for improvement, allowing them to identify and capitalize on new growth opportunities. 

Data can be used to identify customer pain points and develop strategies to address them, leading to increased customer satisfaction and loyalty. Furthermore, a data-driven customer success program allows businesses to track key metrics such as customer churn, lifetime value, and engagement. 

This data can be used to gain insight into customer behaviors and preferences, allowing businesses to tailor their services and offerings to meet customer needs better. 

Another benefit is that data analysis can identify trends and patterns in customer behavior, allowing companies to proactively address customer needs and drive growth. Ultimately, investing in a data-driven customer success program is essential for any B2B SaaS business that wants to remain competitive and grow.

Here are the steps you need to follow:

1. Identify the key customer health KPIs
2. Automate customer service operations through playbooks
3. Create an onboarding process that is personalized with automation
4. Analyze customer breadcrumbs from product usage, CRM, tickets, features, emails, invoices, meetings, and CS team perspectives.
5. Monitor customer health metrics (e.g., churn, adoption, and expansion) to identify problems or opportunities for expansion.
6. Look for leading indicators such as product usage trends, ticketing performance, feature requests, communication performance, invoice performance, and meeting requests

The first step is to understand the customer health metrics that indicate if a customer is likely to retain, churn, adopt, or expand. This requires a deep understanding of the customer journey, which can take considerable time to build. 

Manasij Ganguli, the founder, and CEO of ZapScale, has made this process a lot easier by creating a suite of 42 out-of-the-box health KPIs that provide the deepest customer and user health management to make it easier for companies to access this knowledge. These KPIs automate customer service operations via 50 out-of-the-box CS playbooks the company offers along with a one-day onboarding into the ZapScale platform. 

Let’s take a look at how we can gain actionable insights that drive growth.

1. Identify the key customer health KPIs

Identifying the key customer health KPIs can be done by gathering data from several sources and creating a “package” of information that can be used to determine the health of the customer. Data sources that should be looked at include product usage, customer data from the CRM, ticketing, feature requests, emails, invoices, meetings, and customer success team perspectives. 

Combining these data sources can create a trend line of the customer over time and indicate where they are on their customer journey. The KPIs should be focused on customer churn, adoption, retention, and expansion to get the most accurate picture of customer health. As customer success combines a personal touch and a statistical approach, it’s crucial to find a balance between these two to create an effective system for tracking customer health.

Once the key customer health KPIs have been identified, the next step is to create relevant metrics that will measure the success of the customer health KPIs. These metrics should be tailored to each customer to understand their journey and ensure that the KPIs are tracked accurately. 

These metrics should be customized to the customer’s industry and the type of product they are using. For example, if the customer uses a software product, the metrics should be related to user engagement, feature adoption, and customer churn. On the other hand, if the customer is using a service product, the metrics should be related to customer satisfaction, customer retention, and customer expansion. 

It’s also important to keep track of the customer health KPIs and metrics over time to ensure that the customer is on the right track. This can be done by setting up regular reviews with the customer success team and tracking the performance of the KPIs and metrics over time. 

The customer success team should be given the autonomy to adjust the KPIs and metrics to ensure that the customer is getting the best possible service. By following these steps, it will be possible to ensure that the customer health KPIs are being tracked accurately and that the customer is on the right track.

2. Automate customer service operations through playbooks

You can automate customer service operations through 50 out-of-the-box CS playbooks that ZapScale offers. To automate customer service operations with 50 out-of-the-box CS playbooks, businesses first need to collect customer data from various sources. This includes product usage, customer data from CRMs, ticketing, feature requests, emails, invoices, meetings, and customer success team perspectives. 

Once the data is collected, it needs to be analyzed to determine customer health metrics and identify any potential issues that may arise. The next step is to create playbooks that will help automate customer service operations and respond to customer issues promptly. The playbooks should be tailored to the specific customer needs and regularly updated with new data and insights. 

The playbooks should also adapt to changing customer needs and be able to offer the best possible service to customers at any given time. With the right playbooks, businesses can automate customer service operations and provide a more efficient and effective customer experience.

Once the playbooks are in place, businesses can begin to measure the effectiveness of their customer service operations. They can track customer satisfaction, response times, customer health metrics, and other key performance indicators. By monitoring these metrics, businesses can identify areas where they may need to improve or change their customer service operations. This data can also inform future decisions and develop more efficient and effective customer service operations. 

When businesses have their CS playbooks in place, they can focus on customer experience optimization. This includes optimizing customer onboarding, personalizing customer service interactions, and even offering self-service options. With the playbooks in place, businesses can more easily and quickly respond to customer issues and provide the best possible service to their customers. Automating customer service operations through CS playbooks can help companies to create a more efficient and effective customer service environment.

3. Create an onboarding process

The next step involves creating an onboarding process while using a tracking system for customer data. This system should be designed to track customer data from multiple sources – product usage, CRM data, ticketing, features requests, emails, invoices, meetings, and customer success team perspectives – and to present this data in a way that is easy to analyze and understand.

The purpose of this system is to monitor customer health metrics such as churn, adoption, retention, and expansion and to provide a real-time view of customer activity. The system should be designed to quickly identify trends and warning signs indicating a potential problem and allow the customer success team to take corrective action. Additionally, the system should be able to make predictions and provide recommendations to help the customer achieve their goals.

Another criterion for success is to create an onboarding package for customers. This package should include a welcome email, product overview, user guide, training materials, and customer success resources. The onboarding package should provide customers with all the necessary information they need to get started with the product and the resources they need to succeed. 

The onboarding package should also include a customer success roadmap highlighting key milestones and goals for the customer. This onboarding package should be tailored to the customer’s needs and goals. 

In creating an onboarding process you also need to set up customer success touchpoints. During the onboarding process, customer success touchpoints should be established that allow the customer success team to check in regularly with customers and ensure they get the best value from the product. 

These touchpoints should include regular check-ins to discuss customer feedback, measure customer health metrics, and identify areas for improvement. 

Customer success touchpoints should include regular reviews of customer success plans to ensure they are up to date and meeting customers’ goals. As a result, the customer success team can ensure they provide the best customer experience possible by establishing customer success touchpoints.

4. Analyze customer breadcrumbs from product usage, CRM, tickets, features, emails, invoices, meetings, and CS team perspectives.

Analyzing customer breadcrumbs from multiple sources, such as product usage, CRM, tickets, features, emails, invoices, meetings, and CS team perspectives, is essential for understanding customer health metrics like churn, adoption, retention, and expansion. 

It’s essential to identify the different sources from which customer breadcrumbs can be pulled. These may include product usage data, CRM data, ticketing data, feature request data, emails, invoices, meeting data, and customer service team perspectives. 

Once these sources have been identified, the next step is to create a process to filter the noise from these sources. For example, looking at product usage data can help determine if a customer is accelerating adoption, has flat usage, or is decreasing use. This can indicate whether there may be an issue with the customer’s product experience or satisfaction.

Analyzing ticketing data can provide insight into customer needs and issues, while emails, invoices, and meeting data can give more insight into customer behavior and sentiment. The customer service team perspectives will also provide valuable feedback on customer interactions. By looking at all these sources, organizations can more accurately assess customer health metrics and take the necessary steps to improve customer satisfaction and retain customers.

Once the sources have been identified and the process to filter the noise from these sources is in place, the next step is to analyze the data. This involves looking for trends, patterns, and correlations in the customer data that may provide insight into customer health metrics. For example, analyzing the product usage data may reveal that a customer is decreasing usage and may help uncover why this is happening. 

By looking at all these sources together, organizations can more accurately assess customer health metrics and take the necessary steps to improve customer satisfaction and retain customers. Analyzing customer data is a critical part of understanding customer health metrics. 

Organizations must have the tools and processes to effectively analyze customer data from different sources and take the necessary steps to improve customer satisfaction and retain customers. By analyzing customer breadcrumbs from various sources, organizations can gain valuable insights into customer health metrics and use this information to make informed decisions about their customers.

5. Monitor customer health metrics (e.g., churn, adoption, and expansion) to identify problems or opportunities for growth.

You’ll want to monitor customer health metrics such as churn, adoption, and expansion to identify problems or opportunities for expansion. 

This can be done by collecting customer “breadcrumbs,” or data points, such as their usage of the product, data in the customer relationship management system, tickets sent to the company, requests for new features, emails, invoices, meetings, and customer success team perspectives. This data should then be put into a package to track and measure the customer’s health. This includes tracking the customer’s product usage over time and looking for patterns, such as a flat or downward trend, which could indicate an issue with the customer’s health. 

Tracking customer tickets, feature requests, communications, and invoices can give insight into customer health and help identify potential problems or opportunities for expansion. Overall, monitoring customer health metrics can be an effective way to identify problems or opportunities for growth.

You can now take action based on the results of the customer health metrics. For example, if the customer health metrics indicate that a customer is at risk of churning or is underutilizing the product, then proactive action can be taken to ensure the customer’s success. This could include offering discounts, providing a free trial or extra training, or launching a customer success campaign. 

On the other hand, if the customer health metrics indicate that a customer is expanding their product usage or is highly engaged, the company can take advantage of this opportunity by introducing additional features or offering discounts on higher-tier plans. Taking action based on customer health metrics can be an effective way to ensure the success of the customer and the company. 

This is an ongoing process that requires you to continually monitor customer health metrics and adjust the strategy as needed. It is essential to keep an eye on customer health metrics to identify changes in customer engagement and quickly take action.

Customer health metrics should be monitored periodically to ensure that the company’s strategy is still effective. This could include adjusting the customer success campaigns or introducing new features as needed. Overall, monitoring customer health metrics and changing the strategy as required can effectively ensure customer success and growth.

6. Look for leading indicators such as product usage trends, ticketing performance, feature requests, communication performance, invoice performance, and meeting

Looking for leading indicators is to look for breadcrumbs left by customers that can be used to measure customer health. This can include product usage trends, ticketing performance, feature requests, communication performance, invoice performance, and meeting performance. 

It is important to have a system in place to track these breadcrumbs to gain an understanding of customer health. This can be done by capturing data from eight different sources: product usage, CRM data, ticketing, features, emails, invoices, meetings, and customer success team perspectives. By looking for these breadcrumbs, it is possible to gain a leading indicator of customer health and detect any issues or opportunities for expansion. 

While lagging indicators, such as NPS surveys, help determine a customer’s health in real time, it is even more helpful in taking corrective action before it is too late. By tracking these breadcrumbs, customer success teams can be better informed and equipped to address customer issues.

Proactively engaging with customers to identify potential issues will also provide leading indicators. By interacting with customers regularly, customer success teams can get a better idea of their experience with the product and detect any issues before they become more significant problems. 

This could include asking customers for product feedback or questions about their usage or preferences. This can also be done by engaging customers in conversations, supporting them, and staying up to date on their progress. By actively engaging with customers, customer success teams can better identify any red flags or opportunities for improvement before they become too severe. 

Another step in looking for leading indicators is to monitor customer satisfaction. Customer satisfaction should be monitored to ensure that customers have a positive product experience. 

This can be done by measuring customer satisfaction through surveys, customer feedback, and customer usage data. By monitoring customer satisfaction, customer success teams can quickly identify and address potential issues before they become more serious. This will help customer success teams to ensure that customers remain happy and continue to use the product for the long term.

A data-driven customer success program is essential for any B2B SaaS business that wants to remain competitive and grow. Companies can create targeted customer success initiatives that drive growth by leveraging data to better understand customer needs and behaviors. 

By looking for leading indicators, such as product usage trends, ticketing performance, feature requests, communication performance, invoice performance, and meeting performance, it is possible to understand customer health in real time and take corrective action before it is too late. With the right data-driven customer success strategies, businesses can significantly boost growth.

I’d love to hear how you determine your customer’s health… Leave me a comment on how it went for you, or drop me any questions you want me to answer!

Some topics we discussed include:

• Is there value in building out a customer success program? If so why
• Why is customer success being conducted in at least some instances without any science behind it
• What metrics and science to look at to ensure our customer success program works
• How to unlearn preconceived notions around customer service and success to serve customers better
• How ZapScale caters to the nuances of a particular company and their brand
• How can customer success teams reduce the time it takes to understand their customers’ health metrics and measure customer happiness
• What methods can customer success teams use to understand customer health in an SMB or midmarket context where one customer success person is handling hundreds of accounts
• How can customer success teams use data points such as product usage, ticketing, feature requests, communications, meetings, and NPS to understand customer health better
• And much, much more …

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Related links and resources

Connect with Manasij

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