gross revenue retention

7 Data-First Ways to Get Close to Your GRR Goal in 2024

This blog covers why Gross Retention Rate (GRR) matters for CS teams more than ever and the role clean data plays in achieving GRR goals.

As the year comes to a close, revenue teams across companies are focused on planning their goals for the next year. All efforts are diverted towards bettering this year’s number. The idea is to bring in more and more revenue to the organization.

However, is bringing in fresh revenue the only way to increase the overall numbers? What about the existing revenue? What about the existing customers?

It is pivotal for businesses to focus as much on existing customers (if not more) as they do on bringing in fresh deals. Customer retention can not only help with gross revenue retention but is also a viable candidate for upselling your product and services.

To measure and improve gross revenue retention, companies often track a metric known as Gross Retention Rate(GRR). In this blog, we examine what Gross Retention Rate is, why it is important, and how you can improve it with data in 2024. 

gross revenue retention

What is the Gross Retention Rate?

Gross Retention Rate (GRR) is a metric used by businesses to measure the percentage of customers or users that a company retains over a certain period. Gross Retention Rate tells a company how many of their customers stick around over time. 

The Gross Retention Rate shows the percentage of customers they keep without including new ones they get. The gross retention rate doesn’t factor in additional considerations such as new customer acquisitions or reactivations.

Here is the formula for Gross Retention Rate: 

This rate gives a general view of how well a company retains its customers without accounting for new customers gained during that same period. A high gross retention rate generally indicates that the company is doing well in keeping its existing customers or users.

Why is GRR Important?

GRR holds significance for businesses with repeating income models such as SaaS companies. It serves as an indicator of a business’s revenue stability and reflects customer satisfaction levels.

GRR can demonstrate several aspects of a business :

  • Client retention: The effectiveness of a business in retaining its customers
  • Financial consistency: The dependability of a business’s income stream
  • Client contentment: The satisfaction levels of existing customers
  • Customer attrition: The number of customers who departed or lessened their engagement with the business

GRR can additionally signal the potential for increased revenue without altering user spending. A high GRR suggests robust customer loyalty and contentment, whereas a low GRR indicates potential dissatisfaction among customers.

Gross Revenue Retention’s significance goes beyond customer retention. GRR also serves as a crucial indicator for investors, influencing their perception of a company’s growth potential and stability, making it a pivotal metric in shaping business strategies and ensuring sustained success.

Importance of Data in Measuring GRR

Data plays a crucial role in understanding and calculating the Gross Retention Rate (GRR) accurately. Here are some key aspects of why data is essential for GRR:

1. Accurate Measurement

GRR calculation relies on precise data about the number of customers or users at the start and end of a given period. Accurate data ensures the reliability of the calculated rate.

2. Insights into Customer Behavior

Data used for GRR analysis can offer insights into customer behavior, such as how long customers stay with the company, patterns in retention, and potential reasons for churn.

3. Identifying Trends

Through data analysis, trends in retention rates can be identified. This helps businesses understand if there are certain periods, features, or services that impact customer retention positively or negatively.

4. Decision Making

GRR data aids decision-making processes within companies. It helps in determining the effectiveness of retention strategies and guides adjustments or improvements to those strategies based on trends observed in the data.

5. Comparison and Benchmarking

Data on GRR allows companies to compare their retention performance against industry standards or competitors, enabling them to set realistic goals and benchmarks for improvement.

6. Predictive Analytics

Historical data on retention rates can be used in predictive models to forecast future customer retention, allowing businesses to anticipate potential churn and take proactive measures.

Now that we have analyzed the role of data in measuring GRR, let’s have a look at how using data can help accomplish GRR goals.

The Link Between Clean Data and GRR Goals

Tracking metrics associated with Gross Retention Rate (GRR) is essential for businesses as it serves as a compass for understanding customer loyalty, revenue stability, and overall business health. 

GRR, standing for Gross Renewal Rate, holds pivotal importance within Customer Success (CS) teams. However, achieving GRR objectives necessitates a keen focus on the quality and utilization of data housed within foundational systems like Customer Relationship Management (CRM).

Presently, many CS teams grapple with labor-intensive processes to input account data into CRMs. Unfortunately, this data often suffers from incompleteness, inaccuracy, or rapid staleness, rendering the insights drawn from it inadequate for pinpointing account nuances that might lead to churn. Consequently, GRR targets become challenging to attain.

Yet, the advent of AI presents a transformative solution to this data predicament. By addressing data issues at their core, AI technologies enable the utilization of clean, comprehensive data to drive intelligent decision-making.

By harnessing accurate and complete data within your systems, you unlock a multitude of capabilities:

1. Automate the Documentation of CSM Activities

The existing landscape of Customer Success Management (CSM) tools often suffers from an information deficit due to the reliance on manual activity logging by CSMs. By integrating automated systems that capture crucial data points such as contacts, emails, and meeting details, organizations can usher in an era of data-driven decision-making. 

This automated documentation not only saves time and effort but also enriches the repository of insights essential for effective customer management strategies.

2. Strategize and Oversee Executive Engagement

The strategic involvement of executives and key stakeholders, especially during Quarterly Business Reviews (QBRs), holds paramount importance in customer relationship management. Keeping abreast of upcoming QBRs, monitoring attendee lists, and ensuring timely and inclusive invitations to executives and pivotal stakeholders are fundamental to maintaining robust relationships. 

Tracking the completion status of QBRs and monitoring stakeholder attendance empower decision-makers with comprehensive insights crucial for strategic planning and relationship nurturing.

3. Encourage Holistic Engagement with Key Stakeholders

Often, within customer accounts, over-reliance on a single champion can inadvertently restrict engagement to a narrow scope, leading to overlooked perspectives and potential risks. 

Encouraging and fostering consistent engagement across the entire committee of key stakeholders mitigates this risk. Observing and actively ensuring balanced interaction and communication with each crucial stakeholder fortifies relationships, broadens perspectives, and diminishes reliance on a sole point of contact.

4. Mitigate Churn Risk Amid Champion Turnover

Champion turnover within customer accounts poses a significant risk, potentially impacting the continuity and stability of relationships. Immediate notification of such transitions equips organizations with proactive measures to address potential disruptions. 

Leveraging the insights provided by, particularly in deciphering relationship dynamics and engagement patterns, facilitates the identification and cultivation of alternative champions, ensuring continuity and resilience amid transitions.

5. Identify Single-Point-of-Contact Accounts

Identifying customer accounts heavily reliant on singular points of contact serves as a proactive indicator of potential churn. 

Anticipating and swiftly addressing accounts with limited interaction breadth is crucial. Dispatching early warnings via communication channels like Slack, MS Teams, or email to relevant teams ensures swift and targeted action, potentially averting churn risks and preserving valuable relationships.

6. Prioritize Customer Engagement Effectively

Empowering Customer Success Managers (CSMs) with tools and insights to prioritize engagement effectively is pivotal. Equipped with indicators guiding optimal timing and allocation of resources, CSMs can focus efforts on the right accounts and individuals. 

Leveraging these leading indicators enhances the efficiency of customer retention strategies, enabling organizations to maximize impact and value through strategic and timely engagements.

By leveraging AI-driven clean data, companies can not only enhance their GRR but also revolutionize their approach to customer engagement and retention strategies.

Improving the metrics associated with customer retention directly influences the Gross Retention Rate (GRR). Lowering the rate at which customers leave, boosting engagement and satisfaction, and tailoring strategies to specific customer segments result in a more loyal customer base. By focusing on these metrics and continuously refining strategies based on insights gained, companies can steadily increase GRR, signaling stronger customer relationships and sustained business growth.

Enhancing the measurement of your Gross Retention Rate (GRR) throughout the revenue funnel becomes more precise when you optimize your operations. Establishing a strong Revenue Operations (RevOps) framework is the initial step toward accurately measuring these Key Performance Indicators (KPIs) and ensuring their alignment. Solutions such as Nektar are designed to assist in constructing this framework efficiently.

About Nektar 

Nektar is an AI-driven platform designed for optimizing revenue operations. While your organization might currently have visibility into 10% of your customer base, Nektar empowers you with insights into the remaining 90%. 

By leveraging Nektar, you can:

  • Fill in the gaps within CRM data, both historical and ongoing, through AI-driven time travel.
  • Identify new opportunities and potential leads originating from sales interactions and changes in key client relationships.
  • Utilize Slack or MS Teams as an early warning system, actively mitigating potential revenue risks.
  • Rectify your CRM data to enable the utilization of advanced AI capabilities for your Go-To-Market (GTM) strategy.

Nektar helps customers reach their Gross Revenue Retention (GRR) goals. Nektar can help streamline operations to measure GRR more clearly across the revenue funnel.

To explore Nektar’s extensive capabilities and safeguard your hard-earned revenue, get in touch with our team of experts today.


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