It’s no secret that the highest growth area in the technology sector is the subscription-based SaaS business model. With the SaaS market reaching an exponential 18% annual growth rate and 99% of businesses using one or more SaaS solutions this year, the need for SaaS businesses to track customer performance metrics has become a hot topic for tech investors.

From the smallest start-ups to behemoth ERP SaaS vendors, customer churn is a core metric for executive teams and investors assessing the health of a subscription-based business. In a world where customer experience is the lifeblood of a business, customer churn analysis allows companies to proactively manage the success of their offerings.

This is done by maintaining stronger margins from reducing the cost of new customer acquisitions and building more consistent forecasts for their investors.

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Why Customer Churn Matters to SaaS Businesses

One of the main areas of interest for subscription-based and SaaS companies is optimizing the customer experience. Especially in the tech space, there is often a direct correlation between the valuation of a company and the ability to consistently grow and retain highly satisfied customers.

In an industry where start-ups and small SaaS businesses are typically designed with exit strategies in mind, having a firm hold on customer churn and retention is critical to their growth and stability.

In fact, even in a post-acquisition reality, Private Equity firms and Acquisition-centric technology companies heavily leverage customer churn metrics for future acquisitions and within their current portfolios to demonstrate value to their shareholders.

Although there are some fundamental metrics for measuring customer churn, depending on the business model and products sold, the benchmark for an acceptable churn rate still varies widely. One common criteria that will impact churn rate is a product’s “stickiness”.

The stickiness factor defines how easy a customer can drop the SaaS product they are currently using. SaaS product stickiness is especially impactful in the B2B world where the criticality of these solutions will vary in their function.

Take the example of an ERP system typically purchased as 3-year contracts versus a task management solution purchased on a month-to-month basis. Once a business invests time, money and resources in an ERP system, product stickiness is extremely high. Even unsatisfied customers need to heavily consider switching solutions which will highly impact their business.

On the other hand, a task management offering can more easily be decoupled from the business and be replaced with a multitude of solutions that can deliver the same value to the customer with little to no impact on operations.

Hence, the variation in acceptable customer churn rate metrics of 5%-7% in the enterprise software space versus add-on Saas solutions which can reach upwards of 50% churn rate.

All this to say, customer churn and retention matters and for subscription-based companies that live and die by these metrics, the ability to forecast revenue and implement effective growth strategies are intricately tied to the Customer Lifetime Value (CLV) that drives their business decisions.

The Challenges with Customer Churn Data

There are many challenges that are associated with developing a customer churn model from effectively extracting historical data to feed your model to more difficult challenges of pinpointing customer behavior patterns that trigger churn.

With the rise in Artificial Intelligence and Machine Learning, powerful predictive analytic models have entered the market, informing some subscription-based businesses in churn prevention; they’re highlighting customer behavior patterns on application usage and external market conditions, which can impact the customer experience.

Although AI and ML have their merits, most subscription-based and SaaS organizations have latched on to more attainable methods in tracking the success of their customer experience by implementing the ubiquitous Net Promoter Score (NPS) methodology.

This lets them capture customer sentiment and fundamental customer churn metrics specifically designed to gauge the health of their employed business model.

KPI Basics of Customer Churn

Although the extent to which subscription-based companies develop their churn models varies greatly, most businesses will agree that a good starting point begins with implementing some basic churn calculations by benchmarking customer contracts against industry-standard churn metrics.

In order to do so, here are some of the main customer churn KPIs common to most subscription-based and SaaS businesses:

Customer Churn Rate (CCR)

The rate customers stop doing business with you. The typical formula would be:

CCR = number of customers churned - (customers who joined and churned) - (customer who churned & returned) in the defined period / number of customers at start of period.

Monthly Recurring Revenue (MRR)

The percentage of lost monthly revenue from downgrades and cancellations in a given period. This is typically calculated as both Gross and Net Revenue, an essential metric to evaluate the financial state of the business. Typical formulas are:

Gross MRR = (Churned MRR + Downgrade MRR / MRR at the end of the previous month) * 100
or
Net MRR = (Churned MRR + Downgrade MRR – Expansion MRR) / MRR at end of last month

Annual Run Rate (ARR)

Forecasts future earning revenue based on historical MRR assuming no changes in churn and expansions. Typically the formula would be:

ARR = revenue in period X * Number of periods of X in 1 year

Customer Retention Rate (CRR)

Measures the number of customers a company retains over time. Typically the formula would be:

CRR =

[(number of total customers at end of period X - number of new customers added within period X) / number of existing customers at start of period X] * 100

In addition to churn specific KPIs, subscription-based companies further analyze the state of their customer base by calculating periodic and long term value and cost to get a fuller picture of the health of their business.

Popular SaaS KPIs to consider include Customer Lifetime Value, Customer Acquisition Cost, CAC:LTV Ratio, Net Promoter Score, Payback Period, Annual Contract Value, among others…

Leveraging NetSuite ERP to Calculate Customer Churn

Depending on the modules you have included in your NetSuite ERP instance, the challenges in calculating customer churn will vary.

It’s not uncommon for SaaS or subscription-based customers to initially implement NetSuite’s Financial First edition along with Contract Renewals. This does not include the more comprehensive subscription billing functionality (offered as a separate module with SuiteBilling) or strong recurring revenue management capabilities (typically supported by NetSuite’s Advanced Revenue Management module).

For many businesses, NetSuite is initially implemented for its powerful GL and Back Office capabilities.

Nevertheless, an ERP system remains the primary source of truth that needs to feed an organization’s churn analysis model with the necessary customer, contract, revenue and cost details to effectively track customer churn and retention.

More importantly, the flexibility in the format and calculations to be delivered to stakeholders are a necessary requirement to these businesses. Depending on your role, data visualization of these KPIs will vary in their level of granularity and visual depiction.

As is the case with most ERP systems, creating tabular views through NetSuite’s popular Saved Searches are great from an operational perspective, however strategic dashboards, scorecards and graphs can be limited when sharing these mission-critical KPIs to the executive teams in these organizations.

In order to get the most optimal NetSuite data for your customer churn reports you may want to ask yourself the following questions:

Does NetSuite house all the customer churn data necessary for effective reporting?

It’s not uncommon to have contract renewal details in a separate CRM or Subscription Billing system that need to align with your ERP figures. Evaluating a data warehouse solution that can provide more flexibility on all fronts should be considered.

What metrics do you need to track and in which formats?

Customer churn and retention calculations can get quite challenging to generate in NetSuite due to the complexities of mining historical data for forecasting and the calculation of period-specific and subsidiary-specific data captured in the system.

Not to mention, throwing in multiple currencies and consolidation into the mix, which can make report development and data visualization options an effort beyond the out-of-the-box capabilities available in standard NetSuite.

To script or not to script? That is the question.

NetSuite is a super powerful platform that allows customers to address the reporting complexities of customer churn by writing scripts that can, in most cases, get you to where you need to be.

That being said, it is worth running a ROI analysis to evaluate the cost of a custom scripted solution you will need to maintain versus a Analytics offering built for complex reporting often demanded by customer churn analysis.

To learn more about how NetSuite customers can benefit from a comprehensive business intelligence and data visualization solution facilitating your customer churn needs, contact GURUS Solutions today.

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NetSuite ERP for Customer Churn

Why Customer Churn Matters to SaaS Businesses

The Challenges with Customer Churn Data