If you work in Customer Success, then you know the dread that is executive update meetings. You, of course, want to show your team in the best light but also don’t want to sugarcoat everything if there’s a problem.

Thankfully, you can let the numbers do the talking. 

In leadership and executive meetings, certain metrics are critical and tell a story well beyond the information they present. 

We’ve already collated all this into a CS leadership presentation template you can start using today. But if you’re curious about the metrics on their own, keep reading. 

Retention metrics (4 essentials)

You have to start with the money! These metrics sit at the heart of Customer Success work—protecting revenue with existing customers.

1. Net Revenue Retention (NRR)

Net Revenue Retention (NRR) includes all expansions, downsells, new customers, and churn shown as a percentage change.

‍How to calculate it: current revenue / previous period revenue turned into a percentage.

‍Example: $110k revenue this period / $100k revenue last period = 1.1. As a percentage, that’s a 10% increase (or 110% of the total) from the previous period to this period. 

2. Churn 

Churn is the money lost in the quarter.

‍How to calculate it: lost revenue / previous period revenue.

‍Example: $10k in revenue lost in the period on $100k in revenue = 10% churn.

3. Logo retention

This is the number of customers (“logos”) you have and gives an overall indication of retention in terms of actual customers rather than simply dollars.

‍How to calculate it: the number of customers (“logos”) you retained during the period divided by the total customer base.

‍Example: 9 customers at the end of the quarter / 10 customers at the start of the quarter = 90% logo retention. 

4. Logo churn 

On the flip side of logo retention, this is how many customers churned in absolute terms.

‍How to calculate it: the number of logos lost in the period divided by the total customer base.

‍Example: 1 customer churned out of 10 = 10% logo churn.

Expansion metrics (3 essentials)

The second job of Customer Success is to expand revenue—bringing those current customers on a journey of getting so much value that they simply need more of your product in some way.

1. Upsells 

These two metrics—percentage upsold overall and percentage upsold mid-contract—show how often customers purchased more of your product, whether that’s usage, seats, or another lever. It’s the human side of the story, focusing on customers rather than dollars.

‍How to calculate it: 

• Overall: number of customers with upsells divided by the number of customers overall.
• Mid-contract: number of customers with upsells mid-contract (i.e. before renewal conversations) divided by the number of customers overall.

‍Example: 100 customers overall, 14 of whom upsold, 2 of which were mid-contract

• Overall: 14 / 100 = 14%
• Mid-contract: 2 / 100 = 2%

2. Average growth

This metric focuses on the dollar growth (both in monetary and percentage forms) of your upsells. 

‍How to calculate it: the value of upsells averaged and divided by the average contract value pre-upsell.

‍Example: 3 customers had upsells

• Customer 1: $10,000 contract + $2,000 upsell
• Customer 2: $8,000 contract + $5,000 upsell
• Customer 3: $11,000 contract + $1,000 upsell

Average upsell value (AUV): (2,000+5,000+1,000)/3 = $2,667.

Average upsell percentage (AUP): AUV / ((10,000+8,000+11,000)/3) = 27.6% 

3. Upsell trends

Upsell trend is when a majority of customers who upsold did so for a common reason (usually >50% or >75%, depending on how much confidence you need).

‍How to calculate it: identify why each customer upsold—the feature they wanted or why they needed more seats (e.g. fundraising). 

‍Example: 15 customers upsold. 10 had just raised new fundraising rounds and eight noted your latest feature launch was a key reason. That gives you two trends: 66% of customers expanded due to fundraising and growth aspirations while 53% did so due to your latest feature. 

These insights are helpful for future marketing campaigns, sales motions, or customer success upsell campaigns.

Satisfaction metrics (5 essentials)

Money is the result, but satisfaction is a leading indicator of how long someone will keep paying you. Don’t sleep on these metrics—they may not seem important as long as money keeps coming in, but ignoring them could result in a lot of churns in the future.

1. Customer Satisfaction (CSAT) score

After every core interaction, you should send a CSAT score request. This is a great pulse check to see how customers feel when they communicate with you in three core ways: finishing onboarding (the portions you’re involved in), every customer success team interaction, and every customer support ticket or interaction.

‍How to calculate it: Average out scores during the period for each interaction type.

‍Example: of 150 interactions, 100 were support, 40 were success, and 10 were onboarding. 

• Average Customer Support CSAT: 95%
• Average Customer Success CSAT: 92%
• Average customer onboarding CSAT: 88%

2. Net Promoter Score (NPS)

NPS is a popular single-question satisfaction assessment that asks some variation of this question: “How likely are you to recommend this product to a friend or colleague?” A score of 0-6 is considered a detractor, a score of 7-8 is neutral, and 9-10 is considered a net promoter.

‍How to calculate it: assessments should be sent randomly to customers at various intervals to capture a more honest picture of customer sentiment. Scores are then calculated—every net promoter is a score of one, every neutral is a score of zero, and every detractor is a score of negative one. 

‍Example: 50 people selected 9-10, 75 people selected 7-8, and 30 people selected 0-6. Your NPS is promoters-detractors. That means 50-30 = 20. 

3. Referenceable customers

Going beyond NPS is referenceable customers—the people who are happy to let you leverage their name and credibility. This might be through logos on your website, talking about you being a customer on sales calls, or participating in comarketing activities. 

‍How to calculate it: the percentage of your customer base that has given explicit permission for you to reference them in public forums.

‍Example: 100 customers total, 12 of which say you can reference them. 12/100 = 12%.

4. CSM-to-Account Ratio

Understanding how many accounts each CSM is assigned to can help shine a light on challenges or reveal additional capacity you can fill without hiring. 

‍How to calculate it: take how many accounts each CSM has assigned and average it. 

‍Example: four CSMs cater to 100 enterprise accounts

• CSM 1: 20 accounts.
• CSM 2: 35 accounts.
• CSM 3: 25 accounts.
• CSM 4: 20 accounts.
• Average: (20+35+25+30)/4 = 25 accounts per CSM.

This data becomes most useful when assessing against churn—for instance, if the most churn comes from the CSM with the most accounts, it might be an indication that the CSM is being given more than they should have.

5. At-risk accounts

Understanding which accounts are at risk of churning is essential to taking remedial action.

‍How to calculate it: take note of all accounts with low health scores (whatever “low” means in your organization). Then identify the percentage of the overall customer base, the revenue those at-risk customers represent, and any qualitative trends you can identify.

Example: 10 at-risk customers out of 100, each with an ACV of $10,000.

• Percentage: 10%.
• Revenue: 10 x $10,000 = $100,000.
• Key trends example: 8 of the 10 have complained that new features never seem to meet their needs.

Customer fit metrics (4 essentials)

Sometimes customers churning isn’t a bad thing—they didn’t fit, so their churn allows you to focus resources on better-fit customers. Tracking and reporting on it will help you keep executives up to date. Running high-quality churn post-mortems using this data will help you mitigate it in the future.

1. Bad fit customers 

Not all churn is bad. If you realize a customer churned who probably shouldn’t have bought in the first place (read: your solution didn’t help their use case or needs), you want to get an understanding of that information to help sales in the future.

‍How to calculate it: of all churned customers who were a bad fit, note the number of deals and the contract value it represented.

‍Example: 10 bad-fit customers churned with an ACV of $10,000.

• Deals lost: 10.
• Contract value lost: 10 x $10,000 = $100,000.

2. Repeated product gaps 

Whether churned or not, this is the number of customers who highlighted clear product gaps that either hindered them from using the product or hindered them from getting full value.

‍How to calculate it: the number of customers who noted product the same product gaps with the contract value (lost if churned and at-risk if still a customer).

‍Example: 10 customers noted a specific feature gap that they wanted, 4 of whom churned (6 still customers), with ACV of $50,000, out of 100 total customers.

• Total: 10 customers.
• Percentage: 10 / 100 = 10%.
• Lost revenue: 4 x $50,000 = $200,000.
• At-risk revenue due to gaps: 6 x $50,000 = $300,000.

3. Opt-out clause usage

If your contract has any opt-out clauses (for instance, no fee cancellation within the first 30 days), track how many people use it.

‍How to calculate it: the number of deals (as a percentage) and revenue lost due to opt-out clause usage.

‍Example: 10 customers used the opt-out clause out of 50 total, with an ACV of $25,000.

• Usage: 10 / 50 = 20%. 
• Revenue lost: 10 x $25,000 = $250,000.

4. Drivers of churn 

Whenever a customer churns, ask them to identify the reason(s) behind their decision. Collate that data and use it to inform drivers of churn. A few drivers of bad churn are: bad-fit, outside your ICP, the customer had a re-org or acquisition, product gaps, leadership turnover, the customer didn’t see value, the customer shifted business priorities, or there were multiple bugs/issues with your platform.

‍How to calculate it: collate all reasons given for churn, count the number of times each reason was given, and divide it by the total number of churned customers to get a percentage.

‍Example: 10 customers churned. 3 cited product gaps, 6 cited shifting priorities, and 1 was a bad fit. 

• Product gap: 3 / 10 = 30%.
• Shifting priorities: 6 / 10 = 60%.
• Bad fit: 1 / 10 = 10%.

Let data start the story, not end it

Executives want to know the raw numbers behind customer health and churn. But they also want to know what happens next. Namely: what will the CS team do to keep retention, increase expansions, and mitigate churn? There are a lot of paths to take, so let data start your story and set the stage for a broader conversation about what you’re planning for the future. 

And if you’re stuck on how to get this data into presentation form, use our free deck template.