The deal is signed, the ink is dry, the money is in the bank.
Congrats, you've closed a deal.
But in many ways, this is just the beginning. In today's SaaS world, the customer experience is the key to maximizing your revenue.
Today, we're going to talk about what happens after a deal is signed.
The revenue engine would not be complete without your post-sale team - the team in charge of what happens after a deal is closed - including implementation, customer success, and support.
Customer success managers are especially important in recurring revenue businesses because they can go through the upsell and cross-sell motions. Most importantly, they prevent churn, so your revenue returns year-over-year.
Revenue Operations professionals worldwide know that each revenue-generating team is essential, and we shouldn't forget about Customer Success (CS).
But what can you look out for as you build your next (revenue) engine diagnostic test?
Just as with a sales rep scorecard, you can use metrics to create a customer success scorecard.
Regardless of how your post-sale team is structured, you'll want to include these metrics in your scorecard:
Each of these metrics is directly impacted by how a customer experiences the handoff from sales.
Getting a new customer connected with their customer success manager, provisioned an account with the correct features and seats, and an open line of communication with their onboarding team is crucial in those first days, minutes, and hours after a customer signs.
Be more confident in pricing decisions, have a more structured approval process, increase deal velocity, and align your teams.
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If you have a business model with upsell and cross-sell motions, you'll want to include these metrics in the revenue section of your scorecard.
Here is how the two differ.
Measuring the number of upsells and cross-sells over a period can indicate how effective your team is at expansion - generating more net new revenue through your existing customer base.
With RevOps powerful agreement builder, CS and other post-close teams can easily amend contracts for increased LTV and revenue opportunities.
You can look at the number of upsells and cross-sells generated in a year and the win rates.
Remember the formula for win rate?
Here it is: closed deal/total number of qualified deals created.
This is another place in your revenue engine for a Deal Desk Framework to make its appearance. When it comes to generating quotes, obtaining approvals, and streamlining another GTM motion, a Deal Desk framework is critical.
Two other important revenue metrics are Churn Rate and Average Revenue Per Customer.
You may hear the word churn a lot. If you are relatively new to Revenue Operations or recurring revenue industries, it simply means the number of customers who leave and don't come back; they churn.
To calculate your Churn Rate, you can use this formula:
Number of lost customers/total number of customers in a given period = Churn Rate
A few things to keep in mind when measuring your churn.
As someone in Revenue Operations, it's your job to steward data.
And data is only as good as your definitions. That is, everyone should align on what period of time you'll measure churn rates and how to define lost customers.
It will help your revenue leaders understand where the leaks in the revenue engine are and develop strategies for customer retention.
Average Revenue Per Customer might sound like a very straightforward metric, but it's super important.
Average Revenue Per Customer (ARPC) can be calculated as:
Total Revenue / Total Number of Customers = Average Revenue Per Customer
It's essential to use this metric to identify cross-sell and upsell opportunities. Keep an eye on the metric to see how the Average Revenue Per Customer goes up.
What would the most efficient CS team in the world look like? The Average Revenue Per Customer goes up, and the number of customers stays the same.
Talk about a revenue-generating engine!
Important metrics to measure to see if your CS and support team are triaging requests and managing existing customers well are Days To Onboard, NPS, and CSAT.
I like to include days-to-onboard because this is a critical time for your customers. The longer or more disjointed the process, the longer it will take your customers to get to their aha moment.
The longer the time to value, the lower the likelihood they'll renew. Before you know it, there is that sneaky leaking revenue again.
The entire onboarding process will also impact NPS and CSAT metrics.
And, as a bonus for you fellow Revenue Operations professionals, you can help your CS teams optimize the processes and systems to ensure a smoother customer experience.
Days-to-onboard can be measured anywhere - in a CRM, project management tool, a google sheet - the key, as with any other metric, is to make sure everyone understands when the counter starts.
And who is responsible for the accuracy of the data point. If you are using Salesforce or HubSpot, you can date stamp fields and calculate the number of days between.\
An important exercise when you first develop your scorecard is baselining.
Some of you may be starting from scratch, so start gathering the data, then look for trends.
You'll be able to identify the average number of days to onboard, and you can look at these numbers by different account segments. It will help determine which CSMs have accounts with onboarding taking too long.
CS leaders can do a deep dive with the RevOps team to see a system, process, or enablement issue.
NPS and CSAT have been around for a long time. NPS, or Net Promoter Scores, are measured with survey data.
You've probably seen this question or variations of it:
On a scale of 0-10, how likely are you to recommend us to friends, colleagues, or business associates?
Based on the answer, they'll land in one of 3 categories:
Promoters with a score of 9-10, passives with a score of 7-8, and detractors with a score of 6-0.
Net Promoter Score (NPS) can be calculated as:
(% Promoters - % Detractors) * 100 = NPS
As you think about adding this metric to the scorecard, you can look for CSMs who have low NPS scores across their accounts.
How many promoters vs. passives vs. detractors does a CSM have?
You'll also need to keep in mind some best practices around creating surveys, such as your sample size. Trying to get as many customers as possible to answer the NPS survey will increase accuracy when representing your entire customer base.
Lastly, you have the Customer Satisfaction Metric.
Industry benchmarks for CSAT scores. Source: American Customer Satisfaction Index.
Revenue Operations can set up processes to automate the escalation as well if you have high-risk accounts. Waiting until then to do a scorecard review is too late.
CSAT is another metric you'll need to use a survey to capture.
Customer Satisfaction Score (CSAT) is the measure of how satisfied your customers are on average.
There is a bit of creativity involved in this part. However, it should include some questions about how satisfied you are with the product/service you received with a rating of 1-10.
Your CSAT score ranges from 0-100. Then, the calculation for your CSAT score would be:
(Number of satisfied customers / Total number of responses) * 100 = CSAT
For example, if 62 of your 100 responses have a rating of 4 or 5, your CSAT score would be 62.
Well, there you have it. You have a framework to measure the effectiveness of your revenue engine.
It's time to close the hood for now.
Remember that your CS scorecard is tool agnostic, you don't need to create a dashboard with fancy components (although it helps with visualization). The essential things are defining metrics for your business, enabling your systems to gather data, and enabling your GTM leaders to prevent pesky revenue leaks.
