Focusing solely on churn reduction does not consider your business outcomes and how these outcomes affect and are related to the customer.
Your customer success strategies need to be tailored around what your customer wants to achieve from using your product/service. And to do this, you need to use customer success vectors.
These vectors tell you where your customers are heading compared to where they want to go/their goals for using your product/service. Below, you’ll find out how to implement customer success vectors to improve the customer experience you deliver.
A vector is a measurement that has both magnitude and direction.
For instance, let’s say you move four steps forward and one step to the left. You could denote this movement using the vector (4, 1).
If you moved in the opposite direction, 4 steps backward and one step to the right, then your movement would be denoted as the negative vector (-4, -1).
Vectors are often abbreviated using algebra. For instance, vector (4,1) = V, and vector (-4, -1) = -V.
As vectors describe a movement, they are visual measures, and usually mapped on a graph. Vectors are often used to represent physical quantities such as acceleration, velocity, and displacement. How are they then useful in the world of customer success?
Every company wants predictable revenue, but most turn to new business Sales to get it. They create a goal they want to hit – essentially a made-up number the CEO or Board wants to see – and then they try to figure out how to hit that number.
The “predictable” part of all of this comes down to ensuring your pipeline is loaded with (at least) 5x more leads than your target goal so you can hit it with a 20% close rate. Math!
While that may be “predictable” in a spreadsheet, in reality, hitting that goal requires a lot of work, coordination, effort, hustle, incentives, and luck. Yet, historically, this is where companies look for new revenue by default.
That’s changing as companies realize it doesn’t get more predictable than being able to look at your existing customers, say these 100 customers will reach this Success Milestone in the next month, that milestone has a logical upsell associated with it, the value of that upsell is $1000/ARR, and the percentage of customers that should take the upsell based on their Success Vector is 90%.
That means, for that cohort, we’ll add $90k/ARR next month. Then, by combining the expansion value of all of the milestone cohorts, we can give an accurate prediction of the revenue we’ll generate from our existing customers.
That’s actual, real predictable revenue.
Historically, Customer Health Score was a Key Performance Indicator (KPI) for Customer Success, but it wasn’t giving us what we need in this new world of Customer Success-driven Growth. What needed to be done was to tore the idea of a Customer Health Score apart with the sole purpose of giving us a real way to see not just what’s happening with our customers today, but where do we think they’re going in the future.
And when you can build a revenue forecast model based on actual customer Success Vectors, then you can manage against that rather than the other direction where we have expansion quotas. We can say “according to Success Vectors, this cohort should deliver $90k/ARR in the next month.”
When you have Success Vector in place, internal expansion quotas are not needed, which means you won’t have Account Managers trying to shove products down a customer’s throat when they aren’t ready for it, don’t need it, or are otherwise not in a place where that is the logical next step.
Rather, we can say “this is the expected, logical expansion from these cohorts in the next 30, 60, or 90 days” and if we hit that, it means you simply did your job.
However, if we miss that mark, it means the customer didn’t hit that Success Milestone, because if they had, according to Success Vector analysis, they would have taken the upsell. So that’s a fail on Customer Success Management; not that they didn’t make the upsell, but because the customer who we thought would reach that milestone didn’t.
So there’s no need to quota on expansion; instead, use Success Vector-based projections to manage the success – or failure – of your Customer Success Management (including Account Managers, Expansion Resources, etc.) org.
Using business KSIs as opposed to KPIs (aka the customer health score) in customer success gives a measurement that has both a direction and magnitude, as explained:
Your customer’s desired outcome consists of two pieces of information: The appropriate experience and the required outcome.
Together these two measures make up the core of your customer success vectors and will tell you if your customer is on track or heading for the door.
Any vector needs a magnitude. You can think about the appropriate experience as a collection of measures determining – along with the required outcome – the effort needed to take a customer to their desired outcome (vector magnitude).
For instance, you can determine a customer’s appropriate experience by measuring customer satisfaction and confidence. How satisfied are your customers with you?
Here you could draw from your customer health score measures which incorporate customer satisfaction determinants, e.g. NPS score and CSAT.
If your customers are not satisfied with your current offering, this will hinder their relationship with you.
Low customer satisfaction and confidence scores mean you have work to do to establish a healthier relationship. Factor this work in during the early stages of your customer’s journey with you.
Use our Customer Feedback checklist to gauge your customer’s satisfaction and confidence level.
Vectors are visual. Visualizing your vectors helps you understand them, but how would you go about doing this?
First off, you need to understand that your customer success vectors will fall under one of four categories:
Following about two years of research and model testing, we're proud to finally release Smart Signals ✨, small logical indocators that reflect the state of each account/user within a PLG motion. Leveraging Machine Learning 🤖, yet flexible enough to be altered by customers, they eventually shape the foundation for **automatically** detecting signups that are most likely to buy, to expand, or the churn.
Whether setting up workflows for freemium and trial signups to convert more, or for paying customers to be expanding towards a higher tier, or preventing to churn, being able to compare and optimise different workflows for maximum goal conversion is pretty much on every sales and CS leader’s list.
We’ve released Inbox, a place where each platform account/user that needs supervised intervention gets a case with to-do tasks and best-next actions. Built from the ground up for sales and customer success teams, they now have the power to orchestrate outreach throughout the entire organisation... the PLG way!
Changing the way you do business, case by case.
Detect which signups are most likely to buy. Sell more with less effort.
Automatically surface product qualified leads.
Prioritize PQLs call lists and engage with quick actions.
Add tasks and full PQL context to existing CRM and other engagement tools.
Automated sales playbooks and collaborative inbox.
Onboard. Monitor. Get expansion signals. Reduce churn, proactively. Grow.
Automatically detect churn & expansion candidates.
Accelerate onboarding and product adoption.
Align activities around 360° customer view, with health and onboarding scores.
Automated CS playbooks and collaborative inbox.
Build revenue workflows, based on how people use your product.
Use machine learning to uncover new sales opps.
Add slow accounts to nurturing campaigns.
Optimize engagement playbooks for maximum conversion.
Leverage any data without needing engineering.
See which impact your product features have on revenue and churn.
Analyse feature importance, usage and impact.
Build key product metrics without SQL, nor coding.
Easily create customer segments based on any product interaction.
Comply to GDPR and CCPA.
Create your free account and start driving a product-led growth strategy with the tools you're already using.