Srinivasan Shanker, Director of Customer Onboarding at Freshworks, joined Srikrishnan Ganesan, CEO of Rocketlane, to discuss some of the key customer onboarding metrics and how you can measure them in this edition of Preflight's Office Hours session.
This post is a compilation of key takeaways from the session.
Onboarding is a journey.
At the start of their onboarding journey, any customer will have a destination or outcome in mind. It could be more revenue, margins, efficiency, regulatory norms, or customer experience.
They typically start their journey with a vendor involved. The vendor paints a picture for them and sells value. Everything is rosy in the initial stages. Things get messier once the customer signs the contract.
Onboarding is akin to a flight itinerary that starts from point A and goes to point B with multiple hops in between. There might be layovers and other agendas on the way. You need to plan for your food, figure out whether you need to take an RT-PCR test, and everything has to be planned well before departure.
Similarly, onboarding is a journey with several milestones involved. And it is essential for everybody involved, especially the professional services team and the customer onboarding team, to plan this journey in the best possible way.
Maintaining strong customer "health" can help with expansion conversations
Customer Success teams often measure a customer's health after they’re onboarded. But we recently found out that there could be considerable upsides to measuring a customer's health from the very beginning.
If you feel like the customer is getting wowed through the initial partnership, there's potential to have expansion-related conversations even while the onboarding process is happening.
If your customer thinks that things are on track and moving beautifully and everything is professional and well set up, their confidence in you as a partner is sky-high. And if the health of that partnership is determined to be good, it's an opportunity for your CS team to increase NRR right there rather than waiting for onboarding to complete and go to the next step.
Metrics, KPIs, and OKRs, although different, are broadly used interchangeably.
Metrics are just a point-in-time measure of how things currently stand. For example, your Net Promoter Score for a particular engagement is 4.5 out of 5. This is only a measure of the current state and doesn’t work as a metric in isolation: you could have been at 4.9 or 2.6 before.
To understand KPIs (key performance indicators), let's take Customer Health Score as an example.
Our company wants us to keep customer health score at around 80%. If that is the metric our organization decides upon, we should always aim to be above 80%. Essentially, KPIs are indicators of how a particular metric is performing.
Next, we have OKRs (Objectives and Key Results). To measure OKRs, you start with an initial state and try to get to the desired state.
To reduce the Time To First Value by X %, the first step would be measured. Today, it might take 25 days for a customer to see the first value. If I want to reduce that by 10%, I'd have to reduce the time to 22.5 days.
To make critical business decisions based on metrics, you would ideally need a combination of all these measures to truly understand how well you’re performing.
When people talk about indicators, there's always confusion around whether the indicator is a leading one or a lagging one. So, let us clear some myths around it.
As the names suggest, these are indicators telling us what is happening or has happened.
Leading indicators can always help you predict an outcome and can help you plan/course correct accordingly. While lagging indicators are typically used from a business context, which shows the current state of the business. You cannot undo it, unlike leading indicators. For example, a company's quarterly results or the churn rate for the previous year are lagging indicators. While brand recognition, growth in new markets, or sales channels are all examples of leading indicators.
Leading indicators are generally harder to identify and implement compared to lagging ones. But they help you correct your course and prevent escalations when you keep an active eye on them.
So the idea behind sharing these metrics is twofold. One is to share some of the standard metrics that all of us could be tracking for onboarding. Of course, which of these you end up tracking depends on your maturity as a team and a company. Some of them may not be practical at a particular stage.
At the same time, it's good to know what metrics you could be measuring. And the idea was to create these different buckets into which you can look at metrics around onboarding.
It facilitates questions such as, "Am I measuring more on quality? Am I doing enough on the outcome?". You want to strike a balance with all these buckets.
By quality, we mean both the experience your team delivers and the consistency with which they're doing the work. The goal with these metrics is to determine if you could be performing much better than you have.
For example, one of the items we have here is Escalations Logged. As you're going through the different phases in onboarding, are there tickets raised by the customer saying they have a problem with how some module was configured?
Could there have been fewer tickets if you delivered a better experience in one or more phases?
The second bucket we have listed some metrics under is time and effort. These metrics help you understand how much time and effort you invest into each customer.
For example, Time To First Value and Time To Total Value are measures that tell you when you managed to start delivering value.
Let's say you run a service that provides chatbots to customers. And let's say it starts deflecting 10% of the conversations coming into your help desk in a month. That might not be the ultimate goal, but it's still some value that you started delivering pretty fast. How do you orchestrate a journey that optimizes for a faster first value and still ensure that that value is significant?
The next bucket is advocacy and engagement. These metrics measure customer loyalty and satisfaction. Are your customers engaging with your surveys? Are they giving you high ratings?
Collecting public testimonials from customers around your implementation and onboarding experience could also help get the word around. Because it is not all just about the product, right? It would help if you got to a place where you can collect those testimonials as it reflects that you're doing a great job.
We added Customer Engagement Rate to the list. What percentage of your customers are highly engaged? How many of them are proactive about their onboarding and implementation? What percentage requires a constant nudge from your side to get things done? And what percentage of them are outright abandoning the whole project?
Adoption & Outcomes
And finally, we have Adoption and Outcomes. Ultimately, if you've done all the hard work, and it's not led to tangible outcomes for your customer and actual adoption, then having all these measurements isn't helpful.
Here are a few things we recommend on that front.
There are promises that you make, from a scoping standpoint, early on during the journey and what was ultimately delivered. It could also be a genuine ROI commitment like, "Hey, we will deflect 40% of conversations using our chatbot."
So did you manage to get there by the end of onboarding? Or did you get to 20% during onboarding?
As mentioned earlier, the customer's health is usually a post-onboarding measure. But we'd recommend doing one pre-onboarding, too, to bring together information like, what is the customer sentiment during onboarding? What percentage of the promises have been delivered? What ROI has been realized? And using a combination of metrics like these to put together customer health scores.
You have a happy, healthy customer coming out of onboarding; what can you do more with that customer to ensure a great relationship from that point?
For a detailed breakdown of all these onboarding metrics, click here.
So there are multiple levers that we thought through.
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