Metrics are the lifeblood of a good CS program. They are used to track key events in the relationship with your customer – things like customer satisfaction, retention and churn rates, revenue forecasting, customer health, and time to first value.
Used properly, you can impact the outcomes of your customer and increase your business outcomes. Many of these are lagging indicators, but outcomes are already set and are no longer changeable (except for future customers).
To move into a more actionable realm. We also want to find leading indicators – things that will properly allow us to change a lagging outcome before it happens.
It is important to have both types, but organizations often find it more difficult to build strong leading metrics.
So, here are the key insights we took away from the conversation:
- Seems like everyone is defining “engagement” differently but everyone identified the need to measure it. Mostly companies were looking at engagement across a few channels:
- Engagement with marketing activities (I.e. newsletters)
- Engagement with community activities (I.e. discussions)
- Engagement with education activities (I.e. courses)
- Engagement with customer success activities (I.e. audit)
- Build an operating cadence around these metrics – meaning let’s pull the data on a regular basis, get a team of people to review it together and make sure to drive action to improve the metric over time. Without this cadence it falls apart.
- Scaled customer success initiatives are forcing collaboration on metrics with marketing and product leaders – greater transparency around a shared leading indicators to drive the right level of activities and collaboration.
Here is a free flow of notes from the conversation:
The discussion focused on leading metrics, and asked attendees to discuss two questions based on where they were in their scaled journey. They broke into the following groups:
· Not yet started on scaled success
· Just starting out in scaled success
· Midway through the scaled success journey
· Doing scaled success but struggling with aspects of it
Questions to Discuss
- What are critical leading metrics that help you understand if your scaled programs are working?
- What struggles and/or benefits have you had with this process?
Much of the conversations centered around the need to understand customer engagement at a deeper level. Identifying and recognizing what success looks like and where gaps could lead to churn were seen as potential challenges, no matter where along the scaled journey members were.
Here were some important leading metrics that were identified:
- Time to first value - measuring the change (delta) with scaled programs
Ex. Average time to first value went from 45 to 30 days with implementation
- Product Usage – identify the most valuable touchpoints focusing on actual activity, products being used, and frequency of usage.
- Are there smaller touchpoints that should be looked at in addition to the bigger ones?
- Onboarding Times – how can you increase the speed of onboarding to product adoption using effective scaling techniques?
- Support Reduction – how has scaling impacted the cost and time to support customers?
For those teams already implementing scale, here are some of their wins and insights:
- Increased efficiency and customer follow through with limited bandwidth
- You don’t need a large number of customers to scale
- Automating where you can allow you to spend time analyzing the data
- You don’t have to scale everything
- Identify what needs that human interaction and what can be automated
- Increase your ability to focus on all users rather than just those power users during onboarding which gives you a stronger user base
Some of the challenges CS teams are seeing with building scaled programs are:
- Identifying the best leading metrics to track so you understand the impact of scale and can see any gaps quickly before issues arise
- Data availability can be difficult, especially if you do not have a CS Ops team to help, which can derail your scaled processes due to inability to prove value
- Often have limited engineering resources and budget which can make it a challenge to have tech that makes this easier to capture
- Making sure you understand the balance between 1:1 and scaled needs – your program will need both to be done well, so cannot eliminate either of them
- Well-considered customer segmentation must be used to identify scale opportunities
- Poor product fit in the sales process is going to decrease the effectiveness of all programs, including scale
Here are some other musings that we heard while in the room with these leaders:
- Be sure to watch for engagement in other offerings
- Who comes to office hours?
- Who is opening emails/digital QBRs
- Time consuming to build for each customer
- QBR attendance
- Engaged with support
- Product feedback
- References
- Who is coming to training?
- How is data changing after scale is implemented?
- Monitor your monthly active user data to determine how successful your CS team is with getting customer engaged
- How often are users coming back?
- % of tickets resolved
- % of tail end clients renewing
- NPS at a segment level before and after adoption
- % of adoption of automated reports for tail end
- Conversation shift from lower to higher revenue
- Requires heavy CSM dependency, especially the relationship built between CSM and customer
