CS Signals Playbook

Playbook Overview
When should you run this playbook?
You have a fully-scaled CS or Customer Engineering (CE) team.
You are able to track and measure customer engagement with CS/CE.
Who to target?
Current customers who are in frequent contact with CS to troubleshoot or resolve issues.
Playbook goal?
Retain revenue through proactive churn prevention.
Responsible team(s)?
  • Customers who are having a frustrating product experience are likely not seeing value and are at risk for churn.
  • These customers often reach out to engage CS for assistance before reaching a breaking point and churning off the product. 
  • By monitoring the frequency of CS outreach for each account, CS can proactively intervene to offer bespoke support before a customer turns into a detractor.

What is the key signal?

Put simply, frustrated customers are at high risk of churn. While some customers stall out without asking for help, many will begin engaging with CS more and more frequently when they’re beginning to hit roadblocks. For this playbook, the frequency with which a specific account engages with CS is the key signal to identify churn risk.

What is the goal?

Retain customers who are having a suboptimal product experience. Use CS engagement rates to identify accounts that aren’t experiencing value and could become detractors.

When should you use this playbook?

A CS signals playbook works best at a company that has robust customer support, customer experience, or customer engineering teams. To successfully run this playbook, these teams should have the bandwidth to provide limited-time white glove support to identified accounts who may be stuck or frustrated. Often these accounts need temporary assistance improving their processes, integrating the product more deeply, or more comprehensive training for their team.

Try This Playbook

Step 1

Establish baseline behavior. To understand what amount of CS outreach is normal vs. “at risk” behavior, it can help to review how frequently accounts who have churned engaged with CS compared to satisfied customers. This metric is typically best represented by the number of contacts during a period of time, for example, >5 support tickets in a 60-day period.

Step 2

Surface account-level engagement metrics. In order to spot at-risk accounts quickly, your CS team will need a report or view to monitor engagement metrics. This report can be built in a tool like Tableau or Looker, or data can be integrated directly into Pocus so accounts automatically surface when they hit the engagement threshold. 

Step 3 

Intervene when an account hits the CS engagement threshold. Once you’ve established an engagement threshold and have insight into which accounts have reached that critical point, it’s time to take action. Review the communications between the account and CS to better understand the issues they’ve been running into, then proactively reach out to the main points of contact at the account and offer bespoke support. Taking a customer-focused, consultative approach will help the account see you as a partner dedicated to their success rather than a frustrating tool they aren’t getting value from.

Enable this playbook in Pocus

  1. Connect your relevant data sources.
  2. Select your goal (in this case, Revenue Retention).
  3. Build your playbook based on the signal (trigger) and actions outlined above.
  4. Run the playbook by rolling it out to the relevant members of your team.
  5. Iterate over time based on reporting and results. You may find ways to improve this playbook’s effectiveness beyond what we’ve outlined here!
About the author
Alexa Grabell
Co-Founder & CEO at Pocus

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