The “right” KPIs to track in After-Sales?

By /
devops, business, process improvement, development, it, operation, processes, incentives, effectively, efficiently, collaboration, laptop wallpaper, hd wallpaper, quality control, software, speed, delivery, teamwork, free background, art word, wallpaper hd, plan, to build, cool backgrounds, continuously, feedback, mac wallpaper, integration, application, apply, control, operate, beautiful wallpaper, endless loop, loop, gear, arrows, representation, information, software development, 4k wallpaper, symbol, symbolic, design, windows wallpaper, automation, background, concept, communication, maintenance, developer, computer, company, tool, desktop backgrounds, infrastructure, organization, agile, agile it, parts, to qualify, platform, program, it standard, framework, wallpaper 4k, code, free wallpaper, version management, kpi, key performance indicator, releases, static, dynamic, toolchain, binary, full hd wallpaper, formats, itil, configuration, monitor, customers, into each other, table, notebook, screen, eight, swinging, blue, 4k wallpaper 1920x1080, coloured, office work

What are the right KPIs and metrics to track and measure your after-sales performance on? Having driven a complete overhaul of the after-sales organization and strategy recently for a scale-up this was one of the questions I was confronted with. Here a solid framework of post-sales KPIs.

Classical and well-known KPIs are:

  • Net Revenue Retention (NRR) measures the percentage of recurring revenue retained from existing customers over a specific period, calculated annually or quarterly.
    • The formula: NRR = (Starting Revenue + Expansions + Upgrades – Downgrades – Churn) / Starting Revenue × 100.
    • Above 100% indicates your existing customers are growing in value faster than you’re losing revenue, showing strong product-market fit and growth efficiency
      …
  • Gross Revenue Retention (GRR) measures the percentage of recurring revenue retained from existing customers over a specific period, excluding any expansion revenue. It measures your ability to prevent churn and contraction, independent of growth initiatives
    • The formula: GRR = (Starting Revenue – Downgrades – Churn) / Starting Revenue × 100
    • GRR caps at 100% (you can’t retain more than you started with when expansion is excluded). You want above 90% of GRR ideally.
      …
  • Time-to-Value (TTV) measures how long it takes for a new customer to realize meaningful value or achieve their first significant outcome from your product or service.
    • The formula: Is very dependent on the business. It can be time from onboarding start to first successful report generated, first workflow automated, first campaign launched, use of x% of your features, or a core feature etc.
    • This KPI helps reduce churn during the critical initial time of the the relation
    • In a payments service context I turned this into “TTR – Time to Revenue” so the time until the first direct debit run was executed or the first product was sold online using our payment solutions.
      …
  • Churn Rate measures the percentage of customers or revenue lost over a specific period, typically calculated monthly or annually.
    • The formulas:
      • (a) Customer Churn Rate, i.e. the percentage of customers who cancel or don’t renew: (Customers Lost During Period / Customers at Start of Period) × 100
      • (b) Revenue Churn Rate, i.e. the percentage of recurring revenue lost from cancellations and downgrades: (MRR/ARR Lost During Period / MRR/ARR at Start of Period) × 100
    • Churn rate majorly impacts customer health and revenue. Churn is a topic that needs to be looked at at company level, as there are many factors impacting it.
    • There is also voluntary churn (customer actively cancelling) vs. involuntary churn (payment failures, expired cards)
      …
  • Customer Lifetime Value (CLV or LTV) is a metric that estimates the total net revenue or profit a business can expect to generate from a customer over the entire duration of their relationship.
    • The formulas: Simple CLV: Average Revenue Per Customer × Average Customer Lifespan or More Precise CLV: (Average Revenue Per Customer Per Period × Gross Margin %) / Churn Rate
    • CLTV can guide how much you can spend on acquiring a new customer, how much effort you put into retaining a customer, it can help in pricing strategy and investment decisions.
      …
  • Annual Contract Value (ACV) measures the average annualized revenue generated from a single customer contract, excluding one-time fees.
    • The formula: For multi-year contracts ACV = Total Contract Value / Number of Years
    • This metric helps you segment, plan resources, forecast and measure the sales performance of your after-sales team (executed by your CSMs, your renewals managers or your account managers)
      …
  • Annual Recurring Revenue (ARR) is a metric that measures the annualized value of all recurring revenue from active subscriptions at a specific point in time. Respectively MRR measures monthly subscriptions.
    • The formulas: For monthly contracts: ARR = MRR (Monthly Recurring Revenue) × 12, For mixed contracts: ARR = Sum of all annualized contract values currently active
    • While this is a company metric, it is crucial for after-sales, customer success and account management to forecast and deliver to ARR targets for existing clients.
      …
  • Ticket Response Time is a metric that measures how long it takes for a customer support team to provide an initial response to a customer’s support request or ticket.
    • The formula: Elapsed time from ticket creation/submission to when a support team member sends the first reply. How long this is depends on business and can be linked to Service Level Agreements (SLAs) with clients.
    • Response time influences customer satisfaction. Fast responses improve CSAT scores, even if the actual resolution takes longer. It buys you time.
    • Benchmarks: For Email less then 1 hour is considered excellent, for live chat less than one minute. SLAs for enterprise often say that critical issues must have a reply within 15-30 minutes.
      …
  • Ticket Resolution Time is a metric that measures how long it takes to fully resolve a customer’s support request or ticket from the moment it’s opened until it’s closed.
    • The formula: The time elapsed between ticket creation/submission and when the ticket is marked as resolved/closed with the issue fully addressed.
    • This metric is critical to customer satisfaction. Fast resolution directly correlates to higher CSAT and reduced frustration. Internally this shows the efficiency of your support organization and cross-departal collaboration. Patterns in resolution time can reveal areas needing product improvement.
    • This KPI is often “forgotten”, not included in SLAs and not measured in smaller companies yet it is one of the most important service KPIS in my experience.
      …
  • Bot Resolution Rate measures the percentage of conversations that are fully resolved by the AI chatbot without requiring human agent intervention or escalation.
    • The formula: Bot Resolution Rate = (Conversations Resolved by Bot / Total Conversations Handled by Bot) × 100
    • The definition of “resolved” depends on the the company. It can be “customer didn’t request a human agent”, “customer expressed satisfaction or confirmed resolution” or “no follow-up ticket within 24 hours”. You can also correlate bot perfomance with the number of tickets arriving at human agents.
    • There are related metrics like Containment Rate, Escalation Rate, First Contact Resolution, Both Accuracy and Bot Engagement Rate
      …
  • CSAT (Customer Satisfaction Score) measures how satisfied customers are with a specific interaction, product, service, or experience with your company. It is typically measured by asking customer a simple question: How satisfied were you with (Experience).
    • The formula: Customers respond using a rating scale, most commonly a 5-point scale: Very Unsatisfied, Unsatisfied, Neutral, Satisfied, Very Satisfied, in numbers or with emojis.
    • CSAT is often used after support interactions. But can also be done periodically at a larger scale. It always measure satisfaction with specific interactions. It is transactional and no indicator to measure the state of the relation, for with NPS is used.
      …
  • Net Promoter Score (NPS) measures customer loyalty and the likelihood that customers will recommend your company, product, or service to others.
    • The formula: NPS is measured by asking a single queston: On a scale of 0-10 how likely are you to recommend our company/product to a friend or colleague? Based on their rating customers are classified in three groups, Promoters (9-10), Passives (7-8), Detractors (0-6). You then deduct the detractors from the promoters to come to the NPS.
    • NPS effectively measures loyalty, helps predict growth opportunity and a high NPS will likely drive you referrals. World-class NPS is above 50, NPS is excellent between 30 and 50.
    • My recommendation is to do an NPS once a year, to not overload your customers and to combine the survey with a few CSAT questions, checking in on satisfaction with particular teams and features/services.

There are more metrics, but this is a comprehensive set that worked for most businesses.

About Customer Launchpad

We help PE/VC-backed SaaS and Tech scale-ups build scalable customer success strategies across all segments, including digital touch programs for SMB. Through interim leadership and consulting, we design and implement CS systems that actually work.

Want to discuss how we can help you? Get in touch

Related Posts

Scroll to Top