11 Customer Success Metrics That Make A Huge Difference

Let's dive into Customer Health Scores – one of the most powerful customer success metrics.

A Customer Health Score is a consolidated 0-100 rating that pulls together data across several dimensions: product usage, satisfaction levels, and business value metrics. It rolls up all this information into a single number for each customer.

Think of it almost like going to your doctor for an annual check-up. The nurse takes measurements like blood pressure, weight, and heart rate. The doctor reviews symptoms and how you feel. They combine all those vitals together to give you an overall health assessment. Customer Health Scores do the same thing for your users.

Why does having a high-level health rating matter so much?

Well, for starters, it makes it far easier for CSMs to quickly diagnose accounts needing attention. Maybe satisfaction tanked but usage is high. Or adoption is lagging even though the client is happy.

By glancing at the health score patterns, account issues instantly jump out. Resources can be allocated appropriately to nurture customers showing risks.

Now health algorithms might seem complicated, but they don't have to be fancy. Simply create a weighted formula emphasizing metrics correlated to churn and low lifetime value - adoption rates, NPS, support cases, etc. You’ll refine the weights over time as you analyze outcomes.

It’s also smart to establish clear health rating bands, for example:

90-100 = Extremely Healthy
80-89 = Healthy
60-79 = Potential Risk
0-59 = Severe Risk

This makes it easy for anyone to grasp customer wellness at scale without combing through detailed spreadsheets.

As for targets, software firms frequently aim for over 80+ desired customer segments, with 60-75 being more typical industry averages. The goalposts, however, will vary depending on your business model.

This metric is arguably the most important for subscription businesses.

Customer churn measures the percentage of users that cancel or fail to renew each month or year. It directly quantifies customer loyalty and revenue sustainability. Even tiny changes in churn have an outsized impact on profitability over time due to compounding effects.

That's why savvy SaaS companies obsess over this single number. Churn literally makes or breaks recurring revenue models. I always say, show me your churn rate and I can likely estimate your growth potential within a few basis points.

When tracking churn, it's smart to break it down two ways – by gross churn and net churn.

Gross churn tells you the absolute loss; the raw percentage of customers dropping out. However net churn offsets this by customer expansions – whether raising seats, adding products, or increasing spend.

Let me give an example: say 5% gross churn seems high at first glance. But then you see net churn is only 2% after significant upsells across the install base. This paints a very different picture on overall customer satisfaction and effectively “negative churn” through expansions.

Now SaaS benchmarks indicate 5% average monthly gross churn as typical. However the best-in-class companies doing over $100 million in revenue maintain less than 3% churn. And some outliers operate at less than 2%!

So set targets relative to these industry baselines, your market dynamics, and your business model. If churn is north of 7-8%, there likely needs to be a concerted effort to plug the leakage through better onboarding, proactive monitoring, and retention playbooks.

Customer Lifetime Value represents the total revenue you can expect from a typical customer over the entire relationship. It encompasses the initial deal, renewal cycles, potential expansions or upsells, and the ultimate churn outlook.

CLV can vary widely depending on the user segment – for example large enterprises versus small business accounts. But directionally, understanding estimated lifetime value helps tremendously with rational decision-making around investments to acquire and retain customers.

You specifically want to analyze CLTV relative to Customer Acquisition Costs (CAC). An efficient growth engine requires CLV multiples exceeding CAC, otherwise unit economics don't work.

As a rule of thumb, aim for CLV 3-5x higher than CAC across key segments. So if your average sale costs $2,000 in sales and marketing spend, lifetime value should shake out to $6,000 to $10,000 for those accounts.

SaaS benchmarks show this CLV/CAC ratio proves out for many companies scaling successfully. If ratios dip near 2-3x however, ROI timeframes stretch out and growth capital required increases.

Calculating CLV does require using historical data on renewals, expansions, and churn to model expected value over time. But basic spreadsheet approaches work fine before more advanced predictive modeling.

Shifting gears, let's talk about product adoption – the cousin of customer satisfaction and health tracking.

Product Adoption Scores quantify to what degree customers actually use and engage with your product over time. The score synthesizes depth of usage across core features as well as frequency metrics.

This paints a more tangible picture than general satisfaction surveys on if clients experience value. And product adoption directly fuels renewals and expansions. Customers naturally grow into heavier, stickier usage the more they embed your solution into workflows.

Now calculating adoption scoring takes a bit more elbow grease. Start by defining essential activation events, must-have features, and markers for power users by persona. Hook up the scoring model to prod usage and activation event data.

This then rolls up into an aggregate 0-100 adoption rating – almost like a grade on product engagement. You can then segment users by level to target onboarding gaps or between cohorts.

As for good targets by vertical, averages bounce around 50-70% depending on complexity. However, for key customer personas, you’ll want over 80% consistently utilizing your primary value drivers. This leads to much higher lifetime loyalty and upgrades.

While more usage and health data are now available, short satisfaction surveys are still invaluable. They capture subjective emotions and perceptions that pure analytics miss. A customer may actively use a product that still annoys them daily.

​CSAT specifically measures broad satisfaction on a 1-10 or 1-5 scale. It simply asks some variation of “How satisfied are you with XYZ business or product”.


The importance of tracking satisfaction lies in the direct impact on customer loyalty and retention. Multiple studies confirm satisfied users convert better, have higher lifetime values, and volunteer more referrals. It pays to monitor happiness.

Now CSAT scores do vary widely by vertical - complex enterprise software averages 60-80% while consumer apps see over 90% as typical. Benchmark against industry peers, but more importantly look at CSAT trends over time.

Are ratings declining amongst key personas? Is there a gap between power users versus casual users? Layering in churn metrics can quantify whether lower satisfaction aligns with actual turnover.

Beyond CSAT, also consider supplementing with Net Promoter Score for loyalty, Customer Effort Score for ease of use, and journey mapping to detect friction. Together these four metrics provide a holistic view into the emotional customer experience beyond straight adoption stats.

Customer Effort Score is a valuable metric that complements broader satisfaction and usage data. While CSAT measures general happiness, CES zeros in on experience friction.

​It works by asking customers “How much effort did you personally have to put forth to handle your request?” on a 1-7 scale. 1 means high effort, 7 equals very low effort on their end.


This quantifies how easy your product and processes are to deal with across key touchpoints. Think onboarding, support issues, upgrade transactions, renewals - moments of truth.

By directly gauging customer effort and obstacles, you quickly diagnose areas of friction or complexity to fix. You get out ahead of problems impacting usage and loyalty before they accumulate and churn sets in.

For example, a client of mine before had stellar CSAT scores so they assumed customers found their portal very user-friendly. But when they rolled out CES surveys, they discovered users struggled enormously trying to pull reports or view shared project data. They soon overhauled permissions and intuitive settings which boosted adoption.

When it comes to score targets, technology companies average around 6.0 to 6.5 in customer effort currently. However, truly customer-centric organizations benchmark much higher - from 6.3 up to 6.8 for key workflows. This means they continually refine experiences to deliver near effortless, frustration-free journeys.

Track CES across onboarding, professional services, tech support, and renewals/expansions. Then drill down to quantify exactly where unnecessary obstacles exist. Game-changer.

This is a classic metric for gauging customer loyalty and referrals, one that I’ve discussed multiple times before if you’ve read my other blogs.

​NPS measures likelihood to actively recommend your product or business to colleagues on a 0-10 scale. By asking "how likely are you to recommend us," it segments users into promoters, passives, and detractors.

This shows not just broad satisfaction, but willingness to vouch for your solution with personal reputation on the line. That heartfelt endorsement drives word-of-mouth growth.

As for importance, NPS strongly correlates with organic expansion and reduced churn - the dream combination! Customers who rave about you to peers tend to stay loyal long-term while bringing in new accounts. It becomes a virtuous cycle.

Given the link to referrals and retention, NPS works well across onboarding, renewals, upgrades, quarterly check-ins, and post-support surveys - anytime you want a loyalty pulse check.

In terms of targets, technology benchmarks show a wide range - average NPS scores swing from 20 to over 70+. However positive score trends matter more than fixed benchmarks as you tweak experiences. I tell clients “move the needle up and to the right!”

Common pitfalls involve letting detractors languish without follow-up. Set clear paths for correcting issues and winning back critics. This often bumps scores exponentially as you slowly expand promoters.

Continuing our journey into key metrics, let's chat about Customer Education Scores – an emerging area that directly fuels adoption and loyalty when done right.

Customer education spans onboarding, training, ongoing enablement resources, and measuring content resonance. As products grow more advanced, educating users on capabilities and workflows accelerates time-to-value while mitigating churn risks.

However, most businesses track very little on enablement effectiveness besides anecdotal user feedback. Without diagnosing knowledge gaps, you end up with uneven experiences. Some users master the platform, while others languish in ignorance, limiting their perceived value.

That's where Customer Education Scores come into play – quantifying engagement across learning touchpoints while assessing comprehension too.

For example, what percentage of customers actively participate in new release training webinars? How many power users ended up certifying advanced features last quarter? What is the average assessment score on knowledge checks for setting up integrations?

Each of these data points fills gaps in true understanding. You can then spot deficient areas to shore up through better content or guided coaching.

Education scoring works hand-in-hand with product adoption rates too. Because the more customers learn platform intricacies, the more deeply they ultimately use and depend on your solution.

Now implementation takes considerable forethought and coordination across services, support, and marketing teams who “own” pieces of education. Start by auditing what customer data gets captured already around enablement touchpoints. Build targets for participation, knowledge checks, and certifications from there.

Even basic metrics like percent trained on new features, or number of expert certifications obtained per quarter deliver powerful insights. Double clicks reveal how better education ties directly to stickier customers.

Here is the text rewritten with the alternative benchmark of oil and gas companies:

Account Health Reviews or AHRs (sometimes called QBRs or BRs) provide recurring touchpoints to check on user health, reinforce value, and drive adoption, renewals, and expansions. They serve as progress reports across the entire customer journey.

Most oil and gas companies severely underutilized the potential of account business reviews and treat them as 10-minute courtesy calls. But savvy CSMs know how pivotal formal check-ins prove for building trust and loyalty.

AHRs assess satisfaction, business impact, product usage trends, and risks in a structured way – quarterly or as-needed for high-touch accounts. Collecting user feedback is invaluable while you educate them on overlooked capabilities. It becomes a win-win conversation fueling stickiness.

Even simple actions like screen-sharing new features or connecting users to peer power users create tremendous goodwill. Users see your team actively invested in their success. And you get the signals to course-correct adoption issues or churn risks in real time.

Now despite the value, I still see account review frequency lag way below optimal levels when I advise oil and gas companies. Many firms start around 20-30% account coverage per quarter. However top-tier teams maintain 50%, 80%, and even over 100% coverage based on tier.

Think about it – if each CSM oversees 150 accounts on average, how many touchpoints occur yearly at 40% vs 80%? The delta is enormous in relationship-building.

Make no mistake. Consistent, high-quality account reviews drive demonstrably higher satisfaction, renewal rates, and expansions. They provide a conduit to reinforce value and head off customer issues.

Prioritize scheduling recurring touchpoints, equip CSMs with conversation guides, and create templates to capture action items and risks. Taking AHRs seriously transforms customer longevity and lifetime value.

Average Deal Size refers to the mean annual contract value (ACV) or total contract value (TCV) for sales deals closed each month. Segmenting new customer lands versus expansions also proves insightful.

Tracking deal size trends reveals positive momentum expanding accounts. If ACV rises over time, it shows customers buy more seats, upgrade tiers, or adopt multiple products per organization. All fuel-efficient growth.

For context, SaaS benchmarks point to 20-30% average yearly expansion in ACV per account. So if initial lands run $20k, you’d expect to see $24-30k in subsequent years per customer.

Now early-stage startups often expand much faster as they land and expand. But once scale sets in, 20%+ year-over-year account growth makes healthy recurring revenue models. Dips below 10% annually indicate challenges in upselling installed bases.

When analyzing data, focus on ACV expansion rates rather than purely absolute numbers too. Incentives play a key role – you want sales behaviors driving total contract value growth, not just maximizing deal volume at lower price points.

Like any metric, consider average deal sizes relative to product mix, target customer tier, and use case. But healthy growth points to customers deriving more value from solutions over time - the foundation of long-term loyalty.

Sticking with sales and growth metrics, let’s go deeper into customer expansion rates. This tracks the percentage of clients that purchase more services or products over time from your firm. It showcases your ability to drive recurring growth post-sale.

Expansion efficiency remains pivotal for services businesses even if not subscription-based. Growing wallet share with established accounts requires far fewer sales costs than cold prospecting brand-new logos each year.

Plus, analyses show 60-80%+ of revenue at mature professional services firms flows from expanded or enhanced engagements with existing relationships. Upsells and cross-sells become a profit engine over time.

Benchmarks in the consulting and agency world point to top performers expanding 35-45% of customer accounts annually. So if they started 2018 with 50 active clients, the next year 60-70 clients would buy additional services. This compounds quickly as firms scale.

Missteps often involve sales chasing endless new logos through cold outreach while ignoring current customers. Maintaining an “expand first” philosophy ensures account managers nurture enduring, growing client relationships.

This requires incentives promoting expansion selling skills, accountability to retention metrics, and consistent upsell communications built into quarterly client check-ins.

As we've explored across eleven essential metrics, customer success has quantifiable dimensions that directly fuel growth, referrals, and profitability when managed correctly.

By methodically monitoring adoption patterns, satisfaction trends, expansion rates, and predicted lifetime value, you spot risks early and nurture enduring user loyalty. Suddenly customer churn and support costs plummet while wallet share and endorsements rise over the long haul.

Approach these metrics not as a one-time project but an ongoing journey to excellence. Regularly refine target ranges as your product and install base matures over time. Motivate teams by tying metrics to individual rewards and business OKRs.

Embrace customer-centricity as a foundational corporate value that permeates all decisions and processes. Small gains accumulate, compounding the commercial success and advocacy stemming from delighted users. In the end, creating customers for life should remain the north star guiding service businesses towards prosperity.

If you want to keep yourself sharp on the best customer success metrics and practices, I strongly suggest that you register for our No B.S Newsletter, where I deliver tactical advice based on proven results from the field. You’ll get access to retention techniques, insights into different industries, and more!