How to Improve Customer Effort Score: A Practical Playbook
Improving your Customer Effort Score is not about chasing a number — it is about systematically finding the moments where customers work too hard and removing that friction. Your CES tells you where effort is high; this playbook shows you what to do next.
The steps below work whether your score is quietly slipping or you simply want to make your product and service easier to deal with. Each one turns feedback into a specific, prioritized action rather than a vague resolution to 'reduce friction.'
This guide assumes you are already running a CES survey. If you are not yet, or you need the question format and calculation behind the number, start with the cornerstone Customer Effort Score guide. On this platform CES uses a 1–7 scale from Very difficult to Very easy, so a higher score means less effort.
Step 1: Find the high-effort touchpoints
A single overall CES hides where the effort actually lives. Before changing anything, break the score down by interaction so you know which moments in the journey are hardest.
- By touchpoint: measure effort separately for support, checkout, onboarding, delivery, returns and self-service — one painful step can drag the whole experience down.
- By segment: split CES by plan, tenure, device and channel; effort on mobile or for new customers is often much higher than the average suggests.
- Over time: overlay the trend with releases, policy changes and staffing shifts to connect a dip to a cause.
- By channel: compare effort across phone, chat, email and self-service to see where customers are forced into the hard path.
Rank the touchpoints from lowest score (highest friction) to highest. The lowest one or two are where improvement will move the metric most. Compute each from raw counts with the free CES calculator so your comparisons are consistent.
Step 2: Mine the comments for friction themes
The score tells you how hard an interaction felt; the open-text 'why' answers tell you exactly what made it hard. Every CES survey should pair the rating with a follow-up question, and low-score comments are your richest source of direction. The challenge is volume — reading hundreds of comments by hand is slow and inconsistent.
AI analysis solves that. It can group open-text responses into recurring friction themes — repeating information, long wait times, too many steps, confusing navigation, channel switching — and score sentiment so you can see which frustrations are most common and most negative at a glance. See analyzing open-text survey responses for the approach.
A single vivid complaint can hijack a roadmap. AI theme detection and sentiment scoring in AI analysis show how often each friction point actually appears, so you fix patterns instead of the loudest voice.
Step 3: Fix the root-cause friction
You cannot fix everything at once, so rank the friction themes by impact rather than ease, then attack the biggest drivers:
- 1Frequency: how many customers mention this friction point?
- 2Severity: how negative is the sentiment, and does the friction cause customers to give up or contact support?
- 3Feasibility: can you realistically remove it, and how quickly?
Common root causes behind high effort include forcing customers to repeat information, making them switch channels to finish a task, too many steps or form fields, hard-to-find self-service answers, and unclear next steps after an interaction. Match your top themes to the right fix — removing the top one or two friction points almost always moves the score more than spreading effort thin.
Step 4: Prevent the next contact
The lowest-effort experience is the one the customer never has to chase. A powerful way to raise CES is to anticipate the follow-on need and handle it before the customer has to ask again.
- Resolve the whole issue, not just the immediate question, so the customer does not have to come back a second time.
- Send proactive updates — order status, known issues, next steps — before the customer feels the need to check.
- Make self-service answers easy to find so customers can resolve simple needs without contacting you at all.
- Keep the customer in one channel; avoid forcing a transfer or a repeat of details they already gave.
Step 5: Close the loop with high-effort customers
Closing the loop means following up with the customers who reported high effort — acknowledging their frustration, resolving what is still open, and telling them what changed. It is one of the highest-leverage moves in any CES program, because an effortful experience that is followed up well can still keep the customer.
- Inner loop: respond to individual high-effort scores quickly, while the experience is fresh.
- Outer loop: feed recurring friction themes back to the teams that own those touchpoints so the root cause gets fixed, not just the symptom.
- Tell customers what you changed: 'you asked, we made this easier' messages show feedback leads to action and lift future response rates.
Step 6: Re-measure and track the trend
Improvement is only real if the score confirms it. After you remove a friction point, keep measuring with the same scale, wording and timing so the comparison is valid, and watch the trend rather than any single survey's number.
Give changes time to show up, and check both the overall CES and the specific touchpoint you targeted. A rise in the affected interaction is stronger evidence than a small move in the overall average. To understand what a good score looks like for context, see CES benchmarks.
Common mistakes to avoid
Treating CES as a vanity number nobody acts on; reacting to individual anecdotes instead of themes; measuring effort long after the interaction so memory has faded; changing the scale or timing so the trend becomes meaningless; collecting feedback but never closing the loop; and expecting a single fix to move the score overnight. Sustained improvement comes from repeating this loop, not from one big push.
Make the loop faster with AI
Speed matters: the faster you go from feedback to fix to re-measure, the more cycles you complete and the more effort you remove. AI shortens two of the slowest steps. It can create your CES survey with AI from a short description of the touchpoint, and it can summarize incoming open-text responses into friction themes and sentiment automatically so you always know what to make easier next.
For the strategy behind low-effort experiences, see reducing customer effort, and to put the questions to work start from a ready-made design in the template library.
Frequently asked questions
Keep reading
Everything about Customer Effort Score: what it is, how to measure and calculate it, benchmarks, the best questions, a full survey example, common mistakes and AI-powered effort analysis.
Why effort — not delight — drives loyalty, and the strategies that reduce it: self-service, channel continuity, proactive updates and effort-aware processes.
How to interpret your Customer Effort Score: what counts as good on common scales, why benchmarks vary by touchpoint and industry, and why your trend matters most.
How to word the CES question correctly, which scale to use, and 20+ ready-to-use effort questions for support, checkout, delivery, returns and self-service.
Real CES survey examples for support, checkout, delivery, returns, onboarding and mobile apps — with the exact questions and when to send each one.
Compute your Customer Effort Score from raw counts.
Describe the touchpoint and generate a CES survey in minutes.
Browse ready-made CES surveys and edit them for any touchpoint.