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Start with the problems customers are trying to solve
Before changing staffing, scripts, or software, identify why customers contact you and where the support journey breaks down. Review a representative sample of conversations and tickets. Group them by reason, channel, complexity, and outcome, then look for patterns such as repeat contacts, transfers, unanswered follow-ups, or customers having to provide the same details more than once.
- Repeat contacts: Is the same customer returning about the same unresolved issue?
- Handoffs: Does a case move between people or teams without clear ownership?
- Repeated explanations: Does information from an earlier conversation fail to reach the next person?
- Unclear next steps: Are customers left unsure when they will hear back or what they should do?
- Channel mismatch: Is a complex or sensitive problem being forced through a channel that cannot handle it well?
Use these observations to prioritize a small number of specific changes. A high volume of contacts about one confusing process, for example, may call for clearer instructions or a product fix rather than faster replies to each ticket.
Resolve the issue on the first contact when practical
First-contact resolution is not a reason to rush or close cases prematurely. It means solving the customer’s issue in the first interaction when the issue, authority, and available information make that possible. If it cannot be resolved immediately, give the customer a clear owner and a specific expectation for the next update.
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In JD Power’s 2023 U.S. cross-industry study, overall satisfaction scores were more than 200 points higher when issues were addressed on first contact. Scores were more than 150 points higher when customers did not have to repeat the same information. These are associations in that study, not guaranteed effects for every business. The study reported overall customer-service satisfaction of 605 on a 1,000-point scale and an average issue-resolution time of 18.10 minutes, with results varying by touchpoint: 23.64 minutes by phone, 15.62 minutes in person, 11.41 minutes on a website, and 10.75 minutes in a mobile app. Those figures describe the study, not targets to impose on every team. JD Power’s 2023 U.S. study
Qualtrics XM Institute’s 2025 report, drawing on its 2024 Global Consumer Study of more than 23,000 consumers, says 62% reported resolving an issue the first time they contacted customer service. Compared with consumers whose issues were not resolved on the first try, those whose issues were resolved were 1.9 times more likely to purchase more and trust the brand, and 2.1 times more likely to recommend it. These are reported comparisons, not proof that first-contact resolution alone caused the differences. Qualtrics XM Institute, Global Contact Center Trends, 2025
Make first-contact resolution achievable
- Give frontline staff clear guidance on what they can decide, refund, replace, or escalate without seeking repeated approvals.
- Make accurate product, policy, and troubleshooting information easy to find during a conversation.
- Route cases by issue type and required expertise, not only by availability.
- Preserve the customer’s history and prior troubleshooting so a handoff does not restart the conversation.
- When resolution requires time, tell the customer who owns the issue, what happens next, and when they can expect an update.
Reduce waiting without making access to a person harder
Customers value timely help, but a quick automated response is not the same as a useful answer. Qualtrics XM Institute reports that, in its 2024 consumer study, 55% were satisfied with the wait during their recent contact-center experience, overall contact-center satisfaction was 63%, and customers found it easy to connect to a person 64% of the time in interactions not solely involving a chatbot. The same report says consumers satisfied with wait time were 2.6 times more likely to purchase more and trust a brand, and 3 times more likely to recommend it, compared with consumers dissatisfied with wait time. These are study comparisons, not universal performance targets. Qualtrics XM Institute, Global Contact Center Trends, 2025
Reduce avoidable waiting by setting realistic expectations, providing status updates, and routing work to the right team early. If a queue is backed up, be candid about the delay and offer a useful alternative—such as a callback or an asynchronous message—only if the team can reliably deliver it. Keep a clear route to a person for issues that are complex, sensitive, unresolved, or outside the scope of self-service.
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Choose channels to fit the work
Different channels suit different tasks. A brief question may be handled well in chat; an issue requiring screenshots, order details, or several rounds of troubleshooting may be easier asynchronously; a sensitive or complicated case may need a live conversation. Let customer preference and the work itself guide the channel rather than adding channels simply to claim broader availability.
Shopify’s 2026 customer-service reporting guide gives examples of 80% of live chats being answered within 40 seconds and an email standard of within an hour. Those are examples in a vendor guide, not universal service standards; Shopify explicitly notes that benchmarks vary by channel and business context. Freshworks’ 2025 report also recommends balancing responsiveness with resolution depth and matching channels to query type. Its benchmark dataset covers 17,170 businesses across 25+ industries, over 37 million conversations, and 19 million tickets; its performance matrix uses provider-defined tiers, so the figures should be read as vendor benchmark context rather than a universal target. Shopify’s customer-service reporting guide and Freshworks’ 2025 Customer Service Benchmark Report
Keep context when a conversation changes channels
If customers move from chat to email or from a social message to a phone call, they should not have to reconstruct the case. Record the issue, steps already tried, relevant account or order details, and promised follow-up in a place the next person can access. Do not launch a channel your team cannot monitor consistently or connect to the existing support process.
Make knowledge useful to both customers and agents
Reliable answers should not depend on one experienced employee remembering where a policy is buried. Keep internal guidance and customer-facing help content current, searchable, and organized around real tasks and questions. For common issues, include the steps, exceptions, and signs that the customer should stop and contact support.
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- Review contact reasons and repeat questions to choose which guides to create or update.
- Use plain language, descriptive headings, and steps that match the current product or policy.
- Make it clear when instructions do not apply, and provide a route to further help.
- Give agents a way to flag outdated or conflicting content, then assign someone to resolve the flag.
- Check whether customers who use self-service complete the task or still need to contact the team.
Self-service is most useful for straightforward, repeatable tasks. It should not become a barrier that customers must pass through before reaching a person when their problem is unusual, high-impact, or unresolved.
Measure customer outcomes alongside operational activity
A response-time figure alone cannot tell you whether support helped. Pair operational measures with measures of resolution and customer effort, and interpret them by channel and issue type. Shopify’s 2026 guide lists initial response time, first-contact resolution, average response time, resolution time, ticket volume, interactions per ticket, customer satisfaction, and customer effort. These measures become more useful when compared across similar work rather than blended into one team-wide average. Shopify’s customer-service reporting guide
| Measure | What it helps you understand | Read it with |
|---|---|---|
| Initial response time | How long customers wait for the first useful reply | Channel, queue, and whether the response advances the issue |
| First-contact resolution | Whether the issue was resolved in the first interaction | Repeat contacts, reopenings, and issue complexity |
| Resolution time | How long it takes to resolve the issue overall | Issue type, handoffs, and customer updates during the wait |
| Interactions per ticket | How many exchanges are required to handle a case | Resolution quality and whether the customer must repeat details |
| Customer satisfaction | How customers rate the service experience | Response rate, channel, and the type of issue handled |
| Customer effort | How difficult customers say it was to get help or complete a task | Self-service completion, channel changes, and repeated explanations |
| Ticket volume | How much demand the team is handling | Changes in product issues, contact reasons, and channel mix |
Deloitte describes time to respond and time to resolve as operating measures, alongside customer outcomes such as effort, satisfaction, first-contact resolution, and retention. Its discussion concerns B2B high-tech support organization design, so it should not be assumed to describe every consumer-service operation. Deloitte US, B2B High Tech: Next-Gen Customer Support
Use the measures together. A shorter resolution time could reflect better routing, but it could also coincide with premature closures or more repeat contacts. A faster first reply matters less if the customer must contact the team again to get a real answer. Add customer comments and case reviews to explain what a metric alone cannot show.
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Test improvements on a manageable scale
- Choose a specific friction point. For example, focus on one common contact reason with frequent transfers or repeated explanations.
- Record a baseline. Capture the relevant operational measures and customer outcomes for that issue and channel, including repeat contacts, resolution, satisfaction, or effort where available.
- Change one part of the process. You might clarify ownership, improve an agent guide, revise a help article, or change routing for that contact reason.
- Review comparable cases. Compare the same type of work before and after the change, and account for differences in channel or case complexity.
- Look for unintended effects. Check whether faster handling came with premature ticket closure, increased repeat contacts, more customer effort, or weaker satisfaction.
- Keep, adjust, or stop the change. Use both the measured outcomes and what customers and agents say about the process.
This is a practical way to learn from a change; there is no single experiment design or performance target that applies to every support operation.
Decide whether support software will solve a real operating problem
Support software can help with shared conversation history, routing, automation, and reporting when the current process cannot manage them reliably. It does not by itself ensure accurate answers, appropriate staffing, or good resolution. First identify the work the system needs to support: for example, keeping context across channels, assigning cases clearly, surfacing current knowledge, or reporting on repeat contacts and outcomes. Then assess whether the software fits the channels and systems your team actually uses, and account for setup and ongoing operating costs.
The evidence on customer outcomes supports improving access, resolution, and effort; it does not establish that buying a particular tool guarantees those results. A tool is worthwhile when it enables a defined improvement and the team can operate it consistently.
How to choose what to improve first
Prioritize changes using the customer harm or effort involved, how often the problem occurs, and whether the team can make a practical correction. Use a channel-and-issue view rather than a single blended score. When comparing two support approaches, consider:
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- How easily customers can reach an appropriate person.
- Wait experience and whether expectations are clear.
- Likelihood of resolving the issue without another contact or handoff.
- Customer effort, including repeated explanations or channel changes.
- Fit for the issue’s complexity and sensitivity.
- Whether conversation history remains available across the journey.
- Accessibility for the customers who need support.
- Integration with existing operations, staffing requirements, and total operating cost.
- Whether reporting can distinguish issue type, channel, resolution, and customer outcome.
No universal channel mix, response-time target, or staffing model is established by the cited sources. Set expectations that make sense for your customers, your types of work, and the resources you can sustain, then judge them by customer outcomes as well as activity.
Frequently Asked Questions
What is the most important way to improve customer support?
Start by finding where customers’ issues remain unresolved, require repeat contacts, or force them to repeat information. Then address the most consequential recurring problem and check whether the change improves resolution and customer effort.
Which customer-support metrics should a small business track?
A useful starting set is initial response time, first-contact resolution, resolution time, repeat contacts or interactions per ticket, customer satisfaction, and customer effort. Segment them by channel and issue type so different kinds of work are not obscured by an overall average.
Should every customer-support question be answered immediately?
No. A quick, accurate answer is useful when the issue is simple and the team has the information needed. For a complex case, a clear owner and reliable next-update expectation are better than a rushed answer that leaves the problem unresolved.
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Only when it can monitor the channel consistently and preserve enough context to handle cases effectively. Choose channels around customer preference and issue complexity rather than availability alone.
Does self-service replace access to a support agent?
Self-service can handle straightforward tasks, but customers need an understandable path to a person when the issue is complex, sensitive, outside the instructions, or still unresolved.
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