The Tool Desk
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Start with customer preference, not a channel trend
Published survey results can help you frame the decision, but they do not tell you which channel will work best for your business. In Capgemini Research Institute’s 2025 report, based on a survey of 9,500 consumers conducted in November and December 2024, respondents selected these channels among their top three customer-support preferences:
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| Channel | Share selecting it among their top three | What the figure does—and does not—tell you |
|---|---|---|
| Phone support | 60% | A stated preference in this survey; not a measure of resolution rate, current usage at your business, or cost. |
| Email support | 49% | A stated preference in this survey; not proof that email is the best fit for every request. |
| Chatbot or live chat | 40% | The survey reports these together, so it does not establish separate preferences for an automated bot and a human live-chat agent. |
| WhatsApp or messaging services | 36% | A combined category, not a preference estimate for any one messaging app. |
| Self-service portals | 32% | A stated preference, not a forecast of how many customers will complete a task without assistance. |
| Social media | 31% | A stated preference; the figure does not identify a particular social network. |
| In-store support | 28% | A stated preference across the survey, not an estimate for an online-only business. |
| Online community forums | 24% | A stated preference; it does not establish that a forum suits private or account-specific support. |
These percentages describe survey respondents’ top-three choices, not channel market shares, forecasts, or proof of business value. Use them as context, then examine your own contacts by customer group, market, and issue. A channel that matters for delivery questions may be less useful for a sensitive account problem, and a channel used frequently by one customer segment may be rarely requested by another.
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Match the channel to the job the agent can do
First decide what the AI agent is being asked to accomplish, not merely where it will appear. A support interaction may involve finding an answer, guiding someone through a procedure, taking an account-specific action, or transferring the issue to a person. Each proposed channel should support the intended job and the systems needed to do it.
- Information: Can the agent retrieve a relevant, approved answer from the knowledge base? Identify how it should respond when the available information is incomplete or does not match the question.
- Guidance: Can it walk the customer through a procedure, and can the customer complete that procedure in the channel? If a step requires a different interface or supporting documentation, plan how the customer gets there.
- Account-specific action: Can the agent securely access the required system, check the necessary details, and perform only the approved action? Decide what the agent may read or change before enabling the action.
- Routing: If the agent cannot resolve the issue, can it direct the customer to the right team or service route without implying that the issue has been solved?
Task completion is a real use case, not just a theoretical extension of question answering: Gartner reported that 58% of surveyed GenAI users had used it to complete a task. That figure does not establish which tasks are appropriate for your agent. Define a limited set of permitted actions, the conditions under which each action is available, and the failure cases that require a person.
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For example, an agent might be allowed to look up a policy and guide a customer through a documented request, while an exception requiring judgment is sent to an employee. That is an example of scoping, not a claim that every business or system can safely support those actions.
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Customers should not have to pass through an AI interaction for every kind of support. In Gartner’s 2026 survey of 3,566 B2B and B2C customers, 87% said access to a human agent was essential when companies use GenAI for customer service. Gartner analyst Eric Keller also advised service leaders not to use GenAI as a mandatory first step for every issue.
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Make the human route visible and define when the agent should offer or initiate handoff. Relevant triggers can include a request for a person, an issue outside the agent’s approved scope, a failed attempt to complete an action, or a situation your service policy reserves for human judgment. The exact triggers depend on the service; what matters is that customers and staff can reach the escalation path without having to repeat an AI interaction that cannot help.
Where the implementation permits it, carry useful context into the handoff so the customer does not need to start over. Treat that as a system-design requirement to validate in your own setup: the available evidence identifies integrations as important but does not quantify the effect of conversation continuity.
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Channel choice also does not begin and end with company-owned chat. Gartner reported that, in customers’ most recent service interaction, they were about three times more likely to use third-party GenAI tools than company-provided chatbots. That finding is not a reason to put sensitive account details into an external tool. It is a reason to make company-owned routes clear for verifying account-specific information and completing transactions.
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Compare channels against the same decision criteria
Use a consistent set of questions for every candidate channel. A channel’s survey preference score does not establish its suitability for an account-specific task, the level of service you can provide, or what it will cost to operate.
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| Decision criterion | Question to answer | Evidence to gather locally |
|---|---|---|
| Customer demand | Which customers use or request this channel, for which issues and in which markets? | Contact volume and customer research segmented by issue, market, and customer group. |
| Task fit | Can the agent answer, guide, complete an approved action, or only route the request in this channel? | Results from representative tasks, including cases where information is missing or an action fails. |
| Complexity and sensitivity | Does the issue call for reassurance, judgment, or a person? Is the customer being asked to share sensitive information? | Issue types, escalation reasons, service policies, and the data each interaction requires. |
| Integration | Can the channel work with the knowledge base, CRM, and existing phone and email operations? | Confirmation that the necessary systems and workflows connect and that the intended action can be supported. |
| Accessibility and privacy | Can the intended audience use the interaction, and is the information requested necessary for the support task? | Accessibility review and privacy review for the channel and the specific interaction. |
| Continuity | Can context follow the customer if a contact changes channel or is escalated? | A test of the actual transfer path, including what information reaches the receiving person or system. |
| Operational performance | Does the channel resolve the task without creating avoidable repeat contact or excessive handoffs? | Pilot measures for completion, unresolved contacts, repeat contacts, escalation, waiting time, feedback, and operating cost. |
Digital.gov’s contact-center guidance highlights integration with phone, email, knowledge-base, and CRM systems, as well as accessibility and privacy. Treat these as operating foundations, not late-stage extras: a new channel that cannot connect to the information or team needed to resolve a request may offer little beyond another place for the customer to get stuck.
There are no established universal benchmarks in the cited material for channel-specific cost, resolution, latency, or staffing. Compare your channels using the same definitions and pilot conditions rather than treating a result from one channel or business as a general standard.
A practical process for choosing and expanding channels
- Map demand: Use your contact and customer-research data to identify the channels customers actually use or ask for. Break the view down by issue, market, and customer group; use published surveys as context, not as a substitute for local evidence.
- Map issues to channel capabilities: For each common request, record whether it needs structured self-service, conversational text, messaging, voice, supporting documentation, or a person. Note whether the agent should answer, guide, take an approved action, or route the contact.
- Select an initial mix: Choose channels that customers use and that your organization can support with the required systems and service routes. Do not adopt a fixed ranking based on survey percentages or technology forecasts.
- Set the agent’s boundaries: Specify what information it may access, which actions it may take, the conditions for those actions, and the situations that trigger human assistance. Keep the human route available without requiring an AI interaction first.
- Check integrations, privacy, and accessibility: Confirm the connections to knowledge, CRM, phone, and email operations that the service needs. Review whether people in the intended audience can use the interaction and whether it asks for only the information required.
- Pilot and measure: Track task completion, unresolved contacts, repeat contacts, escalation, waiting time, customer feedback, and operating cost. Compare channels using the same issue mix and measurement definitions where possible, and establish your own baseline.
- Expand when results support it: Use pilot findings to decide whether to add another channel, widen the agent’s scope, or improve an existing journey. Preserve clear company-owned ways to verify account-specific information and complete transactions.
Frequently Asked Questions
Does the 40% preference figure apply to chatbots alone?
No. Capgemini reports chatbot and live chat together as one survey category. Its figure cannot be used to compare customer preference for an automated bot against a human live-chat agent.
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It can be useful for an agent to complete a bounded task, but the organization should define the permitted action, required system access, and failure conditions in advance. The cited Gartner task-use finding shows that surveyed GenAI users had used GenAI to complete tasks; it does not establish that unrestricted action-taking is safe or suitable.
How can a business tell whether adding a channel helped?
Run a pilot and compare completion, unresolved and repeat contacts, escalation, waiting time, customer feedback, and operating cost using your own service data. The cited sources do not provide universal channel-by-channel benchmarks for those measures.
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