Use Case

AI phone assistant for customer support

Evaluate an AI phone assistant for routine questions, returning issues and staff handoffs. Compare useful resolutions, remaining support effort and total call costs.

A buying guide for support phone lines

Count an ended conversation and a resolved issue separately

A short support call is not automatically a good outcome; the work continues when the customer returns with the same issue. Start the first pilot with one frequent question group. With your configured test assistant, test missing information, an ineffective suggestion and a request for a person alongside a correct answer. Put the next step understood by the customer at the center of evaluation.

Suggested pilot: a routine usage question

Have a caller ask where to begin a task, then explain that the first answer was unclear. Test clarity rather than repetition of the same sentence. Ask the support team to assess whether the customer understands what to do at the end and which part of the question remains open.

Suggested pilot: an issue that returns

Have a caller say they already tried the suggested steps but the problem remains. Test a route to human review without sending them back to the beginning. Does the representative know what has been tried at the next contact, or must the customer explain the whole issue again?

Prepare before the pilot

  • Current approved answers for the pilot question group.
  • Clear definitions of attempted steps and the remaining problem.
  • Representative hours and handoff rules for unresolved topics.

Measures for the buying decision

  • Support requests reopened because the same issue remains.
  • Representative time needed to understand a transferred conversation.
  • Total call and staff effort per confirmed resolution.

Where a person makes the decision

Repeatedly unsuccessful steps, actions requiring authority and an explicit request for a representative are handoff criteria. The pilot should assess closing a support record separately from resolving the customer’s problem.

Try your support problem with your configured test assistant

Explore the sample conversations. Try your own scenario with the test assistant in your account. Test a routine question first, then an answer that does not help. In a real-call pilot, measure repeat contact and remaining representative effort. Compare pricing by the total cost of a customer-confirmed resolution alongside call duration.

Example panel · Customer Support
example
09:04InboundBilling inquirydone
09:11InboundConnection outage↗ escalated
09:18OutboundPost-fix follow-updone
09:26InboundPassword resetdone
09:33OutboundCSAT surveydone
TR
Turkish-focused voice AI
Example chart
Illustrative call volume
Connections to plan for your pilot
CRMWhatsAppCalendarSMSWebhook
Pilot
Measure in your pilot

Support requests reopened because the same issue remains.

Customer Support
Customer Support

We built AvaritCall so people get good service in a system that wears call-center agents down. We put AI beside people, not in their place.

The weight on the support line.
Inbound
Wait time eats satisfaction.
Customers in the queue grow impatient; the pre-resolution experience sours and NPS drops.
Inbound
The same question, again and again.
FAQ-type questions eat most of the team’s time; complex cases get none.
Outbound
No post-resolution follow-up.
Whether a closed ticket was truly resolved isn’t asked; reopened tickets rise.
Outbound
No proactive notice.
On an outage, delay or maintenance the customer isn’t called in advance; the complaint line fills up.
What it handles

Resolves FAQs, escalates when needed.

Answers FAQs from the knowledge base instantly, 24/7.

Resolves simple issues step by step; guides the user.

Sends resolution steps, documents and links via WhatsApp.

Answers status/order/ticket queries from the live system.

Hands unresolved cases to a live agent with a context summary.

Turns the call into a ticket; assigns priority and category.

Outbound Calls · Follow-up · Proactive

Confirms the fix, informs in advance.

Confirms a closed ticket is resolved and measures satisfaction; on an outage/delay/maintenance it calls the customer proactively — cutting the complaint line and reopened tickets.

Makes a post-resolution follow-up call; confirms the issue is truly fixed.

Runs a satisfaction (CSAT/NPS) survey; feedback hits the dashboard.

Informs the customer in advance of planned maintenance, outage or delay.

Sends resolution summary, survey link and updates via WhatsApp.

Detects reopened/at-risk customers; a priority action hits the team.

Summarizes the call; satisfaction score and action hit the dashboard.

Ticket/customer list
AvaritCall calls
Confirm / inform
Follow up via WhatsApp
Score on dashboard
Data processing scope

Before you start, clarify your data workflow.

Notice and permission
Determine the caller notice and permissions needed for your own workflow.
Data scope
Review the different processing scopes of transcripts, web forms and payment information in the privacy and KVKK notices.
Access and retention
Discuss team access, required retention periods and the process for deletion requests.
Enterprise requirements
Evaluate specific data processing and contractual requirements with the team before launch.

Agree on notice, access and retention requirements for the pilot with your organization; review data processing scope in the privacy and KVKK notices.

How it works
Create the agent

Use an industry template as a starting point and configure the information and conversation workflow for your business.

Test it

Call from your own number, hear the real conversation, fine-tune.

Go live

Connect your number or get a new one; the agent answers 24/7.

Monitor & improve

Track calls, transcripts and metrics from the dashboard and keep improving.

Frequently asked questions

Try voice AI built for your sector today.

Configure your assistant in the dashboard and test it with your own call workflow. Start with USD 5 signup trial credit and pay-as-you-go pricing.

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