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BDC Agent

Handle customer complaints and escalations

Enhances✓ Available Now

What You Do Today

Manage frustrated customers—those waiting too long for callbacks, unhappy with pricing, or experiencing service issues. De-escalate situations, find solutions, and route complex issues to appropriate managers.

AI That Applies

AI detects negative sentiment in customer messages and calls, automatically escalates high-risk situations, and suggests resolution scripts based on complaint type.

Technologies

How It Works

The system ingests customer interaction data — transactions, communications, behavioral signals, and profile information. The processing layer applies the appropriate analytical models to the structured data, generating scored outputs that surface the most actionable insights. The results integrate into the practitioner's existing workflow — presenting recommendations, flags, or automated outputs alongside their normal working context.

What Changes

Complaint detection and escalation become faster with AI monitoring sentiment across all channels.

What Stays

Calming an angry customer, turning a complaint into a loyalty moment, and knowing when to offer a concession versus hold firm are distinctly human customer service skills.

What To Do Next

This section won't tell you what your numbers should be. It will show you how to find them yourself. Every instruction below produces a real, verifiable result in your organization. No benchmarks, no projections — just the steps to build your own evidence.

1

Establish Your Baseline

Know where you are before you move

Before adopting AI tools for handle customer complaints and escalations, understand your current state.

Map your current process: Document how handle customer complaints and escalations works today — who does what, how long it takes, where the bottlenecks are. You need this baseline to measure improvement.
Identify the judgment points: Calming an angry customer, turning a complaint into a loyalty moment, and knowing when to offer a concession versus hold firm are distinctly human customer service skills. These are the boundaries AI won't cross.
Assess your data readiness: AI tools for this area need data to work. Check whether your organization has the historical data, integrations, and data quality to support Reputation.com tools.

Without a baseline, you can't measure whether AI actually improved anything. You'll adopt tools without knowing if they're working.

2

Define Your Measures

What to track and how to calculate it

Time per cycle

How to calculate

Measure how long handle customer complaints and escalations takes end-to-end today, then after AI adoption.

Why it matters

The most visible improvement is speed. If AI doesn't save time, question whether it's adding value.

Quality of output

How to calculate

Track error rates, rework frequency, or stakeholder satisfaction scores before and after.

Why it matters

Speed without quality is just faster mistakes. Measure both.

When to check: Check after 30 days of consistent use, then quarterly.
The commitment: Give new tools at least 30 days before judging. The first week is always awkward.
What NOT to measure: Don't measure AI adoption rate as a KPI. Adoption follows value — if the tool helps, people use it.
3

Start These Conversations

Who to talk to and what to ask

your VP Sales or CRO

What's the biggest bottleneck in handle customer complaints and escalations today — and would AI address the bottleneck or just speed up something that's already fast enough?

They're evaluating AI tools that will change your workflow

your sales ops or RevOps lead

Who on the team has the most experience with handle customer complaints and escalations — and have they seen AI tools that could help?

They manage the CRM and data infrastructure your AI tools depend on

4

Check Your Prerequisites

Confirm readiness before you invest

Check items as you confirm them.