The boostCX Blog

A phone call that goes unanswered is invisible to everyone except the caller. An unanswered comment or message on social media is a public record - visible to every future customer who searches your brand. That visibility changes what "acceptable" response time actually means.

The Expectation

Sprout Social's Index research finds that roughly 76% of consumers expect a response within 24 hours when they contact a brand on social media - a bar that's held steady across several years of their reporting, even as expectations elsewhere have gotten faster. On specific platforms, expectations often run tighter still: customers who complain publicly on X (formerly Twitter) frequently expect a reply within about an hour.

The Reality

Most brands don't hit that bar. Independent industry benchmarking commonly places average social media response times in the 4-to-5-hour range - well past the platforms where expectations are tightest, and close to the 24-hour ceiling on the platforms with more relaxed expectations.

Why This Is a Revenue Number, Not Just a CX Number

Customer response time research from GreetNow found that 73% of social media users say they'll buy from a competitor if a brand doesn't respond to them. Silence on social media isn't a neutral outcome - for a meaningful share of customers, it's the moment they decide to leave.

Building a Contact Center That Can Actually Hit These Windows

• Route social mentions into the same queue as phone, chat, and email - a separate team monitoring platforms manually is how response times slip
• Prioritize by sentiment and urgency, not just order received - a public complaint from an upset customer should surface faster than a routine question
• Set an internal target ahead of the customer expectation - if customers expect 24 hours, target same-business-day as the floor, not the ceiling

The Takeaway

Social media customer service isn't a separate discipline from your contact center - it's a channel with a public audience and a shorter fuse. Treating it as an afterthought is a visible decision, made in public, every time a comment goes unanswered for hours.

"Agentic AI" gets used loosely, often to describe anything with a chat interface. The meaningful distinction is that an agentic system can take multi-step action inside your actual systems - looking up an order, updating a record, scheduling a callback - rather than just answering a question and stopping there.

What It Handles Well Today

On well-defined, high-volume call types - appointment scheduling, order status, account updates - conversational AI voice agents are reported to reach 60-90% containment, resolving the interaction without a human, according to independent analyses of production deployments. That's a meaningful share of contact center volume that no longer needs to queue for a live agent.

The Model Is Hybrid, Not Replacement

A 2025 Gartner poll of 163 customer service leaders found 95% plan to keep human agents while using AI for routine volume. A separate 2026 industry benchmark found that 76% of CX leaders have formalized a split where AI handles routing and availability while humans manage the complex, emotional, or high-stakes interactions. That's not a hedge - it's the operating model that's actually emerging at scale.

Where It Still Falls Short

Anything emotionally charged, highly regulated, or genuinely novel - a contested claim, a retention save call, a complaint that doesn't fit a known pattern - still needs a human. Agentic AI is good at executing known workflows quickly. It's not yet good at the judgment calls that come up when a situation doesn't match any workflow you've built.

A Realistic Timeline

Gartner projects agentic AI will be capable of resolving 80% of common service issues by 2029. Read that as it's written: a multi-year curve most organizations are still early on, not a capability you either have or don't have today.

Where to Start

• Pick a narrow, well-scoped use case with clear, repeatable steps - not your most complex call type
• Keep a fast, obvious path to a human for anything outside the AI's scope
• Measure containment and satisfaction together - a high containment rate with declining satisfaction means the AI is closing calls, not resolving them

The organizations getting real value from agentic AI right now aren't the ones with the most ambitious rollout. They're the ones who scoped it narrowly enough to actually measure whether it's working.

Most industries measure contact center performance across a high volume of routine, low-stakes interactions. Insurance is different. Policyholders typically contact their carrier only a handful of times a year - at purchase, at renewal, or when filing a claim - and each of those interactions carries outsized weight in whether they stay.

Why Insurance NPS Runs Lower Than Other Industries

CustomerGauge's insurance benchmarking puts the industry average Net Promoter Score around 35 - lower than many other service industries. Research on NPS drivers has found that in health insurance specifically, the strongest correlations are with a "painless claims process" and the sense that the company "acts in my best interest." In other words, NPS in insurance is largely a referendum on how the contact center handled someone's worst moment, not their best one.

The KPI That Matters Most: Claims Experience

Research from CX analytics firm Convin found that when policyholders experience smooth claims processing and responsive support, renewal likelihood increases by 35%. That single number should reframe how insurance contact centers prioritize their KPIs - claims-adjacent quality isn't a support metric, it's a retention metric.

KPIs to Track Beyond NPS

• First-contact resolution on claims calls specifically, not blended across all call types - a claim that requires three callbacks erodes trust faster than a routine billing question that does
• CSAT measured at claims resolution, not at first contact, since the emotional stakes (and the CX risk) peak at resolution
• Average hold time during high-volume claim periods (after a regional weather event, for example) - this is when abandonment and frustration spike hardest
• Customer Effort Score at renewal - a renewal that requires the customer to re-explain their policy history is a warning sign, not a formality

Where AI Fits, Carefully

AI voice agents and automation are well-suited to routine insurance contacts - coverage verification, payment status, simple policy questions - freeing live agents for claims calls, where empathy and judgment matter most and where the stakes of getting it wrong are highest. Automating around a claims call, not automating the claims call itself, is generally the safer place to start.

The Takeaway

Insurance carriers don't get many chances to prove their value to a policyholder. The contact center KPIs that matter are the ones measuring what happens during those few chances - not the volume metrics that matter more in higher-frequency industries.

Every contact center leader knows long hold times are bad for the customer experience. Fewer have run the actual math on what abandoned calls cost the business - and the number is usually bigger than expected.

What a Healthy Abandonment Rate Looks Like

Call abandonment rate measures the share of inbound calls where the caller hangs up before reaching an agent. Contact center benchmarking firms including ICMI and SQM Group generally place a healthy range at 5-8%, with anything sustained above 8-10% flagged as a problem worth investigating.

Why Customers Actually Hang Up

It's rarely one thing. The most commonly cited drivers, per contact center analytics firm Balto, are long unexplained hold times, confusing IVR menus, and no visibility into queue position or expected wait. Customers don't need a fast answer as much as they need to know one is coming.

The Revenue Math Behind the CX Problem

A healthcare call center analysis found that a 7% abandonment rate on 2,000 daily calls works out to roughly 140 abandoned calls a day - and, in that specific study, an estimated $45,000 in daily potential revenue loss tied to slow average speed of answer. The exact dollar figure will vary by industry and deal size, but the mechanism is universal: every abandoned call is a customer who needed something and didn't get it, and some percentage of them won't call back.

Fixes That Don't Require a System Overhaul

• Queue position and wait-time announcements - tell callers where they stand instead of leaving them guessing
• Callback options - let customers keep their place in line without staying on hold
• Smarter routing - get callers to the right agent (or self-service option) on the first attempt instead of transferring them into a longer wait
• Reduce the calls that shouldn't need a human at all - simple status checks and routine requests are the easiest volume to shift to self-service or AI voice agents, which shortens the queue for everyone else

The Takeaway

Hold time isn't just a satisfaction metric. It's a queue of customers deciding, in real time, whether staying on the line is worth it. Every improvement to that math shows up as fewer abandoned calls - and fewer abandoned calls are fewer customers you have to win back later.