How a Leading National Home Improvement Retailer Built Enterprise-Wide Performance Management Across Care, Sales, and BPO Partners

The Opportunity

A leading national home improvement retailer runs one of the largest omnichannel customer operations in retail — millions of conversations a year about products that range from a single replacement bolt to a multi-room remodel. Customers expect agents to know the catalog the way an in-store associate knows their own aisle. That bar is hard to clear on a single product line. Across thousands of SKUs, across hundreds of suppliers, across both internal teams and outsourced partners, it had become structurally impossible.

The operations leadership team had two interlocking problems. The first was a customer one: handle time was outpacing the line of business, but customer satisfaction (CSAT) was not where it needed to be. Customers wanted expertise — and they wanted it fast. The second was a frontline one. Supervisors were drowning in spreadsheets. By the time a coaching conversation happened, the agent was hearing about a problem that had been live for a week, and the supervisor was reading data out of a report instead of teaching a behavior.

The team set out to do two things at once: improve the customer experience on every call, and rebuild the operating model that supervisors used to actually develop their agents. The path to one ran through the other.

Choosing a Performance Management Platform Built for the Frontline

The selection process pitted AmplifAI against the incumbent — a large CX infrastructure player already embedded in the retailer's stack. On paper, staying with the incumbent was the easier story. In practice, the incumbent had been built for the back office: dashboards for managers, reports for QBRs, integrations for IT. It had not been built for the seven minutes a supervisor and an agent actually spend together in a 1:1.

AmplifAI's positioning was the opposite. The platform was designed to put performance data directly in the hands of the people who shape outcomes — the frontline agent and their direct supervisor — and to take everything that prevented coaching from happening (data wrangling, system swiveling, contentious conversations) off the table.

The retailer's call center performance management decision came down to a simple test: which platform makes the next coaching session better? They chose AmplifAI.

The 80-Agent Pilot: Daily Data Replaces Weekly Reports

The first deployment was deliberately small: 80 agents inside a single customer care group. The headline change was unglamorous and enormous. Performance data refreshed daily instead of weekly, and every agent could see their own numbers the same day the customer experience produced them — including, for the first time, the verbatim text from customer surveys about their service.

Three things shifted at once:

• Agents owned their own data. They no longer waited for a 1:1 to see what their week looked like. By Friday morning they had already self-corrected what Friday afternoon's coaching would have flagged.
• Supervisors stopped manufacturing reports. Previously, 30–40% of a supervisor's week disappeared into pulling, aggregating, and emailing performance data across multiple systems. With one source of truth, that workload collapsed.
• Coaching conversations changed shape. Before, agents arrived at 1:1s seeing their numbers for the first time — and pushed back. After, they walked in already knowing what the data said, and the conversation started where it should: on the behavior, not the scoreboard.

The retailer's culture is famously employee-centric. Their leadership team described the shift in supervisor-agent dynamics as one of the most visible cultural effects of the rollout — coaching meetings became easier, nicer, and more effective, because the data had stopped being a surprise.

Where the 4% Productivity and 20% CSAT Lift Came From

The retailer measured the pilot the way it measures everything: a controlled before-and-after across two equal windows. Ten weeks of operating data before AmplifAI launched, against ten weeks of operating data after agents and supervisors were live on the platform.

The two KPIs that mattered to the care team were average handle time and the rate of CSAT survey responses landing at the top of the scale. Both moved.

• Agent productivity, measured through AHT against the group's baseline, improved 4%.
• The CSAT survey rate — the share of customer interactions that produced a top-box satisfaction score — climbed 20%.

Those numbers were not the result of any one initiative. They were the cumulative effect of giving agents real-time visibility into their own performance and freeing supervisors to spend coaching time on the behavior that needed it, every week, every agent. The pilot produced enough proof for the team to do the obvious next thing: extend the same engine into a completely different program.

Extending the Same Engine Into Sales: $135M in Incremental Revenue

After the care pilot proved out, the retailer brought AmplifAI into an inside sales team — one of several specialized sales groups that sit alongside the core service organization. The objective changed from satisfaction to revenue, but the operating model did not. Daily data. Supervisor coaching focused on the next-best behavior. Agents owning their own numbers.

The analysis window was a single quarter — the first full quarter the sales team operated on AmplifAI after their ramp. The team comparing baseline to AmplifAI was 112 sellers at the start of the quarter and 114 at the end, so headcount was not the lever. The lever was what those sellers did with their time.

Conversion went up. Productive time went up. The economics of each conversion went up. Carried forward across the quarter at the team's new run-rate, the lift represented $135 million in incremental annual revenue from a single sales team — a comparison anchored against the same team's pre-AmplifAI baseline.

What made the result transferable, not just impressive, was that the operating model was the same one the care team had been running for months. The retailer had not bought two products. They had bought one coaching and performance management system and pointed it at a second program.

From Pilot to Platform: Scaling Across 10,000+ Users and BPO Partners

What started as 80 agents grew steadily. Customer care. Specialized sales. Then the rest of the retailer's contact center footprint — and, critically, the outsourced BPO partners handling overflow and program-specific work. Today, AmplifAI is the performance management layer for more than 10,000 users across the retailer's internal and outsourced contact center population.

Bringing BPO partners onto the same platform mattered for two reasons. First, the retailer's brand experience is the same whether a customer reaches an internal agent or a partner-staffed one — so the operating model that drives quality had to be the same. Second, performance conversations with BPO partners had historically been about reports and SLAs. With AmplifAI, those conversations became about agents and behaviors. The partner relationship became operationally identical to the internal team's: same data refresh cadence, same coaching prompts, same accountability model.

The retailer's director of operations process and strategy summarized the position publicly:

The frontline experience tracked the leadership view — supervisors on the platform for the long stretch of the rollout described the same shift in coaching dynamics, with agents arriving at 1:1s already aware of their own trends and ready to talk about behaviors rather than scores.

Independently Validated by an Industry-Leading Analyst

An industry-leading analyst firm — covering customer service and support technology — published independent research on the program. Their report described the same three operating principles the retailer had been running on for years:

• Performance transparency. On-demand access to performance data encourages accountability and accelerates communication around improvement areas.
• Supervisor next-best-action. Data-backed coaching suggestions help supervisors recognize improvements and follow up on missed opportunities — making limited coaching time count.
• Isolating supervisor impact from team baseline. Measuring the percent of coaching sessions that lead to agent improvement separates supervisor performance from raw team performance — and tells managers exactly which supervisors need development themselves.

The same research validated three prerequisites that the retailer had committed to from the first 80-agent pilot: data must refresh frequently enough to match the coaching cadence; it must be consolidated and pushed to the supervisor (not pulled from five systems); and it must be visible to the agent before the coaching session, not during it.

The published outcomes the analyst documented from this program:

The independent finding mattered more than any vendor-published number could. The retailer's program was not an internal anecdote anymore — it was an analyst-verified pattern other operations leaders could study and apply.

The Next Chapter: Auto QA and Customer Analytics

The performance management layer was the foundation. The retailer is now extending the same platform into two newer capabilities — Auto QA and customer analytics — that work with, not around, the operating model they've spent years building.

Auto QA automates the quality scoring of every conversation, not just the small statistical sample a manual QA team can grade. That changes two things at once. It makes coaching even more focused — supervisors see quality patterns across every customer interaction, not the four-or-five sampled ones. And it gives the agent total transparency: every call is reviewable, every behavior is visible, every coaching opportunity is grounded in a real conversation.

Customer analytics layers what customers are actually saying — verbatim, at scale — onto the same agent and supervisor dashboards. The signals that used to live in survey verbatims (originally surfaced in the first pilot) now extend across the full conversation set: emerging themes, root-cause categories, sentiment shifts that no longer wait for a weekly report.

What the retailer is building, at this point, isn't a coaching tool layered on a contact center. It's a single performance, quality, and customer insight platform — same data, same agents, same supervisors, same operating model — extended across every conversation, every program, every partner.

The journey is the playbook. Start with a focused pilot that fixes the coaching loop. Prove it on one program. Extend to the next. Bring the partners onto the same operating model. Then layer in the next generation of capability — quality automation, customer analytics — on top of the foundation. That sequence is how a 80-agent care pilot becomes the retail customer experience operating system for 10,000+ users across an entire enterprise.