<strong>Illustrative example.</strong> This engagement is fictional and exists to show format and tone. Replace it with a real case study, with written client permission, or relabel this section before publishing.
Headline: Handling time down 34%, and a peak season with no integration failures At a glance: Multi-channel retailer · 3.1m orders/year · Service Cloud + Data Cloud · 18 weeks
The problem
Agents opened four systems per contact: CRM, order management, courier tracking and returns. Average handling time was eleven minutes, and roughly a third of it was navigation and re-authentication. The previous peak season had also produced a 40-hour integration outage during which order data stopped flowing entirely.
What we found
- 62% of contacts were “where is my order” or “I want to return this” — both fully automatable.
- Guest checkout produced an average of 2.7 records per repeat customer.
- The order integration was a single synchronous interface with no queue, no retry and no alerting.
- Returns were processed by email, with no cycle-time visibility.
- Knowledge articles existed but averaged 19 months since last review.
Order, delivery and returns data surfaced directly in the console via a mix of external objects and cached integration · Identity resolution in Data Cloud across guest, account and in-store purchases · Self-service order status and returns initiation on Experience Cloud · Integration rebuilt with queueing, back-pressure, retry, dead-letter handling and alerting · Knowledge restructured around the top 20 case drivers with a quarterly review cycle · Peak readiness testing at 3× projected volume.
01 · Weeks 1–3 — Driver analysis and baseline measurement. 02 · Weeks 4–7 — Integration rebuild, with deliberate failure injection in testing. 03 · Weeks 8–11 — Console redesign and build, with two agent test cohorts. 04 · Weeks 10–13 — Identity resolution (parallel workstream). 05 · Weeks 14–16 — Self-service portal and knowledge remediation. 06 · Weeks 17–18 — Peak load testing and rollout.
Results (measured across the following peak)
| Metric | Before | After |
|---|---|---|
| Average handling time | 11m 02s | 7m 18s |
| Systems opened per contact | 4 | 1 |
| Contacts deflected to self-service | 4% | 27% |
| Peak-period integration downtime | 40 hours | 0 |
| Records per repeat customer | 2.7 | 1.1 |
| CSAT | 3.9 / 5 | 4.4 / 5 |
What we’d do differently
We rebuilt the integration before the console. That was right technically, but it meant agents saw no benefit for seven weeks, and early goodwill was harder to sustain. A visible small win in week two would have helped.
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