Responding faster to customer requests
Specialty retailer with online sales
Reduce first-response time without lowering satisfaction.
The retailer, which has 55 employees, received 2,400 requests a month. Order tracking and product questions overwhelmed six advisors, and a contractor charged for part of the handling on demand.
Approach
- 01
Frame
The director wanted to cut first-response time by 25% without lowering satisfaction. The project covered three frequent request types; disputes and refunds stayed with the advisors.
- 02
Investigate
I reviewed 800 requests, the contractor’s invoices and the service rules. I measured the full handling time, including corrections, separating simple requests from sensitive cases.
- 03
Explain
Two causes were compared: too few staff, or scattered information. Repeated searches explained delays more than the number of new requests did.
- 04
Build
We compared an improved FAQ, an assistant that prepares sourced answers and an autonomous agent, with the existing setup as the financial baseline.
- 05
Test
A six-week test split 400 comparable requests between two groups. The thresholds were 95% of answers accepted without major correction and a 25% reduction in full handling time. The test reached 96%, and full handling time dropped from 7 to 4 minutes.
- 06
Decide
The director chose drafts reviewed by the advisors. The pilot was run on a budget of $16,500, including $5,500 for strategy. The drop in subcontracting must be confirmed on the invoices before any expansion.
- 07
Steer
Each week, the manager tracks errors, satisfaction and the requests still billed by the contractor. A request type is paused if major corrections exceed 5% for two weeks.
Test results
What AI contributed
AI helped me group the request types and prepare the test. In the service, it suggests answers based on approved documents; the advisor validates each response before it goes out.
Business model (projection)
At steady state, 9,000 requests a year leave the contract, at $4 each, for $36,000 in avoided spending. The staff time freed up is not counted as savings. In the prudent scenario, only 4,500 requests leave the contract.
| Initial investment | $16,500 CAD |
|---|---|
| Annual gains | $36,000 CAD |
| Costs to subtract | $9,600 CAD |
| Net annual gain | $26,400 CAD |
| Simple payback | 7.5 months (at steady state) |
| Prudent scenario | $8,400 CAD net, payback in 23.6 months |
Annual projection built from the results of the engagement. It is not a guarantee of performance.
A comparable challenge?
Describe the decision to make and the data available. I will suggest an approach to prepare it and the evidence to gather before deciding.
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