How a Seasonal Retailer Cut Average Wait Time by 44% Through Peak
44% drop in average wait time
About this case study: results are from a real Salamtalk deployment. The customer’s name is a pseudonym and their logo is withheld under a confidentiality agreement. The metrics below are reported as measured.
The situation
ShopSphere Global runs a seasonal e-commerce contact center that is lightly staffed for most of the year and scales sharply around peak retail events, Black Friday chief among them. The previous contact center platform was sized for average volume, not peak, which meant every seasonal spike exposed the same weaknesses.
- Queues backed up within minutes of a peak starting. The platform could not add capacity quickly enough to match sudden demand.
- Channels were siloed. Phone, chat, and email queues were managed separately, with no shared view of a customer’s history across channels.
- Supervisors had limited visibility. Coaching happened after the fact, from call logs, rather than in real time during a live spike.
What they needed
ShopSphere needed a contact center that could flex capacity up for short, predictable peaks without being sized — and paid for — at peak levels year-round. Omnichannel queueing was a firm requirement, as was a CRM screen-pop so agents could see customer and order history the moment a call connected. Supervisors needed real-time monitoring and coaching tools they could use live during a spike, not just in post-event reporting.
What we deployed
| Requirement | Implementation |
|---|---|
| Elastic capacity | Burst capacity for seasonal peaks, scaled up ahead of Black Friday and scaled back after |
| Queueing | Unified omnichannel queue across phone, chat, and email |
| CRM integration | Screen-pop of customer and order history on call connect |
| Supervisor tools | Real-time monitoring and live call coaching during peak periods |
| Reliability | Geo-redundant routing, 99.9% uptime SLA |
| Integrations | Connected to ShopSphere’s existing CRM via Salamtalk’s integration layer |
The CRM integration was the piece agents felt most directly. Rather than looking up an order manually while a customer explained their issue, the relevant account and order history appeared automatically as the call connected.
How the peak scaled
- Baseline contact center configuration built and run during a normal-volume month to validate queueing and CRM screen-pop.
- Capacity plan agreed ahead of Black Friday, based on the previous year’s peak volume plus a margin.
- Additional seasonal agents onboarded onto the platform in the two weeks before peak, using the same queue and screen-pop setup as permanent staff.
- Supervisors ran live monitoring throughout the peak weekend, reassigning agents between queues as call and chat volume shifted hour to hour.
- Capacity scaled back down to baseline in the week following peak.
Supervisors used the real-time view to spot a chat queue backing up on the Saturday after Black Friday and moved agents over from phone support for several hours, something that was not possible to do responsively on the previous platform.
The results
- 44% drop in average customer wait time during peak, compared with the prior year’s Black Friday
- Omnichannel queue gave agents and supervisors one view across phone, chat, and email instead of three
- Supervisors reassigned agents across queues in real time during the peak weekend
- Capacity scaled up for the peak event and back down afterward, rather than being held at peak size year-round
The wait-time improvement was concentrated in the first 48 hours of the peak event, when the previous year’s queues had backed up the most. Supervisor ability to shift agents between channels in real time was the main contributor, alongside the added capacity itself.
What was harder than expected
Forecasting the right amount of burst capacity was not an exact science. ShopSphere based its capacity plan on the prior year’s peak, but volume patterns shifted enough that chat demand ran higher than phone demand for part of the weekend, which the initial plan had not weighted correctly. The flexibility to reassign agents between queues in real time compensated for this, but a more accurate channel-level forecast would have reduced the need for last-minute reassignment.
Seasonal agent onboarding needed more lead time than planned. Bringing on temporary staff two weeks before peak worked for platform familiarity, but screen-pop and CRM conventions took closer to three weeks for newer agents to use fluently under pressure. ShopSphere has since moved seasonal onboarding earlier for the next peak cycle.
Next steps: see contact centers for omnichannel queueing, integrations for CRM screen-pop setup, or talk to our team about planning for seasonal peaks.