KEY RESULT
40% cost reduction
in customer support spend by month 3
Client: $1.4M/month consumer DTC brand on Shopify. 71% of WISMO calls resolved without escalation.
A $1.4M-per-month Shopify brand was drowning in "Where is my order?" calls. WISMO was about 62% of their inbound voice volume. The support team spent most of the day doing what amounts to a database lookup and a polite update.
What was the problem?
At $1.4M/month in revenue, they were processing hundreds of orders a day. Customers called to check tracking, confirm delivery dates, ask about returns, or verify order details. Every call looked the same: caller reads order number, agent pulls it up in Shopify, reads status, answers the question. 50+ times a day.
That meant 62% of support hours were going to a task that didn't need a person. At typical loaded support rates of $25 to $35 an hour, with a full FTE dedicated to voice, they were spending somewhere between $180K and $240K a year to read tracking numbers out loud.
The bigger problem was after 6 PM. Phones went to voicemail. International customers calling outside business hours got voicemail and no callback. Anyone ready to troubleshoot or start a return just couldn't reach a human.
How did ClearCall AI deploy?
We built a voice agent wired directly into Shopify's API. When a customer called, the agent asked for the order number or email, pulled the order live, and read back tracking status, expected delivery date, and return eligibility on the spot.
Simple WISMO calls the agent closed on its own. Returns, damaged goods, or anything that needed a person, it collected the details and handed off with full context already in the ticket so the customer wasn't repeating themselves.
It ran 24/7 and caught the after-hours calls that used to go to voicemail. We also connected it to the brand's shipping provider API so the tracking it read back was live.
What were the results?
Month 1: the agent closed 71% of WISMO calls without any escalation. The support team stopped answering routine tracking calls. Instead of 50+ lookups a day, they got only the calls that actually needed a human. Phone fatigue dropped almost immediately and the team started getting their day back.
Month 3: the capacity that used to go to WISMO had been redeployed to retention work — proactive outreach to at-risk customers, return follow-up, relationship stuff. Support costs dropped 40% (from about $220K to about $132K annually). CSAT ticked up at the same time, because customers were now getting answers in under 30 seconds at any hour instead of waiting for a business-hours callback.
Unexpected bonus: after-hours buying calls now had somewhere to land. Customers with sizing, materials, or shipping questions could get answers and actually complete the purchase instead of placing an order they'd later regret and return. The team estimated that saved them roughly $40K to $60K a year in prevented returns.
Why this worked
WISMO is about as clean an automation target as it gets. High volume, low complexity, all driven by data the brand already has. The agent didn't need to make judgment calls or do emotional work. It needed to query a database and read back a result. The data was clean, the Shopify API was reliable, and the agent behaved consistently from day one.
The real unlock was the shipping provider API. Customers got live, accurate tracking the instant they asked — better than what the support team was getting when they checked the same source. The agent ended up faster than a human could reasonably be.
The business win wasn't the cost save on its own. It was what happened after. Support went from transactional (answering questions) to relational (actually working on retention). That's the part the spreadsheet doesn't capture.
Client identity anonymized at their request. Outcome metrics validated against deployment telemetry.