Leverage AI to improve call center profitability
How proton.ai increased average order value by 20%.
Rolled out with a large medical distributor's customer service team. We implemented an up-sell/cross-sell program which increased average order value by 20%.
A large distributor in the medical space wanted to make call centers more profitable. Their customer service centers played an important role in keeping customers happy, but did not generate much revenue. They needed a way to transform these cost centers into moneymakers.
The distributor’s customer service centers are staffed by reps who take calls and orders from customers. The reps are very busy, and must take orders quickly so that other customers aren’t left waiting.
These customer service reps are uniquely well positioned to make sales because they talk exclusively to decision makers: customers that are willing and able to make purchases. But, because they don’t know their customer or what items they are likely to buy, the reps can’t capitalize on this opportunity. The reps talking to the right people — the decision makers — but they don’t have the tools necessary to make sales.
If reps could actively make orders happen, instead of passively taking orders that were already going to place, call center profitability would increase greatly. When customers call to place orders reps should not only complete requests, but also pitch additional products.
This process would be especially profitable given that no extra costs would be incurred. Reps are already on the phone with customers, and orders are already being shipped. If the reps simply encouraged customers to make a bigger orders, almost all of the gross margin would drop to the bottom line.
In order to make this shift, however, reps need an accurate recommendation engine that does not compromise their ability to field calls. Reps don’t need to know everything about every caller, they only needed an accurate source of products to pitch.
The company deployed Proton in call centers. This gave customer service reps access to an AI-driven recommendation engine that tells them which products callers are likely to buy.
Reps still take orders like normal when customers call. However, they now take the additional step of offering customers products suggested by Proton. This includes complimentary items — products that might “go with” past purchases”– or items due for reorder.
For example, when a customer orders latex gloves, Proton might suggest that the rep also offer the caller disinfectant spray. Or, if the customer is due to restock on swabs, Proton may suggest those instead, keeping the repeat order.
Regardless of the products pitched, the underlying strategy is to increase average order value (AOV). When customers place orders Proton helps reps increase profitability.
“With proton, customer service reps can make what seem to be well-researched up-sells and cross-sells at the click of a button; driving up our average order value"
Chief Operating Officer
Large Distributor Customer
Results and next steps
Reps and managers successfully used Proton to increase AOV. Proton users reported an AOV 20% greater than peers who did not use Proton.
Customer service reps enjoy privileged access to decision-makers. These reps, however, can only leverage this position to increase sales with the support of a good recommendation engine.
Reps care about AOV, because it indicates an ability to do more than just take orders. Customer service reps are never going to generate revenue by attracting new customers. That’s not their role. But they can greatly increase profitability by getting existing customers to spend more.
When effective reps increased AOV by persuading callers to make bigger orders, they generated revenue without increasing costs. Phone time remained unchanged, as does the number of shipments being made. However, as the increased AOV indicates, the distributor was making more money.
The distributor can further increase call center profitability by encouraging more reps to use Proton, and by eventually fully integrating it into their CRM system and rep protocol.