Before starting Idiomatic, I founded EAT Club, now the country’s largest online corporate lunch delivery company. In our first year, I personally fielded every customer service email and call, showering each customer with attention.

Along the way, I got to know hundreds of our early customers. I learned their names, where they worked, and their favorite meals. Importantly, I learned what they loved and hated about our experience, allowing my co-founder and I to focus on fixing the largest pain points.

Our happy customers spread the word, and the business grew. But, we quickly learned that my original strategy “do whatever it takes” doesn’t scale for large customer support teams. The dual challenges we faced were maintaining high support quality while controlling costs.

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These are growing pains that any service organization scaling from 5 to 50 to 500 agents has to overcome. Progress on one often comes at the detriment of the other. At Idiomatic, we work with great customer support organizations that have managed to simultaneously raise service quality and cut costs. The secret is constantly improving by learning from customer interactions.

The best way of managing customer support costs is for customers to not have problems in the first place.

As wonderful as your customer support agents are, your happiest customers are the ones that never have to talk to you. The best customer experiences just work with no unnecessary friction.

While no product or service is perfect, leading companies continuously monitor top contact reasons and complaints. Their product and operations teams actively work to fix the root causes of customer complaints, and when they’re successful, those types of complaints disappear. Over time, iterating on this process results in a refreshingly smooth customer experience, low contact rates, and high customer satisfaction scores.

To identify and quantify top customer pain points, companies tag support tickets with granular user issues. To start, they do this in-house, but a technological solution like Idiomatic can be very helpful at scale. My co-founder Chris recently wrote an excellent primer on ticket tagging best practices.

Agents need a smart playbook that fits the specific customer problem.

Whenever I call my cable company, the agent always asks me to unplug my device, wait 10 seconds, and plug it back in, even when it’s obvious that won’t fix my problem. This is infuriating because it feels like the agent wasn’t even listening to me and was just blindly following a checklist. Many modern companies try to avoid this trap by asking agents to use their best judgement.

The customization strategy is fine early on but breaks down at scale; depending on which support agent handles the customer’s case, wildly different outcomes can occur. This inconsistency is bad for the customer and stressful for the agent.

Training a team to provide consistent service is hard. Each time new a support case opens, four things need to happen:

  1. support-process-final
    The Process of Support

    the agent reads the ticket to understand what the customer is experiencing

  2. the agent diagnoses the actual problem by checking internal systems or soliciting more information from the customer
  3. the agent chooses and implements the solution
  4. the agent closes the loop with the customer

For an inexperienced agent at a complicated business, there is ample room for error in this flow. The agent could misinterpret the problem, misdiagnose the root cause, or choose a poor solution, all of which leads to longer resolution times, frustrating the customer and costing the business time and money.

The customer service operation model that we’ve seen consistently deliver great service at scale works the following way: new support cases are rapidly classified and routed to an appropriately experienced agent along with a playbook for diagnosing and solving that specific user issue. That playbook is drawn from prior cases dealing with the same specific user issue that resulted in high customer satisfaction. This way, the agent can confidently speed through the diagnosis and solution steps, and focus on having empathetic interactions with the customer.

Putting this model in place requires substantial data engineering, human case routing, and knowledge base management that makes it seem like a distant holy grail for most customer service organizations. That’s why here at Idiomatic, we’ve built artificial intelligence technology that understands the customer’s problems to streamline the deployment of this model.

To recap, listening to customers is key to scaling a customer service organization because it offers you two key abilities:

  1. Fixing the root causes of why customers contact support in the first place is both cost effective and creates a better customer experience.
  2. For the remaining issues, arm your agents with a smart playbook that streamlines issue diagnosis and solution.