The first support agent at your company knew most customers on a first name basis. They knew the history of every product change. The voice of the company developed around them. Customers raved about the service because it was friendly, personal and incredibly helpful. And, the company saw this agent as an incredibly important source of reliable customer insights.
Add a few more agents, and you start feeling the strain of providing the same level of personal service to every customer. Your customers begin to feel more anonymous, and training agents to the same level as the first agent becomes impossible.
Fast forward to opening your third office, 24/7 support with multiple products and the old way of doing things just doesn’t work anymore. Transferring knowledge through the grapevine, or even in a weekly support meeting can’t keep up with the demands of a mature organization.
But it’s not just the support team organization that’s become more complex. As your team has grown, so has the product and engineering teams. They’re likely shipping new releases every day. How does a customer support team support a product that is changing that quickly?
Complexity isn’t a problem that can be solved by adding more warm bodies in office chairs. In fact, adding more agents actually makes many of the problems worse. Knowledge and playbook management becomes more difficult as the team grows. Instead of continuing to hire, at some point, it’s better to do more with less.
With the right strategies, it’s possible to provide consistently excellent support to customers – even as your company grows. In this post, we look into how some companies are winning the battle against the effects complexity has on customer experience – without resorting to throwing more bodies at the problem.
Obsess over your Customer Contact Index
Your customer contact index is the average number of times each active customer contacts customer support in a given period (usually a month). It’s calculated by dividing the number of conversations by the number of customers. For example, if you have 100 customers, and receive 150 tickets during the month, you’d have a CCI of 1.5.
As your products become more complex, it’s natural for CCI to increase. Customers will need more assistance getting started, and there’s more opportunity for things to go wrong. But a higher CCI means more incoming tickets and your team will need to grow to keep up. Keeping CCI low allows fewer support agents to support more customers – scale!
The only way to scale customer service effectively is to reduce your customer contact index as you grow.
To reduce your customer contact index, focus on your biggest contact drivers. The best way to determine what’s driving customer contacts is through analyzing customer conversations. Natural Language Processing (NLP) and Machine Learning can help, but most companies will start by tagging incoming customer conversations.
Make the product more intuitive: feed insights back to your product development team to improve the usability of the product. As friction points are reduced, customers don’t need help as often.
Improve documentation and self service: identify questions that could easily be resolved with documentation, and ensure customers are able to find what they need, when they need it.
Reduce repeat contacts: customers shouldn’t have to contact you multiple times for the same issue. By implementing next issue avoidance techniques, you can keep the customer happy AND reduce the amount of incoming contacts.
Automation, but make it human
Machines are really good at analyzing large amounts of data. They are not, however, very good at empathy or problem solving in complex scenarios.
As you grow, it can be tempting to throw AI at customer support to deflect tickets through self service and chat bots. But complex products need human input to resolve.
In our AI for Customer Support blog post, we’ve explored why using AI solely as a cost reduction tool fails. As customers, we’ve all experienced the frustration of hapless chat bots, that don’t understand what we want, and can’t connect us to a human. At idiomatic, we believe that “AI systems for support should not result in poor customer experiences in order to reduce costs, nor should they avoid solving the hard problems inherent in fundamentally improving the customer experience and customer support teams’ workflows.”
Let the machines do what they are good at, and leave the human connections to humans. Machine learning can help customer support teams invest in the right workflows through analyzing customer conversation data. Automation helps your company find breathing room, so that you can dedicate more time to the human side of support.
Lean on Culture
When it comes to determining what “human” looks like in your company, Jeff Gardner, Director of Support at Intercom says it’s all about culture. “Culture beats strategy, culture beats everything. You’re going to have a culture whether you want to or not. Whatever that culture is, it’s going to trump whatever you say you want done. It’s important to double down on making sure that everybody understands it, everybody actually celebrates it when people do a good job, and call out when people fail or fall short of the culture.”
Developing a culture of empathy and customer centricity is key for distributed teams. As Jeff points out, when your team grows globally, at any one point in the day, someone will be asleep. It’s not possible to always be watching when everyone does, nor should you. Instead, it’s critical that every agent knows the values of the team – and is empowered to act accordingly. Keeping customer support personal, even as your company grows, relies on developing a culture that supports it.
Information becomes a precious commodity as you grow. With multiple offices, spread across multiple time-zones, it can be really difficult to communicate product and process updates. Getting everyone on the same page requires constant attention to documentation. Asynchronous, easily referenceable forms of communication become essential to ensuring nothing slips through the cracks.
If your internal documentation still lives in a series of Google Docs, or if you’re asking “what internal documentation?”, it’s time to upgrade your knowledge management processes. Ideally, there’s two things you need to look out for:
- Agents need to want to use it. That means it needs to be easily accessible, built into their workflows and searchable.
- Information needs to be up to date. Keeping documentation current is a big struggle for constantly evolving products and teams. The best solutions surface out-of-date articles and help your content team provide trustworthy information.
Guru is a knowledge management system that works within the tools you already use to automatically keep your documentation up to date and easily accessible. It’s particularly helpful for teams on Slack, because their integration allows you to search content right from your Slack channel. If the requested information doesn’t exist, Guru will prompt you to create and save the content so that it can be reused by the whole team.
Having (accurate, up to date) information at your agents’ fingertips reduces the strain of complex products. Guru agrees. “We believe that the knowledge you need to do your job should be brought to you directly in your workflow, where and when you need it,” states their website.
Taking the time to document important information as you grow is essential to managing complexity.
A playbook codifies the essential processes, workflows and “ways of doing things” that make your support team tick. A great playbook should be thorough and instructive, but flexible.
Dana Kilian, VP of Customer Service at Eventbrite shared with First Round Review how her team has scaled customer service through flexible processes that empower the agent to do their best work. “[We] provide the basic fundamentals our team needs to do a really good job with customers. The team is disciplined and aligned around providing a really great experience,” says Kilian. “That said, they have a lot of freedom to handle situations on their own.”
Keeping playbooks simple helps allow for the flexibility that complex products and teams demand. As Dee Hock, founder of Visa explains, “Simple, clear purpose and principles give rise to complex and intelligent behavior. Complex rules and regulations give rise to simple and stupid behavior.”
As DigitalOcean’s product line became more complex, Zach Bouzan-Kaloustian, Director of Customer Support realized their current structure wouldn’t scale with the product. They’ve now organized their support organization into vertical teams to specialize on each product. This way, they can develop deep knowledge and specific playbooks.
On the Support Leaders podcast, Zach explains that throwing bodies at a problem is almost always the wrong approach to scaling. Instead, teams need to look at implementing tools that make their existing team more effective. More agents means more complexity, which means more trouble down the road.
Scale customer support the smart way
Even as your company grows and your team and product become more complex, there are still ways to provide the same quality of service. But it doesn’t involve hiring more and more people to deal with the volume. It’s about using the team you have more effectively.
Finding ways to keep customer contacts low (in a customer-centric way) will enable your team to focus on what really matters. Integrating knowledge management systems into your workflow, enables your team to focus on what really matters. Finally, developing flexible playbooks that reduce complexity where possible, enables your team to focus on what really matters.
Because whether you’re a team of 1 or 500, the end goal is always the same: providing a well executed service experience for happy, satisfied customers.