If you’re looking for solid numbers that support the effectiveness of live chat customer engagement and revenue potential, look no further than our recent conversation with Dean Shaw, Global Chat Program Manager at SAS. A provider of analytics software and solutions for business, SAS has been making sense of the toughest business problems for decades. In Part One of our interview series with Dean Shaw, we talk about chat as essential to any omnichannel engagement strategy, and how to support customer contact agents to optimize performance.
RB.AI: Let’s start with the basics of the SAS contact center, such as average deal size, number of customer contacts as a whole, customer contact average per company, number of employees, etc.?
DS: The SAS Customer contact center is a global one, providing customer support for North, Central, and South America, EMEA, and APAC (China, Malaysia, Hong Kong, Philippines, Australia, New Zealand). This is done through three hubs located at SAS headquarters in Cary, North Carolina; Dublin, Ireland; and Manila, Philippines. Our global support continues to expand as we add countries where it’s feasible to do so. Each country also has informal customer support if they are not covered by one of the three hubs.
Our customer support strategy focuses on providing customers with their ‘channel of choice’ and includes, social, phone, email, contact request form, and live chat customer engagement. In our hubs, chat and social account for the majority of customer engagements, with chat itself accounting for about half of the engagements.
Interestingly, neither of these channels existed for us just a handful of years ago and their popularity underscores the importance of being where your customers are. When we first launched our chat and social support channels, we saw very little cannibalization of other channels indicating that we had been missing out on a whole segment of customers and prospects that may have needed assistance but weren’t going to use phone, email, or contact request forms to get it. We also think that social and chat are more suited to younger generations who are unfamiliar with dialing 1-800. In fact, our engagement volume was up ~22% in 2017 vs. 2016.
We can’t disclose deal sizes, but I can tell you that chat is a very effective lead generation channel for inbound engagements. This is based on volume, lead conversion, and richness of engagement information when leads are passed to inside sales. Live chat customer engagement to leads is around 7%. We also know that our site bounce rate is 62% so we feel like offering a simple way for a site visitor to talk with us helps prevent us from losing them completely. Finally, our CSAT for chat is 92%, so we also know site visitors appreciate the support.
RB.AI: You’ve been able to transform SAS from a customer contact center into a ‘revenue center’ using data analytics and strategy. This is our big push at RapportBoost.AI. We show brand-conscious companies that live chat can increase sales, and help them generate revenue through effective communication. Could you discuss some of the strategies you engaged in to support this transformation?
DS: We initially established chat to provide pure customer support. We had no lead generation expectations – we didn’t even measure it. However, it quickly became clear that even though we were called the customer support team we were sending a lot of leads to inside sales via live chat customer engagement and other channels. So we quickly started measuring those KPIs as well. They included engagement to lead, lead to qualified lead, pipeline amount (quantity and dollar amount), and sales (quantity and dollar amount), and others. We also added lead generation to our chat strategy and tactics alongside customer support. For the latter, our KPIs included CSAT, Customer Effort Score, Net Promoter Score, response time, availability, etc.
As an aside, you’ll notice I didn’t include total length of chat conversation in our KPIs. The mandate we give to our chat reps is, make the visitor happier when they leave than they were when they arrived. If you can do that in 30 seconds, that’s great! But if it takes eight hours, that’s fine too. We’ll go get you lunch while you work with them. Handle time metrics aren’t customer focused. They just put pressure on the customer support representative to watch the clock rather than to solve the problem. We know that if we train customer support representatives well and tell them not to dwell on non-business related discussion, they’ll complete the chat session quickly and to the customer’s satisfaction.
RB.AI: Interesting. So do you track handle time?
DS: Our current chat handle time is 11:27, but we use this metric for coaching rather than for punishment or reward. In my opinion, many companies are a bit backward when it comes to supporting customer support agents. We have team goals for KPIs, not individuals goals. When we made that switch the morale and collaboration that occurred among the team skyrocketed, and our support KPIs improved. We still monitor individual KPIs but use these metrics for coaching exclusively.
The numbers are in – live chat customer engagement is integral to omnichannel customer support. But as with any customer contact channel, there’s an art to its implementation. Customer contact agents benefit from informed coaching, and brands benefit from using the language that best speaks to their customers.
Contact the team at RapportBoost.AI for live chat agent training solutions, and leverage your live chat channel into sales.
As global chat program manager for SAS, Dean leads SAS’ Chat Program that, in addition to maintaining ridiculously high CSAT scores, also acts as a lead generation and chat analytics machine. Dean began his digital marketing story with americangreetings.com at a time when Herman Miller chairs and foosball tables defined you as viable venture capital target. He continued on to the mobile industry with Motricity when the StarTAC was the coolest mobile device on the planet. Following that, acted as a digital analyst at SAS capturing the impact of web, mobile, and social media on the digital experience. He also measures everything as though his life depended on it.