In part two of our interview series with Dean Shaw, we talk in detail about live chat lead generation and using voice of customer data to optimize live chat. Dean is Global Chat Program Manager at SAS, a provider of analytics software and solutions for business that’s been making sense of the toughest business problems for decades.
RB.AI: Earlier you stated an impressive fact, that chat is a very effective lead generation channel for inbound engagements at SAS. What strategies do you use to drive live chat lead generation? How has your chat channel improved leads?
DS: Once we discovered we could drive significant and highly qualified leads we started to focus on optimizing that effort. We started by looking at conversion rates by page. Not surprisingly, the high conversions tended to be on product pages – the ‘money pages’ as we like to call them. We made sure on-demand chat tabs were highly visible on-desktop and mobile and constantly played with triggers for proactive chats to find the right balance between helpful and annoying. We did A/B testing on custom invites to make them congruent with the messaging on the page they were presented on. We also worked with the outbound teams to target marketing campaigns that drive people to those high volume conversion pages. They included pages like our “How to Buy” page, “Analytics-Pro” page, price request page and many others. We also looked at conversion rates for less traveled pages and targeted those with high conversion rates. For example, “If you can get more people to the SMB page we can convert them at a 46% rate.”
We also believe in training customer support agents so that they are effective not only in getting visitors the content they need, but also looking for potential lead opportunities. This means the customer support representative isn’t just directing the customer to a white paper that’s part of the knowledge base; they’re also offering to pass them to an inside sales person for a deeper conversation, or to a video that requires registration, for example. Training customer service agents is the key to live chat lead generation, which for us, means fostering the conversation rather than focusing on how quickly it’s completed.
We also became obsessive about voice of customer data. Using text analytics we looked for trends in the transcripts to give us clues as to what we were doing well and doing not so well. We would pass those insights to stakeholders to address. Sometimes it’s not even about engagement, it’s as simple as making a page more clear. Traditionally you would just design a page the way you thought was best, which often meant best for the company, not necessarily for the page visitor. Many companies might do focus groups where they let twelve people who may or may not even be customers or prospects determine the direction. Often times these people are more interested in getting paid to participate and a free lunch, and in the end, you listen to the two loudest people in the room. On the other hand, by analyzing transcripts, you are basing insights on thousands of people rather than just twelve, providing a much more democratic view of the customer experience. After all, these are people on your site, giving you free feedback without even knowing it. When this data is aggregated, you get a very clear picture of the hurdles your visitors experience in completing their objective on your site. Used properly, you are able to continually improve the site experience and drive CSAT and live chat lead generation.
RB.AI: Could you shed some light on what optimization means for SAS, on several different levels i.e. scheduling, chat rep training, reviewing chat transcripts?
DS: In short:
- We invest in ongoing training of our operators. This along with the sheer volume of engagements makes them the smartest people on campus.
- We have daily communication huddles on campaigns and company events that we may need to be prepared to support.
- We aim for 95% availability to ensure that we always have someone to talk to a customer.
- Using web analytics we determined that extending our hours until 8 pm EST in the United States had value both in terms of volume and lead generation. We’ve gone from being a 9-5 shop to an 8-8 shop. We have also experimented with Saturday hours. On a related note, we are now turning some of our GEO silos from vertical to horizontal so that the Dublin team can handle our early US traffic and we handle some of the EMEA late traffic. We will do the same with the APAC region. In this case, the only requirement was English being the support language.
- We do regular team chat reads where we review chats that went well and chats that didn’t go so well. The transcripts are anonymized since the point is not to malign or punish individual reps, but rather to improve engagements. Interestingly enough, in a supportive team environment, the representative will often say, “Yeah, that was me, I really screwed it up.” Of course, there’s no punishment for the individual rep, just opportunity for improvement.
Optimizing the funnel with A/B testing, adding attention to web pages with the highest conversion rates, and using customer data to inform customer support center operation are crucial strategies for driving live chat lead generation. In case you missed it, check out part one of our interview series with Dean Shaw for tips on live chat customer engagement.
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.