A guest blog by Tony Medrano, CEO of RapportBoost.AI
The idea of consultative, or conversational, selling means engaging prospects and customers in an open and free dialogue that ultimately identifies opportunities faster and with greater effectiveness than traditional acquisition models. This occurs mostly on websites where live chat agents greet visitors and ask how they may assist them in finding the information they seek.
Good reasons exist to employ this lead nurturing strategy. Reaching out to a contact while they’re in the midst of evaluating offerings will shorten sales cycles and increase conversion rates far more than the standard web lead form that transmits an automated email followed by a live call back a day or two later. Conversational selling, if executed correctly, also enhances the personal engagement, improves a sales department’s emotional quotient, and leverages the adage that people do indeed buy from people. CloudTask coins this well in its “5 Things I’ve Learned While Using Sales Chat” blog when discussing the power of proactive outreach.
Moreover, the company accurately points out in its guest blog by Tom Williams, Co-Founder, and CEO, DealPoint, that consultative selling, deployed at the time when prospects seek advice and counsel, will make less effort for them in obtaining the answers they seek. “Anytime you can reduce work for your prospects,” he said, “you’re in a better competitive position, and the deal is more likely to close successfully.”
Validating these lead generation approaches are industry studies that show the consumer shift away from social media and towards messaging apps. eMarketer predicts that in just one year from now, 65 percent of the global population will use messaging apps. Today’s online shopper wants a fast response time to their customer service query, and a friction-less way to initiate support. Forrester reports that 55 percent of adults will abandon online purchases if they can’t find a quick answer to a question, with 77 percent stating that good online customer service is the most important thing a company can do for them. Connecting with website visitors through live chat also takes less time and human resources than phone support.
Moreover, a Zendesk Benchmark report indicates that 92 percent of chat conversations receive a favorable satisfaction rating. Online retailers that listen to their customers’ requests for the convenience of purchasing with human-assisted online chat will undoubtedly benefit.
A plethora of offerings now exists to service this growing need from different angles, including Drift, and Gong.IO. These services work toward enhancing the customer experience through live chat, email or voice, and in such a way that improves the dialogue between companies and prospects that convert to additional customers. The systems all share a common theme using the right words at the right time to trigger a buy. Drift notes in its blog “How to Write Sales and Marketing Emails That Get Replies and Start Conversations” the need to keep marketing and sales discussions genuine, even if in so doing companies need to depart from their “Professional Voice.”
As necessary, though, marketers must understand that the NUMBER of words used in conversation can also impact conversion rates as much as the word choice itself. Carry on the dialogue for too long, and recipients will get lost in the process. Herein lies the secret to live chat. At its core, this critical sales channel must appropriately balance the words and their usage against their ability to stay succinct.
You also don’t want to be too vague as this might have the customer feel their problem isn’t being addressed properly. The occasional use of the “was this response clear for you or does this make sense” answer makes identifying whether or not your live chat is effective.
We see this in clients that use our RapportBoost.AI Conversational Analysis Platform-as-a-Service offering, where the number of words per message can determine the degree to which prospects will convert to sales, high customer satisfaction scores, average order size, and other critical revenue and profitability metrics. In the case of Jenny Craig, one of the largest and most respected weight loss brands, RapportBoost’s conversational analysis platform analyzed four months of live chat data to come up with the optimal word count that drove the most dollars. From there, our dashboards showed where each chat agent fared in comparison; a quality assurance management report if you will.
The analysis aligned well with the company’s consultative selling and television marketing campaigns designed to drive traffic to JennyCraig.com where visitors can chat with live agents. Armed with an increased level of emotional intelligence, the agents worked to build rapport with visitors in order to book an appointment with a sales agent so that the visitor would sign up for a membership. In just three weeks after implementation, the platform identified performance initiatives that helped increase Jenny Craig’s chat conversion rate by 10 percent. Four months later, that same metric rose to 37 percent while maintaining the same levels of quality and customer satisfaction as before. Also, the company’s live chat team increased operational efficiency by raising their capacity to handle more concurrent chats and decreasing their average time per chat. Most important, Jenny Craig’s customers were more engaged and had more fun.
Of note, platforms like ours that leverage artificial intelligence can serve chat agents well, but only by augmenting, not replacing, them. Through deep learning, natural language processing, and multivariate analysis, we're able to analyze more variables and more extensive data sets than is humanly possible to help agents perform better at their jobs. The goal of these systems should focus on arming humans with information they can use to engage the customer more effectively. We've discovered that the very best chat agents aren’t the ones who are naturally gifted at charming the customer. They’re the ones who possess superior situational awareness and defer to the algorithm in certain circumstances and their instincts and experience when different situations require different tactics. The combination of human AND machine once again beats either one alone.
About the Author: Tony Medrano is CEO and Co-Founder of RapportBoost, provider of a conversational analysis platform for live chat that uses advanced machine learning and deep conversational analysis that empower organizations to guide their human customer success AND chat sales teams to build stronger connections with customers. He can be reached at email@example.com.
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