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AI conversational lead sources

People buy cars with emotion. The decision to purchase is influenced by the way both the vehicle and the customer experience at the dealership makes them feel. Generally, the more positive emotions a buyer feels throughout the buyer’s journey, the higher their intention to purchase.

Sales reps with higher emotional intelligence, also called emotional quotient (EQ), generate double the revenue. For these reasons, emotional intelligence is arguably the most important skill salespeople need to hone. Emotionally intelligent sales reps interpret other people’s emotions and act appropriately, contributing to a personalized and empathetic customer experience. They could, for instance, detect when a lead is having doubts without being told and respond by offering additional support.

Sales AI gives sales reps the time they need to build emotional connections with prospects, such as getting to know them more intimately and having the flexibility to respond when needed. Sales reps typically spend more than half of their time on repetitive tasks that don’t directly impact revenue like data logging and chasing non-responsive leads. AI models, whose forté is replication and automation, can automate many of these tasks and reduce the time sales spend on them by as much as 40%.

As more people are shopping online, data is coming in thick and fast. With such a radical shift in the way customers shop compared to a decade ago, dealers are faced with high volumes of data from multiple channels and sources. It’s no surprise that they struggle to streamline the influx of data and make useful analyses.

Fortunately, AI models can tidy up the process by doing the painstaking groundwork of collecting and organizing marketing and sales data. Unlike humans, AI is capable of processing large volumes of data quickly.

Sales people will be required to make sense of the data insights that AI presents. For example, AI algorithms can cluster leads based on data variables such as lead source (website, third-party), demographics, and vehicle type. In this case, sales people would need to interpret any trends and correlations, say, people from a certain geographical area prefer large vehicles. In short, the more comfortable sales reps are with analyzing AI data, the more they will learn from their sales data.

While data analysis is a crucial part of the sales job, taking decisions based on data is even moreso. Salespeople will need the skills to put their analytical observations into action.

Armed with powerful new insights into lead profiles, conversion rates, and other sales data generated by AI models, salespeople no longer have to act on a hunch — they have the tools to make better informed decisions than ever before to improve their sales results. Skills required here include the ability to assess options, weigh up risks, and imagine creative solutions.

An example of creative problem-solving involves advanced conversion insights. If AI models reveal that certain leads convert better than others, sales teams can address this finding in several ways. They could choose to delve further into the data to find out why. They could choose to focus more time on these leads over others. They could run an initiative to attract a higher volume of this kind of lead.

Where AI reveals poor conversion rates, sales teams may choose to increase the frequency of follow-ups or make more relevant suggestions per customer segment.

While AI models can generate highly accurate results, they can perform even better when sales teams are involved in their training. With first-hand knowledge of sales tasks, salespeople are uniquely positioned to assess the quality of AI responses and even show AI how to best respond according to the situation and improve the accuracy or results.

This is the premise of Superhuman, a Matador feature (in beta) that improves the relevancy of responses to leads. The Superhuman AI model uses Natural Language Understanding (NLU), a subset of Natural Language Processing (NLP), to identify questions and suggest a range of responses. Experienced sales execs review the responses to select the most fitting one for a particular scenario, ensuring that the conversation flows just like a human-to-human conversation.

The idea that AI will replace humans seems ironic when, in fact, AI allows and even encourages sales teams to delve further into their humanity. AI can automate low-value sales tasks and reveal business insights much quicker and with more accuracy than even the best sales exec could manage. This means that salespeople can call on soft skills essential for human connections, such as their emotions, analytical and creative intelligence, and their collaboration skills.

The most successful salespeople of all have not only exceptional soft skills, but also the technical ability to get the best out of the powerful AI tools at their disposal. When sales meets AI, the results speak for themselves.

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