Analytics Manager, Marchex
Call analytics for sales is a powerful tool from a modern context. For companies looking to automate their sales cycle, call analytics and tracking could vastly improve how their sales reps engage with the customers and close more deals. We spoke to Erin Murphy, Analytics Manager at Marchex, to understand how the automotive and travel industries have embraced this emerging technology.
Tell us about your role at Marchex and the team/technology you handle.
I’m a Data Analytics Manager for the Marchex Institute, a sector of the company that focuses on data insights. As an analyst, I identify impactful or interesting trends that occur on consumer phone calls to businesses and provide these results to our customers and various stakeholders within the company. I primarily work with our Speech Analytics product which captures actionable intelligence from over-the-phone interactions, along with our call recording technology and Call DNA which transcribes and visually maps every phone call. Recent analyses that my team has published include our report on America’s speech trends, a travel advertising conversion rate analysis, and a call handling insights report for the automotive industry.
What is the state of Call Analytics for Sales in 2018?
As people begin to realize the importance of phone calls, which was recently demonstrated in a Forrester report, they will begin to realize how important it is to measure and optimize them. There are so many ways that firms are losing business due to how they’re handling their phone calls. Without call analytics, you don’t realize how your agents are losing customers, let alone how the top performing agents are winning customers. We are starting to see many industries realize how valuable these insights can be, from ensuring brand consistency to understanding how to improve the process of making an appointment or dealing with an awkward sales situation. The automotive and travel industries in particular have been quick to embrace the emerging technology. During the first quarter of 2018, we added more than seven new clients, including several real estate and health customers. It is clear that call analytics are critical for businesses to stay competitive and drive customer loyalty.
How do you leverage data to improve your various analytics products?
Marchex has many different teams who leverage data to improve our products, from using AI and machine learning to custom analyses of large data sets. My team and I are in a unique position of being power users of all of Marchex’s products and have an opportunity to work directly with clients. We analyze calls to find trends and then surface insights directly to our customers. If we see similar trends across industries and clients then we work with engineering to add new features to surface these insights in a more scalable way. Since launching in April 2017, 100 million calls, more than 400 million minutes and nearly four billion utterances have been analyzed via Marchex Speech Analytics—that translates into a significant amount of data that continuously makes our technology more accurate, intelligent and scalable.
What are the key takeaways from your recently published report on the anonymized call conversations in the US?
We analyzed more than 6.8 million calls placed by consumers to businesses across the United States and uncovered some fascinating trends in conversation patterns across America. For instance, people from more rural states like Wyoming, Montana and North Dakota tend to be the most talkative and polite, and Pacific North Westerners tend to be the least patient as they hung up more quickly after being put on hold. We also found that cursing increases as the day progresses. On average, cursing is least likely before 4:00 p.m., but then the curse rate on calls doubles after 6:00 p.m., jumping from three percent to six percent. Visibility into these types of conversation trends empowers businesses to not only improve phone interactions with customers but also tap into these insights to optimize marketing and sales efforts.
How could sales teams utilize these findings to improve their customer conversions?
This study is fun in nature, but it reveals a lot about how people communicate over the phone and provides practical insights into how agents can best engage with different customers. For instance, residents in the Pacific Northwest hang up 1.48% faster when put on hold, so regional store managers could advise agents to limit hold times to under 20 seconds. The Marchex Institute also found that low-performing agents actually tend to apologize more often—saying “sorry” 50 percent more often than agents who facilitated positive outcomes with customers. The distinction here is that agents should be empathetic, yet focused on the solution. Explaining what you can do to help and focusing on positive solutions keeps customers engaged and more inclined to convert. We also found that it’s best to avoid negative phrases like “No, I don’t think I can” or “No, that’s not right.” Agents with lower sales rates said “no” twice as often as the top performing agents.
To what extent can analytics further boost sales automation and intelligence?
One area we’ll see speech technology play a key automation role is agent interactions. For example, speech technology can provide insight into common customer intent, such as booking an appointment, which involves a common set of inputs— the type of appointment, estimate of cost, date, time, etc. With speech recognition technology, businesses can analyze the top customer inquiries and provide marketers with chatbot solutions to automate these interactions, rather than having a live agent. They also can respond to inquiries not just during business hours but 24/7, increasing their ability to increase sales volume.
With GDPR incoming and disrupting data management practices, what change to your data strategy have you made? How would it benefit your employees and customers?
How do you work with Data Science and AI/ML for better call analytics?
Marchex Speech Analytics leverages machine learning algorithms to analyze calls and predict the business impact of customer conversations in real time. It’s a technology that brings the intelligence of AI and big data analytics to organizations that rely on phone interactions with customers to drive revenue and strategic growth. In addition to accurate, real-time transcription, speech analytics needs to recognize colloquialisms of everyday speech, as well as detect tone and emotion. The more calls we analyze, the more intelligent data we have to teach our machines.
Thanks for chatting with us, Erin.
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