Artificial Intelligence Gets Real
It’s still evolving, but AI is helping businesses learn new ways to improve their sales and their processes.
This is an excerpt from a Twin Cities Business Magazine Article. To read the full article click here.
Better consumer insights
Start with Coopet’s own company, Rambl. Officially launched in March, Rambl’s current product is “an AI-powered inside-sales phone system,” Coopet says. With Rambl, each sales call “is turned into a processable data stream using machine-learning techniques,” he says.
Most sales calls, Coopet notes, are not being processed or analyzed. When the sales manager wants to evaluate how well the caller is performing, he or she often listens in. The same is true of a new salesperson who needs to learn the ropes. That makes learning and training ad hoc, Coopet says. What Rambl’s technology promises is a more data-driven approach to determining what works on a call—the kind of wording, style of conversation, and type of product features that are most likely to appeal to certain customers. Rambl’s technology, in a sense, does the listening and picks out patterns in the salesperson’s patter that make for a successful or unsuccessful call.
Coopet sees Rambl’s market opportunity as just about any company that does selling by phone, particularly where it is engaged in high-volume dialing. Rambl’s technology also integrates with CRM (customer relationship management) tools such as Salesforce and HubSpot to streamline the salesperson’s data entry and logging, so salespeople can focus on their primary task, not administrative chores. The latter, says Coopet, can take anywhere from 10 to 20 minutes per call.
Because Rambl is rooted in machine learning, Coopet argues it will only get stronger as it learns what to listen for in spoken conversation. He notes that’s very different from written communications. “Five years from now, we believe that businesses will be able to search and learn from voice conversations as easily as email,” he says.
Rambl is a homegrown AI firm. Coopet co-founded Rambl after nearly 15 years at Minneapolis-based backup and security software company Code42, which he helped launch in 2001.
A newcomer to the local AI scene with origins outside the state is Cludo, a Copenhagen-based company that opened its U.S. office in Minneapolis in February 2017. Cludo has developed a site search and analytics platform that incorporates machine learning to continuously improve the site’s response to search queries, with a goal of improving customers’ online experiences as well as boosting website sales conversion rates.
In addition to making company websites more useful, Cludo’s technology also captures visitor data that is quite valuable, CEO Philip Andersen says. Machine learning and AI can give structure to this unstructured data, which, Andersen says, can help companies understand customers’ needs and purchasing habits at an increasingly deeper level.
With AI and machine learning’s capabilities for finding patterns in digital consumer data from purchases, social media, and so on, it’s not surprising that retailers and marketing firms have been exploring its uses. Their goal, of course, is to better target products to people who are most interested in buying them.
Andrew Eklund, founder and CEO of Minneapolis-based digital agency Ciceron, has been working with a variety of AI platforms. One of its key partners is St. Louis Park-based Equals 3 LLC and its Lucy technology, an AI-based “intelligent agent” powered by IBM’s Watson supercomputer. Lucy’s ability to parse large amounts of consumer data “helps us make more informed, faster media-buying decisions,” Eklund says.
Ciceron also uses AI to pick through online data to discover “how pockets of people are having conversations about brands,” Eklund says, and to learn the language that consumers actually use. For instance, Ciceron has numerous health care clients. To reach those clients’ customers and patients, the marketing firm needs to differentiate between how consumers talk about their health concerns and the terminology that physicians and nurses use. AI technology helps Ciceron sort through the conversations that consumers have so that the agency can address them in ways they can comprehend. That’s instead of “expecting everyone to have a medical degree to understand what we’re talking about,” Eklund says.
For marketers, there’s one notable drawback to AI. “We have several very large platforms, specifically Amazon and Facebook, that are walled gardens of data,” Eklund notes. “You can’t get information out of those systems.” And that closes off a vast amount of particularly useful consumer information.