Guide to using advanced analytics and AI in business applications
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Artificial intelligence is coming, but only companies that have laid solid groundwork are going to reap the rewards of this disruptive technology.
"It's like when you see a skyscraper: You're impressed by the height, but nobody is impressed by the foundation. But make no mistake, it's important," said Akshay Tandon, vice president and head of strategy and analytics at LendingTree Inc. "You have to have good data management to take advantage of AI."
LendingTree is investing heavily in customer analytics and AI projects designed to enable the online loan marketplace operator to sharpen its customer interactions.
Teams are currently using predictive analytics to better target marketing campaigns and to determine the financial products for which individual customers might qualify. Algorithms also score the likelihood of a customer accepting an offer.
Right now, a lot of the analytics work is being done in a cloud-based tool from DataRobot Inc. Business analysts use it to develop models for their specific areas. Additionally, the company has a team of data scientists using open source tools like R and Python. The data scientists are currently planning AI projects and investigating how such projects could sharpen existing customer-targeting initiatives.
It may be a while before those efforts bear fruit, Tandon said, adding that the important thing right now is to be in a position to take advantage of AI once it matures a little more. And that's where having good sources of data and proper data management in place becomes important.
"I think the companies that will win out will be companies that are invested in data," he said. "We've been able to take advantage because we invested in data a year or two ago."
A lot of the data used for targeting offers to customers comes from LendingTree's website. The cloud-based tool from DataRobot can grab that web data directly. It also links to external sources of credit data.
Ensuring no breaks in the chain from data source to data model has been a big part of LendingTree's current data management efforts, which Tandon said he thinks will prepare the Charlotte, N.C., company for future AI projects. LendingTree has also prioritized developing data governance best practices to ensure that data is used and stored consistently.
"For companies that are in the tech space, AI is undoubtedly going to give an edge," Tandon said. "You're going to see an increased use by business. It's already starting to happen. It's impossible to think about every aspect of where the customer is. Investing through AI that thinks through that cycle is an undoubted edge."
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