Marketers have long grappled with how to best leverage the data they’ve collected. It’s certainly a challenge, as data fuels nearly all of their marketing efforts—including personalization, audience segmentation and targeting.
“Most marketers understand that taking third-party data and looking at what is driving your competitors’ traffic and conversions can give you a view to what customers do before they ever even reach you,” said Julie Lyle, co-founder and CEO of Zytara Inc, a computer software firm. “And understanding those moves from a customer are the way to truly accelerate acquisition.”
Watch the full interview with Zytara’s Julie Lyle below.
But vetting through piles of data can be a headache even for the savviest of marketers.
“There’s not an easy answer to it,” Lyle said. “There are over 7,000 different marketing tech tools out there, and we just don’t have time to explore them all. If you think about it intuitively, marketers have grown up alongside their technologies. We have specialists on our teams—a content specialist, someone who’s good at social, someone who’s good at search—and they all have their individual tools, and in many cases their own vendors. So they have a different agency for each one of those functional areas. But they don’t talk to each other, and the data sets don’t align.
“Because of that, each one of those marketers is building a road map or a marketing strategy, and reacting to KPIs based on his/her particular silo. And silos are not only wasteful, they’re disastrous in terms of managing the relationship with a customer.”
According to Lyle, whose past roles have included CMO of Walmart and Prudential, technology like artificial intelligence (AI) is helping marketers better streamline their efforts and analyze the data they’ve collected.
“We had to learn how to harness AI really well, and we’re becoming much more savvy about the way we manage the science,” Lyle said. “We … are learning how [or how not] to bend our strategic thinking processes toward the capacity of AI. It’s easy to negatively influence what AI delivers because of our bias. We think we know our customer, so we tell the algorithm to go look for these things, when in fact we should say to the algorithm, ‘Just go look, and come back and tell me what matters or what doesn’t.’
“If you … aren’t constantly refreshing your skills and staying on top of these things and challenging yourself, you’re going to become obsolete overnight,” she added.