This year’s Data Marketing conference brought dozens of speakers and exhibitors to Toronto to share their knowledge about what works and what doesn’t in the brave new world of data-driven marketing. We heard from everyone from IBM to McKinsey to TD Bank and Tangerine. Here are a few of the highlights.
More data scientists is not always the solution
When confronting a mountain of data, the response is often to build a bigger data science department. But the way J.D. Nyland, Adobe director of product management, sees it, this doesn’t solve the core problem: that marketers on the ground need to understand and use the data in day-to-day business. (It’s also expensive and very difficult to find talent.) But since a lot of the analysis that marketers need has been done before, they don’t necessarily need dedicated experts to design complicated statistical methods every time they want to do an email campaign. A lot of these operations can be automated, which is of course the opportunity that Adobe Marketing Cloud’s analytics tools are looking to exploit. The goal, Nyland said, is to put the tools for using data in the hands of marketers, and keep the data science department focused on a few really important and innovative projects.
Assume everything you know is wrong — including your data
Marketers and creatives have gotten used to hearing that data trumps their intuition. Data is turning marketing into a science, and it’s overturned some of the most basic assumptions that marketers have relied on for centuries — so to get the most out of your data, assume everything you know is wrong. But we also know data isn’t infallible. Data can lead businesses astray. So when should marketers believe the data, and when should they trust their gut? McKinsey senior partner Tim McGuire agrees with the rule that marketers should go in with a fresh perspective, assuming nothing — but he said that applies to data insights, too. Don’t just assume that something is correct because it’s based on data. Be skeptical, test the insight, and see if it holds up, just as you would with anything else you think you know.
Assume everything you know is wrong — including your data.
Data privacy is not just about consent
Many marketers assume that if they have consumers’ consent to collect data or place cookies, that’s enough. But Adam Kardash, legal counsel to the Digital Advertising Alliance of Canada, warned that data privacy regulations have gotten a lot more complex. “Consent is a remarkably small piece,” he told the audience. “It’s about data governance, data governance, data governance.” The term data governance has come to be a catch all for respectfully and securely handling consumer data — not just asking for consent to collect it, but storing it securely, ensuring it’s used only for its intended purpose and being accountable if anything happens to it. Kardash stressed that, legally speaking, companies are responsible for what happens to data in their possession, and as we’ve seen with the ongoing epidemic of data breaches, consumers are starting to exercise legal options to keep companies accountable.
…but it doesn’t have to detract from business interests
Ann Cavoukian, director of Ryerson’s Privacy and Big Data Institute, argued that data governance shouldn’t just be seen as a compliance cost. Business interests align with good data governance, she said, and we need to avoid “zero-sum thinking” that says respecting data means doing less with it. She advocated a proactive stance, where companies start with marketing objectives and develop tactics to reach them that inherently respect consumer privacy, instead of trying to tack on privacy measures once data programs are up and running (or once a PR crisis forces them to). And data governance isn’t something companies should keep quiet about, she said. Consumers want to know their data is in good hands, and being transparent about privacy practices will grow their trust. If consumers trust a business, and feel like they’re informed and in control of how their data will be used, they’ll be willing to share more and different kinds of data.
Look for the serendipity sweet spot
The marketing world is abuzz about data personalization, the idea that marketers can send unique messages tailored to every individual based on their interests. But there’s a real challenge with too much personalization: consumers can have too much of what they want. TD Bank senior manager of customer segmentation Nick Necsulescu used an analogy with Starbucks. He said he likes that barristas at his local Starbucks know his order; but every once in a while he wants something else. On one occasion the barista prepared his drink before he even ordered it, and when he ordered something unusual, they ended up throwing out the drink. Email offers and other personalized messages can have the same problem — while every consumer has preferences, most don’t like their shopping habits to be too predictable. The sweet spot to aim for with personalization is serendipity, Necsulescu said — a balance between predictability and chaos will make the consumer say, “Just what I wanted… how did you know?”
