Alight Analytics' Michelle Jacobs on data-driven marketing and respecting customer privacy (pt. 1)

Key Takeaways:

• Avoid the Data Death March. Like single-use plastics, individually prepping massive amounts of data using yesterday’s methods (like Excel and PowerPoint) for each and every meeting, presentation, and report is wasteful. The right technology can free up time and resources by centralizing this data and allowing it to be multi-purposed on-demand across all departments.
• From top-to-down best practices. Think about the question you want to answer first.
• Data turns marketing from an expense into an investment. With the right data to trace factors that go into lead generation, clients can quantify exactly how their marketing dollars make a difference beyond black-and-white sales figures.
• Messy data vs. clean data vs. no data. Data quality is good enough when it's directionally accurate.
• Consolidation is your friend. If you’re a marketer and you’re looking to make educated decisions, get your marketing data in one place so that you can look at it holistically and understand how your entire ecosystem is performing.

Key Quotes:

We really preach a theory where you’re starting from the top down. So you’re figuring out what questions you want to answer first. … Once you determine what that is and outline that, then it becomes really easy to know what data you need to pull. So you know what questions you’re trying to answer then that leads to the sources that you need to pull from. … So it’s really about where you’re spending your efforts and your money from a marketing standpoint and making sure that all of those touchpoints are included so you have a completely full picture of where all of your money and your efforts are being spent.

I think it’s easy to get stuck in this thinking of, okay, we need analytics and we don’t know what that means exactly, so we’re going to go hire a bunch of people. … And then I think they realized, okay, I’m just throwing money and people at the problem. And this is actually a system problem, not a people problem. And it’s a strategic problem, not an effort issue.

Is messy data still better than no data?

If it’s consistently messy, then it’s usually directionally accurate! The reality is no data is going to be a hundred percent perfect. But as long as you’re consistent about how you’re gathering it, what you’re doing with it, then you can use that to make some accurate assumptions about the data and decisions. So think about if the data quality is enough to be directionally accurate.

Is flipping the 80 percent of time we spend preparing data with the 20 percent of time we spend analyzing it just a matter of up-skilling our teams?

I think that’s part of it too, for sure. It’s the two pieces, right? It’s investing in a solution that can get you all of the data together [in a way that’s] consumable, make sure it’s accurate, make sure it’s updating automatically. Let’s get our solution in place, and then let’s make sure we have people who are either trained or that we can train that understand marketing, understand our campaigns, and can analyze it in a way that allows us to do something with that data.

Do clients trust their gut more than the data?

It’s not as bad as it used to be, but we’ve had clients over the years specifically that we have shown them, analysis after analysis, that says “Stop doing direct mail.” And they tell us, “I know that says to stop doing this, but my gut says it’s working.” … And I’m not picking on direct mail at all. It could be, you know, Ad Words. It could be whatever, it’s just this was one specific example where it wasn’t working for them anymore. I mean, it works for other people, but we do have a lot of attribution models that our clients can use out of the box, and you have to try to put your feelings aside and trust the data. And that can be very difficult to do.

My business partner, Matt, he speaks a lot in educating marketers and he has this slide that shows the Data Death March … it’s getting the data out of these systems and then putting it into Excel and then putting it in the PowerPoint and then you try to analyze it, and somebody has a question — you have to go do the whole process over again. So this Data Death March is why almost all of our clients come to us; they’re typically in that situation where they’re manually working through data and doing exactly what you said, they’re spending 80 percent of their time just getting data ready for an analysis and 20 percent of their time, if they’re lucky, actually analyzing it.

Is PowerPoint where data goes to die?

Over all these years, we’ve all [gotten] this great data together and [we’ve made] these amazing charts, and [we’ve] put it in PowerPoint and [we’ve presented] it. We never look at it again. It’s just not sustainable. It’s not as great as having something that updates for you every day that you can look at.

Not only is technology moving faster, but from a marketer’s standpoint, there [are] more and more ways to get your messages to people than ever before. Every day, there’s a new source, a new channel — that’s [a pain point] that we’ve heard [about] from people who try to manage all of this data themselves without relying on a partner.

How the data proves that marketing is more of an investment than an expense:

Marketing has always been treated as an expense, so we tell people it’s an investment. When you have analytics, marketing can be an investment — it shouldn’t be the first budget that gets cut. You should show them that it’s actually working for the company.

As a woman in data who understand the importance of diversity in the field, what does Michelle do to promote this diversity?

We try to hire as many women as we can possibly find for any of our tech jobs, and the honest truth is: there’s just not enough out there. We try to network and do other things to encourage women to know who we are and to apply.

How might we entice more women to enter the field?

I think it’s a pipeline problem. … I’ve had conversations with a lot of younger women who were going into college and trying to figure out what they want to do with their life. I tell them to learn how to code, and they don’t want to. … I try to encourage it, [but] I think it’s an age old question of women tend to go more into the arts and marketing kind of careers and men tend to go more into the math and science tracks. And I think until we’re able to really redirect that at a young level, we’re going to continue to have this challenge.

Advice Michelle would give to a new or aspiring data professional:

If I were starting over, I would be as hands-on as possible. I would build my own website. I would put analytics on it. I would buy some ads. I would spend a few dollars on Google, buy some ads, making sure my organic search is optimized. … And while that’s really marketing specific, the more you understand about that underlying data and the strategy behind marketing, the much better you’re going to be at your job and a lot easier it’s going to be.

One of Michelle’s biggest takeaways:

If you’re a marketer and you’re looking to make marketing decisions, get your marketing data in one place so that you can look at it holistically and understand how your entire ecosystem is performing.

Bio:

Michelle Jacobs is the president and co-founder of Alight Analytics, and she's on a personal mission to revolutionize how marketers use data.

Alight's marketing intelligence platform ChannelMix fuels a suite of next-generation solutions that enable any marketer to turn marketing from an expense to an investment. Alight's solutions combine the speed and precision of software with the flexibility and expertise of consulting, delivering an experience that's utterly unique in its industry.

Before co-founding Alight, Michelle drove marketing, advertising, and Web analytics strategies for leading companies such as H&R Block, American Century Investments, Saatchi & Saatchi, and Toyota. Michelle is a sought-after speaker and panelist with a unique perspective both on marketing analytics generally and being a woman in data and MarTech specifically.