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CEO Perspective: How Marketers Can Get the Most from Analytics

Michelle Jacobs, president of Alight Analytics, shares her recommendations for how marketers can get the most from their analytics initiatives.

Technology is valuable, data strategies are important, and self-service and AI are popular application features, but marketers will get more from their data if they focus instead on asking the right questions. Michelle Jacobs, President of Alight Analytics, explains this and other tips marketers can use to maximize the value of their company's data.

For Further Reading:

How Predictive Analytics is Transforming the Ad-Tech Industry 

How Can Augmented Analytics Benefit Your Role?

Five Drawbacks to Self-Service BI

Upside: What technology or methodology must be part of an enterprise's data strategy if it wants to be competitive today? Why?

Michelle Jacobs: For marketers, everything must start with strategy. You need a comprehensive strategy that encompasses the entire life cycle of how you gather, structure, and use data to develop actionable insights that, in turn, allow you to achieve the kinds of results you want to see in your business.

Too often, people only get it partly right. They might have a data strategy -- a plan for connecting to the originating data sources and bringing everything together in one place. However, they aren't clear about the kinds of questions they're trying to answer, so the resulting data sets aren't structured in a way that facilitates analysis.

A better approach is to "begin with the end in mind" and build an analytics strategy. What kinds of results are you trying to achieve in your business -- higher lifetime value, lower churn? Once you're clear on your goals, you know what kinds of questions you need to ask. Then you know which data sources you need to aggregate and how you need to structure your unified data sets. It's a more targeted, more powerful, and much, much less frustrating approach to marketing analytics.

What one emerging technology are you most excited about and think has the greatest potential? What's so special about this technology?

Honestly, it's not a technology. Rather, it's a realization among marketers that technology can only do so much.

Today, there are multiple platforms that can aggregate, blend, store, and visualize data. Many of them are excellent at what they do. At some point, though, you need a human being who can ask the right questions and develop a plan for leveraging data to answer those questions. You also need somebody who can step in when the technology breaks -- because it always breaks.

I know a lot of people are excited about artificial intelligence, and I've seen examples where AI can provide quick, useful answers to questions. Usually, those questions aren't very complicated. To tackle more sophisticated analysis such as attribution and predictive analytics, you still need human expertise.

What is the single biggest challenge enterprises face today? How do most enterprises respond (and is it working)?

Marketers are still struggling to take control of their data. Most don't have an efficient method for gathering, organizing, and storing data in a format that's useful for reporting and analysis. That's because marketing teams tend to use multiple platforms -- in some cases, literally hundreds of sources -- and each has its own way of setting up metrics and dimensions. Unifying all that data into a single source of truth can consume enormous amounts of time.

There's no shortage of platforms that are trying to address this issue, and many of them promise a self-service, DIY experience so user-friendly that anyone can operate their platforms. Marketing's data ecosystem is so diverse and fragmented that it's still challenging to automate entirely.

Is there a new technology in data and analytics that is creating more challenges than most people realize? How should enterprises adjust their approach to it?

It's not that new, but self-service analytics software is still causing headaches for so many marketing teams. I'm talking about platforms that promise an all-in-one experience -- data aggregation, blending, warehousing, visualization, even prediction and attribution in a single piece of software that basically anyone can use. These tools are created by software developers, not marketers, so they don't always understand the demands that marketing teams face.

Case in point: Self-service software depends heavily on templates. Your data needs to fit into the software's ideal schema, and you have to visualize everything with prebuilt dashboards that allow limited customization. Eventually, you reach a point where this software won't allow you to do something that you really need to do, and in marketing, the need for these weird little customizations is fairly commonplace. So you're stuck with an end product that might be easy but doesn't deliver what your client or boss demands.

The other problem with self-service: a lot of the time it's not really "self-service." You still end up writing your share of SQL queries. If the connection to a data source fails, you're responsible for figuring out what's wrong. This isn't a problem if you have the expertise on your team, but most marketing teams don't. To make a self-service tool work, you have to hire an extra person or shell out more money to the software company's service department.

Where do you see analytics and data management headed in 2020 and beyond? What's just over the horizon that we haven't heard much about yet?

More marketing teams will adopt a solutions-based approach to producing insights and analytics. They're going to choose partners who can provide a holistic package of technology and services -- solutions -- instead of building a martech stack on their own or trying to find the one perfect piece of software that does everything with no human intervention because that Holy Grail doesn't exist yet.

A solutions-based approach is better because it can be customized to a particular organization's unique challenges and goals. Marketers get everything they need in one offering, both platform and services, so they can concentrate on their areas of excellence: developing insights, running campaigns, optimizing spending, and budgeting.

Describe your product/solution and the problem it solves for enterprises.

ChannelMix gives marketers solutions that instantly answer their most important questions about cross-channel marketing performance. It's a modern, end-to-end intelligence solution that aggregates data from any marketing, media, or sales platform, producing unified data sets that are perfect for next-level reporting, analysis, and modeling of paid media, social engagement, search, web, e-commerce, lead generation, sales, and agency operations. Best of all, ChannelMix is supported by Alight's team of dedicated experts who can help you develop a data strategy, enabling any organization to take its analytics strategy to the next level.

About the Author

James E. Powell is the editorial director of TDWI, including research reports, the Business Intelligence Journal, and Upside newsletter. You can contact him via email here.


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