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Why Smart Data Is So Much More Important Than Big Data

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I'm officially sick of the term "Big Data." Marketers have access to lots of data—got it. However, Big Data in and of itself doesn't sell more products or services, or make high-value prospects aware of your brand. Big Data is merely the pool in which we swim to target and generate results. Smart data is the spear gun—this is where we need to focus.

As direct response marketers, we think of data in terms of insight to make better decisions that drive to an action.

Smart data breaks into the following categories:

1. Creative optimization

Every creative concept comes from an insight from customer research and/or campaign data. We build a creative approach—based on some form of insight around what a particular target audience is doing, thinking, feeling, responding to, not responding to or is concerned about—to elicit a response.


We start many of our creative exercises with the search for a "wow, I can't believe that" type number. For example, when working with one brand targeted to children, inspiration came after we learned that 97% of kids play video games regularly, but only 33% of kids get regular exercise. A body at rest tends to stay at rest, but a body in motion tends to stay in motion. The brand needed to inspire kids to turn off the games, get up, and get going.

The stats that inspired this brand's communication have nothing to do with Big Data—just smart data.

2. Campaign optimization

Use specific data to plan a campaign, target a specific audience, and optimize media against what is working or not working and testing variants like message, offers, call-to-actions, creative themes, and so on. Doing all that is extremely data-centric and requires a smart approach.

For example, it's possible to optimize a DRTV campaign on the fly. During an eight-week flight, we'll see which markets convert at a higher rate during the initial weeks and focus our media spend there. We can also use response data in our digital buys to harness the ad-serving technology to optimize campaigns in real time. Pre-planning the use of data and optimization is critical in campaign optimization.

3. Conversion optimization

Conversion optimization is a unique data set in and of itself. The data focus here is on getting the customer to take the next logical step using micro actions, calls-to-action, call center optimization, and/or website optimization. There is a heavy reliance on split testing and multivariate testing that requires smart test planning and execution.

In a mobile marketing campaign, for example, does a click-to-call convert at a higher rate than a get-more-info button? Should the button be red or orange? Which headline is converting better on a desktop vs. tablet vs. mobile device?

4. Campaign reporting

The success (or failure) of campaigns and programs can be shown in reports that are as detailed as needed for analysis or rolled up into top-level metrics for a helpful overview. Smart reporting of data helps tell the story of progress, what the ROI of the campaigns is, and what the marketing dollars of the organization are contributing to key performance indicators (e.g., sales!) and whether those numbers are improving or sinking.

Having a history of results can help you avoid mistakes like reading the data too soon. If a campaign hasn't had a chance to mature, you may pull the plug too early.

5. Attribution analysis

Attribution analysis is a difficult thing to do well when you start layering in multiple campaign sources, offline and online multiple sales channels, and different length of buy cycle. We separate out campaign analysis from attribution analysis because they serve two different purposes:

  • Campaign analysis and optimization is more tactical. It answers the question, "How can I get better results out of the marketing dollars I'm spending on this campaign/channel?"
  •  Attribution is more of a budgeting and allocation process. It helps to answer the question (based on best available data): Where should I be allocating more or less marketing dollars over the next cycle?

6. Executive reporting

Selecting the right metrics to surface to directors, vice-presidents, and C-suite types is a skill unto itself. How this data is presented, how often it gets updated, what charts/graphs/visualizations are used, and, especially, what story the data is telling is extremely important for communicating progress of your programs as well as outlining opportunities for what's next.

This kind of reporting is not something you set and forget. It needs to be carefully crafted to avoid any kind of miscommunication. In fact, I recommend you set a regular appointment and present the data in person, so you can tell the story that you want to tell and personally address questions, concerns or issues that come up.

7. Privacy and compliance

Use an ISO 27001-certified company with systems in place to process and handle data to comply with the strict requirements for remaining certified. This should include separating client data in addition to keeping health care information and personal identifiable information and digital behavior information private and separate from each other.

I'll take quality data over quantity of data any day. Understanding where the data is coming from, how it's stored, and what it tells you will help tremendously in how you use it to narrow down to the bits that allow smarter business decisions based on the data.


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Scott Fasser is director of Digital Innovation for HackerAgency, a global digital/direct agency based in Seattle.

LinkedIn: Scott Fasser 

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Comments

  • by Dan Cropsey Tue Feb 3, 2015 via web

    Well said Scott...couldn't agree more

  • by Cheryl Tue Feb 3, 2015 via web

    Thanks for reframing the discussion--great points!

  • by Dominique Levin Fri Feb 6, 2015 via web

    Scott, great article. I assume your key point is that if you collect data for data sake, it's useless. You have to act on the data, either automatically or through human intervention. However, as long as you have an automated system in place to analyze the data, cut through the noise, and prescribe the right action - such as by automatically sending a highly personalized preventative touch campaign to a customer at risk through your email system - then the "amount" (how big) your data is doesn't really matter. In fact, in that case, just having data on some customers, instead of all, would not make sense.

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