Measure Success: Market Research and Analytics Yield Results
Metrics and Analytics 03.03.2022

Measure Success: Market Research and Analytics Yield Results

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Advertisers and agencies both need to come to the table – and right from the outset when it comes to optimizing outcomes. How, when, and why that should happen is the focus of this episode of Sunny Side Up, which features Earl Potter, Senior VP of Media Analytics at Quad. He brings extensive experience with technology and analytics, helping clients get the most out of their market investments by finding the right combination of technology, method, and analytical framework to optimize media spend. Before joining Quad in 2019, Earl worked in senior positions at some of the largest global media analytics firms, including Gain Theory, a marketing effectiveness consultancy that is part of WPP, and Mediabrands, the media and data arm of Interpublic group. He shares insights on advertisers and agencies – how they can best leverage ad dollars and maximize ROI through candid communication, planning, research, and transparency.

About the Guest

Earl brings extensive experience in technology and analytics to his role as Senior Vice President, Media Analytics at Quad. He helps clients get the most out of their marketing investments by finding the right combination of technology, method, and analytical framework to optimize media spend. Before joining Quad in 2019, Earl worked in senior positions at some of the largest global marketing analytics firms, including Gain Theory, a marketing effectiveness consultancy that is part of WPP, and Mediabrands, the media and data arm of Interpublic Group.

Contact with Earl Potter

Key Takeaways

  • Maximizing advertiser spending is primarily tied to the realities of specific markets, which can be broken down into four dimensions: Geographic, Target Audience, Media Options, Cost of Media.
  • Agencies are not serving their clients if they don’t suggest DMA (designated market analyses) to understand the market into which they’re advertising. The investment has a definite ROI.
  • Market testing is incumbent on agencies, which often fall back on simplistic formulas and do not serve their clients. The result? Some advertisers bring the work in-house.
  • With respect to the budget, what’s the right amount to allocate for market testing and analytics?
  • Getting a healthy advertiser-agency relationship off the ground: What’s required and why.
  • Set realistic timelines and expectations. Transparency and planning are key.

Quotes

“Test boldly, test all the time, and do so with your eyes open to the fact that every market is unique for a variety of reasons.”

Highlights From the Episode

What are some of the dynamics at play between advertisers and agencies?

Markets are defined most often by one of four variable factors: Geography, Target Audience, Media Options, Cost of Media. When you start looking at how to optimize reach, it’s clear that the media plan will differ based on different market dimensions. This can be expensive, but Earl believes the payoff for advertisers is significant.

Is it on the advertiser or the agency to propose smart strategies?

Both sides need a win, so the conversation comes down to whether there’s a willingness to spend more from a labor or technology point of view to formulate a sufficiently nuanced media plan. Based on the analyses he’s seen, Earl believes the optimal, maximum, effective reach from market to market varies widely. The smart money, he says, is invested in market intelligence and testing. The trick is having open, transparent conversations about the cost and the ROI.

When is the right time to go in-house, and is it something advertisers should do?

When advertisers bring their business in-house, it’s because agencies haven’t taken on the complexity of defining market spaces or have done a weak job. At that point, advertisers ask themselves: Why not do it ourselves? There are many hypotheses for getting the most out of advertisement dollars, but there have to be rigorous tests to test them – a step many agencies fail to take. It’s often the result of slipping through the cracks for lack of a team member dedicated to overseeing regular, targeted testing.

From a budget point of view, what’s the right allocation for testing?

If you’re going to test a new channel or message, you need to be bold in order to get the kind of conclusive result necessary. But at the same time, testing that big idea can’t break the bank, which is why Earl recommends focusing on individual markets and understanding the spending at that level. However, this only works if, indeed, you have an understanding of each of those individual markets. Otherwise, you’re doing bold testing blind. You’ve got to build the toolsets and capabilities to support bold – but smart-testing across a range of markets.

What are some ideas for setting up a healthy client-agency relationship from the outset?

Hypothesis, testing, execution, and measurement are the flywheel. A given agency may not be able to help with all those elements, so it’s up to the advertiser to know where and how they can engage. It’s a long-term relationship and commitment to whatever onramp(s) to which everyone agrees. It’s important to set expectations and a clear framework so that clients don’t wind up frustrated or disappointed.

What kind of lead time should advertisers expect when setting testing timelines?

There is a lag time that requires anticipation and preparation. It’s important to put the roadmap on a calendar and collaborate about how testing will unfold quarter over quarter. It’s unfair to agencies for advertisers to put pressure at the last minute. This reality makes the relationship more complex, but there’s tremendous maximization of benefit ultimately in the outcomes of advertising budget dollar for dollar.

Who is responsible for measuring media results as converted into sales results?

Earl believes that situations vary based on agency size. If the agency is measuring, the advertiser needs to have confidence that they’re honest brokers. Bringing the measurement function in-house can make sense in these situations, but it comes back to whether the necessary talent and expertise are available to manage the analytics.

Recommended Reading/Resources

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