In my last post, I introduced you to Mary, a fictional analyst working at an agency that has recently moved away from multi-touch attribution (MTA) as its primary measurement methodology. Instead, Mary helps her clients leverage incrementality testing to understand their advertising investments’ actual effectiveness better.
The data deprecation trend is real, and MTA relies on cookies and other consumer data tracking mechanisms that are degrading at a high rate. Real brands and agencies—not just Mary’s fictional company—have been using “lift tests” like these for decades. They always worked very well but were often expensive, complex, and took a long time to run. However, with today’s AI and machine learning innovations, incrementality testing has become affordable, more accessible, and tests require much less time to conclude.
Part 2: A Day in the Life of Mary, the Marketing Measurement Pro
And we’re back…In Part 2, we rejoin Mary for her afternoon tasks as she continues to drive value for her clients with the agency’s fairly new incrementality practice.
1:00 PM: monthly measurement meeting
After a quick lunch in her home, Mary walks her dog and contemplates the upcoming monthly measurement meeting. She makes it back home right before the Zoom call begins.
The monthly measurement meeting is attended by the other analysts at the agency and some of its key leaders—various Senior Account Directors (ADs), the VP of Client Services, and their key stakeholder, the agency’s holding company’s SVP of Strategy.
The meeting’s agenda is the same each time. First, they discuss any significant issues facing the agency and how their incrementality practice can help solve those challenges. The VP of Client Services lets them know that their big, global retail client has become a bit unhappy with the recent results of their latest promotional campaign.
To make sure they can nail the next campaign, One of Mary’s fellow analysts offers some ideas on how a few incrementality tests could be run to determine the best creative strategy across channels as the recent new direction doesn’t seem to be resonating with customers. The team agrees and tasks the analyst with developing that program in conjunction with the agency team working on that client.
In the next part of the meeting, each analyst quickly presents a slide with recent learnings from the previous months’ tests. Some of the ADs ask probing questions as they’re still getting up to speed with how incrementality works and how to best train their teams to explain the ins and outs to clients.
The remainder of the meeting is to discuss upcoming tests so that they can all not just know what’s going on across the agency as it relates to their new measurement practice, but also to pick each other’s brains and offer good suggestions into how they can continue improving their programs.
The meeting lasts an hour and a half, and the SVP of Strategy offers some closing words of encouragement and how she will be reporting the solid progress in the holding company leadership team meeting next week.
3:00 PM: knowledge sharing
Mary finishes a few critical emails and joins the meeting on time. In this session, some of the other agencies in the holding company have been interested in what their agency has been doing with their incrementality program. So, Mary’s boss “volunteered” her to meet with some of their senior analysts to discuss the topic.
Data deprecation has been on everyone’s minds for the last few years and its impact on measurement, but each agency has been dealing with it differently:
- Agency A has been working hard to keep their MTA programs working by cobbling together some data workarounds with big Universal ID (UID) vendors. While it helped create some stopgaps early on, the agency has been feeling the impacts of increasing data deprecation and is ready to start testing incrementality as a potential solution.
- Agency B started its incrementality program even before Mary’s agency. Their measurement lead reports that things are going well and even points to a few significant client renewals driven by the new practice.
- Agency C is a pure-digital performance agency that thought it could avoid the data issues altogether by going “all-in” with the big digital publishers. Early on, their fixes worked, but they too are starting to hit a wall as their clients are now asking some concerning questions about cross-platform measurement and as the industry blogosphere heats up on this issue. Without satisfying answers to tell their clients, they know they need a real solution and are interested in hearing how the other agencies are solving it before deciding which direction to go.
- Agency D is way behind. Historically, it has been more focused on creative and branding, so the measurement hasn’t been as scrutinized by its clients as other agencies. However, the lead analyst knows that it’s only a matter of time before they lose clients over this issue and even sees measurement as an opportunity to drive innovation. They are interested in the resource costs involved and vendors they should meet to start thinking long-term.
Mary offers her advice when asked and is interested to learn more about where the other agencies are finding challenges. Then, she makes a few notes to share with her team lead at her next one-on-one weekly meeting on Friday.
4:30 pm: brainstorming
Mary races to the end of her day. Checking her list, she remembers she needs to brainstorm some test ideas from the business challenges she heard with the client in the 11:00 am meeting.
One of the critical things that the CMO client has struggled with for years has been the online/offline connection. The brand knows that these channels must be influencing each other, but without the proper measurement in place, they continue to operate in silos and cannot take advantage of the synergy. Even worse, the CMO worries that their disparate strategies might not just be wasting precious budgets that could go elsewhere, but even that their siloed online/offline marketing might even be working against each other.
So, Mary decides this is where she should start.
Mary uses Skai’s Impact Navigator tool to analyze the client’s historical marketing performance data to develop three geo-split pairings so they can run the next set of incrementality tests in paired Test and Control markets.
Of course, in all of the Control Groups, the advertising spending will continue as already planned without any changes. For each test cell, Mary will measure the shift in digital media investment on total sales and revenue. Although the client asked many questions about measuring success, she thinks the impact on total revenue is an excellent place to start, so they design further tests to digger even deeper once they have initial results.
Because the tests will only run for a month or slightly longer, there’s limited investment and disruption to the media plan. Mary knows that the “test budgets” will also drive awareness, traffic, and sales so that dollars won’t be wasted simply for testing.
Once finishing her analysis, Mary shoots off an email to her agency colleague with a quick explanation so he can share it with the client. It’s time to break for the day and enjoy an early dinner with her family.
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