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To Shine a Light on Marketing Campaigns, UMIA Alone Is Not the Answer—Yet
Unified marketing impact analysis is a promising but early-stage technology. But nothing will help you overcome a shaky data foundation.
Posted Apr 25, 2017
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Your business may think it has a good handle on whether its marketing campaigns are working due to the use of marketing return on investment (MROI) technology. However, the unfortunate reality is that most businesses are falling short in today’s complex media environment, as the mix of digital, mobile, traditional, and app-based consumer actions are not being correctly attributed.

Adding to that, changing consumer behavior, such as increased mobile device use, means that for any single customer journey, an individual can switch between multiple devices, perhaps several times. This channel-hopping is leaving marketers with customer journeys that simply hit a dead end and transactions with no apparent journey before them. Simply put, these challenges are leaving marketers in the dark.  

So how can an organization achieve the necessary level of insight to accurately gauge the impact of marketing efforts?   

UMIA–Black Box Marketing

One approach receiving a lot of buzz lately is unified marketing impact analysis (UMIA), which strives to bring together the most popular methods of marketing analysis—marketing mix modeling and digital attribution—to give marketers a level of visibility across the customer decision journey, spanning online and offline and the multiple channels that exist within each.

To marketers who grapple with several channels, multiple campaign strategies, and dynamic customers that jump across channels on their journey to making a purchase, UMIA may seem like the silver bullet you’ve been searching for. However, the UMIA solutions offered by many vendors appear to have a “black box” element to their technology. Many vendors are protective of their secret sauce, which further adds to the black box feel. Essentially, marketers are being asked to put their faith in a technology that’s still in its infancy.

While the underlying idea of UMIA is a sound one—we do, after all, need a way to address the challenges outlined above—should we take the leap with these new solutions and abandon all that we’ve done before? What it all boils down to is that regardless of approach, the data behind it has to be solid.

All Roads Lead to the Same Data

UMIA or not, marketers need to embrace and manipulate data from the same sources. Accepting that we are using the same basic data, we need to consider where the problems really lie. Is replacing solutions that use the same data going to fix things, or is the data part of the problem? For most of us, our marketing analysis will combine internal and external data sources, and while we should take the time to ensure that the external sources are the right ones, having the right internal data is where our efforts really need to be focused.

Taking a more clinical approach toward data is fundamental to gaining insights that reflect the real world. Doing so allows us to align common elements (such as customer, session, transaction, device ID or location) that can be found in the various channels we operate across. These dotted lines between data sources mean we can more easily follow the customer journey and interactions across channels, rather than treating each as an island.

But the challenge is building on that foundation, with data that allows us to understand the influence of marketing channels and campaigns. In the online world, this isn’t hard to do, and it’s getting easier all the time to gain access to data that gives the precise timing of TV and radio spot playouts. Combining any number of other external data sources with our internal foundation creates a real world in data that can be scrutinized, modeled, and used to influence future decisions.

Starting with good data, marketers can use existing tools to build full integration between MROI methodologies such as econometrics modeling, digital attribution, TV attribution, and test and learn. We know that each method has benefits as well as blind spots, but the best tools allow you to take the best from each and apply them to specific marketing scenarios. For example, econometrics will not help you with granular insights into customer behavior, but attribution will for digital channels. For marketing instruments with limited data/history available, heuristic analysis is one of the best MROI tools. Combining all three will give you the power to assess a campaign in its entirety.  

Ultimately, it all comes back to having that sound data foundation and wisely integrating proven methodologies. This is required to avoid contradictory results and get one clear recommendation. UMIA alone will not be a silver bullet bypassing the need for fundamentally strong and interconnected data.

Embrace the Basics

UMIA might become the solution for the marketing challenges discussed, but currently it’s an early-stage technology that’s still some way from establishing its viability. However, the underlying ideas and problems that drove the need for an answer like UMIA all lead back to making sure our marketing data, the analytical methods, and how we use them are sound. We need to point the finger at ourselves, and task ourselves with confirming that the fundamentals are right. Doing this will bring immediate benefits and ensure that as UMIA platforms mature, companies can eventually rapidly deploy them and realize immediate benefits.


Lars Fiedler is a vice president and solution general manager for Marketing Solutions at Periscope By McKinsey,  responsible for Marketing Solutions’ development and global deployment. Fielder has 10 years of experience in marketing and marketing efficiency, advanced analytics, media mix modelling, and customer life cycle management. He has worked on a broad range of marketing efficiency/MROI projects across industries and geographies. Prior to joining the Marketing Solutions team, Fielder was an associate principal in McKinsey’s EMEA Marketing and Sales Practice with a focus on CLM and advanced analytics.

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