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Measuring Cross-Channel Media with Multi-Touch Attribution Model

in Media Planning & Buying with tags , , , , , , Both comments and trackbacks are closed.

For many advertisers there exists a discrepancy between how they measure media and how consumers actually experience it. Media measurement is often viewed in a silo by channel, an approach which fails to account for cross-channel effects. But, consumers experience media holistically, and their behavior is influenced by the integrated sum of touchpoints across all channels.

The best approach to aligning media measurement with the consumer experience is multi-touch attribution modeling (MTA). This model provides advertisers a greater understanding of how different channels individually and collectively affect the consumer journey, from the first interaction with a brand all the way through to a conversion.

Unfortunately, some key operational issues have prevented widespread use of this data-driven attribution methodology. Further, cost and implementation complexity have been significant barriers for advertisers to overcome when trying to rationalize deployment of an MTA solution. Recently, Google significantly reduced those barriers by integrating Adometry’s data-driven models into DoubleClick and making them available to platform users at no additional cost. Now, a sophisticated MTA solution is readily available to thousands of marketers after just a few mouse clicks.

This update could significantly disrupt the marketplace and rapidly accelerate adoption of MTA as the preferred media measurement approach. Below, we dig into the benefits of using MTA and the importance of exploring the model and understanding its incremental opportunities.

Why Use MTA?
Using MTA, advertisers can optimize smartly by better understanding performance across all channels. Many marketers currently use last-click attribution models, but those models tend to undervalue new customer acquisition campaigns, which can ultimately lead to inefficient budget allocation decisions across channels. In contrast, MTA measures how much each channel fractionally contributes to driving a conversion, from customer acquisition to final sale. If, for example, a marketer spends $50,000 in a month on Display banners generating 250 sales for a cost-per-action (CPA) of $200, and spends $50,000 in Paid Search generating 500 sales for a CPA of $100, a last-click model would show Paid Search as being 2x more efficient than Display.

This would indicate that budget should be cut or even eliminated from Display to fund more Paid Search. However, MTA would account for Display’s role in feeding Search new customers. As a result, Display might get credit for, say, 20% of the conversions that a last-click model would attribute to Search. That 20% credit would significantly reduce the efficiency gap between Display and Search, leading to different budget allocation decisions. In the long-run, optimizing with MTA can help marketers prevent underfunding demand-generating Display campaigns. Without the demand generated by Display, Paid Search would suffer from a shortage of new customers, which would ultimately harm Paid Search efficiency and curtail overall business growth.

Multi-touch attribution is a necessity for advertisers to maximize the productivity of their marketing budgets. By utilizing MTA, marketers are able to more accurately value each channel’s contribution to KPIs. Proper channel valuation is a necessary prerequisite for smarter budgeting strategies that maximize performance.

Understanding Incremental Opportunities
Utilizing MTA helps shine a light on channels whose impact on overall performance can be hard to measure. Even within Direct Response-focused channels, marketers can use MTA to understand which efforts are driving the most impact for advertisers. These insights can help marketers make a case for incremental budget. It is important for marketers to look deeper at how multi-touch attribution breaks down credit for conversions, and should do the following:

  1. Look for channels earning MTA credit for conversions possibly attributed to other channels. Channels which have lower first/last-click conversions tend to gain more credit using MTA. Be sure to support and fund channels influencing conversions elsewhere.
  2. Understand the connection between demand-generating channels and channels closing conversions.

It can be easy to look at MTA insights and see demand generation tactics getting more credit while DR-focused channels “lose” credit. But advertisers should keep in mind that they need both of these pieces to be successful, and should avoid snap judgements that take away from a channel they may need to close conversions.

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Advertisers must adopt a holistic, cross-channel approach to media measurement to make strategic marketing decisions that maximize the effectiveness of marketing programs. Now that the barriers to entry have been significantly reduced by Google’s integration of Adometry into DoubleClick, marketers have more reasons than ever to explore MTA.

Data-driven attribution is no longer a luxury. It is an essential tool marketers should leverage to gain greater insight into how their campaigns influence behavior.

Authors: Brandon Speers, Senior Media Manager and Sam Franklin, VP, Data Science at 360i

Cover photo via Exchange Wire.