Marketers looking to optimize their media investments today face an extremely difficult directive — accurately allocating credit for a conversion or engagement activity that resulted from an increasingly complex touchpoint path that spans many channels, devices and interactions. The majority of marketers can’t say with confidence exactly how valuable each channel or touchpoint is during each customer’s purchase activity. That means they can’t say they’re effectively spending their budget and optimizing revenue, which is the entire goal of attribution. Marketing attribution — assigning credit to a marketing touchpoint — has never been more complicated. The explosion of marketing channels and devices has added layers of complexity to what was, not long ago, a relatively simple funnel.
Legacy attribution methods no longer serve the purpose, as they cannot take cross-channel influences and synergies into account. To develop a more precise customer reach strategy, optimize spend across multiple tactics, campaigns and channels, and to measure the impact of cross-channel marketing campaigns, marketers need to use an advanced algorithmic attribution methodology.
And, to complicate matters further, this must be done quickly in order to take advantage of changing market conditions, and to keep pace with the competition and changing customer behavior. Currently, marketers are challenged to optimize their media buys using algorithmic attribution models due to inflexible budgets and partner contracts, a mass of customer data that is locked in silos, and the sheer time it takes to collect data, interpret insights and execute the optimization strategies that they present.
It’s now imperative for marketers to demonstrate the value of their campaigns and show what worked or didn’t.
How does your marketing team handle the complexities of attribution?
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