How Cross-Channel Attribution Powers Smart Marketing

cross-channel attributionIntegrating digital campaigns is key to building a seamless user experience, but marketing across channels can make it difficult to track which campaigns are driving conversions. When you can't pin down performance for separate campaigns, you can't apply optimizations with accuracy and ROI remains a mystery.

This is why cross-channel attribution is so important. Attribution is the process of accurately crediting separate campaigns with the results they drive on an individual basis. This isn't as easy as it seems — if one customer engages with a brand through three separate channels before converting, there's rarely a clear indicator of which channel was most instrumental.

The right performance metrics are critical to optimizing performance, and these metrics are only available when using an analytics solution capable of cross-channel measurement and attribution. Without this tool at your disposal, brands can't squeeze the best ROI out of their campaigns. Here's how cross-channel attribution drives smarter marketing.

Attribution Powers Instant Change

The latest attribution technology doesn't just nail down performance per channel. It can also drive instant change to certain automated marketing processes. For example, technology can sync with real-time buying engines that purchase online ad spaces through programmatic buying systems, scaling spending up or down based on recent performance metrics. All of this can happen without your oversight, allowing quicker and easier optimization through attribution platforms.

Elusive Values Are Seen With Clarity

Marketers aren't trying to solely quantify conversions and other finite metrics. Even those tough-to-compute gains of marketing — think brand recognition and saturation — can be assigned values through attribution technology. This not only pins down value by channel, it also provides a more comprehensive view of what each channel is providing. This is crucial when evaluating channels that don't directly drive conversions but are instrumental in top-of-funnel engagement, including raising brand awareness.

Predictive Modeling Can Forecast Channel Value

According to eMarketer, an estimated 57 percent of marketers were leveraging cross-channel attribution models in 2017. One reason for this growth is an explosion in artificial intelligence, both in terms of its predictive modeling capabilities and its availability to brands. Campaign reported last year that Google's analytics platform now offers its AI capabilities for free to businesses, making attribution solutions more accessible than ever before.

Third-Party Data Can Fill in the Picture

Limited data for marketing campaigns can complicate attribution efforts, but this doesn't have to be a deterrent. Because attribution solutions aim to identify patterns of behavior that follow an intuitive logic, third-party data can always help color a brand's marketing performance with a full palette. You can plug data in where your own feedback is scarce and use this information to see how campaigns are working together. This makes the data from even low-volume marketing channels easy to read and reliable in practice.

Cross-channel attribution was once an impossible solution, but today's technology has made it accessible to any brand. If you have the data, you can use attribution to discover the truth about your channel-by-channel performance.

Google Ads Partner
graphical user interface, text, chat or text message
optimize 360 logo
logo, icon
logo, company name
logo, company name
a drawing of a face
diagram, venn diagram
Google Ads Partner
graphical user interface, text, chat or text message
optimize 360 logo
logo, icon
logo, company name
logo, company name
a drawing of a face
diagram, venn diagram

Our Partners and Publishers

When it comes to your digital marketing, we only partner with the top leaders in the industry to help get you the best results possible. Because we're a part of CMG, digital advertising with us is credible, accessible, data-driven and transparent.