For the past 10 years, last-click attribution served the industry quite well. It was a far cry better than traditional media evaluation from the likes of Nielsen, which has been a mostly speculative exercise in measuring consumer engagement with brand messaging.
With the recent emergence of mobile and video, we have moved beyond a purely desktop marketplace. It’s time we take a more sophisticated, holistic view of the brand-consumer dialogue. It’s a dialogue that increasingly flows in both directions — and with vast potential for even greater engagement facilitated by the Internet of Things, last-click attribution is clearly anachronistic. Now that technology and modeling have facilitated marketers’ ability to track and analyze the entire consumer journey, it is time to formalize an industry standard to give credit where credit is due in all sales conversions.
Cross-channel attribution modeling is no longer a luxury; it’s an imperative. Consider how differently consumers behave depending on the vertical under consideration. Consumers in the
market for consumer electronics will engage with branded content and review videos on YouTube, for example in a completely different way and with a different end goal than they would approach content
related to auto brands. Both frequency and sequencing of brand messages become more efficient, effective and engaging when cross-channel attribution modeling is applied.
Here are four factors to consider when implementing cross-channel attribution on behalf of a brand or customer.
Know the tech: Do a thorough survey of available technologies in the marketplace that facilitate data collection of and analyses on customer behaviors across all devices and channels.
Stay the course: With increasing visibility into customer behaviors come new findings. Constructing actionable insights based on these findings is a great beginning, but it may not get an organization from A to Z. Take the time to accumulate enough data to flesh out an accurate story. Stay open-minded through the twists and turns created by the diversity of user behaviors within a singular customer base.
Go interdisciplinary: Big Data can be hard to gather and even harder to interpret. Don’t be afraid to seek help when trying to make sense out of massive quantities of data in a more quantitative, scientific way. Often economists or data scientists come up with better attribution models than anyone else within an organization.
Hold data tight & treat it right: It’s important for marketers to own their customer data— or at the very least, have a trusted technology partner own it for them. Most importantly, all data should be protected and properly deleted according to industry and client-specific regulations.
If properly applied, these steps will help brand marketers from any vertical make significant inroads in optimizing ongoing dialogues with cross-device, cross-platform consumers. It’s never too late to get started.