Parallel to this expansion of digital channels and touchpoints has been the rise of marketing analytics and the explosion of big data used to influence marketing campaign decisions. Today, the emergence of digital into the marketing landscape has led to an oversaturation of big data as more organizations look to understand their audiences across today’s omnichannel customer journey.
In order to leverage big data for more effective marketing efforts and revenue growth, it’s crucial that marketers understand how the introduction of digital media has given rise to this big data explosion. They must also know how to avoid common mistakes leveraging this data in order to properly attribute campaign efforts and maximizer impact.
Along with the new technology and consumer trends that digital media and technology created, the digital revolution also expanded capabilities of marketing measurement and modeling efforts. Beforehand, the marketing landscape was limited to print and broadcast channels. As a result, marketers leveraged long-term, aggregate data through the use of media mix modeling (MMM) to understand their engagement and marketing spend.
As the digital landscape matured, more opportunities to leverage digitally generated data emerged. Analog industries like print and broadcast began incorporating digital capabilities into their operations, leading to an explosion of mass data sets that marketers could leverage as a basis for marketing decisions.
While the emergence of digital media and the corresponding big data influx provided new opportunities for marketers to understand their efforts and attribute value along high-impact channels, it also led to an oversaturation of big data. This resulted in a “paradox of choice” for marketers deciding which data sets to gather and distill into marketing insights. In other words, the marketers who understood the big data they gathered could use it to accurately optimize their efforts, while those who didn’t often misattributed their efforts — leading to inaccurate campaign shifts.
When it comes to the success or failure of your marketing efforts, understanding how to leverage big data makes all the difference. Considering that 64 percent of advertisers globally are now leveraging big data from third-party sources, it’s proving to be the workhorse behind modern omnichannel attribution. However, leveraging large data sets across the online and offline channels used to engage customers can be tough. Just having access to large data sets doesn’t necessarily make them useful. Similarly, if you have the right data but don’t have the capability to piece it all together, it’s likely that data will go to waste.
Understanding where big data fits into measurement and modeling efforts is key to accurately leveraging that data and effectively attributing touchpoints across the omnichannel marketing mix. Diving deeper, understanding exactly what data is required for effective attributions, how to gain access to that data, and finally, how to can distill that data into actionable insights are keys to success.
In order to reap the benefits of big data for marketing attribution measurements in today’s omnichannel landscape, it’s important to understand several key elements that help ensure efforts are accurate, and more importantly, beneficial to campaign efforts. With this in mind, consider the following:
For successful omnichannel attribution across both online and offline channels, look for the specific data sets that can help match consumer actions across channels down to the person level. Specifically, focus on:
Print: Subscriber lists that can be matched to geographic regions
Television: TV and cable box subscriptions that highlight advertising reach and air time
Radio: Broadcast range and zip code data
Digital: Multi-touch attribution measurements and engagement metrics across devices
Market landscape: Brand authority measurements, marketing mix models and creative messaging a/b test data
All marketing analytics software is not created equal. In order to accurately organize and distill the massive amounts of data being pulled, look for a platform with the capability to match congruities together across the various data sets pulled. Piecing together congruities at machine speed allows you to identify consumer behavior down to an individual, helping to attribute across the omnichannel marketing landscape.
In order to turn the big data you’ve distilled into actionable insights, you need to understand where the impact occurs at touchpoints along the customer journey. This way, the touchpoints scored by your attribution models will accurately highlight where a consumer prefers engagements along various channels and when these engagements are most likely to have an impact.
In the wake of the digital takeover, marketers now have access to an overabundance of big data they can use for better marketing attribution. However, this surplus of information has made it easy for marketers to make mistakes when choosing, organizing and distilling that data. To prevent this, marketers need to understand what data they should pull, what martech they need to stitch their data sets together and how to organize it for accurate attribution.