Data, data, data. The digital revolution’s promise was that data would finally let marketers and agencies alike know how their advertising dollars were working and whom they were attracting.
Well, as we all now know, the great promise of digital transformation was a bit of a bust. The path from awareness to conversion and loyalty is not linear.
Ever since the emergence of digital advertising and social platforms, the industry has been obsessed with achieving marketing and advertising’s holy grail: a guaranteed way to ensure that every dollar spent results in a few more earned.
While this pursuit is a noble one, our ability to fully achieve it remains in the future.
On the Path to Data Transcendence
Even so, significant steps have been accomplished in recent years.
Most notably, big data computing innovations, such as Hadoop, have come to fruition that for the first time enable the integrated analysis of hard data (SKU codes, inventory, etc.) and soft data (social posts, web clicks and the like).
“The shift from back-end data analysis to front-end predictive modeling has reshaped our expectations of the digital revolution.”
These processing innovations in turn have spurred new software marketing suites, such as Marketo, that let brands proactively respond to web users’ actions. Suddenly, marketing strategies have moved from performance discussions and back-end reporting analytics to lead scoring and tailored communications.
The shift from back-end data analysis to front-end predictive modeling has reshaped our expectations of the digital revolution.
We have moved from a vision that emphasized the ability to confirm return on investment to a new focus on extrapolating data to predict user behaviors so we can lead our users to predetermined outcomes.
Think about that for a moment. By instantaneously analyzing users’ current actions with historical information and “like” modeling, we can predict their next moves and provide them with information that either reinforces their decisions or shifts them in a different direction.
The Personalization Craze
The transition in the role of data has given birth to a new wave of personalization engines, such as Acquia Lift, that let companies track a user’s every move, connecting actions and movements before, after and across multiple visits to their websites from different platforms—all the while altering the information presented to the user.
To put this in perspective, early in 2017, Manifest had never been asked to build a site with a personalization engine. In fact, no client had even inquired about our point of view on these new tools.
But fast forward a year, and Manifest was building three sites with personalization engines. Today, personalization is a consistent topic of conversation among progressive-minded clients.
One site that we built connects users’ content behaviors to their previous purchases, ultimately affecting the information they see based on their job titles, the size of their companies, geographical location, industry type, purchase history, seasonality, content consumption, and organizational priorities or promotions.
The Coming Content Demands
The potential applications resulting from front-end data analytics are endless, and the implications are great. Managing, analyzing and manipulating data is the future of marketing and will require rethinking how content is created as well.
As personalization engines become more pervasive, the more tailored content will need to be. And the more personalized the experiences, the more variables that content will need to address.
Content will need to provide different views for any one issue to match the dozens of different lenses our potential visitors each bring to their moment of engagement.
