Can Digital Analytics Save Itself?
Digital analytics today is burdened by disillusionment and disappointment. Not that there are no success stories with digital analytics. There certainly are. But they are comparatively rare. Much more common are legions of valiant but frustrated marketers continuing to struggle with the basics:
Is data collection accurate? Once we learn what the data tells us about our business, are we in a position to do something about it? What happens when our agency tells us they’ve taken care of measurement and, behold, the campaigns are “all good” (or at least not a total waste)? What does change really look like, and can we make it happen in time to matter? How do we do that without automation? And where are the successful predictive models that drive automated responses?
The unanswered questions don’t stop there, but for the sake of brevity we shall.
No one suggests that organizations go without analytics. And many businesses do get to a place where they are comfortable measuring with accuracy and understanding. Many fewer end up being able to fix any but the most egregious “disconnects” between themselves and their customers. The vast majority settle for knowing what happened, with a moderately strong determination to do something about it “in the next release.”
How Digital Can Deliver for Marketers
Many of the most dire threats to success in digital marketing can be overcome by adhering to a process. The process is not very mysterious, and, in fact, can, with some alteration, be applied to almost any endeavor requiring rigor and results.
The process looks something like this:
1. Determine key performance indicators
2. Implement data collection and reporting
3. Review and analyze reports
4. Make content changes
5. Measure again to prove success
Following these will go a long way to avoiding disappointment and marketing paralysis, but often it proves devilish hard to get through the process.
Saved by Automation?
The toughest parts of the above process are numbers three and four.
It’s easy enough to figure out your basic metrics and get the data collected properly as long as you have a team of analytics experts. We’re pretty much overrun these days with analysts, but often it’s tough to turn what they say into recommendations. Then, the most difficult part is getting changes made. Figuring out what changes to make, and how to get them made, typically slows the process nearly to a halt.
Automation will be key in changing this from a roadblock to a starting block.
With Tealium’s AudienceStream, you can build in rules and thresholds that send out directives to content delivery systems that let you know it’s time to contact the customer with an offer (for instance). The key to its success is its timeliness and the certainty of its execution. It becomes automatic.
Conductrics deploys Artificial Intelligence to create a system of learning and action based on data. For marketers, this means that Conductrics will facilitate the creation of an “agent” that seeks out challenges and then tackles them (for example, it looks for meaningful patterns and then can direct content to be distributed as needed). Conductrics has likened their agent to a Roomba for digital analytics. It learns its environment and then focuses on doing one task very, very well automatically.
XplusOne [x + 1] markets a product called Origin. According to the firm, “Origin harnesses data to drive real-time, one-to-one interactions across all your digital channels, so every prospect and customer interaction is more relevant.” They also deploy a Data Management Platform that controls numerous customer touchpoints automatically.
These products help conquer the challenges of what many today call omni-channel marketing. They help address how customers can be reached in various “states,” as Rand Schulman has pointed out.
Automation is moving ahead rapidly. It may save analytics by embedding it into an automated process — which probably is where it belongs.