A few weeks ago I wrote about a digital analytics phenomenon wherein many analytics tool vendors had begun making claims they could join data from multiple sources and display the results in a set of dashboards for marketers. I called it Convergence Analytics.
Evidence continues to mount that this has begun to transform the measurement industry. One major development in this regard is that Google recently announced the beta release of its Universal Analytics tool, which purports to join data from multiple sources and display the results in a single dashboard for marketers. Didn’t you just read about that somewhere?
The goal of all marketing analytics has been, and is today, to “get the right message to the right person at the right time.” Companies like [x+1] have been pursuing this goal for many years with success amongst their enterprise customer base, and they have created a “decision engine” to support their real-time recommendations. And while others may have had other ways of saying it and doing it, all analytics tools have been supplying the marketer’s need for insight toward this goal for many years as well. Today’s trend toward convergence analytics makes a general improvement in messaging more likely.
The reason I advocate for convergence analytics is twofold. And neither of them is because I am in love with the idea of data being collected about folks in general (and I do believe we continue to need a forthright national dialogue about what consumers should feel comfortable with, and what they should not).
The first reason for my support is that organizations spend so much money on digital channels but typically get so little insight into success factors that it seems they still need a better way to understand whether they wasted their money or not. I think the “messaging” industries have been exploiting this gap shamelessly, forever. It would be great if they could be held to better accountability – a goal that is part of the promise of convergence analytics.
This brings me to the second reason, and that is simply that much of what passes for “targeting” these days seems more like carpet bombing than corrective surgery. I consider myself a fairly typical Internet user despite it being a focus of my profession. Personally, I limit my time online because I still find things like daylight and river breezes oddly enchanting compared with the latest news on Mashable. But that is what makes me sort of average, I think.
So, being an average user, what is the average quality of messaging I receive online? It’s below average. In fact, much of it is ludicrous.
I am still trying to imagine what behavior of mine prompts messaging to me about “one weird trick” to lower my car insurance rate. Or why shocked-looking seniors are overjoyed to tell me that Obama is giving away money for education. Yes, I have car insurance. Yes, I have an education in my background.
My guess is that too many advertisers are relying too heavily on ad networks to understand this user, based on some overly broad, not very target-savvy algorithms. In fact, I would say the word “algorithm” is probably used much too often to describe what are very unscientific demographic-based “buckets” that have improved little since the last census and that continue to supply the “insight” behind the ad buys of many less sophisticated networks. My guess is that they are almost never relying on anything like actual “decision engines” or deploying any “predictive analytics.”
The latest technology in measurement will be focused on more robust views of customer behavior. The data will come from browser-based behavior, mobile interaction, app usage, social gaming, call-center information, chat analytics, and CRM and POS data. Like Google’s universal data collector, this breed of tools (which will come from both new and existing vendors) will help enterprises understand and correlate user behavior as never before, and will soon represent the standard way for marketers to review cross-channel activity.
I hope it will also successfully perform the weird trick that will save me from seeing yet another ad about a weird trick to get either better insurance, more sleep, or less fat in my diet.
Convergence analytics. It is coming on fast, and we will all be the better for it.
As an organisation, finding the right marketing channels is an essential part of your marketing strategy.
When measuring the effectiveness of discount codes, retailers often get it wrong. In this article, we'll look at how data-driven attribution can help businesses better understand where discount codes produce the best ROI.
Data. It’s the latest ‘buzzword’ in the digital marketing world when it comes to content.
The term ‘marketing cloud’ has gained significant traction in the last few years as major software companies have sought to monetise the growing importance of technology for marketing teams.