In March of this year, ClickZ published a report I co-wrote called “Convergence Analytics: Digital Measurement in Transition.” I am happy to say it was well-received.
In just over three months since publication, the convergence analytics market has grown so rapidly that this column now represents the first under a new section at ClickZ. Expect to see more about convergence analytics in this space, as well as at SES San Francisco this September.
Convergence Analytics Now
Convergence analytics has been called “multi-channel analytics,” “big data visualization,” “business intelligence for marketers,” “real-time analytics,” “enterprise analytics,” and very recently even “omni-channel analytics.” It’s a safe bet that a hundred different vendors are fielding a tool (or suite of tools) that they will claim, in some way, shape, or form, can “measure data from any source” and “present it to the [target audience] in a visual, interactive interface.”
The most remarkable aspect of the market right now is its relative incoherence as compared to more mature markets like “digital analytics” or “direct marketing.” As the market begins to crystallize, both vendors and practitioners will need a core set of definitions around which to formulate requirements and offerings; hence the need for an overarching concept like convergence analytics.
The convergence analytics market encompasses all of these buzz factors and more. It represents the future of all digital analytics from this day forward. As has been said about other rapidly growing industries, “it’s still early days,” but we’re seeing an explosive growth in offerings, and if you’re not already dealing with CA today, expect that you’ll need to do that in the not-very-distant future.
Convergence analytics, from a technology-centric viewpoint, represents an emerging market that concentrates on the confluence of digital analytics, big data, robust algorithms, and advanced visual presentation. From a marketing standpoint, it’s about the “un-siloing” of data from a variety of places within the organization. Start with the combination of desktop, mobile, and social; then go from there.
How It Changes Everything
1. Web, social, and mobile: not cutting it anymore. When we ran our first CA survey, about half of the respondents said they defined “multi-channel” to include the above three disciplines. However, the other half said it included those plus more channels. The number of organizations needing to combine data from more than just these three sources is growing rapidly. “Web analytics” is already retired as a term in and of itself. “Digital analytics” seems fairly coterminous with the above three areas of interest. But just those three don’t cut it anymore. Organizations now want to look at those plus demographics, campaign data, ad-buy data, e-commerce data, in-store data, call-center data, CRM data, unformatted data from a variety of sources, and so-called “big data,” which is a buzzy way of saying “everything that can be tracked.”
2. Connectors, connectors, connectors. As in real estate, in which “location” completes the three most important aspects of a property, connectors may prove to be the most important asset a convergence analytics vendor possesses. Much of the technology behind connectors (and the rest of CA) has been around for some time, yet now it is put together in new ways (the Wright brothers did this with bicycles, boats, and kites; we ended up calling it an airplane). Now existing technologies are coming together to form convergence analytics.
But the most important unit of CA vendor technology – the one they build their businesses around – are the connectors they build to a variety of data sources. If they don’t work properly, nothing else in the analytics process works either.
In order to master convergence analytics, many practitioners will have to understand some previously data-scientist-only terminology like “ETL” (extract, transform, load) – which is what connectors really do. If you thought marketers had already needed to go a long way toward technology and data, it’s only just begun.
Getting to know the details behind how data integration actually deploys will change the workday of every marketer from now on. And if you’re not doing so already, get ready in the near future to ask your current or prospective analytics vendor about how many channels they connect to – and what they will do if you have a new data source for which they don’t already have a connector.
3. Convergence analytics ownership in flux. Who will own convergence analytics? It’s destined to become the clearing house for all marketing data (and much that isn’t related to marketing); but it represents a much higher technology bar than any breed of tracking tools that have gone before. Will marketers really run convergence analytics the way they have run digital analytics? Will they want to? Will the CMO be responsible for a vendor solution that crosses not just marketing disciplines but also IT, sales, operations, and perhaps even finance? Will she want to? Will newly minted data scientists rule the convergence analytics roost?
All of this is unsettled and up in the air. But it’s going to land soon – probably pretty near your desk. And when CA becomes the norm (as it soon shall), get ready for some major organizational changes. Whomsoever can claim to understand this new type of offering best and most comprehensively will likely carve out a new and very desirable niche for themselves within the organization.
The insights available from the control of an unprecedented amount of previously siloed data is going to be – unprecedented! And the winning organization will be the one that gets out ahead of these major transformations with the right people in the right place at the right time.
Image on home page via Shutterstock.
ClickZ and Efectyv have come together for the second time to create a follow-up survey that dives deeper to measure the importance of convergence analytics in the current online marketing environment. The results will be compiled and analyzed into a report that will debut at the Convergence Analytics Executive Summit at SES San Francisco this September. Please take a moment to answer the survey here.
In this article, we look at how to use data to tailor discounts to specific customer segments, reducing the cost of customer acquisition and ultimately optimising conversion in the user journey.
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.