30
Oct

Data Gaps & Governance: What Was True in the Morning Becomes a Lie Before Noon

Written by Andrew Edwards. Posted in Analytics, Data Integration

You sit at your desk, aware you are supposed to make decisions based on data and knowing that a great deal rides on your choices. Which content goes front and center? Which campaign gets yanked? How can you direct your agency in creating content more effective at converting prospects to customers?

The company has invested millions and management wants to know how the new bag of tricks is doing against the old.

You log in to the digital analytics dashboard and find what you think you need. It’s supposed to show campaign attribution–but it’s only based on the last click. It’s also supposed to show content popularity, but lacks conversion perspective. The paths into and out of the contact page are baffling, to say the least. You call up your analytics admin, who calls the report people, who call the agency that was supposed to do the tagging, to find out if this data is the latest.

In the meantime, the decision is due on your boss’ desk by noon… and it’s 11:53. She asks your opinion, so you assume she wanted your judgment, not the digital beeps and bytes of some machine. Looking everything over, you make some lightning decisions and, feeling smart and well-informed, send an email to your boss at 11:59, to which she simply replies, “Thanks.” Time to grab an in-house latte because that cafe around the corner, while it may be better, is charging seven dollars for a cup of hardcore joe and some cream.

At 12:20, you get a call from your analytics admin, who tells you the agency (who don’t specialize in analytics, but are performing the work as part of their premium support package) never got around to tagging that part of the site, because they were “coding a mobile app that took longer than expected”.

“And what does that mean?” You ask, careful that your tone conveys gentle concern.

What it means is that none of the numbers are relevant or even remotely accurate, because none of the new pages have been measured since they launched a month ago.

You drop the phone but rapidly pick it up and place it back on the receiver. Your boss won’t be back until three. Can the site get tagged and measured before then? That, you know, is a vain hope and shame on you for even thinking about it. Worse, even if it could be tagged in a jiff, you cannot “replay” any data because, without tags, nothing was collected. You’ve got goose-eggs. And goosebumps. Perhaps if you check your Twitter feed, it will all go away.

A text from your boss interrupts your foray into the Twitosphere:

“Data inaccurate? Let’s talk at 12:30.”

Your boss is coming back early, and you’ve had this talk before.

Last time, you had recommended a better process; one where agencies did not own the responsibility of tagging their own creative. Where a centralized data collection team, expert in the art and science of collecting and displaying data, in conjunction with perhaps a tag management solution, would provide both expertise and governance.

Like many recommendations requiring a complex initiative, it was praised but ultimately not implemented.

Maybe this time the talk will be different. It could go one of two ways.

First, you might be blamed for providing inaccurate data and therefore useless insights.

Second, you might be asked to resubmit that governance proposal.

Governance has become easier with the right tools; with properly configured roll-up reporting and an up-to-date tag management tool (plus the essential expertise), this can be solved.

Chaos, as a result of lack of process and lack of expertise, defeats technology and the insights that come from it. The expertise is not impossible to find and the tools are maturing.

It should be easier to make the case this time.

You put down your latte and head for your boss’s office.

A Completely Fictional Story, Right?

Not really. This plays out every day like clockwork, across the country, in companies large and small.

Governance is critical in managing the masses of data available in online business, yet 44 percent of respondents to a recent survey by Rand Secure Archive admit their organization still lacks a data governance policy. Within the next year, 50 percent of respondents plan to take action on data governance.

Whether or not you’re a driver for this necessary change in your own organization depends largely on how you sell the necessity to the boss down the hall.

Have you instigated change in how your organization handles data? Share your tips and experience in the comments.

28
Oct

Convergence Analytics Now: 3 Ways This New Market Changes Everything

Written by Andrew Edwards. Posted in Convergence Analytics

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.

 

10
Oct

Convergence Analytics 2.0: Everybody is Still Measuring Everything

Written by Andrew Edwards. Posted in Convergence Analytics

How much does multi-channel analytics really help the marketer?

It’s hard to believe it was only six months ago when ClickZ published the first Convergence Analytics Report that I co-authored. We just launched the second Convergence Analytics report at SES San Francisco and I feel like we were barely able to document some of the latest changes taking place in digital analytics today. Suffice it to say things are moving very, very fast in this field.

Our tag line for the first report was “everybody’s measuring everything”. We were referring to the way nearly every vendor and many practitioners were planning to broaden their web analytics plans to include social, mobile, demographic, seasonal, advertising, customer relationship management (CRM) data and more into a single discipline.

Some folks call it “multi-channel analytics”. We called it Convergence Analytics because we were describing the convergence of many channels into a single tool—but also because we were describing how a multitude of vendors were converging on the notion of providing a single view into many measurement channels.

Today the rush to single-vendor solutions seems more headlong than ever.

But just because everybody’s doing it, does that mean it’s a good thing?

Allow me to answer that question with a definite “maybe”.

It’s a “good thing” if certain criteria are followed:

  • the practitioner has in place both expertise and a process for deployment and action
  • the vendor is in fact delivering an integrated, robust and accurate solution
  • expectations are kept in check
  • costs are managed

In our second report we called out a number of factors that seemed to be impeding adoption of what really is a good idea – the ability to see more data at once, more quickly and at lower overall cost.

The biggest problem in a volatile market like this is that it’s very confusing for the buyer. There are simply too many analytics vendors talking about the same thing. Some are aligning what they say with what they deliver, and that’s the way it ought to be.

Many more are shoehorning themselves into what sounds good at the moment, and at the moment that might be multi-channel analytics. Paraphrasing an old Love Story, “SaaS means never having to say you don’t do that.”

Tomorrow the same vendors will pull back and say they are vertical (specialized for a single-market or single-solution) and would not dream of trying to be all things to all people when their tool is limited or perhaps unfocused. Because that would be dumb. And because investors aren’t putting their money into companies that say they measure everything for everyone all the time (which is probably true).

The ability to look at more information from more sources in one place is prima facie advantageous. For the general public, a device that provided this would have been called (until recently) “the newspaper”. For digital businesses, it’s more technological and less obvious, but it’s the same sound principle: the more you can know about your world, the better decisions you can make.

A newspaper might have told you it was likely to rain later. Better put on your boots. And it might have told you the garbage collectors were striking so you might also want to pack a posey. What about an analytics tool that could tell you how web was affecting mobile, and further, help you automate the content served to specific customers in your CRM database?

A digital analytics tool that would tell you only what was going on with your web pages, and assuming you didn’t have other ways to measure or act upon the rest of your digital properties, would be a prime candidate for retirement. Is it any wonder why, with the sudden emergence of a hundred and one digital channels, that every company that ever measured anything, and some that really never did, would flop towards the concept like seals to a bucket of mackerel?

Seals are smarter than that, and so are most vendors. The bucket of mackerel has only a certain amount of fish in it. And the notion that to measure everything is something everybody can do is more than a little bit fishy. Vendors without strong, integrated offerings and enough cash or customers to stay competitive will either go the way of all seals or find another pool to swim in.

Some market-leading companies, and some very capable upstarts will thrive and prosper in Convergence Analytics. They will find customers that have the right expertise and processes in place to make worthwhile the effort of deploying a complex measurement application. Their tools will be powerful, different and useful, rather than just cleverly described.

I believe the future will see marketers looking at multiple streams of data in contextually relevant ways that help drive their marketing programs more quickly, more efficiently and in a way that yields more tangible results.

At that time, the “maybe” I suggested above would become a more definite “yes”. But until we can better understand how to select and deploy the right technologies and disciplines at the right time, we are just splashing around in the crowded, shallow end of the pool.

Convergence Analytics 3.0

Convergence Analytics 3.0

Written by industry insiders Andrew Edwards and Rand Schulman, Convergence Analytics 3.0 is a Free Guide written for Digital Marketers interested in understanding the most important trends, technologies and practices in analytics today.

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