Tag Archives: Data

Flying Blind

I almost called this post “Nobody Knows Anything” but that might have been overkill. I’ll say what I have to say and let you be the judge. Let’s say that you buy a friend’s newborn a gift. You have it shipped to your house. The data says, correctly, that you bought an infant gift. That might also lead to an inferred piece of data that places your household into the “presence of infant” bin, leading to you seeing lots of ads for diapers. If you’re the one placing the ads for those diapers, you’re wasting money.

Lots of the data marketers routinely use is of that sort. It’s inferred. You can see that some thinking at work if you’re a Netflix user: the recommendation engine infers what you might like based on your past viewing. Of course, if your kids or someone else in the house watch something in which you have no interest, the accuracy of those recommendations is diminished (which is part of why there are separate profiles available when you log in). Inaccurate data is, sadly, more the norm than an aberration. Since this data is really what’s behind personalization and targeting, that inaccuracy is a big problem. Any business that buys data from third parties – and an awful lot do so – may be putting garbage into their system. Unfortunately, most don’t know that because there is little transparency in the data business and it’s impossible to verify what’s good and what’s not.

What should you do? Invest in collecting your own, first-person data. You can also demand transparency in any other data you use (good luck with that) with respect to how it was gathered and what it really represents. Is it inferred or does it come directly from consumers (did someone tell you they had a baby in the house or did you guess they did because they bought one infant item?). Who owns the data and was it gathered with the consumer’s permission?

When Facebook tells its customers (marketers) that they have data on 41 million adults aged 18-49 in the US and there are only 31 million of those adults living in the US, you know much of the data is inferred and also that we have a problem. A recent study that found that 70% of marketers believe that the customer data their organizations are using for marketing is low quality or inconsistent. Why bother to market at all when you’re just flying blind?

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Filed under Consulting, Huh?

Measure What You Can Measure

The NFL is getting ready for the annual combine. This is where players get tested both physically and mentally to see if they’re NFL material. There is psychological testing to test intelligence. They run the 40-yard dash. It’s a 4-day job interview, much of which plays out on TV.

Teams use the data to make decisions about which players to select in the annual draft. They can stack the reams of information from the combine with the data generated over the course of a player’s college career and choose someone who will, hopefully, fit into a team’s depth chart as well as its philosophy.

Anyone who follows the NFL will tell you that all of this data has its place but it’s far from infallible. Kurt Warner, a 2-time NFL MVP went undrafted. So did Warren Moon, a Hall Of Fame quarterback too. Put Tony Romo on that list as well. No team looked at the data and thought any of these men were worthy of a draft pick. Oops.

You just might be guilty of the same thing in your business. The data isn’t infallible and the data only measures what it’s designed to measure. Tom Brady (selected 199th in his draft year) recently told NFL prospects that they can’t measure heart. He’s right, and it’s because there isn’t a solid way to capture that data.

How are you making this mistake? You might be using one data point to draw a conclusion that isn’t right. Correlation isn’t causation, as we hear so often. Grateful Dead fans don’t all smoke pot and have long hair. Identifying a target as those fans doesn’t mean you should be promoting to the stereotype.

Another faulty conclusion might be due to an error in the data itself. I had an advertiser on a site I ran complain that they weren’t getting great results. They had neglected to respond to a question from their salesperson about turning on frequency capping to extend their reach and limit the number of times a day someone saw their ad. They were reading the data correctly but the data itself was faulty due to an underlying issue.

One of my favorite data error is the foundation of the entire TV business, the Nielsen Ratings. The TV and ad industries have attached an accuracy level to Nielsen ratings that even Nielsen says is unreasonable. A study of a few years back found in analyzing 11 years of data that the margin of error for reported results was often more than 10%. That might not sound like much but it can represent hundreds of thousands or even millions of impressions. The issue here is that buyers are too focused on the (inaccurate) numbers rather than on precise metrics such as sales.

Measure what you can measure. Don’t extend that measurement to other things that aren’t measured as well. I bet your results will improve. Let me know?

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Filed under Consulting, Helpful Hints

Fighting About Data

I think everyone knows that a lot of data is collected as we conduct our daily digital activities. Google and the other search engines know what we’re looking for, Amazon and other commerce sites know what we’re shopping for, Facebook knows what we like, LinkedIn knows who we know, etc., etc., etc. These data footprints are collected and in many cases sold to marketers and their agents to allow them to serve ads to you. If any of that comes as a shock to you, I’m not sure where you’ve been for the last decade or more.

What you might not have thought about, however, is that the ads themselves collect data. How many times has someone seen it? What kind of person (that pesky data that the aforementioned guys have) has responded to an ad, and how well do the ads translate to sales (lovingly called the conversion rate as if someone is changing religions…). As it turns out, there is a bit of a controversy about who actually owns that data: the advertiser or the agency. The marketers believe that they are the rightful owners while the agency folks believe just as strongly that they are. Neither side feels that the publishers who serve the ads and, therefore make data collection possible, have much of a claim to it. Of course, even publishers came out ahead of one other group as the rightful owners in the survey: consumers.

As you can see in the chart, only 10% of advertisers and 15% of agency respondents believed that consumers had a claim to their own information. That’s tragic. Why? Because it represents a mindset that is ultimately self-defeating. It can lead to legal problems at worst and consumers opting out (if they can figure out how) at best. What have the advertiser or the agency done to give the consumer value for the data? Nothing, in my mind. One could argue that the ads they serve make possible the content the consumer enjoys, but those very ads make that enjoyment nearly impossible given the state of ad-serving today, particular in mobile.

Unless and until we on the marketing side see the consumer as at least an equal partner in our business and not as a bunch of rubes or just as “data”, the problems with ad blocking, anti-spam rules, and other protective measures aren’t going to go away. What will go away are the people represented by the very data over which the agencies and marketers are fighting. You agree?

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Feeling-based Vs. Fact-based

Before the Thanksgiving break, I did a free consultation with a prospective client (you can get yourself one too just by asking!). We talked about where the business has been and where he thinks it should be going. The problem we identified was that much of his information was feeling-based and not fact-based. I can hear  the frequent readers of this screed preparing for yet another rant on the value of data, so let me surprise you a little today.

English: Cyber analytics is the science of ana...

(Photo credit: Wikipedia)

The hardest thing in business is seeing over the horizon. Oftentimes we need to shut our eyes and project ourselves forward in time, carried on the magic carpet woven from what we know so far and our own intuition. The reason is that in today’s business climate the future is often very different from the past and the analytics that reflect past behaviors have to be projected forward in the context of what might be the future environment. The more ambiguity the future holds for your business the greater the reliance on your own gut.

The issue for this business is that the leadership team was either young or inexperienced in business (they are scientists, mostly) or both. That’s why it seemed as if bringing in experience and intuition (that would be yours truly) made sense. You might not be in that situation but you might be feeling uneasy about your firm’s future direction even as you act in accordance with all the business measures you have in place.

Please don’t mishear me. If you have any sort of digital presence (website, social, email, etc) and aren’t using your analytics to inform you about traffic and how users are engaging with you, you’re not doing your job. If you don’t know or understand those things, find someone who does. If you can close your eyes and feel your typical customer, that’s fantastic, but if the reality of your data doesn’t match your feelings, you need to try again. You can’t let run a business making feeling-based decisions alone. Don’t over-think, but don’t under-inform. OK?

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Some Important News You Might Have Missed And Why You Should Care

There was a bit of news that broke last week which you might have missed since it seems that the election drowns most other news out. The FCC told Internet Service Providers to be much more explicit concerning what information it collects and shares with others, and provide (mostly) clear “opt-in” requirements on some of that data collection. Hopefully, you realize that more than any other entity in the digital age your ISP (and that can be your wireless provider as well) know pretty much everything you do on the internet.

Not surprisingly, there were immediate outcries from both the broadband providers as well as from the Association of National Advertisers. “The FCC’s new sweeping privacy rules decision is unprecedented, misguided, counterproductive, and potentially extremely harmful,” the advertisers’ organization said in a statement.

This comes on the heels of Google changing their policy related to how it connects DoubleClick advertising to other data that it has about you, allowing the company to actually link your name and other identifying information to you as you surf the web. The real issue is that Google isn’t being very clear about how this information is going to be used. At leat, however, they do give you the ability to opt-out and to clear your history. Your ISP gives you no such option. Be that as it may, having to opt out is far different from granting permission by having opted in.

Obviously, the ad industry is upset because less useful data means diminished ability to track and target consumers. Having spent a career in the media business I know that this could be bad for content providers as well as marketers. But I can’t understand why explaining clearly and transparently what you’re collecting and why as well as allowing consumers control over how their data is collected and used is a bad idea. Failing to do so leads to ad blocking or worse.

What could be worse? Check out Sudo. As this article explains it, Sudo allows you to create:

nine “virtual identities,” each of which is associated with a phone number, email address, credit card number, and even profile picture. They’re digital nom de guerres, in essence — fictional profiles for services, websites, and apps to which you’d rather not supply your personal information…Sudos live as long as you want. You can delete one after a week, or devote a profile to activities like online shopping, social networking, or calling.

That, in my mind, is worse. Data is collected and associated with a false person who just disappears. So if I decide to label myself as a 35-year-old woman (which is quite different from my much older male self), marketers will waste money promoting products to me I won’t care about. When I get sick of that persona, I’ll disappear her.

Being transparent and honest with your customers isn’t optional anymore. You can fight legislation but fighting consumer desires is much harder. I suspect that the ISP’s will get around these rules by burying the information they’re forced to disclose in some click-wrap agreement. Nobody reads them; they just click “agree” and move on. I think this is a missed opportunity for the ISP’s to change their behavior, their business model, and their relationship with their customers. You?

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Filed under digital media, What's Going On

How Facts Can Be Fiction

I was discussing some numbers with someone the other day. It was clear from the conversation that she was taking every bit of data as gospel. I tried to explain a few important things to keep in mind when working with data and as I thought about it perhaps my thinking could be helpful to some of you out there in screed-land.

We all want as much certainty in our business lives as we can get. Part of that is wanting all of our numbers to be facts. They’re not. You may be familiar with the term “sampling error.” Basically, it means that the data is off because the sample from which the data is drawn is not representative of whatever it is you’re trying to measure. While you might think that, for example, your analytics measure everyone, they don’t. Most of the data we read uses some sampling. Sometimes it’s a timing issue – financial data, in particular, can be skewed based on where we might be in a business calendar or where those who pay us are in theirs.

The point is that there are error rates involved with many of these “facts” because these facts are really just estimates.  TV ratings, for example, are probably the most widely known estimates and multi-billion dollar businesses involving networks, agencies, and marketers revolve around numbers everyone knows are not particularly accurate. There are error rates.

Here is the advice I give people. Figure out what questions you’re trying to answer and then find as many different sources of data as you can. If possible, see if you can get multiple people to interpret those data sets. In theory, they should all come up with the same answers. It’s critically important that you NOT tell them what position you’re trying to support (can you find me some information that says we should do XYZ). That is a recipe for disaster because it encourages people only to look at data or interpretations of data that supports what you or they already think is true. That is turning “facts”, which are already often on shaky ground, into a larger fiction, and that’s not what we’re after, is it?

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Filed under Consulting, Thinking Aloud

GIGO

The Memorial Day weekend gave me a little time to get caught up on some reading. Some of what I was reading were analytics reports (I know – get a life) and while I very much appreciate the cycle of continual improvement Google fosters within their analytics product, that cycle yields a continuously growing amount of data. The problem that I have isn’t so much understanding what I’m reading but trying to figure out why any of it matters to my clients. I also spend time figuring out which of the numbers are lying to me. 

It’s no secret that there are an awful lot of bad actors in the digital world. Once it becomes clear how fraud is detected those bad actors move on to another form. If viewability is important, they create sites where there is 100% viewability but no content of any value. I had a client get all excited about an increase in referral traffic until I pointed out that most of that traffic was coming as a result of referrer spam. When we filtered it out, traffic was flat. Another prospect got excited by the large “stickiness” – time on site and pages viewed – that her site has. They were impressive until you filtered out the IP addresses of her employees, who spent hours a day on the site.

Silly things, I know, but it points to a common problem. An IDG study of a couple of years ago pointed out that nearly half of marketers said they struggle to make sense of the vast amount of data they get. The other half thinks they know what the numbers mean, yet many of their plans are built to achieve unrealistic metrics. The problem is compounded by what the paper identifies as the accuracy problem I mentioned above:

Why is data accuracy still such a big issue? One possible reason is a lack of investment in a defined data management process that includes ongoing, consistent data migration, data maintenance, quality control and governance. Too often data is held and managed in multiple organizational silos. This results in inconsistency, duplication, gaps and errors.

So while “garbage in, garbage out” isn’t a particular revelation, it does serve as an excellent reminder to take out the trash as best you can while compiling all of that data.  You with me?

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Filed under Consulting, Reality checks, Thinking Aloud