12月 132014

The Big Data MOPS Series with Tamara Dull

In my last post, Where Do You Draw the Line Between Relevancy and Privacy, I talked about some of the plusses and minuses of behavioral online advertising as it pertains to personal (big data) privacy. Finding the balance between honoring people’s privacy while providing them with an interesting and relevant online experience is tricky, complicated, and an issue of context. What I may consider as a violation of my privacy, you may think nothing of—or what you may consider an invasion of your privacy, I may say, “Wow. That’s cool. And maybe a little creepy.”

And about those targeted online ads. We know marketers are working hard with advertising platforms, such as Google and Facebook, to make sure we’re seeing the “right” ad at the “right” time. Do they always get it right, though? Here’s an entertaining story about a colleague’s run-in with one of Facebook’s ads. You be the judge of who got it right.

The post and ad. Here’s what my colleague, Jeannette, posted on Facebook:

Facebook example

What we know about Jeannette. If Jeannette is your Facebook friend, then you also know this about her from the many posts and images she’s shared over the years:

  • Jeannette was born and raised in Los Angeles. She and her family just moved to Austin, Texas, this summer.
  • She is an L.A. fashionista who stockpiles highly fashionable footwear.
  • When Jeannette moved to Austin, she kept us entertained with a running commentary – complete with photos - on Austin’s (lack of) fashion scene.
  • Despite the fashion faux pas, Jeannette LOVES Austin!

What Facebook knows about Jeannette. If you’ve been reading this blog series, you know I haven’t been shy about calling Facebook a machine—a big data machine. It knows and understands Jeannette (and each of us) only through the data we share. The more we share, the more Facebook learns about us. Here’s what we can assume Facebook knows about Jeannette:

  • She’s been in Los Angeles since she created her account, but she recently moved to Austin. Facebook knows this through location data, and the fact that she updated her Current City from Los Angeles to Austin.
  • She expresses a lot of positive sentiment about fashion, shoes, restaurants and rock & roll.
  • She has expressed higher levels of negative sentiment about Austin’s sense of fashion and shoes (but very positive sentiment about their restaurants and music scene).
  • She fit into the demographics that the advertiser, QVC, was looking for. That’s why the ad showed up on her profile page.

Is it possible that Facebook really understood Jeannette’s disillusionment with Austin’s fashion scene, and offered up these Austin-appropriate shoes to help her fit in? Perhaps we will never know, but it does make you wonder how effective behavioral online advertising really is.

The IM chat afterwards. After this Facebook exchange, I IMed with Jeannette. The story gets even better. Despite her initial outrage at this ad, Jeannette wrote: “I may now buy something from QVC because of [the ad]. But not those sandals – even though they seem to be popular here.”

Mission accomplished. The advertiser, QVC, gets a +1 because they got a new customer. Jeannette gets a +1 because she discovered a new retail site that can keep her fashionista cravings satisfied. And Facebook gets a +1 because they connected the dots between an advertiser and a buyer.

My only question is: If Jeannette were still in L.A., would she had ever seen this ad for mandals? My vote is no. What do you think?

Author's note: This post was reviewed and approved by Jeannette Fino, who is now the proud owner of four new pairs of shoes from QVC.

Originally written for and published on Smart Data Collective as part of the Big Data MOPS Series

Editor's note:

John Balla will not hear Tom's canvas wedge sandals.I can totally relate to the cool/creepy reaction here. Either Jeannette and I are living alternate lives because Facebook is serving me ads for Tom's canvas wedge sandals that Jeannette would probably like (screen-shot to the right).

The more likely scenario is that the prompt from that ad came from my teenage daughter's not-so-subtle hint about what she'd like Santa to bring her. You see, two weeks ago, she searched for the shoes on my home computer and then left the browser up on the screen - with a handbag in another tab and then a couple of blouses in two other tabs.

So how do I get Facebook to understand that my daughter gave the same not-so-subtle hint to her grandmother, who has already bought the shoes? Our family has moved on from the canvas wedges.

I think that's the next evolution in personalization - where it becomes interactive somehow. Because I already find these ads annoying and I'm certain I'm not the only one.

tags: advertising, big data, facebook, personalization, privacy, social media
12月 052014

The Big Data MOPS Series with Tamara Dull

We have a love/hate relationship with ads. Whether they’re on television, in our favorite publications, or online, we love them if they’re relevant and interesting, or get annoyed when they get in the way of [insert whatever we’re doing]. I have to admit: I rarely watch a television show in real-time anymore. I’ll record a show, wait 20+ minutes, and “chase the show” with the recording—ad-free.

So what does this have to do with big data privacy, the “soapbox” I’ve been standing on for weeks? (Ha!) Well, some would have you believe that the big data privacy debate is all about online advertising—i.e., you get interesting, relevant ads in exchange for your personal information. If this what you believe, you’re sort of missing the point. Read on and see if you agree.

About online advertising. Do you remember September 3rd when Facebook had an 18-minute outage? Given that Facebook generates about $22,000 per minute, this means they lost almost $400K during that outage. This may sound like a drop in the bucket for them, but if you add in all the lost revenue from all the businesses who generate ad revenue on Facebook’s platform, a lot more than $400K was lost.

Behavioral online advertising example

Advertising is big money, and behavioral online advertising is even bigger money – and companies like Facebook, Google, and Yahoo! get that. They know what we’re clicking, posting, liking, and commenting on, and they’re using this information to better target us for advertisers. And contrary to popular belief, when it comes to advertising and privacy, advertisers really don’t care about what we do or where we go. They only care about one thing: getting us to buy whatever they’re selling.

Why this matters. You may be thinking, “So what? What’s the harm?” I mean, who doesn’t appreciate a targeted ad when you’re surfing for a certain item online or a coupon delivered to your smartphone when you’re near one of your favorite stores? It seems like a harmless trade-off: a little bit of your personal information in exchange for some helpful, free service that could help save you some money.

But here’s the catch: the information we freely share is not just used by these advertisers selling stuff to us. It’s being used, bought, and sold by a lot of other data “players”—some good, some bad, some we’ve given explicit permission to, some we haven’t—and none of which we have any control over.

The big data privacy debate is not just about online advertising—or even the collection of data. It’s about who’s using our data, why they’re using it, and how we can protect ourselves from privacy invasions when we don’t even know who’s watching us. It’s about you, me, them, and us.

The bottom line. Vigilance, not apathy, is the right response to the opportunities and challenges this big data era is ushering in. Be mindful of what you click and share. If you don’t click it or share it, “they” can’t use it or abuse it.

Originally written for and published on Smart Data Collective as part of the Big Data MOPS Series

Editor's note:

We all get it now - big data is both a challenge and an opportunity for marketers. And the opportunity is realized by applying analytics to garner the insights that lead to better marketing. And big data is really BIG - so the data now available to marketers is like a digital "horn of plenty," a virtual cornucopia just overflowing with potential information.

And the point for marketers in Tamara's post here is analogous to the message of this biblical parable once used by John F. Kennedy:

To those whom much is given, much is expected.

As the steward of the customer relationship, marketing can't just harvest and use the truckloads of customers' personal data irresponsibly - it's reasonable that we'd be expected to safeguard it and respect the rights of the owners of that data.

There's more information on consumer's expectations regarding digital behavior and personalization that you can read in this report based on a global study SAS conducted this year:

Finding the Right Balance Between Personalization and Privacy

Check it out and let us know what you think!

tags: advertising, big data, Big Data MOPS Series, privacy, search
12月 042014

For marketing analysts, one of the beautiful things about digital advertising is it’s “trackability.” Every interaction on the web generates a piece of data, so in theory, you know where and when your ad was seen, who clicked on it, and any subsequent conversion.

When paying for clicks, how many of them are from bots?But what if the online advertisements you were paying for weren’t getting to your target audience? Or what if robots were running rogue on the Internet and hijacking your impressions? Robots?? Bots – software that performs automated tasks - and Botnets – basically robot code that coordinates with other bots across a network – are bad news for consumers and advertisers.

The bad bots generate false impressions and clicks. Really bad bots can create phony user profiles and enter information into web form fields (anyone who has a blog and doesn’t turn on their spam filter will know what we’re talking about). They infect our computers. They redirect traffic to phony sites allowing the bad guys to falsely collect advertising payments through middlemen.

The “Chameleon” botnet discovered by in 2013 had infected 120,000 host machines and was emulating human visitors on certain websites, resulting in the display of billions of ad impressions. On the 200+ websites targeted by the bot, 65% of web traffic was accounted for by the bot, and resulted in an estimated $6.2 million in additional (false) advertising costs per month. Worldwide, the Interactive Advertising Bureau (IAB) estimates that 36 percent of all web traffic is generated by bots.

In addition to the problems that this causes in trying to measure the impact of your advertising message, the cost of the advertisement is based on impressions and clicks. It's estimated that corporations lose between $5-10 billion annually due to bot fraud. With an estimated more than one-third of all online advertising coopted by bots, marketers have no way to accurately manage or measure the impact and efficacy of their messaging and campaigns.

An industry consortium led by a number of marketing trade organizations has embarked on a “Making Measurement Make Sense” (3MS) project. Currently, marketers pay for online advertising space based on served impressions – which represents the number of times the ad is served to a “consumer” (and bot). The industry is trying to move towards a metric based on viewable impressions, a more accurate way of tracking whether an ad was seen by an actual person.

The challenge for marketers is that digital marketing is too critical a channel to ignore or defer until the problem is fixed. But while marketers continue to invest money in this space, they are more aggressively trying to monitor how that money is spent. Bob Liodice, CEO of the Association of National advertisers said, “When you bundle bots, click fraud, viewability and lack of transparency, the total digital-media value equation is being questioned and totally challenged.

Many organizations are making investments in digital fraud detection technologies, combining session-based analysis with big data weblogs to track down, identify and block the bots. In the meantime, marketers can take action as well: Reduce digital fraud exposure risk by identifying traditional web metrics that can easily be faked by bots (impressions, click-through-rates, completion and last-touch attribution models) and using more concrete ROI metrics for campaigns.

This blog was automatically generated by a Bot - not!

tags: adaptive customer experience, advertising, Digital, fraud
7月 142010
Thanks for your feedback on this topic. As promised, I am circling back on the Advertising: To Gate or Not to Gate post I wrote in late April. As you'll recall, I initiated a little experiment to offer one of our assets via an online ad without registration. For a period of almost two months, we ran ad units with 1 to 1 Media, American Marketing Association, BusinessWeek Online, destinationCRM and The Wall Street Journal Online.

The results are in!

And they're not what I expected (which prompts me to want to tinker some more). For the time being, here is what we found when we compared the two trial periods:

  • The Click-Through Rate (CTR) went up from 0.09% to 0.50%
  • The Conversion Rate (CVR) went down from 3.32% to 2.65%

To put those numbers into plain English:

  • When we removed registration, the proportion of the viewers that clicked through went up five-fold from 0.09% to 0.5%.
  • At the same time, the subset of viewers that clicked through and then also downloaded the whitepaper shrunk by 21% from 3.32% to 2.65%.

The CTR results were unexpected because we did not change the wording of the ad to say “no registration required,” so unless I don’t fully grasp this concept, there is no outward indication that would prompt more clicks. The CVR results are also unexpected because this should be like the bowl of Halloween candy left on the porch of the folks not at home. Remove the doorbell and the first group of trick-or-treaters hit the jackpot, but in the case of our ad it didn't play out as expected.

The “after” numbers (no registrations) were confirmed in the following weeks as the proportions remained the same. Preliminary conclusions based on these results are that if our objective with online ads is to drive awareness, then it’s more effective to offer assets ungated. Conversely, if we were looking to generate leads, then it would make more sense to continue gating our assets on the ads we place.

If you will recall, the asset we’re promoting in these advertisements is a Webcast summary paper titled, Tips from the Trade - Competing on Web Analytics from a Webcast called by the same name (Webcast Link). The Webcast featured an discussion with author Eric Peterson from Web Analytics Demystified and SAS Customer Office Depot, moderated by SAS' own Michele Eggers.

I am going to see if we can try another test, but this time changing the wording in the ads and the landing pages to see if that drives a different result and let you know what happens. Until then, let me know if you expected those same results. Have you had similar experiences? Share your thoughts when you have a chance. Thanks!
4月 212010
Just the other day, we had our regular review meeting with our advertising account team, where we look at our inventory of ads, check their performance and discuss any needed refinements and next steps. During that review, we considered our plans to promote our new Social Media Analytics solution, which got me thinking about one of the mantras of Dave Thomas, our Social Media Manager: a key ingredient to building a community and establishing relationships is to share good content. Hmmm…

That concept once again opened a thought process we’ve had for some time regarding the question of our content and its value. Up until that meeting, I was of the mind that our assets are valuable and it was right and good to expect something in exchange for getting the asset. After all, these whitepapers, Webcasts and research reports are the result of some work we’ve done with a domain expert (either in-house or outside of SAS), and that expert says smart things and we all listen. So these assets have value.

In order to “protect” the perceived value of the ad, we’ve always required registration, or in the world of advertising, we “gate” the asset. We all know the drill with registrations. And we all know exactly what happens to that registration data and why it’s required.

And while my account team assures us that getting 0.93% of the audience clicking on the ad is “very good” and then 4.95% of those people converting are “phenomenal” results, it still makes me wonder about the much larger percentages of people that do NOT click on the ad, and do NOT convert by registering. I know I am not the first one to think these thoughts, and ultimately it comes down to a simple question: To gate or not to gate - that is the question. (Okay – you’re allowed one mental eyeroll for that. Sorry, Shakespeare.)

So of the people we managed to get to click on the ad, there are 95.05% of them that do NOT convert. Since our goal with advertising is to build awareness, and it turns out we do have the means to measure conversions without requiring the target to register for the asset, and we’re not really getting a lot of strong leads out of the process, I am left wondering: why do we gate?

Justin and I decided to see what would happen if we ungated one of the assets we’re promoting, so we chose a summary paper from a Webcast called, “Tips from the Trade – Competing on Web Analytics” that featured author Eric Peterson from Web Analytics Demystified and SAS Customer Office Depot. It’s a great document that includes 9 tips to reaping the full potential of your Web channels, and since that link does not go to our campaign landing page, go ahead and click on it and it won’t mess up our little experiment.

I’ll report back on what happens. In the meantime, what do you think about registering for an asset? Good, bad or indifferent? Share your thoughts.
7月 102009
I'm doing my weekly round-up of text mining/unstructured data/information management news. Having lived in numerous continents around the world, I like to make sure my information hunting is equally intercontinental. Different cultures have different slants on topics.

This morning's search led me to an article posted by the New Zealand Herald entitled "How Can YouTube Survive?" A section of the article mentioned insider's technology blog, TechCrunch, and a guest blog post entitled "Why Advertising Is Failing On The Internet" written by Eric Clemons, Professor of Operations and Information Management at the University of Pennsylvania. A very interesting read, and also a very provocative one (validated by many comments to the blog post).

According to this excerpt from the NZ Herald article, Clemons "argued that the way that we're using the Internet has shattered the whole concept of advertising. We need no encouragement to share our opinions online regarding products and services and offer them star ratings; as a result, we're much more likely to look for personal recommendations from other customers than wait for a gaudy advert to beckon us wildly in the direction of a company website or online store. He claims we don't trust online advertising, we don't need online advertising, but above all we don't want online advertising."

Based on my personal Internet shopping habits, I agree! I'd much rather see personal testimony about a product in addition to (or instead of) marketing collateral. This personal testimony has becoming a new form of marketing. It would serve marketing professionals well to pay attention.

Understanding individuals' commentaries about products helps marketers better understand consumer reaction to the four P's of the marketing mix: product, price, placement and promotion.

This evolution of marketing influencers is exactly what makes text mining a pivotal technology for this generation. It provides the ability to gauge those huge volumes of Web-based consumer reactions in an automated, consistent manner. And then you can actually do something about it -- or with it!