Lairig Marketing

The Business Revolution Will Not Be Digitized

Reading marketing blogs (other than Lairig Marketing, of course) would lead a person to think every communications process and means of distribution had been fully digitized. The recent “Minding Your Digital Business” report from McKinsey will bring such people back to reality.

One of the many questions for McKinsey’s study group of nearly 1500 global “C-level” execs was how big a priority “Big Data” is (a faux phenomenon we covered in depth here). Only 25% put it in the top three (which sounds to us to be twice what you’d expect).

That means we’ll see another million “Big Data” articles over the next two years until the C-suite gets the memo.

Oddly, only 39% said they were using Big Data for “Budgeting, Forecasting & Planning.” More oddly, budgeting was the only one of nine survey options that showed a lower number for ideal usage. Translation: execs believe they are currently using TOO MUCH data for setting budgets!!!

Metaphorically, we presume, a finger in the wind counts as “digital.”

Half of the execs said they would be investing less than 2% of their company‘s total COST base on digital initiatives. (Perhaps the percentage spent would be higher if they used Big Data for budgeting, but we digress). A mere 25% will spend more than 3%.

Yet, unbelievably, a full 35% expect they will realize better than 10% improvement in operating income as a direct result of their digital programs. That’s an ROI of more than 300%, folks.

When McKinsey asked what the biggest hurdles to digital success are, for the millionth time in a row 50% of the surveyed execs said “lack of quality data” and “poor IT infrastructure and systems.” Still and forever, stuck in the proverbial digital first gear.

Back to the future.

Little Data Kicks Big Data’s Butt

A month ago we posted a thoughtful piece on the “Big Data” meme-of-the-month currently Pac-Manning its way across the marketing (and IT) landscape. Tons of bits and bytes, looking for a problem to solve, as we said then.

To point out how overengineered Big Data is, we also said this: “Most marketers can’t even tell you how many website visitors they had yesterday.”

Today we back that up with a true story.

Background: Lairig Marketing helps a client rethink and execute a customer e-newsletter. It is emailed to tens of thousands of customers, with a headline and two-sentence abstract describing each of three articles. For some reason, a digital person decides to put social media links (Facebook, Twitter, et al.) in the email alongside each article’s abstract.

Expectations are that customers will link through to read one or more of the full articles on the client’s website, at a rate higher than prior newsletter issues.

We track the email data after a few days, eager to check the newsletter’s performance. Counts of “clicks” show that three-hundred or so people have linked through to article #1, nearly four-hundred to article #2, and 150 to article #3.

Then this: nearly 2200 readers clicked on the “Tweet This” link for article #1, 2150 for #2, and 2250 for #3.

Dumbstruck that more than one reader would have retweeted a 50-word article abstract FROM AN EMAIL, we asked the email vendor to recheck the data (to protect the vendor, we’ll only say it is a four-letter name beginning with the letter “Z”).

The data come back with the “tweet” numbers essentially divided by 2. Some sort of “mistake” we are told. And, by the way, if we want an updated set of numbers it will cost us additional out-of-pocket.

Net net: we are being held hostage. By sh&t data. We know the “tweet” numbers should be zero. So what faith should we have in the rest of the data?

A simple, but illustrative example of what will happen in about a million businesses today across the U.S., and it promises to cut Big Data at its knees. Imagine if we responded in “real time” to these 3000 phantom clicks. It’s why Big Data will have us firing nuclear missiles on Canada soon.

Until Little Data is clean, Big Data will be a flop.

Whoever came up with the name for those hard square disks we use to insert into our desktops was a genius.

What Does The USA Not Get About Microsoft ?

If you read yesterday’s post – and shame on you if you did not – you would have been linked through to an older story in which we highlighted how Microsoft was awarded the #1 ranking in the Australia “Authentic Brand Index” for 2008. (The world – or Australians at least – are still waiting for the results to be released from the 2010 index research.)

What’s up down under, oi?

There must be something funny in the water in Canada too. In late January, Adweek and researcher Ipsos Reid released their first ever (and, based on the results, maybe last ever) “Brand Influence Index” covering Canadian companies. Guess which brand is the most influential up dair, eh?

• Tim Hortons? No.
• Loblaw? Not even top ten.
• The Ottawa Senators? No. And please lose game 7 tomorrow night, you bums!

Once again, Microsoft. Eh.

Eh?

Better than Apple? Better than Google? Why don’t we Americans hold Microsoft in anything near the same regard?

The Influence Index was based on consumers’ ratings of brands in six areas, including “Relevant,” “Leading Edge,” and “Engagement.” Again we ask, how could Microsoft rank higher than Apple? Or Facebook, for that matter?

This really ought to signal the death knell for brand rankings. All of these attempts – Interbrand, BrandZ, Ipsos Reid, et al. – are just variations on a mash-up of objective and subjective “measures” that call for the loudest “So What?!!?” possible in response.

With these types of measures, a brand can only be compared to itself – a la “is our brand getting stronger and more influential over time”?

In other words, stop sweating over those brand rankings.

Google Does A Double Split

While the "Do No Evil" guys shocked Wall Street with its faux (and evil) stock split, announced during last week’s quarterly earnings review for Google, there was another “split” discussed, and it seemed to fall through the cracks.

Over the two days following the call, GOOG fell $35 (nearly 5%), made worse by $10 of pre-announcement run-up. Google didn’t meet expectations in a key metric – cost-per-click for the paid-search business that still constitutes the bulk of Google’s total revenues.

Cost-per-click “growth” for Q1-2012 was negative 12% compared to a year ago, and down 6% quarter-over-quarter. This metric caught everyone’s eye in Q4, when Google saw the first year-over-year decline in CPC in more than two years.

CFO Patrick Pichette had this to say, in an attempt to calm listeners on the earnings call:

“…dynamics around CPCs and paid clicks are just simply very complex…”

SIMPLY complex. [We love reading earnings transcripts for these verbal tics…]

Pichette then spun the complexity wheel by stating the CPC decline was driven by five factors. The one marketers should pay attention to = “…the shift in search activity from desktop computer to mobile computer.” This is the other “split” that everyone else might miss.

This, of course, is not good news looking forward, unless the many, many hands on the mobile advertising steering wheel get it together. One major driver in raising CPC is demand (i.e., more marketers bidding on a keyword, ratcheting up its price), and as we have said at Lairig Marketing about a billion times, “The Year of Mobile Advertising” is about six years late.

One wonders when someone will come up with the idea to track the CPC metric for iPads and other tablets SEPARATE from smartphones. The delta there must be significant, and getting larger over time.

The mobile CPC dynamic will certainly impact Facebook, but will be a discussion that won’t take place before the IPO, we wager. But you only have to look at Pandora’s stock price to see what low mobile CPCs mean from a business standpoint. After debuting at $16 last June, Pandora tread water around $12 until this March, where it has trended straight down to $8-and-change.

Mobile CPC is indeed a sensitive topic. When a Barclays analyst took another attempt at interrogating Google’s cost-per-click performance on last week’s earnings call, CEO Larry Page had this to say:

“I'm just going to close the call here…”

And then he split.

Big Data – No Big Deal

The concept of “Big Data,” known to IT folks for a few years now, has found its way to marketing “meme-ville.” It will likely finish 2012 as one of the “top five marketing issues.”

McKinsey made hay with some appropriately massive Big Data white papers in 2011, emphasizing the ways marketers could harness it. First, McKinsey’s definition:

“Big data refers to datasets whose size is beyond the ability of typical database software tools to capture, store, manage and analyze.”

The overly long trail runs cold, however, due to McKinsey’s inability to get into the technology weeds. Instead, lots of mumbo jumbo like this:

“McDonald’s…has equipped some stores with devices that gather operational data as they track customer interactions, traffic in stores, and ordering patterns. Researchers can model the impact of variations in menus, restaurant designs, and training, among other things, on productivity and sales.”

What “researchers” is McKinsey referring to? McDonald’s has two restaurant designs – what variations are feasible to test? Who has ever tied cause and effect between “training” and “sales”? What “other things”?

The IT guys are no better. Here is IBM, defining Big Data “velocity”:

“…big data must be used as it is streaming in to the enterprise in order to maximize its value to the business.”

LMAO. Most marketers can’t even tell you how many website visitors they had yesterday.

The requisite surveys are now underway, to see how prepared marketers are for this brave new world. According to a study done in February by Columbia Business School and the New York AMA (Marketing, not Medical), the biggest challenge to success with Big Data is “lack of data sharing across the organization.”

Perfecto, for the guys like IBM. “If we can just fix the technology…”

Database marketing, a practice unknown to most marketers, is nearly 25 years old. It started with a problem to solve – how to make marketing slightly more efficient and vastly more effective? A problem looking for a data solution. A workhouse still in existence.

Big Data, however, reverses the equation. We have embarked on a years-long journey, throwing good money after bad.

Where data, and all its related high-powered technology, can look for a problem to solve.

Flurry’s Flurry of Bullsh&t Data

With all the outcry over SOPA and PIPA, we continue to be amazed that no one (other than Lairig Marketing) – NO ONE – has bemoaned the privacy risks associated with online analytics vendors. Companies such as Flurry, who explains itself thusly:

“…the world's leading mobile application analytics and data-powered advertising platform, with more ground breaking [sic] services in development.”

No idea what that means, but we eagerly await the promised earthquake (sorry for the reference, El Cerrito).

Here is an example of what Flurry has access to:

“…[we take] a sample of 60,000 daily active users on iOS, from among a total group of 6 million for whom we have demographic data…”

Flurry knows who you are and follows you all around every single place you go on your smartphone, all day long. And there are dozens more similar companies. You either don’t know or you don’t care. Potentially a much bigger story than Google and Safari, but we digress.

Flurry has been able to parlay all this snooping into two large helpings of marketing analytics catnip. The trade press and blogarrhea live for headlines like this:

1. “Flurry finds mobile apps usage dominates Web.”
2. “Flurry finds time spent in mobile far outpaces ad spending.”

Let’s take the first one, um, first. There was something else Flurry found out in that study that no one mentions, ever: half of the 90 minutes a day an average that a smartphone user spends on apps is – drumroll – PLAYING GAMES.

All these people you see coming straight at you, heads down, on the sidewalk? Playing Pac-Man. Or whatever. (Still wondering why there is high unemployment?)

The next 30% of “apps time” is spent on social networking (read: Facebook – still wondering why there is high unemployment?).

And so you have one reason from Flurry’s first “finding” as to why its second finding is nonsense – ad spend is low on mobile because the apps people are using are not suited to it.

But that’s just a sliver. In fact, Lairig Marketing wrote about this “underspending” topic – BACK IN MARCH 2008 – when data pundits of that period were wailing about how online ad spend allocation wasn’t aligned with people’s time on the Web.

Here is a summary of what we said then, and still say now. Four years later, the % allocated to online spend is still lower than the % of users’ time on the Web – and therefore mobile will always be “under” – because:

• Cost of ad production is infinitely lower than TV or print
• Cost of online media is pennies on the TV dollar
• TV still has better mass reach
• Average people are not your customers

Please, please help us pass the word the next time you see this “underinvestment in mobile advertising” claim.

In the meantime, here is an example of what Flurry knows that ought to make privacy advocates sh&t their pants:

"...our analysis shows that females and males, between the ages of 25 and 34, who have higher levels of disposable income and a bachelor's degree or higher, more strongly interact with mobile ads.”

Marketing Analytics: The Stuff In Between

Judging by the nearly infinite number of articles about “attribution” recently, we’d say marketing analytics “thought leaders” are on a crusade. Their intent is to move marketers away from the easy focus on first-order metrics like banner clicks and email open rates, and focus them at the other end of the spectrum – on the “sales” that marketing can (hopefully) take credit for.

This is a bit misguided. And, frankly, becoming very boring and nearly unreadable. As an example, here is an excerpt from a recent MediaPost “Metrics Insider” column:

“On a basic level, attribution produces reports with data containing insights at a single dimension, such as channel “A” is contributing X% to your success, compared to channel “B” at Y% and channel “C” at Z%.”

That is at a “basic level,” mind you.

Missing in this discussion is what Lairig Marketing calls, technically, “the stuff in between.”

Here is an example, using a financial advisory firm for illustration.

Let’s assume the “sales” end of the advisor’s marketing cycle is a face-to-face meeting where a customer signs up for a $250 financial plan. Prior to that is an initial meeting with the advisor, where the only goal is to press for the second meeting.

Prior to that is a series of touches with calls to action that push the prospect forward. In reverse order from meeting #1 might be these marketing tactics: a download of a sample financial plan, which was driven by interaction with an asset allocation calculator on the firm’s website, which was driven by an email to the prospect, which was driven by a webinar in which the prospect’s email address was registered.

This is “the stuff in between” – planned marketing touches that can be measured precisely, to determine where improvements are needed to increase individual response rates and send more prospects to the next step…ultimately increasing the number of people who show up at the second, final meeting.

It can also inspire the addition of MORE stuff in between: “What if we sent a letter to the prospect confirming the appointment for the second meeting, throwing in a $15 Starbucks card to minimize cancellations?”

Instead of all this hard work, the “analytics attributors” believe they can automate data collection and analysis, and as a bonus, optimize the digital touch points (only). Ergo – they can prove that last month’s online banner campaign with a 0.09% click-through generated $24,550 in sales.

Oddly, that attribution effort results in more, not less, focus on clicks.

And all that “stuff in between”? Attribution pretty much leaves it as a big, black, unattributable box.

The Not So Super Super Bowl Stock Portfolio

Back in 2008, we debunked research that concluded Super Bowl advertising was an assured booster to stock prices. Coincidentally or not, the guy who headed the research, Professor Chuck Tomkovick, has seemingly abandoned that focus and switched gears to test the effect of “sexy” Super Bowl ads.

So, we felt this might be a good time to retest his bold statements in 2008 that “[The Super Bowl] is a tradable event” and “Wall Street rewards firms that run Super Bowl ads.”

The process to do this analysis is excruciating. These are also the steps an investor would take to actually set up this portfolio. It would be easier to sit for a bar exam. Blindfolded.

• Determine which spots ran nationally
• Find out the parent company
• Determine if parent is a public company
• Find out if international parents trade U.S. ADRs
• Obtain the proper stock symbols
• Adjust for company earnings announcements
• Track the S&P 500 index as the baseline

We ended up with 20 companies. It would have been nearly impossible to find the date each announced its intention to advertise in the big game (which could immediately impact share price), so we used the closing price on Friday February 3 as the starting point.

Next, we took the close on Monday after the game, to determine what if any immediate lift the ads had on stock price. Then we checked the close on Thursday February 9, to measure residual impacts – especially important in 2012, given the social media fanfare. (We used Thursday’s close since the entire market tanked on Friday).

After one day? An even-dollar-weighted Super Bowl portfolio increased 0.6%, against a flat S&P. Fourteen of the twenty stocks rose in price, while six fell.

After four days? The Super Bowl portfolio increased 1.5%. Just four of the stocks were still lower at this point. The S&P baseline was up 0.5% for the period, so Tomkovick was right. Almost the same gain his team calculated in 2008 (except they used a two-week period).

[Quick note about earnings announcements. Three companies released results during our measurement period, so we excluded them from the four-day calculation. This did not change the result significantly due to offsetting impacts – one of the companies had a very bad quarter.]

But hold on. Let’s introduce some Lairig Marketing reality. Unless you have your own seat on the New York Stock Exchange, you must pay a broker to get you in, then out. Using an average $10 commission per trade, there is an additional $400 bogey before you make money.

Let’s say you had $20,000 to play with. You bought $1000 of each of our 20 companies. Factor in those commissions. After day 1, you are down $275. After day 4, you are still lagging by $115.

It could have been worse. One of the portfolio stocks – Skechers – caught an upgrade Monday morning, February 6. This lifted Skechers stock so high that it ended up being 50% of the portfolio’s total gain after one day, 30% after four days. Without this stroke of luck, your day-1 loss expands to minus $330, and your $115 day-4 loss grows to minus $150.

As in 2008, we conclude two things:

Trading a “Super Bowl Portfolio” isn’t super.

The stock market is, still, a casino.

Start Your Hmmmm File Folder For 2012 Now

Lairig Marketing is just one day from winding down for the year. That means, as of next Monday, you’re on your own as far as finding useful marketing and business information goes. So much garbage “research” and “analysis” and “advice” to sort through, most of it the same old junk, recycled for the hundredth time (“Five Surefire Ways To Be An Expert Innovator Like Steve Jobs” blah blah).

Here is a suggestion to help you churn through it all. Keep a separate folder somewhere in or on whatever it is you use to access “written” content on the Web – a laptop, an iThingie, whatever. Label the folder something that represents information that goes against the grain, opposed to the typical party line, interesting items that no one else seems to notice or know how to incorporate into his or her analysis. Use “Hmmmm” as a label if you can’t think of anything.

Save stuff into it like these tidbits we’ve collected over the past few months.

OK, Maybe All Kids Aren’t All Digital Savvy
“A study by Ypulse found that fewer than one in five students have ever used [QR codes] and nearly two thirds of students have no idea what they are.”

Don't Phone It In
According to PwC research fewer than 25% of survey repsondents “had an interest in watching premium video on smartphones. PwC said the lack of enthusiasm for mobile video is consistent with research it has done over the last 18 months.”

Like You? No, But I Love Your Discounts!
“The top reason for following or liking a brand, company or celebrity on social networking sites is to receive discounts and special offers, according to a recent survey of global online consumers conducted by Nielsen. North American consumers showed the strongest interest in using social media for deals (45%)…”

Build It Well And They Will Pay
"Condé Nast is the latest publisher to claim a boom in digital magazine sales from the launch of Apple’s Newsstand…the publisher says that new subscription sales, per week, across nine digital editions, was up 268%, with single copy sales up 142% compared to the previous eight weeks."

Influence On The Run?
“According to a Forrester study…the percentage of U.S. online adults who use geolocation apps has grown to 6% [ed.: WOW!!!]…early adopters are…twice as likely as the average U.S. adult online to share product information, but they are also more likely to share promotional coupons, discount codes, or the results of a game they’ve played.”

Save this one off as a reminder to look for future research, focused instead on the recipients of all this narcissistic pestering. Let’s see how much influence these influencers really have.

It’s Not The Tactic, It’s The Overall Value Proposition
“American blazed a path for the airline industry to switch to a la carte pricing for checked bags in 2008.” American is now (officially and financially) bankrupt. Southwest (no bag fees) is profitable.

Whether or not you ever go back into it, just the process of filling up your “Hmmm” file is going to make you a much better marketer.

Whether or not it will make you a more trusting person is hard to say.

SocialCode Fans On Facebook Fan Value

Had another post in mind this morning, but a link drew me away, like a moth to a flame. I cannot resist the temptation of an article that claims to reveal – finally, ONCE AND FOR ALL – the value of a Facebook fan.

I read these for the humor. I was not disappointed when I clicked over to an article titled “Why Brands Still Need Facebook Fans.” As if anyone has been saying they didn’t.

The subtitle was even better: “Fans Are 291% More Likely to Engage With Brand [sic] Than Non-Fans.” To that I say: f*cking duh.

The article was based on analysis by SocialCode, a Facebook-only social media agency. I would put several of the words in that prior sentence in quotation marks, but then I would be guilty of writing like Stuart Elliott.

SocialCode tracked ads on Facebook over several months and divided users who responded into two categories: (1) users who were already a Facebook fan of the brand that was in the ad, and (2) users who weren’t.

As you might expect, fans clicked more often than nonfans. However, because the response rate was so much worse for nonfans, their cost-per-acquisition (CPA) was much higher (roughly $15, versus a $5 CPA for existing fans).

Net of the study should have been: “It costs $10 more to get a nonfan to respond to an ad on Facebook than it does to get a fan.”

But no, the article says this: “SocialCode is the latest firm to try to calculate the value of a Facebook fan as part of a new study. Their verdict: about $10 per fan…"

Since SocialCode HASN’T PUBLISHED ITS OWN STUDY ON ITS OWN WEBSITE as reference, it is unclear if that verdict is theirs or the author of the article – Ad Age’s Cotton Delo.

In any case, the “verdict” is bullshit, but will run through Twitterville like fire. What a shame. A sham.

This is value measured by a lesser-of-two-evil-costs approach. Since fans cost $10 less a head to acquire, then their value is $10? Nonsense. Value must be measured in terms of return – revenue, sales, operating income. There is none of that in this study.

While we are at it, here are some other interesting points to consider in SocialCode’s analysis:

1) Why would I need to spend a penny to get Facebook fans to do anything? Isn’t that the whole point of having fans – to deepen the engagement and relationship right there on the Facebook brand page? What is the point of spending money ON ADS to acquire someone I already acquired? From this perspective, the “value” of a fan is negative $5. Money eating itself.

2) Of the seven types of calls-to-action that SocialCode tracked, the one that received by far the lowest response (a paltry 2%) was “program sign-up.” Isn’t it interesting that the activity requiring the most commitment and providing the deepest engagement opportunity had the worst response?

As interesting as the conclusion that no one really gives a sh*t about meaningful analysis anymore.