big data

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There is no strategy without tactics. Guys like me who write about brand strategy may seem like we’re above tactics, not wanting to get our hands dirty. (Twenty years ago, Peter Kim a McCann-Erickson mentor told me “Once I’ve sold the brand idea, I want to be done.” Everything after that gets messy, he explained. Approving ads, media, talent and all other things subjective.

The thing about planners, especially older planners, is we like to understand the big picture first. We like to go big. Once we understand how to solve the category, the deepest pent up consumer need, then we can focus on the specifics. Problem is, marketers aren’t looking to solve the world’s ills, they’re looking to sell shit. Flat out, right away, cha-ching the cash register, sell shit. Today in this fast twitch media world, marketing directors want their chunk of the returns. Big data? Hell no. Little data about my product. Yes. Data that says “more sales.” Period.

So we planners need to get the pipes out of our mouths and start talking tactics with clients. (Maybe keep the big picture stuff to ourselves a little more.) All my rants about claim and proof? Here’s one: Good branding works. Sales are proof.


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I once ran a promotion for ZDNet where we asked readers to write short essays as to why they were techies. The prize was a swim with porpoises in the Florida keys. We received over 35,000 responses. “Oh boy, now what are we gonna do?”  That’s a lot of reading. How would we scale? ZDNet had to hire temps to be judges. Unexpected expense there. I was talking to someone recently about a similar project and their approach was to build a reading/grading algorithm. At least to winnow the thousands to hundreds.

I guess you teach the algo some rules (like what?) and let it do its thing. It’s sad actually. When we use social media monitoring to gauge sentiment, that’s also algo-driven. And frankly, that’s not social.

I likes me some big data, no doubt. But when I drill into the big data I’m looking for humanity. The open ended question section of quantitative is a favorite. It’s where subjects, after checking boxes, get so fed up they want to blow out the important insights. It’s where they expect you to listen.

Marketing at scale has to have its eye on the sea of humanity, not the statistics alone. Right Mr. Spock? Peace.


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“Because we’re selling millions of set top boxes already, we hear what’s working and we hear what’s not working,”  said Peter Larsen, Amazon VP yesterday during his presentation of the Fire TV set top box.

No one has to tell you Jeff Bezos is smart and that Amazon is juggernaut to end all juggernauts, but this quote points to a market research revenue stream that will be a new business for Amazon. One smart big-data nerd with some UI chops is going to create an algo and process to tap, parse and quantify sales, comments, and loyalty behavior that few, if any, companies can match. And it will happen at Amazon.

Have you ever tried to purchase data from IRI, Mintel or Euromonitor?  It like ten grand.  Since web companies like to give it away, why not do so with market research? There are crazy amounts of data available to Amazon and SMBs are data-starved. I was kidding about giving it away, but only a little.  With a low price point for qual and quant, Amazon can build $100M business in 12 months. And it will grow and grow.

Remember when Sabre (American Airline’s ticketing system) became more profitable than their fannies in seats business? Of course you don’t.

This will take some work, however. Have you ever sold consumer products on Amazon’s and been inside its data portal?  Oy. OY.  It’s like Excel clones from another planet. Think one man with one pick looking at the side of an ore mountain. Even so, the data opportunity is impressive. Especially aggregated category data.

Data waiting to be mined has got to be Amazon’s next business. Fergus O’Daly, a smart mentor of mine, once said about marketing “nothing happens until somebody buys something.” There’s a whole lot of that going on at Amazon. Peace.

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data nerd

When hired as director of marketing at a company selling interactive whiteboards and professional development to the K12 education sector, I was very excited to build a department for the new digital economy. We already had digital peeps: a coder, a manager, an applications developer, all of whom were smart and proficient.  Also, they were excited to learn how to use the web for marketing good.  

One of the things I wanted to introduce to the department was a data nerd. It was in my plans but not a top priority — not until I got the brand plan right. And not until I had begun the process of enculturating the company (and especially the marketing and creative dept.) with the strategy.  The company, BTW, had over 100,000 records of past customers, with which it was doing nothing. The records were in various forms: paper, Excel, SharePoint, and a few other databases. This was an asset I’d seen at very few companies of this size. The nerd, was to be the cherry on the sundae.  Didn’t happen, my failure, and the company suffered. 

My first data nerd was a grandfatherly scholar at a huge health system. He was the “insight” that drove the brand strategy. He once told me in the catchment area surrounding one of the system’s more up-market hospitals, 50% of the woman gave birth via C-section. Come se convenience?  There was little this dude didn’t or couldn’t know. And he is still killing it 15 years later.

All big dog marketers get the data nerd concept.  When SMBs get it and invest in it, there will be an amazing whoosh in marketing effectiveness. Now, wash your hands an make me another 2 for 1 Tweet.



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Okay, there’s not an app for Christmas but there will be one for Christmas shopping.  You know how hard-to-shop-for people “Oh, I have everything I need”? It’s often true.  So how do you find a nice gift that they really want? That they like and need?  Big data.

I was watching Robert Scoble interview some big data dude yesterday on the web and the interviewee happened to mention that soon there will be 100 times more data available about consumers than ever before.  Once available, you will know I get Good and Plenty in my stocking, a rock and roll tee shirt from my kids, and shirts from my mom (16.5 neck).

It is enjoyable to find the perfect gift for the right person, but it is hard. I smell an app. The app won’t average a person’s demographics it will actually know consumption behaviors. Wear out and maybe even refill speeds.  “Dear Mr. President, please don’t collect private information on the populace – unless it’s to buy better gifts.”

Peace on earth!

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There were lots of clues leading up to the recent cultural/political explosion in Egypt. Guard dog sales were up and tourism jobs were tanking. Peru, a nation on an economic high, shopping malls filled with middle and upper class citizens, at first glance seems to be hitting on all cylinders. But monthly exports of copper, other metals, and minerals were down the first 6 months of this year; China is buying less.  Someone adding up mall sales may think all is good — but they’re measuring the wrong things.

In brand planning, knowing what to measure is a key planning tool. Paul Matheson, a planner with some big old chops taught me early on that we need to look at contemporary culture so as to have richer context for our strategies.  It’s not enough to use the typical brick and mortar marketing data, e.g., sales, share, demographics, etc.  And frankly, data sources are growing like crazy, thanks to big data computing and all the neat information trails provided by digital agencies.  That said, we must understand the beyond the data and see the culture of buying. And that includes the larger macro surround. Cue data, a la guard dog sales and the culture change it implies. 

The planner’s brain can do its own multivariate statistical analysis, without the math and expense, if it knows where to look. 

Find the cues and win the day. Peace. 

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A great deal of market research is focused on understanding and mapping how consumers buy. With big data making almost every consumer transaction recordable and quantifiable we have more information than ever before about “when” and “how” buyers buy.  That’s quant. Beyond the data charts, there are qualitative ways to watch how buyers buy. Store observations, mall intercepts and focus groups. This helps get us to the “whys.” All good learning. 

I learned early on however, that understanding the buyer is not enough. I like to watch the sellers sell. More broadly, I like to watch them work. That’s why ad agencies tend to put creative people behind the counter at fast food restaurants when pitching Mickey Ds and the like. Sales people will tell you how they sell, but watching them is often a different story. It’s the theory vs. the practice. And it’s not just sales people that need to be watched. It is other employees. Don’t overlook anyone when studying a company. Insights are everywhere. Context is everywhere.

If you are hunting for insights, look beyond consumers to the sell side (not just what c-levels tell you).  It provides lots of complex flavor for your plan.  Peace.

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Over the last few days I’ve met with two really smart Joshes. Okay, one Josh and one Joshua. Both gentlemen live and work in digital and media realms and both were nice enough to hear about “Twitch Point Planning.”  A twitch is a media moment during which a user leaves one media or device for another in search of more information or richer clarification. Twitch Point Planning attempts to intercept them at these moments and put in their way some branded value, moving them user closer to a sale. Of course, it must be done elegantly and with a contributory vibe.

The two Joshes told me it’s time to get out of theory land and into practice land.  Advice I’ve been giving to marketers for years. There is talk and there are deeds and only the latter create true muscle memory for consumers.

Since these two gentlemen are digital natives and work in marketing worlds catalyzed by big data, they’re also looking for evidentiary data. “65% of TV watchers who twitch to a retail site on Foursquare buy from its brick and mortar store within 4 days” kind of stuff.

Okay, I preach it but have failed to practice it. Shame on me. Off to practice.  Off to data point. Thank your Josh. Thank you Joshua.


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In the Netflix earning report yesterday it was noted that 75% or all streamed hours of content were recommended by the algorithm.  What does that tell you?  It’s an example of the algorithm winning over social recommendation social recos being the “likes” and “ratings” and “reviews” which are the ballast of so many web communities.  

Many marketing studies rate purchase influence and far and away the winning source of influence is always  “friends.”  Advertising is usually way down in the pecking order.  But where is the algorithm in those studies? Not included.

Ad serving is pretty dumb most of the time.  I’m still getting ads served based on project work, not even closely related to what I care about in my personal life. Sluggish algorithm.  But the algorithm employed by Pandora and Netflix?  Now these use energetic algorithms. This is where big data targeting is going. This is where Twitch Point Planning is going. In the “understand, map and manipulate” triumvirate of the TPP process, smarter algos will feed the understanding component. (I am so excited about Twitch Point Planning I could pizzle myself. Even The New York Time paper-paper is using it by providing video links to twitch to a multimedia part of the story.)

Understand the algo — the many competing algos — they are the keys to the marketing future. Peace!    

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In a presentation I wrote while with JWT during its tenure on Microsoft I came upon an insight I called the “logged and tagged society.”  It was intended to be a business insight identifying how employees at larger companies are somewhat interchangeable – with knowledge workers being replaced by armies of freelance soldiers with log-ons and access to tagged assets, information and data. But that was then…a couple of years ago.  It’s still true but logged and tagged now is also extends to consumer life.

Facebook yesterday launched a new search tool called Search Graph which does more than count likes, it attempts to get one to personal proclivities faster.  I tried to read the story but got a little tangled and bored and twitched away. That said, it is Facebook’s way of trying to improve search results keeping people on “the book” and making more of da monies.   Using my logged and tagged lens, it’s their way of fighting through the tags and searchables.

As the searchable words and tags grow in this exponentially data driven world (Can I read any more big data stories before breakfast???), search will continue to become less accurate and in need of improvement.  And as communications agents continue to spread the pop marketing fallacy that consumers own brands, this environment will create greater demand for brand planners. Brand planning is about returning control to marketing…not algorithm tweaking.


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