Lets Not Run Towards the Creepy Line Before We Can Walk

Just Give Me a Signthe-man-with-two-brains

There is a very funny scene in an old Steve Martin movie The Man with Two Brains where our hero, Dr. Michael Hfuhruhurr, looks at a painting of his beloved, dead wife, Rebecca, and asks if she is happy with his feelings for the new love in his life, Dolores. An ethereal voice whispers noooooo, the painting begins to spin round, candlesticks burst into flames and an ungodly wind blows through the room. All the time the voice grows louder and then, when it all stops suddenly, a dishevelled Dr Hfuhruhurr says Just give me a sign … any sign … I’ll be looking out for it.

Predictably

I saw a recent presentation from, err let’s say one of the big three global technology corporations, which reminded me of this scene. The presenter talked us through a scenario where a young man is presented an offer to use some loyalty points. In the world of #bigdata, the presenter, went on, we will know that he has been dating for a little over eighteen months so the offer will be personalised towards romantic destinations.

Using recent purchase history, presumably an engagement ring, the intent of the trip is determined and the couples experience is further customised.  A taxi, rather than hire car, to their intimate dinner for two and at a restaurant that provides just the right setting for them rather than say, a young family or a solo business traveller. No piece of data or algorithm is left unturned to create the perfect weekend for our fictitious couple.

I am not sure I am ready to be second guessed about major life decisions by businesses that have yet to work out that googlemail.com and gmail.com is the same email suffix

Creepy Line

I know, the presenter conceded at one point, some of you might be concerned that we are crossing ‘the creepy line’ here. And the room relaxed a little and listened intently to a world where algorithms applied to increasingly personal data ensured that each need was carefully met before the couple even realised for themselves that they needed it.

The story concluded with a marriage proposal and an assertion that all of this is possible in a world of big data, machine learning and predictive analytics.

Second Guessing

Now, I welcome a world where cars are recalled before we experience a breakdown, where risk is assessed and mitigated and where fraudulent use of my credit card is spotted before any real damage is done to my own or my providers finances. All good.

However, when it comes predicting what we will want next, to second guessing us, I am not so sure. And here’s why.

based on their  personalised  marketing,this is what I think they actually know about me. They know my email address and that I buy mens clothes. And err, that’s it.

Personalise This

I am a man , no longer in the blush of youth. In spite of that, I maintain a distant interest in fashion. I care, actually very much, about the clothes I wear even if those around me might be surprised by that. I apply two universal rules. I don’t ever want to buy clothes that my Dad would wear and, even more importantly, that my Son would wear. I tend towards blues but don’t want it to be the only colour in my wardrobe and whilst the trend is towards slim fit trousers (pants for my US pals) I have to check the fit carefully because I have (let’s saystrong) calves. I very rarely wear knits, like jolly (but certainly not ‘humorous’) socks, prefer smart over casual, never go double-breasted and I almost always wear a collar particularly for dinner. As I say, older dude. I shop on-line, actually pretty frequently but I have to know the store well before I do because I have little time for the rigmarole that comes with returning parcels using  a service that seems largely geared to those that live in 1975.

And Here is What You Really Know

I buy from what I believe to be pretty innovative retailers but, based on their personalised marketing, this is what I think they actually know about me. They know my email address and that I buy mens clothes.

They don’t even have a firm grasp on the email thing to be candid. I am not sure I am ready to be second guessed about major life decisions by businesses that have yet to work out that googlemail.com and gmail.com is the same email suffix and that offering me an item at a discounted prices makes any sense if they don’t have it left in my size.

Listening

I occasionally send an email or respond to a survey to grumble about an unhelpful web site or to call out a particularly helpful assistant that didn’t assume I was looking for everything in beige. However, according to Gartner, whilst 95% of businesses collect feedback only around 35% use the insight that they have collected. A tiny 10% improve their business with this information and only half of that small group circle back to the customer and tell them that they did so.

Our customers  talk to each other on social platforms and they comment on their experience of our businesses in their own voice. Many also talk to us as directly. They leave reviews and some, though the rates are decreasing, respond to our surveys. More would answer our questions too, if they were asked thoughtfully and if we demonstrated that we did something with their feedback from time to time.

Surveillance and Second Guessing is Creepy. Listening is Human

Privacy is an important issue, I don’t mean to diminish it, but let’s forget where the creepy line is for now. Instead, why don’t we try something fundamentally human as businesses. Why don’t we try listening.

So my message to the CMO of those very large and resourceful businesses that currently have my tentative loyalty. Rather than looking for patterns, trends and algorithmic intent in data you have no place being you can read this blog, my tweets, my comments or even ask me what I like or what (to quote Spencer Trilby played by Charlton Heston in True Lies) blows my skirt up. And on that subject, I am not going to wade through 50 questions designed for your departmental silos. Let me tell you in my own words and in my own time.

Or you can continue to wait for a sign and risk me moving on to someone that listened.

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Is Cold Calling Dead? More Importantly Who Gets to Kill it?

Is Cold Calling Dead?

Cold calling is dead, at least as we know it, according to Forbes contributor Ken Krogue. Wait a minute, perhaps not. Matt Heinz, President of Heinz Marketing, blogger and author, holds the contrary view in his post If you think Cold Calling is Dead, You are Doing it Wrong. As it happens, for every article heralding the end of traditional cold calling there is another extolling the virtues of the very same thing, providing you just do it right. Most only seem to disagree in the headlines.

Who Decides if it is Alive or Well?

When I speak at sales conferences and workshops, I often ask the assembled group of professional sellers ‘Who really enjoys cold calling?’ Inevitably, I will see one or two defiant hands reaching high and I have made it a habit to seek them out during a break to find out more. They are invariably resilient, optimistic and interesting people. However, I am not sure I am asking the right crowd.  If I asked a room full of business buyers ‘how many of you enjoy receiving a cold call?’ then I suspect I would see either no hands or a similarly small number. In fact a study on buyer preferences commissioned by IBM revealed that cold calling is 97% ineffective. As buyers, we simply do not like the intrusion.

It is difficult to believe that businesses would continue with any activity that only works three times in a hundred let alone an activity that is not welcomed by more than 9 out of 10 of prospective customers.

Is it the Right Question?

Those three positive connections must seem pretty good to the caller after ninety or so curt and dismissive responses. I have heard it called ‘living for the yes’ a euphoric high as a result of affirmation after a truck load of human rejection. I have nothing but admiration for those that do it, do it well and manage to stay positive dial after dial. However, it seems to me that we are asking the wrong question of the wrong people.

The Connected Buyer

We are living in the age of the connected buyer. Sophisticated business buyers that use online resources and their professional social network to make their purchasing decisions. These, often senior decision makers, prefer to find their own information and validate with social proof through those they trust. Connected buyers are in control of their buying process and are simply not interested in being invited into a sales process at the wrong time through a cold call.

The Right Question

Whilst my audience of business buyers is hypothetical, all the evidence is that they want cold calling to stop. This is why they screen their calls and don’t return messages. It is also why receptionists, office managers and assorted colleagues tell sellers that the target of their call is ‘with someone right now’ when they are not. Business buyers have wanted cold calling to end for a very long time, Seth Godin introduced the term interruption marketing in the 90’s and it wasn’t a new problem then.

For sellers, cold calling may be dead. Or it may not. For business buyers and decision makers though, its demise, whenever it was or is, will not have been soon enough.

Big Data Indescribably Large

Lost for words

I have been the first to be overly critical of those that define big data solely by size and (absence of) structure. That being said, it is inescapable that data volumes have reached an inflection point. In an article for the Wall Street Journal, Andrew McAfee makes a pretty startling observation. Data has gone from being measured in terabytes to petabytes and exabytes. He explains that in 2012 Cisco announced that its equipment was recording a zettabyte of data. Not startling so far and, in any case, outside of the circle of data geeks, few will have heard of a zettabyte.  The more jarring fact is that the next metric for measuring data is the final one. After the zettabyte is a yottabyte (10 to the power of 24  as you asked ) and then that’s it. We have literally run out of words to describe how big, big data is.

Big v Different

Commentators such as Jeff Jonas and Kenneth Culkier make the point that big is not just big. Big can be different.  David Weinberger, one of the authors of the CluetrainManifesto, makes a similar point in his book Too Big to Know. He proposes that knowledge has been shaped, perhaps even limited by its medium. Only the most important, meticulously researched facts were  committed to paper until the invention of the printing press. Even then, the printed medium carried figurative and literal weight.

In describing Big Data in Decision Sourcing, we  contrast transactional data with ambient data. Transactional data was limited by traditional data processing originally in the form of the punch card and more latterly the relational database. Ambient data, however, exists all around us. It’s size meant that it went unobserved or at least uncaptured. This is what has changed. Affordable and available technology means that signals generated through the internet of things and human social interaction can be captured in digital form providing new (and different) sources of insight. The relational database limited us to recording invoice lines and account details whilst new forms of data management allow us to capture every human gesture, comment and click. Meanwhile  the machines are logging everything they do.

Whats’s next?

Metric prefixes were last updated in 1991 at the 19th General Conference on Weights and Measures and beyond yotta, we got nothin’. Big Data means disruptive, transformational change in a way that we don’t completely understand today. In fact we don’t even have a name for what comes next. Yet.

Living the vida nube

Ricky+Martin+r10A career in consultancy and services leadership has not really helped me develop a sense of rythm, a party spirit or noteworthy alcohol tolerance. It is fair to say that Ricky Martin’s crazy life passed me by. Mostly.

That being said, I am  living the vida nuba. There are less sequins certainly, but it has made me more efficient, more connected and more adaptable to the myriad ways in which a working day can pan out. Life in the cloud is really working for me.

The basic step of making  personal and professional docs available in the cloud had the immediate benefit of making everything accessible from my home and/or office. However, the consequential benefits  have been unexpectedly pleasing too;

Unchained 

I am with Kivi Leroux Miller on this. In her blog she describes, how for many of us, work has become a state of mind, not a place.  It’s true. I cannot express enough how much freedom cloud gives me during a working week. I can write or work on trains, in coffee bars and, as I do from time to time, in the 7th floor bar of the Tate Modern. The views are an inspiration.

Sure wifi isn’t everywhere but it is mostlywhere and there really haven’t been enough exceptions to care. I have forgotten thumb drives more often.

Zen Computing

Once I started using cloud applications I quickly realised that I actually did not need all the features in ‘other’ bloated desktop tools. Last year, I wrote a book, a full twelve chapters plus bibliography, fore and after words without ever dropping into an unwieldy desktop word processor except for a few frustrating minutes before sending it to the publisher. Hey the future is here, it is just unevenly distributed.

All that space on my hard (SSD) drive and my head is replaced with tools and apps that make other parts of my life more productive. Just finding space for Evernote in my world has been a blessing and occasional lifesaver.

Everyware

When I made the  move to Mac a few years ago, there was no need to scour my C drive for old mail, spreadsheets and documents. They were all good to go. I have forgotten what Hot Syncing was (really, what was that all about?) and instead I have become device independent. Whichever bit of kit (phone, phablet, tablet or laptop) fits the task in hand is the one that gets picked up and used.

Moore is More

Sure, things go wrong from time to time and a broadband outage can make me disproportionately edgy. I am, overwhelmingly though, enjoying a law of increasing returns and keep finding new things that delight me. I  no longer have those panicky moments where I don’t know if it is on ‘this’ computer. It is. All of them. If someone makes a convincing book recommendation at a conference, I don’t make a note of it – I buy it. If a battery runs out on one device, I move to another. You get the picture.

The list goes on. Whilst it doesn’t give me swivel hips or a desire to go dancing in the rain, it does give me a heady sense of freedom, flexibility and control.

Big Data Week: New and Different

Big Data Week

I was able to take part, albeit fleetingly, this week in Big Data Week a series of events run in 25 cities across the globe.  There were a series of evening meetups hackathons and panels throughout the week in London with the key event running out of Imperial College on Thursday. Edd Dumbill O’Reilly Strata chaired and speakers included the excellent Kenneth Cukier (co-author of Big Data) and Nick Halstead (founder UK start-up Datasift)

First off my congratulations go to Stuart Townsend and Andrew Gregson who  pulled together a program that was excellent,  free of hype and as grounded as the title ‘Putting Data to Work’ suggests. Superb.

Because of pressing commitments with the day job, I dipped in and out of what I thought would be the ‘best’ bits and was mostly right with only one session that really missed the mark for me.

Takeaways

My takeaways;

– Big Data projects are still largely about click stream, native internet businesses and one off mash-up projects (more often public and ngo than corporates)

– Big Data has its origins in the web (thank you Google) and this is where most of the corporate activity remains. ‘mainstream’ (whatever that means in the networked age) corporate use is a way off

– We are still largely defining Big Data in technical terms (a good 40% of the group in one session described themselves as ‘technical’ when polled

– It is still very early days. Innovation, interest and investment is still high and growing

New and Different Data

The highlight for me was Cukier who has come closest to providing a satisfactory definition of Big Data for me. As you may appreciate from previous posts, technical definitions based on volume are, strictly speaking, spot on but leave me a little cold. I attempt to get closer to something more vital (shameless plug alert) in Decision Sourcing (Roberts and Pakkiri, Gower 2013) by describing it as ambient. By describing it as such I am asserting that it is data that has always existed around us (temperature readings, product mentions, consumer comments, buyer behaviour) but it has only recently been captured and made available to us as data.

Let me explain. If I abandon my basket in Sainsbury because I couldn’t find the one thing I came in for and it can be seen by the store manager when the close but not understood. Not so for Amazon. The thermostat in my home is the very definition of ‘there or thereabouts’ but a Nest captures, stores and learns from accurate readings. When I share how great brunch is at Balthazar around the office, someone may make a mental note. When I do it on Facebook, it’s a piece of data to go with the other 1.5 billion that day.

The point is not that big data is big, though it is. It is that it wasn’t available to us before either because it wasn’t being captured (social mentions) or it’s volume and variety (web clicks, smart meter readings) made it impossible to store and analyse and therefore understand.

As Cukier put’s it. Sometimes more is not just more. Sometimes it is so much more that it is different. Big Data Week 2013 seemed to be a great success to me. I look forward to New and Different Data Week 2014.

Big Data: Let’s agree, no more V’s

3Vs

I don’t quite know when it happened but we have recently added another V to the three existing characteristics of big data. Perhaps more. Gartner analyst Doug Laney gave us the first batch. High volume, real-time, rapid change velocity and unstructured variety. This certainly set big data apart and at least partially explained why the old tech combination of columns, rows and sql were no longer big, strong or fast enough to deal with it. We needed hadoop, columnar, nosql, massively parallel and other innovations to deal with a full three V’s.

4Vs

More recently veracity has qualified for this somewhat exclusive club. Dealing with notions of sentiment, mentions and sociographics from tweets, facebook status updates and youtube comments is an imprecise practice very unlike traditional data processing where all transactions balance and net out to zero. According to IBM, one in four business leaders do not trust the data that they make decisions on and this new world is unlikely to make them feel any less queazy.

More V’s

A quick search will find other candidate V’s including visualisation. Indeed, one source suggests we are up to six V’s but it is time to stop counting. Whilst classifying and characterising big data in this way is understandable it is not completely helpful. In fact, according to Wherescape CEO, Michael Whitehead it perpetuates the stereotype of navel gazing IT types. This ever increasing collection of V’s is not strictly true either. Some Big Data is not high volume, some not real time and some might even have a little structure.

It kind of misses the point as well as it misses out another twenty five letters of the alphabet. Big data is certainly sourced from different places – from web sites, social platforms, machines on the internet of things. It also certainly plentiful and strange. However, defining it in terms of where it has come from or how it is processed is a technicality. It would offer far more insight to discuss it in terms of how it can be used in retail, insurance and telecommunications.

One V

Indeed, like many others, I can only really get behind one v. V for value. Like all data the test is what you do with it once you have it. If the answer is identify fraud, adjust an insurance premium in real-time, predict climate change patterns or alert a physician that a therapy regime is dangerously out of step then we can see something of value. If the answer is nothing then all that hadoop’ing, nosql’ing, massively parallel’ing and v counting is for idle curiosity.

See also Big Data – Why the 3V’s Don’t Make Sense, What is Big Data? and the Top 5 Myths About Big Data.

Facebook Graph Search: The Power of the Nodes and Edges

According to Mashable, Facebook Graph Search could be it’s greatest innovation. I tend to agree. FB have eight years of Big Data (including almost over two billion new Likes each day) to help us identify products, services and brands that we might need through the experiences of those in our social network.

Actually, a graph consists of only two things; Nodes (people) and edges (their relationships) Analysis of these though can reveal much. The simplest is a measurement of neighbours, the number of edges and their direction. A node with a large number of inward edges (or indegree) can be thought of as popular. One with a large number of outward edges gregarious. If it were possible, Lady Gaga could make a whole boutique full of dresses out of her indegree. Simple analysis of these elements are behind ‘People You May Know’ features in LinkedIn, Chatter, Connections, Jive and Facebook to mention just a few.

New Nodes

Of course, the FB Graph includes other types of nodes (businesses, brands, products) and many other types of edge including the ubiquitous Like. FB also have demographics and psychographics because we surrender more information about ourselves to FB than we would feel comfortable doing in any other survey online or offline. We’re all concerned about privacy but generally end up somewhere around ‘what are you gonna do?’.

These simple elements add up to something very powerful. It’s possible not just to find French restaurants in Frimley but those that are preferred by frequent travellers to the Côte. Not just DIY stores nearby but those popular with power tool enthusiasts. Robert Putnam could have found countless examples for his book on the decline of social capital Bowling Alone. And it is just the beginning. Let’s not forget that those edges include ‘listened’, ‘read’, ‘watched’,’hiked’ and ‘cooked’ to name but a few of the verbs now residing in your facebook apps list and your personal social graph.

Big Data Breakthrough

This is a Big Data breakthrough for Facebook and puts some distance between them and their competitor, Google.  I am not sure that plus’ing is enough of an ‘edge’ at this stage. And for those that can’t see that FB and Google are competitors then remember that there is no revenue in Search. No one actually pays Google to organise the worlds information. Nor do we part with our cash for maintaing personal networks on Facebook. There is, however, a group of people willing to pay for connecting people to products they might enjoy. Advertisers. In other words there is revenue in creating new edges between nodes.  That’s the power of the graph.