Tag Archives: marketing

Big Data, complexity, customer experience, customer strategy, Lean, Marketing, Strategy

How Big Data will change marketing (part 2)

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Big Data imageBig Data is coming. It will change Marketing, but not necessarily in the ways we might expect.

In an earlier post (How Big Data will change marketing (part 1)) I wanted to introduce the idea of Big Data in practical terms. My take on Big Data is not in terms of volume, velocity or variety, (as coined by Gartner analyst Doug Laney) but in terms of what it is in practice and how it might encourage action.

In my view, Big Data has seven characteristics:

  1. Big Data is not (just) big data.  Big Data is more than data warehouses and structured data repositories.
  2. Big Data is unstructured data. Big Data is messy, error-strewn and has fuzzy edges.
  3. Big Data is behavioural, not attitudinal.  Big Data is about what people do, not what they think
  4. Big Data is about small interactions. Big Data comes from the simple stuff we do, often without realising it
  5. Big Data changes.  All the time.  Big Data is never still. It is always being added to.
  6. Big Data is online, mobile and the real world.   Big Data is coming from all kinds of activity, on- and offline.
  7. Big Data is informational debris. Big Data is a side-effect of other activity – it is mainly not the information we as customers enter consciously when we think we are sharing personal data.

For marketers, the looming presence of Big Data is likely to change many things, including these:

Scientific method  The scale and nature of Big Data are making marketing a rigorous, experimental discipline.  We are getting the means to interrogate very complex data sets very quickly to decide which marketing idea works best.  This is already happening online.   Disciplines such as A/B testing and the thinking embodied by Eric Ries’ excellent Lean Start-up are already in action in many places. Examples include Amazon offering A/B testing as a free service to android developers and Barack Obama using it to raise $60m.  (See also my post, ‘Let’s go hippo hunting‘). This thinking is rapidly moving offline.   Marketers will have to master strict, efficient scientific method to succeed in this new world.

Attitudinal marketing is dead  Well, if not dead, then it’s about to enter life-support.  The  quantity and predictive value of behavioural and activity data means that what people think or feel about a product or brand will become increasingly irrelevant.  We are already finding this on the web.  If A/B testing shows us that consumers prefer to press a red button, and not a blue one, then we are better served by changing all our buttons to red than spending a fortune trying to understand why. This thinking will soon apply everywhere.

Prepare for the segment of one   Big Data will enable us to direct contextual, customised marketing directly at individuals based on such things as (say) their mobile GPS history, online and social media activity, and offline behaviour.  In effect, a marketing campaign for one person.  One implication of the segment of one is that a consumer marketing operation may well need to deliver a million tailored campaigns a year.

This is not just an automation problem.

To run at this level, with minimal errors, cost-efficiently, means the winning marketing operations will be those which adopt and implement the Lean manufacturing disciplines which enabled car manufacturers to deliver a batch size of one, with a cycle time approaching zero. (See my earlier post – SMED: The secret sauce of customer experience, for a related discussion).

We are all going to become Lean, people.

Create platforms, not campaigns  The role of the creative will change. Increasingly, we will need our creatives to design communications platforms, rather than individual campaigns. These platforms will have to flex in innumerable ways to meet the contextual demands of the segment of one.

Brand as algorithm   Brands will be formulated into heuristics – rules which can drive real-time decisions to enable real-time marketing.  The automated brand is coming.

Source, don’t build, your data  By definition, Big Data is a mix of different data sources.  Very few organisations have the capability to assemble, structure and support such heterogeneous sets of data and stay sane (and profitable).  Ignore the Big Data hype about the need to build Hadoop clusters and recruiting data scientists. This isn’t how it is going to go.

Here is how it might.  Companies are going to realise soon that they will be better off working with trusted data intermediaries rather than trying to build their own Big Data. They will pose questions to these intermediaries, such as “….what is the best way to segment the market to identify the people most likely to buy our stuff?…”, or “…when in the customer’s day are we most likely to get positive attention for our proposition…?”  or “…who could be our next customers….?”

These intermediaries will orchestrate data sources quickly to get the best answers to these questions. They may already own some data, some data they may rent, some they may commission and some will come from their clients – but such tasks are best left to specialists.  There is no need to build your own data engine. Spend your time instead trying to understand the questions you need to answer to get to market most effectively.

Of course, for companies which specialise in data harvesting, brokerage, mashup and orchestration, this intermediary role will be a lucrative opportunity. For the rest of us, being able to use such services intelligently will become an increasingly important skill.

Big Data is going to change marketing. But those marketers who do embrace this change will become hugely more effective, productive and  influential.

It will be marketing, Jim, but not as we know it.

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Big Data, complexity, customer experience, innovation, Marketing, Strategy

Big Data is already here

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vorratsdatenspeicherung-540x304In my earlier post, How Big Data will Change Marketing (part 1),  I offered a definition of Big Data.  Here is a brilliant example of what it looks like.

A life revealed

Malte Spitz is a member of the Bundestag, the German parliament.  He sued mobile operator T-Mobile to get their records of his cell phone activity for a six month period in 2009.  It came in an Excel spreadsheet with 35,851 rows.

Zeit Online, the digital imprint of Germany’s top-selling weekly newspaper, Die Zeit, combined this data with other information about Hr. Spitz’s life which they gleaned from social media and publicly available online sources.

The result was illuminating.

To quote Die Zeit:

“Each of the 35.831 rows of the spreadsheet represents an instance when Spitz’s mobile phone transferred information over a half-year period. Seen individually, the pieces of data are mostly inconsequential and harmless. But taken together, they provide what investigators call a profile – a clear picture of a person’s habits and preferences, and indeed, of his or her life.

This profile reveals when Spitz walked down the street, when he took a train, when he was in an airplane. It shows where he was in the cities he visited. It shows when he worked and when he slept, when he could be reached by phone and when was unavailable. It shows when he preferred to talk on his phone and when he preferred to send a text message. It shows which beer gardens he liked to visit in his free time. All in all, it reveals an entire life.”

To model what they mean, Zeit Online produced this interactive map.

This is Big Data in practice.

I will leave it to other commentators to discuss the political, legal and ethical issues raised by Big Data.  I am going to assume, instead, that it is here to stay and that it will increasingly affect our lives.

In my next post, I will develop further some ideas about how Big Data will affect Marketing.

Tip of hat to Roland Harwood of 100% Open for the original Die Zeit article.

Image credit: Zeit Online

Big Data, complexity, Marketing, Strategy

How Big Data will change Marketing (part 1)

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Big data imageIf Big Data delivers what it promises, then the implications for Marketing – and indeed, all of business – will be profound. Before we can understand what these implications might be, we first need to understand what Big Data actually is.

The promise of the new oil

Big Data, we hear, is “…the new oil”. It is the next big thing, the new realm of business opportunity, the them thar hills in which gold can be found. With Big Data, we are told, we can see flu outbreaks before they happen, tell how the stock market is going to move today and discover that you are pregnant before your family does.

Big Data makes big promises. But many of these promises have been made before, with, for example, data warehousing (and the famous beer and diapers story). What is different this time, and what difference will it make?

Consultants and technology companies have been beating the Big Data drum for some time, but there is little consensus of what the term really means.  If, for example, I am trying to build a data centre to handle big data, then naturally my definition will reflect the size and complexity of the data to be handled.

I believe, however, that most of us with a business perspective need a definition which enables us to think about the value and uses to which Big Data might be put.  My stab at doing so is below, borrowing freely from excellent recent articles by Hung Lee (Big Data is Not ‘Lots of Data’) and Alex Cocotas of Business Insider.

Big Data is not (just) big data

What makes Big Data interesting is not the the size of the data sets (although these can be mind-bogglingly big). The value of Big Data is much more about the kinds of data which it embodies, and (particularly) the uses to which it can be put.

Big Data is unstructured data.

Big Data is not that which fits neatly into a relationship database or which can be categorised by tags (although it may well contain data of this type).  Big Data is a hybrid mashup of different kinds of data such as geolocation, contextual data, telemetry, life events, video, demography, social media and more.  It’s messy, complex and has fuzzy boundaries.

Big Data is behavioural, not attitudinal.

It is about what people do, not what they think. Big Data is not, for example, about focus group findings or survey results.

Big Data is about small interactions.

Big Data might include transaction information, such as what is in our shopping trolleys – but this is a known game and is only an adjunct to the important stuff. Important stuff?  What we do before we put things into our trolleys.  Where we have walked. Whom we have met.  What we do for fun. What the weather is like.  What we are wearing. What everyone else is doing. The TV channels we watch. You know: the small stuff we do all the time.

Big Data changes.  All the time.

Big Data is gathered continuously, in real-time, often from millions of dynamic sources. This means that at any time, we can only have a snap-shot of this continuing river of data. By the time we look at it, it’s already changed.

Big Data is online,  mobile and the real world.  

Big Data is credible because Google and Amazon and (a very few) others have been able to farm and use complex online customer behaviour data to make serious money. Now mobile is changing the game. Those of us with smart phones use them everywhere.  We use apps to help us in the physical world.  We use services like GPS and geolocation which note everywhere we go.   Now when we turn on our mobile phones, we create data about our behaviour in the physical world in ways comparable with the data we create online. What do we call this melange of online, mobile and physical information?  Big Data.

Big Data is informational debris.

Big Data is what we throw off when we do other things.  When we stop what we are doing to fill in a form, or have our picture taken or scan some stuff to get ourselves registered or updated – that is not Big Data. Or if it is, it is only a small part of it.  Big Data is what we leave behind us when we play games, or take pictures, or move house, or phone someone up, or browse around a shop, or go for a run or change the channel. It is a side effect.

That’s my shot at defining it.  Does this work for you? What have I missed or got wrong? Let me know.

If Big Data keeps its promises, the implications for all of business – but especially Marketing – are profound.  I will explore some of these implications in my next post.

This series of posts arose as a result of a panel discussion earlier this week at IQPC’s CMO Exchange event at St Albans.  I had the pleasure of sharing the platform with Paul Blacker of BT and Michael Woodburn of Capital One, and it was admirably chaired by my old chum Vincent Rousselet, CEO of the Strategic Planning Society.   Our conversation offered a good range of views on these questions. These opinions I express here, however, are entirely my own.

CRM, customer experience, customer strategy, innovation, sales, Strategy

CRM can be fun. No, really.

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Finish line.Thinking about CRM (Customer Relationship Management) from the sales team’s point of view has stimulated some interesting new possibilities.

I once oversaw the transition of a B2B CRM system from a locally installed brand name system to a market-leading cloud-based competitor.  The old system had limped along with inaccurate data, incomplete records and resentment by the sales team.  People saw it as something that could not be trusted, an overhead that  got in the way of sales and marketing.

We were not alone, as Ben Meredith points out in a recent post.

When we came to implement the  new system we had one primary principle: it had to work for the sales team.  This meant that it had to be exceptionally easy and attractive to use, relevant to their roles, with clear triggers for when and how it was to be updated. All other requirements were secondary.

The outcome? An almost seamless transition within six weeks and excellent adoption.

Results? Better accuracy of data, trustworthy analytics and sales forecasting. Better marketing, easier sales, improved customer relationships. Everything we wanted our CRM system to deliver.

These results happened only because we paid attention to the core challenge: whose job are we trying to make better?  For most CRM implementations, this will be the sales team. Get it right for them, and things will get better for the customer too.

Which is why I like the thinking of app developer LevelEleven. Their newly rebranded Compete app adds game elements to Salesforce.com to help drive sales team performance. Their real trick, of course, isn’t the app, but the psychology: good sales teams thrive on competition.

CRM as fun? That can’t be bad.