Category Archives: complexity

How Big Data will change Marketing (part 1)

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.

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Contact centres – the end of 28 days later

28 DaysContact centres aren’t perfect, but they are better than what went before.  They are here to stay, even while we continuously improve their performance.  Contact centre transformation is easier when we don’t lose sight of the core reason for the centre in the first place: to enable customers to talk to our company, buy things and get help.  

28 days.

Nowadays it has a different association (see illustration) but many of us in the UK still associate this timeframe with a familiar phrase:  “Please allow 28 days for delivery.”

It was a routine part of the terms and conditions for mail order.

A serious customer journey

Mail order, of course, meant not just receiving goods by post, but ordering them by post as well.  Find the product you wanted in a newspaper (or magazine or catalogue), fill in a paper form, cut it out, write out a cheque for payment, put them both in an envelope, address the envelope, put a stamp on it, go to a post box, post it…

…and wait.

For up to 28 days.

Almost a month.

Then when the parcel arrives, open it and see if what you have received is anything like the black and white image in the original advertisement.  Or the right size.  Or if it works properly.  And has not been damaged in transit.

And if it’s not right, begin the whole rigmarole again. In reverse.

Not, by any measure, an ideal customer journey.

Contact Centres make it better

Contact centres changed all that.  Want to buy something? Call up, place the order and it will be dispatched quickly.  Problem with a product or service? Call up and the agent will handle your problem or help explain what we need to do to resolve it.

Sure, none of us like being put on hold or to have to navigate through endless sequences of IVR numbers; and many of us have service disasters we can recount about when we got to speak to the agent from hell, but we forget, sometimes, how much better it is than it used to be.

Oddly, the internet hasn’t killed off the contact centre. Despite that we can now order things and services online from our laptops and tablets and mobiles, many of us still want to call up and talk to someone. And when things go wrong, while email, customer forums and online chat are all very well, many of us still want to call up and talk to someone.

Why?

Because our lives are complicated and what we want is complicated and our problems are complicated and sometimes we need to explain to someone – a person – what we want, and have them confirm that they have understood what we want, and that something will be done about it.

And a website can’t do that.

Sometimes, of course, it doesn’t work this way, and every one of us has a horror story to tell. But most of the time it does, and often, it works very well indeed.

Contact centres enable this experience.  And they continue to do so: while most now also handle customer communications across a range of channels, the customer telephone call tends be the heart of the operation.

Keep sight of the purpose

The challenge facing all of us who work with customers, however, is how we equip our people in contact centres to deliver a service which is consistently good, and consistently cost-effective – while  customers remain complex people with changing needs, and the technologies available to customers and to us develop constantly.

I believe that the only way to succeed in meeting this challenge is to remember one thing:  the core purpose of the contact centre is to enable customers to talk to our companies, to buy and get help.

Everything we do in a contact centre is about doing this better.

And when it gets hard to do this – and it will – we can console ourselves with one fact: even when things aren’t great, for most of our customers, things are much, much better than they were.

Contact centres revolutionised how we engage with customers and vice-versa. People complain about  them, sure, but how many of us remember what it was like before they were commonplace? I, for one, don’t want to wait 28 days again…

Stop complexity from killing the customer experience

Complexity mazeComplexity kills good customer service. We can use the rule of 50/5  to cut through this complexity and  transform the customer experience.

I once worked for a multi-national technology company with a turnover of tens of billion of pounds. The organisation’s processes and systems were so complicated and intertwined that any improvement efforts were doomed, if not to failure, then to mediocrity.

Any new customer fix – a system, a process, a metric or a behaviour change – was just another complication in an already complicated environment. Sooner or later, those in the customer front line would make mistakes because complexity introduced by the new fix made errors more likely. Their normal tasks might often take longer, as the new fix might need new skills or new thinking. It might increase complaints, perhaps through teething problems, or because expectations for improved performance were too high.

In short, because corporate sclerosis was gumming up the customer experience veins, ‘improvements’ were likely to make things more error-prone, slower, less easy, and, almost certainly, substantially more expensive.

This is because of one of the infallible laws of business, something I was fortunate to learn early in my career, courtesy of George Elliott: complexity ALWAYS increases costs, and by much more than we think.

Paradoxically, however,  how complexity drives costs offers a powerful way to enable customer transformation. This is because (again as George explained in my youth) these costs always appear in the same way: they follow the rule of 50/5.

50% of your costs are associated with 5% of your activity, and vice versa.

In the almost one hundred companies with which I have worked, while some the precise numbers have varied a little, I have never seen this rule to be wrong. It is a cast iron law of business.

What’s brilliant about this principle is that it applies in so many ways. Here are some I have found useful:

  • 5% of customers account for 50% of service costs
  • 5% of customers account for 50% of revenues
  • 5% of our customer enquiries yield 50% of our sales
  • 50% of our people’s time is spent working on issues raised by 5% of our customers
  • 50% of escalations come from 5% of customers

For each one of these, the complementary statement is also true: as well as 5% of customers causing 50% of service costs, so 50% of customers cause only 5% of service costs.

Why is this important? Because it means we have a practical way to focus our improvement efforts to deliver effective transformation, reduce complexity and make things genuinely better.

So for one tech company for which I worked, we found that 3% of escalations were consuming 38% of engineer time. We identified and eliminated the causes of almost all these escalations. This enabled the organisation to free up a quarter of their engineers to work on proactive services,  adding value to their customers. At the same time they kept some engineer capacity in reserve to handle the many fewer new escalations which inevitably would still arise.

For another company, recognising that 4.5% of their customers yielded 53% of their revenues drove them to offer premium services to these customers – increasing revenues and retention.

At the same time, they reduced services to the 48% of customers who contributed only 4.9% of revenues, but offered them the chance to upgrade. Result? Some of these unprofitable customers left, some stayed, but cost less to serve – but enough upgraded to make this customer segment twice as profitable.

This thinking works.

But beware. Standard accounting cost models don’t give you a true picture of these costs (because they assign overhead costs uniformly across the board as opposed to how the costs are actually being consumed) .

So let’s begin using the rule of 50/5, but not by looking at budgets and costs on a spreadsheet. Let’s get out from behind our desks to see what is really happening. Let’s look, not at the cost numbers, but where our people are putting in the work with our customers. We’ll soon see where the rule of 50/5 works in our business, and how we can use it to cut through complexity to make things better for our customers.