Customer Experience: Beware The Data Trap

Data. It is being made out to be sexy – really sexy. Many folks even think that collecting mountains of data and stuffing it into CRM and/or marketing automation systems is the access to delivering great customer experiences.  They are mistaken. Collecting mountains of data can be useful to marketers in helping them achieve higher direct marketing ROI through better targeting. It may allow the folks in operations to tune aspects of operations. That is about it.

What is the basis of the assertion that I am making? Lived experience. I invite you to ponder the following:

To describe me as weighing a certain amount is …. to “disregard the existential state of being-in”. It is to describe me  in a way in which one may describe any physical object. I can weigh x pounds as a living Dasein or a corpse, it makes no difference.

So, if we disregard a person’s existentially and treat him or her simply as a physical object, we can describe that person in terms of his or her factual determinations. In doing so, however, we are missing what makes his or her life the life it is. People do not just weigh x pounds: they live such a weight as being overweight or underweight or as being indifferent to their weight. Weight, as a way of being-in-the-world, is not an indifferent physical property, but rather an existentiall condition. We may similarly between biological sex and gender, between physical height and stature.

– William Blatner, Heidegger’s Being and Time

I say that if you are to excel in the domain of designing and staging great customer experiences then it is not enough to collect masses of data. Collecting data can actually be a distraction from the real task. What is the real task? The real task is to get a handle on the facticity of your customer’s life: a gut level grasp of his/her life and in particular what makes his/her life the life it is.  Data of the kind that ends up in databases cannot and will never provide this kind of insight.

Does this kind of insight into your customers matter? Yes.  This is the kind of insight that allows you to come up with business models, value propositions, products, services, and customer experiences that attract and retain the customers you have chosen (intentionally or accidentally) to serve. It is also the kind of insight that you need to call forth the very best from the people that work for you and work with you. This requires a level of humanness that is rarely given space in established large organisations.

If you do not get the passage that I have quoted above then I say you are wasting your time in the Customer Experience sandbox. You’d be better off in the direct marketing, CRM, or operations optimisation. If you do not get this passage and choose to continue playing in the CX sandbox then know that is perfectly OK. Why? Because you will find many like you in the CX sandbox – you are in the majority.

Thanks for listening. I wish you a great day.

Three reasons why converting data into valuable business results is no picnic!

Nancy Porte knows what she is talking about

I have been reading a PR release on the latest Verint-Vovici voice of the customer survey.   The key finding is “organizations hailing from a wide range of industries and company sizes are catching on to the value of the Voice of the Customer”.   And the conclusion is “research shows that as long as companies aim to enhance the customer experience, improve customer loyalty and increase profitability, the VoC will always fill a mission-critical role”.   It is good to see that an ex-employer, The Peppers & Rogers Group, has been involved in this study.  Let’s move on to the part of the press release that did catch my attention:

“People are amazing at collecting data, but they’re often less skilled at creating insights out of it and spreading them throughout the whole organization,” adds Vovici’s Porte. “Data is great, but it rarely means anything unless you’ve figured out exactly what that data is saying and what you’re going to do about it.”

What happens when you give a budding Alexander the Great a fleet of stealth bombers?

Imagine that you turn up at the residence of a budding third world ‘Alexander the Great’ – a dictator with dreams of empire.  You offer him a fleet of stealth bombers with all the associated armaments.  You are excited, the dictator is excited – you see yourself as rich and the dictators sees the world at his knees.  What you have both forgotten is that it takes highly skilled pilots to fly these stealth bombers.  And you need to put in place a whole ‘infrastructure’ (hangars, airstrips, fuel, missiles, technicians) to enable highly skilled pilots to make use of these stealth bombers.  You might be wondering what this has to do with VoC and Customer Analytics.  Everything.

There are plenty of vendors offering analytics stealth bombers (advanced data mining and analytics platforms, packages and ‘solutions’).  Before you embrace your dreams of ‘world domination through analytics’ you might want to consider and prepare for the following:

  • The fuel (data) that powers analytics is typically missing, insufficient and/or ‘dirty’;
  • The pilots (statisticians) that need to fly the stealth bombers (the analytics packages) are in short supply – there simply are not enough of them to go around to fulfill the dream that is being aggressively communicated;
  • The infrastructure (leadership, mindset, culture, practices, processes….) that is required to ‘make use of the skills of the pilots’ and ‘exploit the potential of the stealth bombers’ is simply not present in the vast majority of organisation and putting it in place is a BIG ask, which requires patience (think long term) and commitment (to face and overcome the hurdles – big and small).

What is so in the real world?

What is the state of affairs in the real world?  I cannot answer that question as I have not sampled the whole world of business.  Yet, I can share my lived experience with you when it comes to the analytics front.  Allow me to illustrate with two examples.

As a customer based strategist I need and generate insights in order to construct viable strategies.  In one consulting engagement I asked a question: how many customers did you sign-up last year over channel X?  Sometime later I was handed a report.  I got a different answer depending on which page I looked at.  There was only a small difference between the numbers and the point is that there should have been no difference!  Either the definition of ‘customer’ was not consistent over the enterprise.  Or the definition of the ‘channel X’ was not consistent.  Or the enterprise systems and/or people were not able to add up properly.  Sound bad enough?  What if I told you that the managers in this enterprise prided themselves on the quality of their management information?

In another consulting assignment (involving the formulation of a customer strategy) I was in the process of getting to grips with the customer base – specifically, customer profiling and segmentation.  I needed to understand who was buying a particular product.  So I asked a helpful member of the client organisation to come back with the answer.  I was handed a small document and it clearly stated that the buyers were male, in their thirties and living in the larger cities.  Having been burned more than once, I asked to see the actual figures.  Upon reviewing the figures I found that the buyers (customers) were indeed in their thirties and living in larger cities.  However, there was no statistical difference in gender: the buyers was just as likely to be female as male.  You might be wondering how someone who is trusted (and whose job it is) to interpret data get it wrong so badly?  I can tell you that this is no exception – misinterpretation of data is the norm rather than the exception.  Why?  Because we are not statistically minded.  Thinking statistically is arduous and is a skill that has to be learned and continually practiced.

Why big data and analytics will not make you the next Apple

Are  ‘big data’ and ‘analytics’ the latest fads?

In my view there is a little too much hype around ‘big data’ and the power of analytics to drive business growth and profitability.  Can ‘big data’ and ‘analytics’ help you improve operations?  Yes – they can help you better staff and manage your call centre  or improve your supply chain or target your marketing better.   Will ‘big data’ and analytics make you the next Apple?  Highly unlikely.  Why does that matter?  Because whilst you are busy optimising operations someone else is inventing a future in which your optimised operations become redundant: think music, think publishing, think mobile phones.  Let’s explore this further.

What are the root causes?

Years ago when I worked in the business planning & analysis team of a brand name drinks company I noticed something interesting.   Managers could drill down and find out which particular markets had failed to make their numbers.  Great – we know which business unit is underperforming.  But why is this unit doing better or worse than expected?  This is where the fun started.  First, there were almost as many opinions as the people we asked.  Second, there was no easy to work out whether the answers given by local management held any resemblance to the ‘truth’.  When I dug further I found out that local management did not know why they had failed to make their numbers (revenues).  When they were asked, the local managers simply came up with the most plausible story.  So month end because a ritual where HQ asked questions and the local managers invented plausible stories.

Lesson 1:  For any complex event there are a multitude of plausible answers and working out the ‘real reason’ is notoriously difficult.

Lesson 2:  Without a sound grasp of the root causes it is difficult to formulate a sensible course of action to address the situation.

What do we do about it?

Lets assume that you have all the data and analysis has been done.  You know there is a problem.  What do you do about it?  Is it easy to get all the actors – who have to play ball – to agree on the course of action to take?  In my experience the answer is no: the more ‘strategic’ the issue at hand the more difficult it is to come to an agreement on a sensible course of action.  Let’s take a look at the recent banking crisis.  Did all the main actors (the western economies) come to a consensus on what course of action to take?  No.  Just take a look at the Euro crisis: why is it that the leaders of the EU cannot agree on the right course of action?  First, because different people have different ideas about what constitutes the right course of action.  Second, the right course of action from an objective perspective may simply not be viable from a political perspective.

Lesson 3: The more that is at stake the harder it is to get all the actors to agree to a single course of action and then act to play their part and execute that course of action

Lesson 4: If you are unable to act decisively and as a single unit then all the data, analysis and insight is worthless

Does it really tell you what you need to know to thrive in the future?

Larry Freed has written an article that resonates with me.  He points out that you need to be clear on what you know and what you do not know.  I’d say that you need to be clear about what data and analytics is telling you and what it is not telling you.  Larry, talking about a website, asks do you know:

  • Why visitors come to your site (to research, to buy, to complete a transaction, to get product support, to learn more about your company before interacting with you through another touch point, etc.)?
  • What influences visits to your site (a referral, a social media interaction, a failure to resolve an issue with a call centre, an advertisement, a news story, a previous affinity with your brand, etc.) and which customer acquisition sources result in traffic that is the mostly likely to convert?
  • What visitors need from your website? How needs differ by population segment or other segmentation that is useful to your business—perhaps first-time vs. repeat visitors, heavy users vs. light users, etc.?
  • What visitors expect from your website? Do men and women have the same expectations? Old and young? Do people who arrived as a result of a Google ad have the same expectations as those who arrived because of a TV ad?
  • What channel your visitors prefer, and are there ways you can influence that preference so they frequent less costly, more profitable channels?
  • How customers view your business, compared to the way non-customers view your business, relative to your competition?
  • How your customer profiles and expectations change in response to market and broader economic conditions? And what, if anything, you need to change as a result?”

Colin Shaw in a recent post makes the same point in a different way.  Here are some relevent extracts from his post:

“Google and Facebook, as Eli Pariser discusses as a part of TED, are engaged in the process of quantifying preferences from the timing and frequency of online clicks, and using this information to alter web content. The stated goal of this practice is to “personalize” the web experience.

A lesson gleaned from Dell’s 1990s laptop boom illustrates the point that preference and value are two different things. Dell let its customers customize all aspects of their computer’s hardware – from screen size to keyboards to RAM – everything but color. Nobody thought to customize color, because a laptop was supposed to be black or gray. However, when color laptops were introduced, sales skyrocketed and we all learned that color was indeed an important factor.

Imagine if Google and Facebook had monitored “clicks.” They would infer that because customers did not indicate a laptop color preference, it doesn’t drive value and is therefore irrelevant.”

Lesson 5: there is an assumption behind all predictive analytics and that is “all things being equal” – that is to say that predictive analytics assumes that the future will be a replay of the past.

Lesson 6: human behaviour is shaped by the ‘structures’ in which human beings are embedded, change the structure and you are likely to see human beings change their behaviour. Think about how the recession (e.g. job losses) have changed the shopping habits of consumers in the western economies.

Why won’t big data and analytics make you into the next Apple?

Apple was busy creating a new future (a break from the past) rather than exploiting the past.  If you take a look at the US automotive industry the big US automakers were busy building and selling gas guzzlers because the analytics showed that these were the cars that Americans were buying.  At the same time Toyota was busy living into a very different vision of the future: hybrid cars and electric cars.   Who was right?  According to the data and the analytics it was the US automakers.  What would you say now?  Toyota?

If you are not inventing the future you can still prosper by picking up the weak signals that point towards a new trend.  I once asked Bob Greenberg (R/GA) the secret of his success and he told me it was his ability to see these trends and act upon them before others.  You might imagine that analytics might help you to spot trends.  My experience of traditional analytics is that the modelers do all they can to strip out the outliers and create a normal distribution so that the maths works – in doing that they filter out the ‘weak signals’ that point towards these trends.

Perhaps it is best to end by remembering what Colin Shaw points out: how would analytics have disclosed that customers wanted to customise the colour of their laptops and that once this option was made available then Dell’s laptop sales would surge.

What do you think?  If I have it wrong then please do educate me.

Self service is not an easy fix or why I love Kylie

Yesterday I read an interesting article on self service (well worth reading) and this got me thinking about my recent experience with the Home Delivery Network, a parcel delivery firm that operates in the UK.

One day I was handed this card by wife.  She told me that it looked like a parcel had come for me and as no-one had been home the driver had not been able to deliver the parcel.  The first thing I noticed was that the card had not been completed and so I was not able to tell:

  • who the parcel was for as there are five of us living at this address;
  • when the delivery firm had attempted to deliver it and failed;
  • what had actually happened to the parcel –  taken back to the depot or left with a neighbour etc.

What I did notice was 8 digit parcel ID and the instruction to look at the back of the card for contact details.  Reading the back it became clear that I was being urged to go to the website.  I did exactly that and entered both the parcel ID and my postcode.  The website responded with the following message: “Your parcel(s) cannot be rescheduled for delivery, please contact customer services on 0871 977 0800”.  Just to make sure that I had not made an error, I had a second go at entering the parcel ID and postcode and found that I got the same message.

So I called the number and found that straight away (no waiting) the IVR kicked in and once I had entered the parcel ID it spelt out when I could get the parcel delivered.   As it was a Tuesday, I requested delivery on the Thursday and left my home number so that delivery firm could ring me back if there was an issue.    At this point I was happy with the experience as it had been easy to schedule a delivery.

Thursday arrived and departed: we did not get the parcel delivered and we did not get a phone call to let us know that there was an issue.  So I contacted customer services (the IVR) and proceeded to listen to the option and select another date for delivery.  That date came and went: no delivery, no phone call.  Then I made a third attempt and met the same fate.

At this point I became rather frustrated even angry.  Why?  Because I wanted to get my hands on the parcel and I could not.  Every time I dialled the customer services number I found myself faced with the IVR which spelled out the dates when I could reschedule delivery.  I was wondering: how do I get through to a human being who can help me with my problem?

Then I made another attempt to contact customer services.  This time I listened to the IVR and did not opt for any of the delivery dates and found that right at the end I was given an option to speak to a human being.  I selected that option and found myself talking to Kylie.   She greeted me warmly, took my details, looked at her system and was able to tell me that the parcel was addressed to (my wife) and sent by Republic (the clothes retailer).

Kylie also told me that the delivery drivers handheld had failed and so he had not been able to upload the information into the system.  As a result I had not been able to find and reschedule the delivery of the parcel.  Then she went on to tell me that the notes on her system were telling her that the parcel had actually been delivered the very first time.  And clearly that might explain why I had a lack of success in getting the parcel delivered!

When I told Kylie that my wife and I had not received that parcel (despite what her systems said) Kylie went on to clearly explain what I need to do.   She was great and she completely changed my mood and my attitude: she took away my frustration because she had shed light on my situation and provided me with a clear path that I needed to follow to close the matter out.  Above all she had a friendly, helpful disposition throughout our conversation: she made me feel that she was on my side.

So here is my take on self-service technology:

Your self-service technology is only as good as the people, processes, technology and data that sits behind your self-service technology

If you consider my experience, you find that the driver left the card behind even though he had delivered the parcel according to Kylie.  Second, the delivery driver did not fill in the data fields in the card: either he should have filled in the data fields or the data fields should not be there.  Third, his handheld failed to update the data into the delivery tracking system.  Fourth, the IVR allowed me to schedule a delivery even though there was no parcel to be delivered as it had already been delivered.

Give customers an incentive to use the self-service technology: make their life quicker and easier

At first I jumped at the idea of rescheduling the parcel delivery through a website.  Why?  Because, in the past I have had to make a number of calls and/or wait a long time to have delivery depots answer my calls, find my parcel on their system and then reschedule a delivery.  Even when the website did not work, I was happy to use the IVR to schedule the delivery as it was quick and easy.

Give customers an easy way to bypass the self-service technology

It is necessary to give customers an easy to find option to bypass the self-service technology.  Why? Because the self-service technology can fail and does fail as it did in my case where neither the web nor the IVR was able to tell me that there was no parcel left to deliver or to deliver that parcel.  In my case, I made four failed contacts with the delivery firm before I was able to figure out how to get through to a helpful human being – a customer services agent called Kylie.

Also because not all customers can or want to use self-service technology.  A case in point is the UK supermarkets replacing cashiers with self-service tills where the customer has to do the work of the cashier.  I am in that segment of people who do not agree to the proposition that I should do the work of the supermarkets especially as the two times I have made the effort the process has not worked and I have had to wait for one of the supermarket staff to come over and sort out the issues.

The more you replace human-human interactions with self-service technology the more important human beings become

Why?  Because human beings are usually the best at dealing with and sorting out the problems that you create for your customers through the introduction of self-service technology.  This is where Kylie was great: she simply defused by frustration and anger by listening to me, getting where I was at and then helping me through to the solution.

Whilst self-service technologies can improve the functional experience it tends to be at the cost of the emotional experience

At a recent conference I heard several female customers mention that whilst they appreciated the ease and convenience of banking electronically with First Direct they did not feel any emotional bond with First Direct because they never spoke with a human being.   This points to a truth: whilst technology can make life easier it rarely makes human beings feel acknowledged, appreciated, respected, valued.  This is why I love Kylie:  she made me feel all those things when the self-service technology had left me feeling insignificant, neglected and helpless.

Voice of the Customer: following in the tracks of CRM?

I am noticing that there is a lot of buzz around Voice of the Customer (VoC).  There are lots vendors out there who will supply you with the frameworks and the technology to get access to the VoC.  There are even companies out there that will do it all for you.

To my skeptical mind the promise and the buzz sounds remarkably like that of CRM in its early days: heaven on earth or put differently profitable and enduring relationships out of the box.  So what is my concern, what is my issue, what is keeping me awake?  In a nutshell, the hype, the overblown expectations.

The digital world is overflowing with data.  The first challenge is to gather the data from the various fields in which it grows and bring it together in a useful way.  Having been involved in data mining and predictive analytics I can tell you that it is not as easy as it sounds.  The next challenge is to find patterns in this data.  The bad news is that technology alone will not cut it: notice that Google has just changed its algorithm to deal with the loophole found and exploited by Vitaly Borker.  So human being are required.  Human beings who understand the process; who understand the technology including it’s limitation; who understand the business; and who understand customers.  Then the fun really starts.

Having found the patterns and interpreted the patterns from the VoC these wonderful human beings have to convert these patterns, these insights, into a language that the people in the business can understand.  Believe it or not this is not as simple as it sounds.  The people who are often best at finding the patterns in the data really struggle to convey their insight in a way that the business people get. Incidentally, finding people who are good at turning data into insight is not easy.

Now we get to the really serious problems.

Human beings have a strong tendency to discount anything that does not fit in with their view of the world, their values, their goals, their self-interest.  This is particularly so when these people have been completely divorced from the process of gathering, integrating and making sense of the data. So it is not at all guaranteed that the wisdom that has been gathered from VoC will actually be accepted by those who have the power to act on it.

Next we come to the central problem and it is this: knowing really does not make the difference.  Think of all the obese, unfit, people in rich societies and then think of all the mountains of ink that has been written on eating the right foods, in moderate amounts and the need for exercise.  I have known for many years that I need to exercise more, yet I did nothing until I had a blood test that frightened me a lot.  Now I exercise for at least half an hour a day, every day.

So where am I going with this?

First, all the work and cost associated with VoC is only worthwhile if there is real hunger in the organisation (started with the Tops) to use it to improve the lot of the customer and to improve the effectiveness of business operations.  I have worked in an organisation which spent considerable amount of money and effort on conducting NPS surveys.  Whilst one set of people were passionate about the process, the bulk of the European organisation (at all levels) was not.  As a result, nothing significant changed from one survey to the next.

Second, there is absolutely no substitute for the Tops (the Csuite, the elite) getting away from their offices and walking in the shoes of their customers and of their people who have to interact with and serve these customers. I believe that was the lesson of the Undercover Boss tv series.  So by all means do VoC but not at the expense of having senior and middle managers walk in the shoes of customers and front line staff.  If I absolutely had to choose between the two, I would drop VoC and insist managers work on the front line regularly.

What do you think?