Chapter 9

How small data can make the difference

In the era of big data the experience world actually revolves around small data – we will see that single pieces of data can be critical to creating memorable experiences and challenge the theory that ‘more is more’ in terms of data in customer experiences. Does your data pass the ‘so what?’ test. Let’s consider these questions:

• How do you find the important data?
• How can you use data to enhance experiences?
• How will legislation change the way we can use data?

For this chapter I decided to collaborate with an expert in the field of data but someone who also can act as the bridge between the twilight world of deep data and the real world of customer experience. When working with experts in data or technology my approach is always the same: I can describe what I need us to do for the customer, I can describe exactly how it needs to both look and feel for customers – I will leave you to figure out what needs to be done to deliver that behind the scenes. Frankly I don’t want or need to know the details so long as the experience is delivered the way it has been designed. So meet Jonathan Carter, that unusual hybrid technical person who acts as my interpreter both ways – you will see his contribution later in the chapter.

Data can be a scary subject for an organisation to come to terms with: it is often seen as confusing, steeped in mystery and only truly understood by a few highly technical experts. Let’s just consider some of the terminology used in the data world that creates this impression. Data scientist, analyst, decision scientist, data miner, ‘big data’, of course terabytes, and now that the internet traffic has grown so great it is measured in exabytes! Perhaps it should read ‘terror bytes’? We are of course surrounded by data and our brains process huge amounts of data every single second, and it is this very scale that can make data seem to be too big to understand. Where do we even begin?

The customer area has probably been one of the greatest contributors to the big data storage warehouses that have developed over the past 20 years. The thirst for data driven by research departments, whether to analyse transactions or create loyalty schemes has meant that vast quantities of customer data remain stored almost in perpetuity, trillions of transactions are tracked every day and the investment in acquiring data is huge. Yet the returns are in many, many cases tiny or actually negative and in some cases never even tracked at all.

Ask yourself some basic questions:

• How much does your company spend on collecting data?
• . . . on storing data?
• . . . on analysing data?
• How do you create value from your customer data?
• How many people are employed in the company to collect, manage and analyse data?

Information or data is only valuable if it can be used to provide insights which then actually drive change. Sadly the most effort and expertise and applause is given to those who design and deliver incredibly complex statistical reviews of data over time – the beauty is in the complexity and the presentation not in the usability.

What is data? In my view it is very broad in terms of its definition: it can be a myriad of different things from a name and address, to a set of transaction histories, to a list of common issues endured by customers.

In my time as an executive my challenge at the end of a research or data debrief was always the same: ‘so what?’ I have spent £100k: what have I actually learned that is usable and I can connect to a return? Too often the reports simply confirmed what we already knew.

You need to understand broadly where the company is today in terms of its available customer data.

So following on from how much it costs:

• What do we do and how do we use data to improve customer experiences?
  • The first step is to do a basic rough audit. Find out what customer data do you capture – for example, what personal details do you capture? Do you capture transaction history, do you have a single view of your customer use of your products and services?
  • Understand what you are missing. For example, do you log calls and use the rich stream of information from customers that they contain? Do you log and categorise customer complaints and compliments?
• Who uses the data and how is data used?
  • Sort your data into quantitative and qualitative buckets (e.g. transactional, customer complaints/compliments, CSI, annual surveys, personal details, voice of customer programmes).
  • Is your data compliant in terms of privacy and permissions – i.e. can you use it?
  • Review the balance of customer data – quantitative versus qualitative – this reveals where the focus is in the business.
  • How accurate is the data? How many data errors occur – e.g. in a direct mail campaign how many email addresses come back as errors?

Remember a good start point is to examine what happens with a new customer or client – what data is captured, how is it stored, what permissions are sought and how is it used

This basic information is often hard to collate, which is an issue in itself, but will be useful as an indicator of the current health of your customer data. Additionally, this data will be useful both to challenge the data strategy in the future and to ensure you are able to draw on data to better design future experiences and to use data to identify and fix issues.

As the senior executive you should be asking the question: ‘what is the return on investment of our data assets?’

Remember the ultimate question you are answering is not how much data do you have, but who has it and how is it used?

It can be helpful at this point to have some CJM software into which you can collate information – the structures that support these practitioner-developed tools will also act as a guide for you to approach your audit in a logical way. Why is this helpful? My preference is for the platforms that have been developed by practitioners because they will have done the initial thinking for you and know what type of information is likely to be out there to help you build out your customer journey data.

Having done this simple and basic audit you should stop looking for more data sources and instead wait until you are looking at a specific business issue from a customer experience design perspective. Too often data is looking for a home and a purpose, you need to review or create experiences and then look at the available data to support the delivery and identify any gaps.

Big data or small data?

So what is big data? According to Wikipedia:

‘Big data is a term for data sets that are so large or complex that traditional data processing applications are inadequate. Challenges include analysis, capture, data curation, search, sharing, storage, transfer, visualization, querying, updating and information privacy. The term often refers simply to the use of predictive analytics or certain other advanced methods to extract value from data, and seldom to a particular size of data set. Accuracy in big data may lead to more confident decision making, and better decisions can result in greater operational efficiency, cost reduction and reduced risk.’

As we noted at the start of this chapter, that is scary! What you should be thinking about is small data and how relevant pieces of information delivered or used at the right moment can be immensely powerful.

How often have you heard the expressions ‘it’s the little things that count’, or perhaps ‘the death of a thousand cuts’? Customer experience experts and professionals know that it is always the small personal touches that get noticed: the greeting by name, the smile, the ‘please’ and ‘thank you’, the gratis aperitif at the restaurant and the chocolate on the pillow or fresh flowers at the hotel.

These and countless other examples of the ‘little things that matter’ are what create the emotional connections covered earlier in Chapter 3, so aptly summed up by Maya Angelou in the quote highlighting the truism that ‘people will never forget how you made them feel’.

It works in reverse of course: that annoying rattle in the car, the wrong name in communications, slow data connections/websites, long queues at the service desk, surly help on the shop floor, asking for the same information again and again – these will over time erode the customer experience and the customer’s trust in brands that fail to see the value in getting the little things right!

Data from the customer interactions is the lifeblood for any organisation to view, understand and optimise the customer experience both remotely and on the front line! In the same way that customer experience experts understand that it’s the little things that count, it’s the small data that can make all the difference.

Of course big data can be used to power huge signposts or even predict customer experience issues and those road signs can then be used to drive corrective actions. Equally, if sufficient thought is put into the experience design then specific small pieces of data can be captured and used to deliver an enhanced customer experience. So data can be used both tactically and strategically – the common theme is that the requirement for that data has been determined by a customer experience. At one level you need to know if you are failing to deliver an expectation in sufficient time to recover the situation; at the other level you are actively collecting data to enable the delivery of a planned experience that is enabled by data.

Remember in both cases knowing about it is one thing, actively doing something about it is another

Consider the following as examples of each of these tactical and strategic influences on customer experience, each using data with a potential connection to experience.

A company issues contracts to clients on a regular basis; by their nature the contracts have a degree of complexity and the language used can be confusing and open to interpretation. The company regularly has client queries – read anxiety and stress for the client, meaning a degrading of their experience – about a particular clause. The company takes no action to mitigate this issue even though the data is available to show or predict that this will occur and it will inevitably have a negative impact on the client relationship. The cost of highlighting and explaining this clause in plain English perhaps using an example is minimal; the upside of saying ‘can I just point out this [and maybe a couple of other specifics] clause and explain what this actually means as even I was confused when I read it’ is significant in terms of trust.

At the strategic level consider the company behind the computer game Destiny. This game had an amazing $500 million investment plan before a game was ever sold. The game’s producer Activision Blizzard said, ‘of course we have very precise and well modelled projections of what we think the audience size is, who we think the game will or could appeal to if we market it correctly’. The game apparently has a multi-year rollout plan and data is at the heart of that plan and customer experience. How do I know this? Because my son is a Destiny player. Imagine how he felt when the latest release of the game was due and he was sent a link to a very high definition video clip. The clip used his name, spoke directly to him and used his real playing data. The level of engagement was amazing, his experience exceeded expectations. The company set out to collect very specific pieces of in-game data – they knew or predicted what the player would be interested in seeing but with a specific experiential outcome in mind. The data was collected over a period of months and then USED to great effect.

Remember in each of these examples it is not big data that is the answer, it is small, highly targeted pieces of data that can be used

It is not about deep data analysis to predict behaviour, it is about actively designing experiences and then applying data to enable the delivery. Cumulatively making lots of little changes using very specific pieces of data will aggregate to a bigger impact.

• Which of these examples demonstrates a company that uses data to improve the customer experience?
• What data do you collect on new customers?
• Do you design experiences and then apply data, or do data analysts prompt change in your company?
• Consider your business: what individual pieces of data do you need in order to improve or define your critical customer experiences?

The message is that the way to discover what you need is to design an experience from a customer perspective and then define what data you need to bring that to life.

What have we as customers experienced to date?

I remember a time when data about our customers and prospects was in short supply! Prior to the world of online communication – yes, there was one! – data about people, their names and addresses connected to that ‘offline’ ID, their attitudes, behaviours, preferences and intentions were subject to the laws of supply and demand and therefore relatively difficult and expensive to collect or buy, maintain and leverage in a privacy-compliant way!

This obviously became commoditised over time, but bad marketing practices and rogue customer data sources were common and the governance around that ‘offline’ customer data in terms of its accuracy, recency and levels of consent for marketing purposes was – shall we say – a little looser than it is today. This left room for some industries to become renowned for exploiting both those bad practices and rogue data, and in the process, contributing to a less than healthy reputation for direct marketing in the eyes of the consumer.

Remember that customers have a predisposition to mistrust companies that ask them for data based on a legacy of bad practices

Since that time, as we all know too well, the worlds of data technology and digital communications have collided and triggered the ‘big bang’ in terms of our data universe. That ‘big data’ universe is expanding at an ever-increasing rate as more of ‘how’ we as customers think and ‘what’ we actually do with our lives on a day-to-day basis – via mobile, apps, the internet of things, cars – becomes digitally connected.

Brands are strung out along a fairly long line in the process of moving down the path from direct marketing to data-driven marketing and customer experience with some barely off the starting line, but the reputational ‘hangover’ from the irresponsible use of data in earlier days of direct marketing still persists!

Consequently, as customer experience practitioners we have seen policy and legislation continue to tighten around data protection, privacy and data governance with the financial and reputational penalties and costs for breaking those rules becoming ever greater and customers becoming more aware of their rights under those rules.

Remember you should know the rules around data, so go online and check

For example, if you search for European Regulation on Data Protection you will find simple explanations of key shifts in policy. These regulations tend to have a ripple effect so you can expect similar changes in due course around the world.

The rise of this regulation does present you with an opportunity – this will be raising the data issue to the board level and it will begin to appear on risk registers: take advantage of that high profile.

It has now become and continues to grow as a significant source of organisational stress, marketing weakness and fundamentally a barrier to optimal customer experience for almost all organisations as they struggle to understand what they can and can’t do in a legal and privacy-compliant way to leverage their customer knowledge, insight and awareness to engage the right customers and prospects, with the right message, at the right time, through the right channel and with the right tone of voice to deliver the best possible customer and prospect experience.

Remember, the answer is simple in principle – deliver a customer experience where the customer sees real value from how you use the data that they share with you and they will keep interacting/sharing that data and their consent for you to use it!

To balance my simple customer experience expert view of how you can use data, I asked Jonathan Carter to outline how that translates into a data and technology world – to give companies a chance to operationalise their data to help create the positive customer experiences that we design.