It goes without saying (one hopes!) that our customers are all living, breathing humans with expectations, feelings and long memories, their needs become more sophisticated and demand to be treated as individuals. They expect to be contextually understood. They want a quick response to their needs. They expect us to anticipate those needs, and in many cases they even expect us to propose actions suiting their future needs (even if they don’t yet know what those needs might be).

As marketers we must pay close attention to all this and understand and act upon following stages of the customer experience:

what they expect it to be (Anticipation)
what they feel during it (Interaction)
what they remember about it (Recollection)

Think of it as gift giving, where we are the ones giving the gift, and our customers are the receivers. They might spend weeks if not months thinking about, researching and waiting for the gift in question (anticipation). They spend a very short time unwrapping; hopefully much longer enjoying the gift (interaction). And then, if we the givers, have gotten it right, they reflect on how thoughtful we were and are intrigued by how it was that we knew what they wanted, and when to give it (recollection).

This last point: knowing the right gift and when to give it, is the holy grail of creating positive, long-lasting customer experience.

To know the customer is to deliver for the customer.

Underlying that positive customer experience is the creation and management of a customer view. Please note that this is not the fallacy better known as the “Single View of the Customer”; instead it is a view of consistent perspectives based on a commonly used set of core data that identifies who the customer is, synchronised across all touchpoints where customer data is collected and used, quality controlled proactively through its lifecycle - ‘cradle to grave’.

The data can be collected from a variety of sources, structures and stores, combined through a diverse set of approaches and technologies to create the view, be it

  • an enterprise scale MDM solution
  • an operational data warehouse, store or cache
  • a federated view where the underlying data remains in situ
  • a slice of the (Big) Data lake
  • an integrated marketing data mart

Though each have their merits, each also has its significant challenges and constraints, so selection should reflect your data strategy, as well as current and targeted capabilities. At a minimum it must ensure that customer data is matched, governed and enriched with analytical insight, preferably in (near) real-time to ensure it is accurate, valid and timely, and made available in a consumable way i.e. services.

Sprinkle with analytical insight.

Building on a solid platform of data and its management, the insights gained through analysing this data and the application of those insights are the special ingredients for ensuring that a customer experience is as good as it can be. Such insight makes sure the experience is enriched with not just the base facts, but with all appropriate inferences and propensities, and thus demands that significant investment is made in this area.

This goes far beyond technology and Big Data, moving past the hype of “Big is Beautiful” to a more rounded, measured view where the real value is no longer viewed as simply storing large volumes of data in a Hadoop ecosystem, but instead shifts to what can we do with the data, how best to analyse vast and complex data sets to anticipate and deliver this insight into actions driving superior experiences to our customers.

This starts with a cultural change with people working in a more digitally agile manner—very different than the more traditional bricks and mortar culture. Building this new operating model and the underlying team can’t be done overnight. It would be better suited to a blended team of business SME’s, statistical analysts and technologists working together to emphasise strengths and minimise weaknesses, rather than holding out for the mythical Data Scientist ‘unicorn’ as the special gift we are all hoping to find under the tree.

Serve hot, while the customer is still interested.

Now that we have good data, enriched with analytical insight, we need to act quickly (ideally in real-time), to create the best customer experience. This is where it gets difficult, as deep-rooted changes to operations and systems are needed to deliver those positive experiences as we evolve beyond customer-aware and become customer-obsessed.

We want to take action where and when it has most value, usually at the point of interaction (even better if before). This is first enabled through specialised decisioning rules engines which use machine learning to ascertain the correct course of action based on business rules fed with previous customer interactions, customer profile including value, and commercial prioritisation. These next best actions can then be plumbed into all customer touchpoints to provide a truly consistent omni-channel experience.

Then as our decisioning capability matures, we want to combine events and actions into a full event driven architecture, in which each interaction (customer generated or not) is identified and mediated, (complex) patterns are detected, a holistic view is taken (risk, CVM, fraud etc), and the most valuable action is determined through deterministic, predictive and prescriptive analytics.

Loyalty is fragile and fleeting. Build it in.

If we’re lucky, the customer experience will last longer than a single interaction and we will have the opportunity to cultivate the relationship further. One way to ensure this—that a customer comes back and tells other of the great experience they’ve had—is to build loyalty into the interaction from the start.

The usual incentives still apply, but wouldn’t it be better to let the customer in, let them take more control, and let them determine what incentive they actually want and how they want it? We want to encourage customer advocacy and viral promotion, enable customer participation in data product development work or product design itself, and not waste valuable time and effort seeking perfection. Instead we move quickly to adapt to satisfy the customer’s evolving and dynamic needs, thereby creating market opportunity, momentum and increasing market share.

Switch perspectives. What does DNA offer the customer?

Very often businesses look at data, data analytics, decisioning and loyalty programs from the singular perspective of “what do all these tools and capabilities deliver to my business, to my bottom line?” While this is good and necessary, I’d like to suggest here that we switch perspectives and ask the question “What do our new tools and technologies deliver to our customers?”

Switching perspectives in this way is positive for both parties, creating a more empowering and beneficial relationship. The customer is treated as an equal in the experience and their data is used appropriately and openly to mutual advantage. Their preferences and considerations are taken into account, rather than creating an inflexible situation in which they are forced to compromise. Our approach to data collection and use is respectful to customers. This is critical as customer increasingly become aware that it is their data and it has monetary value. In return we must offer fair value in exchange for use of that data. This is true data democratisation, in which customers choose to remain and thrive while gaining value.

A good experience is based on positive perceptions from all parties throughout and so I would suggest we view data collection and analysis not from a negative, intrusive and rather creepy “Big Brother is watching” view, but rather as a more positive and inviting perspective “the better we know you, the better we can serve you.” In practice, and in summary, this looks like:

  • know where they are (customer address validation)
  • know what they are looking to get and, to some degree, what they don’t want (customer preferences, consents, usage patterns)
  • understand past behaviour
  • predict future behaviour
  • deliver the best incentives based on their actual needs and wants
  • deliver incentives at the best time to avoid disappointment (context event driven action)
  • connect each instance to the other, no matter the occasion, the location, the culture (omni-channel)
  • ensure each person feels special (personalisation, segment of one)
  • adapt and respond to the current climate (interaction intelligence)
  • deliver what you promise (end-to-end logistics, customer loyalty)
  • and above all ensure security, privacy and safety of their data and their experience. Trust is hard gained, almost impossible to regain

James Moore

Head of Data Practice at Comet Global Consulting

James has been a chief data architect at Vofafone, T-Mobile UK (precursor to EE) and more recently with Barclays. Prior to that he gained a good grounding in delivery, with experience at consultancies who, specialised in Business Intelligence, CRM and Decisioning, Information management and governance where he undertook a diverse set of roles ranging from business analysis, project manager, design and development, tester and release manager at varying levels of seniority, working on projects across the globe in multiple industries including Financial Services, Telecommmunications, Utilities, Retail and Public Sector. During his working experience of 17 years, a constant thread has been evident, a focus on Data, big or small, starting with how it is collected, its management, how it is understood and made available, assuring it is fit for purpose and made secure, what can and can’t (or shouldn’t) be done with it, ensuring it drives value for our clients and their customers. It is this focus on the Data space that James brings to Comet GC and will bring to this blog, aiming to share insight and spark debate in current and future trends, innovation of data products, services and practices, how-to guides with lessons learnt, tips and tricks to gain and then maintain stakeholder buy-in through successful delivery of what is of value and is sustainable.