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The ROI of customer data

(Image credit: Image source: Shutterstock/Carlos Amarillo)

Why is customer data so important today?

Whether your organisation is online or offline, B2B or B2C, a startup or a long-standing corporation, the common truth in today's digital world is that you can’t craft an effective customer experience if you don’t truly understand your customers. And you can't understand your customers if you don't have the right mix of data to give you the insight into their behaviours, needs and challenges.

Netflix knows this. Amazon knows this. Facebook knows this.

These billion dollar empires are built on vast amounts of user data, but their success is based on a relentless need to get smarter and faster about interpreting that data. That's what enables them to provide their services and make recommendations to their users in real-time, taking account of their behaviour, preferences, history and context to deliver a great experience.

And because the last best experience that anyone has anywhere, becomes the minimum expectation for the experience they want everywhere, how smart organisations are at using the data they capture has never been more important.

How can U.K. organizations effectively collect and organize customer data?

The explosion of connected devices - smartphones, digital assistants, wearables or biometrics - means that data can be collected across multiple touchpoints in the customer journey in ways that have never been possible.

We’re on the cusp of being able to deliver hyper-personalised experiences for customers where algorithms analyse data in real time and then generate unique experiences, messaging and media that fully reflect things like where an individual is in a customer journey, where they are in the real world, who they are with and their current state of mind.

This gives organisations a huge opportunity to gain competitive advantage, not just through hyper-personalised customer experiences, but also through surfacing trends, operational efficiencies, competitive benchmarking and other valuable insights hidden in the data.

To turn customer data into business value, organisations need robust data management strategies, procedures, and processes - and because most customer data is generated in the cloud, it makes sense to have a cloud-based infrastructure that is flexible and agile enough to share and update customer touchpoints in real time.

AI can be trained to make sense of data from all these different sources, organising it in a way that identifies patterns and areas of opportunity and impact, and supports analysts and decision makers to deliver world-class experiences.

What are the potential challenges in collecting and leveraging customer data?

Data comes in many shapes and sizes, not all of which are electronic. Legal, insurance and healthcare organisations still manage high volumes of their data in paper formats, creating challenges for workflows and inhibiting their ability to deliver customer experiences with real-time, contextual responses.

Perhaps this paper-based reality somewhat explains why nearly 70 percent of organisations around the world have experienced a data breach of some kind. Traditional industries have always been product focused and process driven - slow and steady. Disruptors are customer focused and service driven, relying on data to fuel their scale.

Maybe that's why - even with high profile legislative responses to issues around data integrity and privacy like GDPR - 38 percent of consumers in the U.K. still aren’t confident in sharing their data with businesses. This will only increase as more connected devices make it possible to literally collect data anywhere, at anytime, from biometrics and voice inputs to heart rhythms and skin signatures.

Some organisations are betting that technologies like blockchain will go a long way in resolving these fears and provide a competitive advantage at the same time. But in the meantime, leveraging data for actionable insights is a real and present issue for organisations, simply because data scientists, AI specialists and CX experts are so hard to find and expensive to recruit.

How will customer data collection evolve in the future?

Technology has become more natural and ambient, and the space between humans and technology is occupied by interfaces. And it's the growth and diversity of these interfaces - keyboard, voice, tapping, gestures, signals, biometrics - that presents challenges for organisations seeking to collect and use their customers' data.

Right now, humans adapt to technology, but technologists are working to change the dynamic so that technology adapts to us. We’re building intelligence into everything - fridges, cars, toilets - so that our technology can start to understand the context of the tasks in our daily routines, and learn how to serve us better and improve our lives.

In the U.S., Walmart is working on a shopping cart that takes a baseline of your information when you grip the handle. It tracks data like heart rate and pressure on the handle through the customer journey and if your heart starts racing or you start to sweat, it sees this an indication that you might be stressed out and directs a Walmart employee to come and find you and see if they can help. What's interesting about developments like this is that there's no actual cognitive input.

I think organisations will begin to see the benefits of matching their data with other sources to optimise their services and deliver more complete experiences. For example, the Apple Watch 4 ships with an ECG monitor and fall detection, so it can detect if a vulnerable person has fallen over or become unwell, and alert relatives or employers. This signals a move towards biometric health insurance, and this sort of dynamic real-time model will replicate across industries.

How can organizations achieve effective ROI by leveraging customer data moving forward?

The more an organisation can learn and personalise an individual customer’s experience, the more the organisation can tailor the brand to its customers.

Consumers demand intelligent channels powered by AI, infused with context from data, and augmented by products and services - all supported through human interaction when it's needed.

Organisations have been investing significant amounts of time and money trying to capture and interpret data to surface user intent (attribution), but AI has reached a maturity where it can now do that work for them - especially in natural language processing (NLP). NLP opens a window that allows people to tell organisations what they are looking for in a way that delivers the organisation a whole new level of insight into intent, allowing them to provide a customer with the shortest route and the least amount of friction.

That represents not only a significant step in the relationship between humans and technology, but also a huge opportunity for return on investment.

Cynan Clucas, Consulting Studio, Globant (opens in new tab)
Image source: Shutterstock/Carlos Amarillo

Cynan Clucas, Consulting Studio at Globant, a digitally-native technology services company.