The era of the ‘always-on’ consumer is in full swing. The sheer amount of customer data available is monumental – by 2020, 20.4 billion connected devices will be in use, and by 2025, the world will have generated 163 zettabytes of data.
For businesses, this data can be used to both refine and enhance the customer experience. Even now, technologies such as artificial intelligence (AI) and machine learning (ML) are helping brands like Burberry improve customer interactions through data insights. Indeed, tech giants such as Google and Apple are increasingly focusing on developing AI systems that will boost consumer engagement in a number of ways.
The age of digital transformation
Many businesses across a wide range of industries are currently undergoing a process of digital transformation. Broadly speaking, this change empowers them to dramatically improve how they operate and how they provide value to their customers, by adopting innovative digital technologies and strategies.
>See also: Digital transformation: business first, technology second
However, companies that want to successfully implement a digital transformation strategy first need to consider how they are planning to retrieve, store and process all the data they have available to them. Technologies such as AI and ML will only ever be as good as the data which fuels them, so businesses need to ensure their focus is on data quality – not quantity.
To successfully digitalise their operations, customers must be placed firmly at the centre of all strategies. A data-driven approach that taps in to the needs and desires of individuals is key to this process.
Customer-centric processes as the driver of transformation
Customer expectations have changed to reflect the digital world in which we now live. Services such as Amazon and Netflix have pioneered a highly personalised approach that has now become a minimum requirement for businesses that want to retain and attract customers.
A one-size-fits-all approach just won’t cut it anymore; all interactions need to be both relevant and timely. The results of such an approach can be incredible – according to research from IBM, 80% of consumers have chosen or recommended a brand that offers a personalised experience.
>See also: Digital transformation: why it matters and how it can be achieved
The potential of technologies such as AI and ML to enable businesses to offer these tailored experiences is huge. A business can use AI to create a seamless experience for a customer, using data to target the right person at the right time with a relevant ad, and even making a sale with the help of a chatbot.
Consumer data can help to predict the individual needs of a customer, as well as frame the interaction in the most effective way. But unless a business actually has its data house in order, it won’t get the results it desires from digital transformation.
And while digital transformation plans provide one incentive for businesses to take control of their data, there is another reason why it is imperative to organise their customer insights.
The General Data Protection Regulation (GDPR) will be implemented in May 2018, and to comply, organisations must have a full handle on how customer data is collected, stored and processed.
How to gain control of your data
Plenty of companies have fallen into the trap of trying to run before they can walk when it comes to customer data. A recent survey of Fortune 1000 business leaders by NewVantage Partners found that only 48.4% of respondents said their firms had achieved measurable benefits as a result of big data initiatives. It’s clear then that investment in technologies designed to improve outcomes could be wasted if businesses are unclear about how best to utilise the data they have at their disposal – or fail to weed out the low-quality data.
>See also: Business metamorphosis: digital transformation of the enterprise
To maintain control of their data, businesses need to audit the information they already have, to put themselves in the best possible position to not only drive an effective digital transformation strategy, but to comply with GDPR.
This is not a straightforward task – there is not only a great deal of data to process, but much of it will also be unstructured and reside in different silos across the organisation. The most effective solution is to bridge data silos, and pull all information into a central space – rather than completely starting over.
The second part of the process is to unify data with the ultimate aim of creating a single, holistic customer view. Again, with much of the existing customer data residing in separate silos, this isn’t simple, but once businesses have built bridges between fragmented information, via a Universal Data Hub for example, they will be able to gain useful insights into customer behaviour and maxmise the potential of new technologies such as AI.
It’s important to understand that there are no shortcuts here – digital transformation processes need to be built on solid foundations. Bringing data storage and utilisation practices up-to-date is the first step on the road to refining and improving businesses processes – as well as moving toward GDPR compliance – so addressing these issues should be a high priority for everyone.
Sourced by Lindsay McEwan, VP and managing director EMEA, Tealium