Predictive analytics tools transform customer journey

With consumer expectations evolving too fast for traditional marketing methods to keep up, brands are turning to predictive analytics to pre-empt what customers want based on their digital journey

In the increasingly competitive digital economy, having a good product and an interesting brand narrative are no longer enough to grow a business. Companies must deliver the right message at the right time and on the right channels, and doing that requires an unprecedented understanding of customers’ needs and behaviours.

Achieving such insights can only be achieved with predictive analytics tools, which adopt machine intelligence and data mining with modelling capabilities to enable companies to pre-​empt future customer preferences based on past behaviour.

By analysing the data at a company’s disposal, these kinds of advanced customer analytics tools are increasingly enabling businesses to forecast key business factors such as spikes in demand. Armed with such knowledge, they can more accurately promote content to target audiences to drive repeat business.

Digitalisation has both reshaped and extended the customer experience, while putting power in the hands of the consumer

Coca-​Cola uses an analytics platform to merge, prepare and analyse data from multiple disparate sources and make insights accessible across the organisation. This enables the company to predict which components will require maintenance in the near future and what provides the best product mix across different regions.

“One of my biggest wins of late involves the Coca-​Cola Freestyle machine, a touch-​screen fountain that allows users to create their own perfect mixture of flavours,” says Jay Caplan, senior business analytics manager at Coca-​Cola. “Consumers love it because they have the freedom to customise and choose what makes them happy. We love it because we get a level of insight into the Coca-​Cola experience that has never been possible.”

From mobile devices and apps to the internet of things, machine-​learning and artificial intelligence, consumers are now exposed to a vast array of powerful technologies. This has created a new kind of buyer who is constantly connected and expects relevant, convenient and responsive engagement across every interaction with a company.

The smartest brands go beyond cookie-​based advertising and utilise customer-​behaviour tracking to analyse both declared and undeclared user preferences through clicks, mouse movement, inactivity and time spent per page. Customer desires evolve constantly and predictive analytics enables companies to track behavioural changes. In the near future, it is also likely to change how consumers want to pay for products.

“Dynamic pricing, or pricing based on supply, interest or competitor’s availability, is an ageing game,” says Sal Visca, chief technology officer at Elastic Path, which develops an application programming interface-​based commerce platform. “Instead brands have a real opportunity with personalised pricing. What is the buyer doing in real time? Are they a loyal customer? Are they highly engaged and have they added a product to their cart without buying? It looks at these factors and more to find a price that’s more attractive to a buyer in an individual moment.”

Digitalisation has both reshaped and extended the customer experience, while putting power in the hands of the consumer. An abundance of information is right at the fingertips of consumers, which means they can research every individual aspect of a product before deciding on a final purchase. This has resulted in a staggering increase in the interactions between the consumer and supplier.

In sectors such as travel and hospitality, and of course retail, the number of interactions behind a single transaction has more than doubled over the last decade to more than 1,000, according to Huw Owen at engagement database company Couchbase.

“Where once holidaymakers browsed brochures in travel agents to book their summer getaway, they now head online to search every combination of destination, flight and hotel to identify what’s right for them,” he says. “In the process, they’ll share information about their preferences, which is used to further personalise offerings to secure a sale.”

Data on customer behaviour enables organisations to craft a much more unique customer journey, one tailored to each individual. Such capabilities represent a significant shift in how businesses engage with customers.

Previously, customer experience was transactional; just 15 years ago, simply having a website and the ability to process payments was seen as the pinnacle of customer engagement. By gathering a plethora of data, brands can now build a 360-​degree view of the customer to provide more personalised experiences and anticipate customer needs.

“The sheer volume of this data, the increase in interactions, the need for real-​time analytics and the momentum as more and more people shop online mean companies must modernise how and where they store and manage data,” says Mr Owen. “Organisations that adopt databases designed to enable customer engagement will be the ones best positioned to build truly fantastic customer journeys.”

Indeed, the opportunities relating to predictive analytics are huge, but with underlying technologies such as artificial intelligence and machine-​learning relying heavily on data, it’s crucial accuracy is maintained. Intelligent predictions drive better business outcomes, but when they’re inaccurate because the data they used was insufficient, this can result in biased decision-​making. It’s therefore paramount that organisations have their data in a clean, accurate and organised state before embracing advanced analytics tools.