COVID-19 has split the retail world along retail and digital lines. Despite this disruption, we’re seeing many success stories as retailers have adapted to online shopping and socially distant store experiences.

Never has it been more important to drive differentiated omnichannel experiences to meet consumer needs and expectations in today’s landscape. Empowering customer experience (CX) teams with new data technology and analytics tools to unlock the full potential of data, create a single view of customers across all touchpoints, and build better relationships must be top priorities for all retailers.

But it’s easier said than done. To handle the rigors of customer data management today, you need to bring together the teams who are responsible for it at both a strategic and technological level. That means the usual suspects of marketing, sales, analytics, and customer service, but also IT and legal, need to be working together to take down the technological and cultural silos.

For retailers to empower their teams into better data-driven creators, it starts with understanding and optimising every stage of the life cycle of their business’ customer data: the data supply chain. In its most basic form, the data supply chain represents how the data is collected, standardised, transformed and enriched, integrated and ultimately activated to drive action or analysis.

The way your team collects data impacts how you can use it. You can universally collect customer data from any source including websites, mobile applications, IoT devices, kiosks, servers, ­les, and more.

Transparency is key at this first stage. Data integrity, or the combination of data quality and governability, brings together the dual concerns of having usable data that’s protected and auditable. If partnering with a customer data management infrastructure, your chosen vendors should be trusted partners, committed to maintaining transparency in how data is being collected and where it goes.

Standardise and govern
According to research by Splunk and TRUE Global Intelligence, only 45% of the data companies collect end up being usable. The other 55% winds up as “dark data” which they define as “data that they know has been captured but don’t know how to use and data that they’re not even sure with certainty that they have.”

No matter how much data you collect, if it isn’t governed it isn’t usable. In fact, you won’t need all of the data you collect, but knowing what data you need and when will make you a much more agile organisation. With an adaptive framework, you can unlock huge advantages making data easier to use and analyse to respond to new digital business needs.

Transform and enrich
A single piece of data on its own does not provide a complete picture of the customer; in the transform and enrich stage, all of the data you’ve collected is brought together and aligned with a technology that can create individual customer profiles like a Customer Data Platform. This stage is all about making the data fit for your business use cases by performing tasks such as processing, transforming, ingesting, transferring and loading.

To get the most out of your customer data insights, you need to be able to link together data from various sources and to deduplicate data to create a unified, 360-degree view of a customer. That data set may include relevant information about the customers’ profiles, transactions, preferences, and relationships with other suppliers. Retailers need to seek to build such a view to more effectively or efficiently improve the CX, retention, share of wallet, or sales.

This final stage involves deriving insights from this data to inform the next best action or customer interaction. This is followed by sending segments, with instructions for activating them, to executional teams and tools for email campaigns, mobile messaging and advertising, for example.

It’s no secret customers demand real-time personalised experiences with brands now, but retailers can struggle with this when the data supply chain isn’t built on a real-time data foundation. Now, some customer experiences will not be taking place in real-time, but when customer are ready to act, the data needs to be activated in real-time, in the right channel, with the right message.

No single technology will deliver all of these capabilities, but the right customer data management technology infrastructure can. Tealium Predict ML is one such solution to help optimise the data supply chain, enabling marketers to create more intelligent audiences to predict consumer behaviour, improve the customer experience and maximise ROI.

Chris Russell is managing director for Australia and New Zealand at Tealium