Retail was traditionally thought of as an in-store industry, made up of single, over-the-counter transactions. However, today’s retailers find themselves a world away from that image.
Shifting customer expectations and needs have utterly transformed the landscape over the past decade. As convenience has become king, the desire to shop without leaving the home has grown – a movement that has been further exacerbated during the pandemic when many brick-and-mortar shops were forced to close their doors. Even as some semblance of normality returns, the way people choose to purchase goods and services has changed forever, with online UK (United Kingdom) retail sales now valued at some £120 billion.
In this online world, every action, reaction, and interaction produces data. When harnessed effectively, this data becomes the single most valuable asset that any retailer owns. Its insights can be used to drastically improve the customer experience and operational performance at every single level – something that has never been more important than it is in our current competitive landscape. However, whilst many retailers are all too aware of data’s value, for many, there are still some challenges when it comes to truly maximising its potential.
The Evolution of Retail (and Retail Data)
Over the years, the retail landscape has become increasingly complex. Today, as well as being expected to operate both in-store and online, those in this sector are contending with a long list of different touchpoints. Each of these touchpoints is creating a never-ending stream of data, which – if utilised correctly – could be the difference between a retail business thriving or not surviving.
However, there is one big problem; often all these touchpoints are siloed. For example, information taken at the point of sale does not always go into the CRM (customer relationship management) system or make its way to the supply chain. In essence, there is no unified view of the customer which makes any sort of effective analysis extremely difficult. This means that key decision-makers are unable to make informed decisions about which strategies are working and which need to be altered.
For a long time, retailers sought to overcome this challenge by trying to keep all data in the same place, copying it first into data warehouses, then data lakes, and then cloud environments. The mantra was to ‘get everything in one location and create one single centre of data gravity. However, as data sources continue to grow this methodology is becoming impossible to follow. The advent of IoT (Internet of Things), connected devices, and even social media have changed the game for retailers and the sheer amount of data that they have access to each day means that they need to think about new ways to manage it.
The Full Picture
If retailers are to truly improve customer experiences, operational efficiencies, and overall economic performance, they need to have a complete view of the customer, product, supply chain, and competition in real-time. This is where implementing logical data architectures – such as a modern data fabric – can help.
Data fabric is one of the architectural patterns currently being championed by both Gartner and Forrester. It informs and automates the design, integration, and deployment of data objects, regardless of where that data comes from or is being stored. In essence, it creates a universal access layer that contains all sorts of data sources. By utilizing modern technologies – like AI (Artificial Intelligence) and machine learning – data fabric provides retailers with actionable insights and recommendations on data management and integration design as well as deployment patterns.
Of course, there’s no way to talk about data fabric without also mentioning data virtualisation. The two go hand in hand. Data virtualization enables retailers to use data fabric to combine historic and current data sets to give them the insights they need for the business whilst leaving live data at the point of creation. By using data virtualization retailers can save huge amounts of data movement and boost agility.
To put this into perspective, as consumers, many of us now enjoy real-time music streaming services like Spotify, Qobuz, and Tidal. We no longer have to hold collections of CDs or records in the home. We get what we want when we want it each time. This is what data virtualization brings to retailers. Through the abstraction of data, it improves data management and enables real-time access from original sources, only as and when required. It removes the need to move and copy data into physical data marts and eliminates shadow IT.
In modern retail, it is not possible to centralize the never-ending stream of data into a single location. As such, modern data architectures – such as logical data fabric – and the technologies that support them – such as data virtualization – need to be embraced. Through improving data management, retailers can ultimately ensure that new insights are easier and quicker to determine. In our new digital landscape, this could be the key to boosting customer experience and getting ahead of the competition.
The author, Charles Southwood, is Regional VP at Denodo.