By Charles Southwood, Regional VP at Denodo
Historically, retail has always centred around the in-store industry and is categorised as singular and transactional. However, as data begins to underpin the retail industry, retailers are discovering that is far from the case in today’s society.
As our lives have become busier in the return to a post COVID climate, convenience and the practicalities that it brings are now embedded amongst consumers. The notion of being able to online shop from the comfort of your own home and via your smart phone has transformed the retail industry. This was unfortunately highlighted when many shops closed their doors and ceased trading during the 2020 and 2021 lockdowns. Despite the complete lifting of restrictions, the way people choose to purchase goods and services has changed forever, with online UK retail sales now valued at some £120 billion.
Ultimately, this is because in the online sphere, every action, reaction and interaction produces data. If utilised successfully, this data can be advantageous to the progression of a business. Insights from the data can be used to improve the customer experience and operational performance, which is something we know is paramount to both the retailer and the consumer. Although the industry has seen many retailors recognise the importance of harnessing data to its maximum potential – there are still many who face challenges adopting data driven practices within the retail sector and are still implementing legacy systems.
The advancement of data in retail
The retail landscape has evolved hugely over the last few years. Despite the expectation of the retail sector operating both in store and online, those in this sector are contending with a long list of different touchpoints. Each of these touchpoints creates a continual stream of data, which – if capitalised upon correctly – is often the difference between a successful retail business and one that struggles to survive.
Despite businesses capitalising on the touchpoints, there is still a large issue at play – namely that they are often siloed. This is highlighted in the fact that when information is taken at the point of sale, it does not always go into the CRM (customer relationship management) system or make its way to the supply chain. This provides issues because there is therefore no unified view of the customer which makes effective analysis extremely difficult and creates a disjointed data set.
Unfortunately, this means that key decision makers are unable to make informed decisions about which strategies are working and which need to be altered – thus hindering strategic operations models within retail businesses. Ultimately, this can affect the longevity of the retail sector and be the deciding factor in whether businesses simply survive, or thrive in their environments.
Traditionally, retailers have tried to overcome this challenge by keeping all data in the same place, copying it first into data warehouses, then data lakes and then cloud environments. The plan was to get everything in one location’ and create one single centre of data gravity.
On the contrary to this, as data sources expand, it is rapidly becoming near enough impossible to continue implementing this methodology. In the wake of IoT, connected devices, and the increasing use of social media – the playing field has changed for retailers dramatically; the vast quantities of data that businesses have immediate daily access to means that companies have to come up with new and innovative ways to manage data.
Looking to the future
If retailers and businesses alike are serious about improving customer experiences, operational efficiencies, and overall economic performance, it is paramount that they 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 – come into play and can support the advancement of the retail sector.
Data fabric is one of the architectural patterns currently being championed by both Gartner and Forrester. Data fabric informs and automates the design, integration, and deployment of data objects, irrespective of where that data comes from or is being stored. This creates a widespread access layer which contains all sorts of data sources. The data fabric then works by utilising modern technologies, like AI and machine learning, and provides retailers with comprehensive insights into areas such as data management and integration as well as deployment patterns, an idea that legacy systems do not currently achieve.
Data virtualisation also works seamlessly within the data fabric. Data virtualisation enables retailers using a data fabric to combine both past and present data sets and provides them with the invaluable insights they need for the business, whilst leaving live data at the point of creation. By adopting data virtualisation within their businesses, retailers can save large amounts of data movement and boost agility in their systems, thus creating lasting developments within the sector.
When looking at this with a consumer lens, many of us enjoy real-time music streaming services like Spotify, Qobuz, Apple Music and Tidal. CD collections and records have largely become redundant within the marketplace and in the age of these streaming sites, consumers get what they want, when they want it. This is what data virtualisation brings to retailers. Through the harnessing of data, virtualisation improves data management and enables real-time access from original sources, only as and when required, like the way streaming websites do too. Ultimately, it removes the need to move and copy data into physical data ‘marts’ and eliminates the need for legacy and outdated IT systems.
In modern retail businesses, it is not possible to centralise the astronomical amount of data that companies obtain into one single location. It is therefore paramount for retail businesses to adopt modern data designs – such as a logical data fabric – and the technologies that underpin them – such as data virtualisation, to tackle the stream of data which these businesses are being presented with, as left untouched, this issue will only intensify as the online retail market continues to boom.
If retailers adopt data virtualisation systems and improve their data management, they will begin to see the benefits right away, with these systems guaranteeing that new insights are easier and quicker to determine. Within the everchanging digital landscape, this adoption could be crucial in not only advancing the position of individual businesses, but also catalysing the entire retail sector to be more efficient within its data management and thus transforming the industry forever.
