How retailers can harness tech to battle the crisis on the high street

It is no secret retailers face a challenging environment on the high street. The national news is frequently awash with stories of store closures and profit warnings, with huge household names including John Lewis, LK Bennett and House of Fraser significantly affected.

The retail sector’s most recent bellwether event, Christmas, offered little respite. Instead, it portrayed a mixed picture. Aldi saw like-for-like sales over the festive period increase 10 per cent, but those fortunes were not mirrored by Mothercare, which saw like-for-like fall 11.4 per cent. Sainsbury’s, Marks & Spencer and Debenhams all saw sales over the Christmas period fall from the year before – and HMV fell into administration for the second time in six years.

Often, the rise of online giants like Amazon is blamed for the woes of bricks and mortar retailers on the high street. The success of these disruptors has led to growing numbers of consumers shopping online, lured in by convenience, lower prices and a more personalised experience. Yet while traditional retailers face a testing environment, those decrying the ‘death’ of retail and our high streets will not necessarily be proved right.

Across the retail sector, greater attention is being given to digital transformation and the possibilities it can bring. A recent survey by IT Pro revealed that 66 per cent of retailers considered digital transformation to be crucial. These attitudes suggest many bricks and mortar retailers are poised to make a step change and adopt technology that can help transform their fortunes. Those that do will find themselves best equipped to fight back against the crisis on the high street.

Digital transformation – where to start?

As high street retailers try to turn the tide against a startling concoction of falling profits and store closures, innovative tech offers a lifeline. Increasingly, retail executives look towards digital transformation as a conduit through which they can ensure their brands remain competitive. They are alive to the rich potential that customer data can hold – and want to implement systems that will allow them to gain transformative business insights. They are intrigued by the ability of machine learning to create accurate sales forecasts and predict future patterns of demand. They can see how new technology can help present a more compelling offering to customers. What they can’t always see, however, is that to realise these aspirations they need to take some formative steps on the road to digital transformation.

For bricks and mortar retailers looking to realise the potential of advanced data analysis and machine learning across their business, the first step is to adopt cloud infrastructure. One reason for this is because the collaboration cloud infrastructure facilitates is key to creating a unified and effective data strategy. To gain meaningful insights from their data, retailers need to have one data set. A data lake that stores data collected across different teams, from which meaningful dashboards and visualisations can be created to uncover genuine business insights. Without this in place, retailers run the risk of holding fragmented data, siloed by the teams that collect it and of limited use to the business as a whole.

It is also important to get the correct infrastructure in place from the start, to make sure it can meet the demands that will be placed upon it. IT infrastructure needs to be able to cope at peak times – handling high volumes of traffic. It also needs to provide storage for vast volumes of data. Investing in the scale of on-premise infrastructure needed to achieve this can be prohibitively expensive. It may also constitute a poor return on investment if it is only required to operate at close to peak capacity occasionally. Maintenance, too, can prove expensive.

In contrast, the flexibility offered by subscription-based cloud infrastructure, such as Google Cloud Platform, allows infrastructure to scale in line with fluctuating patterns of demand. For example, infrastructure can be expanded at peak times, like Black Friday, and then scaled down after automatically. The ability to scale cloud infrastructure alongside periods of peak activity also improves reliability because servers are no longer overwhelmed with high volumes of traffic.

Migrating to cloud infrastructure also offers retailers the ability to simply ‘lift and shift’ their existing IT infrastructure to the cloud. Alternatively, it opens up the possibility for them to work with a cloud services specialist to re-architect the infrastructure to improve its reliability and performance. Taken together, the capabilities afforded by cloud infrastructure provide the essential basis from which the potential data analysis and machine learning can be realised.

The power of data

Once retailers have infrastructure in place to organise and store data in one location, they can uncover key insights and make smart predictions. This can give them a serious competitive edge.

Data analysis can create unique insights into customer behaviour. Differences in purchasing decisions between certain demographics can be uncovered. Seasonal trends can be explored and understood in greater detail than before. The performance of certain products with different audience groups can be better measured. All of this can help retailers become more customer-focussed in their approach – allowing them to be more attuned to customer demands and make better business decisions based on factual insight.

More than this, retailers can use their data to harness the power of machine learning. Not only can the data that retailers hold be analysed, through the implementation of machine learning technology it can be used to accurately predict future behaviour and trends. The predictive powers of machine learning can help them forecast seasonal patterns of demand and sales with a greater degree of accuracy. In turn, this can help retailers make more informed decision on stock purchases, which can allow them to maximise sales and minimise wastage. Machine learning could also help retailers serve more compelling product offerings to customers based on their previous purchasing decisions – driving further revenue and enhancing the customer experience

Combined, these abilities can have transformative effects for retailers. Digital transformation can unlock a huge array of untapped capabilities and provide unique business insights to drive revenue and efficiency.

There is no reason to believe bricks and mortar retailers who harness its potential cannot thrive in the future.

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