How can Retail and E-commerce Benefit from Data Science

The global retail analytics market is expected to grow by $5.1 billion by 2022 to an estimated $8.64 billion. This extraordinary growth will largely be driven by the use of data science in disrupting the retail sector –  changing the way retailers do business online and offline, from the way stores organise their layout to hyper-targeted and optimised pricing and offers.

Data Rich Retail

In the UK alone, the retail sector is worth more than £368bn, employs 2.3 million people and accounts for 1/3 of all consumer spending. Retail generates huge amounts of highly valuable data that businesses are only recently starting to utilise. However, recent reports suggest that the sector is struggling, due to changing spending habits and shifting shopping trends. In most cases these risks can be averted or mitigated by using data science techniques. To do this, retailers require the innovative power of data skills.

“Harnessing all of data and turning it into actionable information requires a specific skillset and expertise that hasn’t been required until now… You need to understand how to analyse the data, but also the business processes and needs … This person is critical for not only collecting, managing and analysing supply chain data, but also for garnering advanced predictive analytics to help executives make more intuitive, accurate and reliable [decisions], allowing them to deliver goods and services ahead of the competition.” – Richard Howells, Global Vice President Of Extended Supply Chain at SAP.”

 This is why data science is the hottest job in retail right now – it’s a role that offers the greatest potential for significant improvements.

So How Is Data Science Disrupting Retail?

Some forward-thinking retailers are already discovering that data science is revolutionising retail, by ensuring more positive consumer experiences, promoting more efficient future transaction options and securing cost-effective ordering and shipment processes for firms. Through the adoption of machine learning and deep learning algorithms, retailers are better placed to determine the needs and wants of their customers and predictions for forthcoming orders. All this contributes to a positive impact on the bottom line.

A Gartner study, suggests that AI solutions employed by retail companies might autonomously manage as high as 85% of all customer interactions. Micro-segmentation, for example, is an approach that had been utilised to a lesser degree throughout retail for some time, but its use is expected to increase rapidly. Segmentation supports functions including pricing, stock management, product sorting and promotions. The natural evolution of this approach is that retailers can remove the guesswork from operational planning and develop and measure multiple what-if scenarios for various customer segments, identifying those more likely to improve operational functions such as planning, decision-making, and execution.

Utilising highly valuable data that is accessible from Wi-Fi, beacons, and RFID tags support retailers in offering more effective and rewarding sales and customer experiences. From managing stock levels more precisely to assessing customer behaviour and implementing more successful marketing plans, IoT can secure improved activity throughout the whole retail business. We are just scratching the surface here.

Data Science Practice – Ted Baker

At Pivigo, we recently worked with Ted Baker deploying machine learning to help predict and personalise consumer shopping habits. Recognising that there was value in the wealth of data from their online base, Ted Baker’s marketing team had a number of challenges for our data scientists to solve, relating to various marketing channels, profitability, customer engagement and how machine learning might enhance their business. Our team of four data scientists concluded that customers who made at least three purchases on Ted Baker’s site were likely to visit five times more prior to making the purchase than new customers. However, the existing clients spent up to 33% more on return visits – highlighting that Ted Baker can target the existing customer base using an improved recommendation system which would reduce browsing time and increase sales frequency.

A machine learning model was designed that would predict, for any given week, the return on investment for marketing channels given the percentage of the total weekly marketing budget spent on it. A second model was then used to predict the overall return on investment.

Other retail brands who are early adopters include US glasses retailer Warby Parker, who are investing heavily in data science on ways to help it optimise a wide range of operational challenges, from where to locate stores, to how to create hyper-targeted offers for customers. The future development of the business currently relies on the success of the newest technological venture – optometry tests carried out at home. By way of eliminating the need for customers to seek sight tests from a competitor, Warby Parker is investing in technology that will measure how far a user is from the screen displaying the actual test. The team considered everything from tape measures to sonar before hitting on a clever hack in which a phone’s camera determines distance by measuring the size of objects on the computer screen–a solution for which Warby was granted a patent last year.

Global Retail Data Science

The Al Futtaim Group in the UAE believes the future is all about unlocking value in data and is investing heavily in data scientists. Retail groups like Al Futtaim are looking at companies like Alibaba and Amazon and correctly identifying that a key reason for their phenomenal success is their ability to analyse data and get a very deep, clear understanding of their customers, products and supply chains.

In Australia, startup Brosa is aiming to disrupt the furniture retail market by using machine learning and data science to plan for and meet future demand, whilst gathering more information about its products. Brosa has just won a series B round worth USD 3.9million, a big vote of confidence that this approach is seen as the future of retail.

Forward Thinkers – Get In Touch

With reduced margins and increasing competition, the retail sector globally needs to look for ways of creating better service, more efficiently and at a lower cost. Major names in a variety of sectors are recognising that data science holds the key to higher profit margins and a better customer experience. Forward-thinking retailers in the UK and around the world, are bucking the trend of challenging trading conditions through innovative thinking and quick implementation of data science skills within their workforce. To find out how Pivigo can help you add value to your retail business, get in touch.

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