How the Retail Industry is Getting Into a
Data Science Mindset

Retailers are using the power of data science, artificial intelligence, machine learning and analytics to be smarter with growth, faster with operations and be more customer centric.

To keep up with the changing consumer habits, market volatility, and competitive dynamics, retailers rely on big data. There is no denying that the pandemic has caused the retail’s great data-driven reset. During the last two covid-stricken years, the retailers realized the importance of digital adoption. To rise in the new tomorrow, which is starkly different and demanding than yesterday, retailers use the power of data science, artificial intelligence, machine learning, and analytics to be smarter with growth, faster with operations, and more customer-centric.

But then, data and its auxiliaries are not just confined to the boundaries of technology. While the universe of data converges around diverse and vast complex raw data sets, it demands a data-first mindset with a favorable organizational culture shift. A shift that helps the retail organizations – otherwise legacy run – connect with evolving customer needs and workforce aspirations. Data culture matters because it propels the executions of data science and steers them towards generating greater business value.

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This chart shows us, among other sectors, where retail stands to apply data science, machine learning, analytics, and AI. Retail is not exactly in the top league but emerging.

To turn data into a competitive advantage, CTOs are strategically investing in the data science while worrying less about immediate P&L and counting more on creating value for customers and employees.

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According to a Deloitte study, 80% of executives surveyed in 2022 plan to make moderate-to-major investments in the digital, supply chain, and make the workforce future-ready. Moreover, the study finds that strategic emphasis on planned financial investment separates the leaders from the laggards.

US retail leaders are acting in these three areas to ride the wave with data and bring it into front and center – albeit in different gears. They are Strengthening data management and analytical capabilities: As consumers have started demanding a fusion of digital and physical union, creating a seamless and simple customer experience at par with other industry sectors is expected to reign. To understand customers and continuously improve their experiences, retailers will synthesize data to tailor a range of products and services. With its Reimagine Retail project, Tommy Hilfiger uses AI to watch future industry trends and improve the design process quicker than competitors. Consequently, designers and partners engaged with Tommy Hilfiger get opportunities to lend their hand in practicing NLP and computer vision in designing personalized clothing. Mark & Spencer, a major multinational retailer analyzes customer sentiment data so they can buy more of what its customer likes and eliminates products that score less well.

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