Big Data Analytics for Big Retail Success

Big Data in Retail

With growing Internet penetration worldwide, the adoption of connected mobile devices, such as mobile phones and tablets, is increasing at a rapid pace. As per a report from the International Telecommunication Union, the number of Internet users worldwide rose from 738 million in 2000 to 3.2 billion in 2015. That is more than 43% of the world’s population crawling through the Interweb. The use of data-intensive technologies has also increased among enterprises and general consumers. Data generation has, therefore, been increasing at an exponential rate. According to IBM, 2.5 quintillion bytes of data is generated every day. Ben Walker, a marketing executive at Vouchercloud, put this in perspective; 10 million Blu-ray discs would be required to store 2.5 quintillion bytes of data. If these discs are stacked, they would scale four times the height of the Eiffel Tower.

Evolution of Data and the Role of Analytics

Enterprises deal with enormous datasets on a daily basis. Over the years, data has evolved significantly in terms of volume, velocity, and type. Laurie Miles, analytics head at SAS, pointed out that around 75% of the data generated is unstructured in nature. Analytics helps enterprises organize and segregate this data. This enables enterprises to derive meaning and useful information such as trends and patterns.

Akin to other industries, the retail space is witnessing a data deluge brought about mostly by the emergence of e-commerce and the increased use of connected devices and apps. Retailers are using converged and hyper-converged infrastructures for storing data. Compared to traditional storage systems, these infrastructures offer benefits pertinent to flexibility, scalability, cost savings. The use of advanced storage systems in tandem with analytics is setting retailers on the path to achieving digital dominance. Retailers use analytics platforms and solutions to leverage customer insights. Analytics sheds light on customer behaviour and tendencies by extracting metrics such as frequency of purchase, the average amount spent in transactions, conversion rate, the amount spent on specific product types, etc.

Retail Analytics Market Overview

Factors such as urbanization, rising income, and changing consumer preferences are driving the retail sector. The Indian retail market stood at $600 billion in 2015 and is likely to reach $1 trillion by 2020 (source: However, the adoption of analytics solutions in this fast-growing Indian market is slower compared to that in the western counterparts. Retailers in regions like North America and Europe are miles ahead as they were the early adopters of analytics. Nonetheless, Indian retailers are catching up, albeit slowly, with retailers like Shoppers Stop, Croma Retail, and Babyoye using analytics solutions to improve customer experience and drive sales.

The global retail analytics market was worth $2.25 billion in 2015 and will likely reach $7.47 billion by 2022 with a CAGR of 18.7% (source: Stratistics MRC).

Retail Analytics: Use Cases (India)

Big Data in Retail
Image Credit:

Shoppers Stop leveraged big data analytics through First Citizen, its loyalty program. First Citizen enabled the retailer to study the buying patterns of its customers. Based on the findings and insights, the retailer created targeted promotions for trousers, which resulted in an additional sales revenue of ₹10 crores in a span of three weeks.

Croma Retail was facing a challenge when its large and diverse product portfolio was ironically causing a decline in conversion rates. The decline was due to the fact that customers were having trouble finding the products that they needed. Also, new products were not getting noticed unless they were promoted manually. Therefore, Croma adopted analytics solutions not only to study historical data but also to understand customer intent in real time. The solutions enabled the retailer’s e-commerce team to perceive the changing preferences and needs of shoppers. The solutions also allowed for efficient product recommendations and seamless website navigation, thereby eliminating the need to promote products manually.  After six months of adopting analytics, Croma witnessed an increase in revenue share, conversion rate, and orders with recommendations by 24.9%, 217%, and 28.8%, respectively (source:

Significance of Customer Intelligence & Predictive Analytics

According to Dean Abott, the president of Abott Analytics, customer intelligence and predictive analytics are critical to the growth of the retail industry. Customer intelligence is the process of generating contextualized customer data. Retailers, through predictive analytics, use this data to understand customer intent and determine future customer behaviour.  Also, such insights help retailers send targeted advertisements and relevant offers to their customers, thereby improving customer engagement and retention.

Retail Analytics Spectrum

Retail industry experts are working in conjunction with data scientists and predictive modelers to achieve marketing goals. Experts in the retail domain help data scientists and modelers understand as to what kind of data needs to be prioritized and focussed on. The predictive modelers then use the relevant data to derive insights that would contribute to crucial marketing decisions.

BRIDGEi2i’s retail analytics solutions help retailers leverage the power of data to derive insights on customer behavior and develop a personalized customer-centric approach to product, marketing, pricing and channel strategy. Recently, BRIDGEi2i helped a US-based high-end fashion retailer identify high-value customers, enhance customer experience through touch point personalization, and maximize customer lifetime value. To know more, read the complete case study here.

Retail Analytics: A Game Changer

Clearly, big data analytics serves as a powerful marketing tool, and its growing adoption bodes well for the overall retail industry. The convergence of technology and data is allowing for digital dominance with the implementation of digital marketing strategies like marketing automation and user-centric content marketing. In the era of big data, retailers are not only staying afloat in the data deluge but also finding success owing to improved demand forecasting capabilities, smart merchandising decisions, increased operational efficiency, valuable social media insights, and of course, skyrocketing sales figures. Analytics is here to stay indeed, and it will only grow as more enterprises worldwide learn of its seemingly boundless potential.

About BRIDGEi2i: BRIDGEi2i’s Retail Analytics solutions have been carefully developed with a combination of extensive industry expertise, advanced analytics capabilities, and proprietary technology accelerators. These solutions have helped retailers solve critical business problems around customer experience, marketing effectiveness, operational effectiveness, pricing and ROI enhancement, to name a few. To know more BRIDGEi2i’s Retail focus visit BRIDGEi2i Retail Analytics page.