How New-Age Analytics Can Transform the Retail Industry?

Retail brands can also leverage data-driven frameworks to gather relevant information regarding potential consumer bases across various geographies and devise their expansion strategies accordingly.

To say that the Indian retail industry is thriving would be an understatement. Accounting for more than 10% of the country’s Gross Domestic Product (GDP), and over 8% of the employed workforce, it is the fifth-largest global retail destination in the world.


As per a recent IBEF report, the total consumer expenditure in India stood at USD 1,824 billion in 2017 and is projected to nearly double by 2020 to reach USD 3,600 billion. The online retail segment is also expected to record similar year-on-year increase, growing at a CAGR of 31%.


Numerous factors are responsible for the industry’s rapid growth trajectory. These include rising per capita income, changing lifestyles, and evolving consumerist sensibilities of the urban and semi-urban Indians. Increasing digital connectivity and the fast pace of technological development have also been key catalysts driving the sector’s evolution.


However, despite the pace of its growth, there remain several dormant opportunities and latent markets for the retail sector to capitalize on – and data analytics holds the key to unlocking its full potential.



Opportunities in the Indian retail landscape


  1. More efficient mapping of consumer demand

With numerous foreign brands entering the country and many emerging indigenously, the modern Indian consumer has become extremely brand conscious. Driven by rising incomes and growing consumer purchasing power, this change in consumer mindset is not limited to metropolitan cities alone. Even consumers hailing from semi-urban markets want to keep up-to-date with the latest trends.


The rise of e-commerce has further contributed to the creation of new-age consumers across the country. With the Government of India allowing 100% Foreign Direct Investment (FDI) in the online retail of goods and services, the e-commerce sector has received a major fillip in recent years. This has facilitated increased access to a wider variety of product options for Indian consumers.


These developments have also significantly increased competition in the marketplace. Retail brands looking to thrive in such a rapidly-transforming digital landscape need to read the pulse of its consumer base – and, for that, they need real-time access to enterprise data that may be located in various places. In a market as large, diverse, and fragmented as India, this becomes a major challenge, as most of the relevant information is trapped in individual silos across various online and offline environments.


  1. Driving market penetration beyond tier-1 geographies

Organized retail in India is mostly restricted to tier-1 cities and select tier-2 markets. It is virtually absent in semi-urban and rural areas, even though almost 70% of the country’s population resides in these geographies.


Why is this? Because, to expand into these areas, players in the organized retail space need to make a heavy investment of capital, time, effort, and resources. However, they often don’t have enough data about the target market and its consumers, or are unable to translate the accrued data into actionable insights. It leads to hit-or-miss strategies that can greatly impact profitability – a risk that most retail brands are unwilling to take. As a result, these lucrative markets remain relatively untapped by organized retail.


  1. Disorganized supply chain management

The absence of a robust, data-driven logistics network is another factor which inhibits retail business owners from maximizing their profitability. Most of the data generated at each step of the supply chain is neither digitized nor organized. Thus, the lack of digital optimization is the foremost challenge towards establishing a streamlined and agile distribution channel across the country.


Enter Data Analytics


Today, data has become the axis around which the modern, increasingly digital-first world revolves. Indian retailers can leverage analytics to glean insights on the existing gaps across verticals such as sales, inventory, and service delivery. Retail brands can also leverage data-driven frameworks to gather relevant information regarding potential consumer bases across various geographies and devise their expansion strategies accordingly.


Additionally, geospatial visualization and analytics like QlikGeoAnalytics has a unique ability to provide businesses with a unique view when it comes to decisions like store site selection, store performance and customer behavior analysis. Businesses can then deploy relevant, data-driven decisions to bridge these gaps most effectively.


One question, however, remains: how do retailers make use of their data?


Leveraging new-age analytics to streamline retail data operations


It is no secret that the entry barrier into analytics has historically been high. Traditional analytics processes require specialized data professionals to gather, analyse, and create insights from raw data. Even if we discount the extensive investment of time and resources to set up an in-house data team, there is still the issue of the data funnel that such centralized data operations typically lead to; data queries made by different users are prioritized as per the business requirements and authorization, increasing the time it takes from data aggregation to insight generation to action.


Leading data analytics companies address these challenges by providing retail players with solutions for end-to-end management – from data integration to analysis of their data and then even bringing insights to the business user through a chat interface. This enables retail businesses to extract information from across different silos, formats, and storage environments – including on-premise, cloud, and hybrid – before combining and analyzing it to generate insights. These insights are then embedded into business processes and workflows to be delivered to the end-user at the point of decision.


For instance, LUSH cosmetics in the UK decided to invest in a business intelligence (BI) solution that could deal with multiple data sets, including data sourced from electronic point-of-sale, stock-management and payroll systems. The aim was to make data analytics available to shop-floor staff, as well as to employees in its warehouses and manufacturing divisions, so they could have near real-time information at their fingertips. Once deployed, retail account teams could use Qlik to drill down into the numbers behind sales in each shop. All shop managers and employees on the shop floor could also access reports for regular updates throughout the day, including live access to their sales information and stock position.


Additionally, the manufacturing department used Qlik for stock management, allowing the team to better organize orders between the UK factory in Poole and the shops, as well as monitor the stock position throughout the country. Qlik helped LUSH improve its sourcing of key ingredients from ethical suppliers and maintain freshness in its supply chain, which is a major factor in customer satisfaction and the company’s success. Since deploying the business intelligence solution, LUSH has significantly boosted in-store profitability with user-driven BI and delivered more than £1 million of savings in stock loss. The key to this achievement was combining Qlik with LUSH stock value management systems.


As can be seen from the example above, cutting-edge analytics solutions provide the end-user with contextual information that is relevant to business decision-making. More importantly, they enable business users to self-service their queries. Not only does this drastically bring down the time taken from insight to action but also allows the end-user to freely explore various data combinations in any direction to unlock hidden business value.


In order to realize the Indian retail industry’s full potential, data analytics needs to be made a part of everyday workflows. Each and every business user along the retail value chain needs to become more comfortable with data, whether it is reading, analyzing, working, and arguing with data. Doing so will ensure that the aforementioned data-driven business framework will yield robust dividends. When all of these boxes are checked, the flourishing retail sector can further accelerate its growth trajectory.


The article has been penned down by Ankur Goel, Managing Director, India, Qlik

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