In an industry that is largely driven on brand power and customer sentiments, big data analytics play an immense role in pushing the frontiers in the retail industry. Irrespective of whether the business is large, medium or small and whether it is a brick-and-mortar establishment or an eCommerce venture, the value of customer data cannot be undermined. To survive in times where there are countless choices, it is essential for businesses to up their value by understanding the customer sentiments.
Data Relevance in Retail
Data relevance in retail business cannot be ignored by the simple fact that retail business runs mostly on trends. The latest trends, trends that are repeated and trends that do not work are all a result of reigning customer sentiments. Of course, the trend-setters also come from the retail business itself. However, all this is data that is much essential for finalising the business goals for the moment. Considering trends can be short, medium or long term, data gets recycled at a faster rate in the retail industry.
The Omni-Channel Challenges
As retail business takes a turn for omni-channel operations, it is important to understand consumer behaviour across the different channels. Customers interact with a brand via brick-and-mortar stores, eCommerce, social media and websites that review products and services or list them in their directory. These interactions take place across mobile and desktop devices, besides the conventional mediums of televisions, hoardings, newsprints etc.
With volume, the velocity of interaction has also increased and data is expanding rapidly due to a combination of these factors. To top it all, customer expectation for relevance and personalization has also increased largely owing to latest technologies such as beacons, wallets and location-based applications.
Comprehending Relevant Data
It is not just about finding effective data, but also about deriving actionable insights that will drive brand differentiation and profitability. It is not necessarily big data but small data is equally relevant for deriving behavioural data and actionable insights if read correctly. What is essential is to mine and organize data through targeting, personalized communications and much planning.
The future of retail lies in delivering personalized services to customers and the tools for deriving this personal data is already at hand. In order to capitalise on this data it is not enough to get it fast, but to act upon it just as quickly. Without effective control over data, it is not possible to respond quickly.
Data Sources and the Scope for Analysis
Transactional data from off-the-counter purchases, loyalty programs and in-store queries have been available for a while with retailers and the data has been channelized effectively by most of them. For instance, UKS major supermarket chain Tesco has been using the data derived from the loyalty programme to create personalized offers for its customers. So, if in a month the number of baby products purchased by a customer suddenly swings upward steeply, they send them targeted offers on baby products such as diapers and baby care.
Multiple channels of approaching the retailer have added a lot of advantage but also made the data complex as the approach for every channel varies. Having an efficient system for collating, sorting and comprehend these vast and complex data sets is highly essential for retail success.
