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Big Data is being used in a big way in the retail industry where data is getting churned at every step; right from when the customer first associates him/herself with the brand by reading the label to the point of checkout and even after the sale has been completed. Retail industry is all about establishing a brand image to maintain customer loyalty. In the face of the fickle consumer behaviour in the digital marketing era, it becomes imperative to have a strong foundation established by solid data.
Where is big data captured?
Big data is captured at the point of sale (POS), through sales receipts and payment gateways, from promotions via loyalty cards and click through rates and there are other modes such as direct surveys, social media interactions etc.
How to decipher it?
Retail business generates data from millions of sources and the size may run up in terabytes depending on the size of the business. It becomes imperative for the data to be categorized and viewed in bits to be able to assess its veracity and capture trends. If big data is analyzed correctly, then it can make a lot of difference to the business sales. Here are a few ways big data can be used:
- POS data can be used for identifying busy and lean times, make staffing decisions accordingly and ascertain open and close times.
- Inventory data are the predominant indicators of what goods are in great demand, which need to be heavily discounted and what goods can be discontinued.
- Website traffic analysis gives information on where customers are hearing about your store, what online channels to focus your advertising on and thus focus your marketing budget and time on the right target.
- Email marketing analytics tell you how many of the recipients opened the email and based on the feedback change the content, email delivery time or recipients.
Multiple channels for sale
As the channels for sales have multiplied, so has the complexity in data. Apart from brick-and-mortar stores and eCommerce websites, sales are largely being made on mobile devices on applications and mobile websites. Here, it becomes important to study which mobile platforms will be suitable for launching the app, where majority of the sales made are and also managing in-app permissions.
Spotting the window-shoppers
Big Data technologies such as Hadoop have in-built systems for tracking window shoppers by capturing unstructured data such as the customer’s movement through the store via an internet storefront. In conjunction with business intelligence tools, these technologies ascertain loss of sales through such avenues.
Optimizing the Store Structure
An actual correlation between web traffic and sales can be made to come at the exact figure of the sales and profitability. Many stores are using the data for better layout planning, product placement and investigating why the traffic is not getting converted. The bar code and RFID system allow us to track the product sales in real time and every delivery can be visualized when products from online shopping are being delivered.
There is a burning need for managing privacy issues, however, in the meanwhile, the accrued benefits to the retail industry cannot be denied, in spite of the increased competition.