How does the retail sector adapt to my ever changing needs?
‘Data! Data! Data! I can’t make bricks without clay!’
– Sir Arthur Conan Doyle
Sir Conan Doyle’s famous fictional detective, Sherlock Holmes, could not form any theories or draw any conclusions until he had sufficient data. Data is the basic building block of everything we do in analytics: the reports we build, the analysis we perform, the decisions we influence, and the optimizations we derive.
Don’t we all wish to have a personal shopping assistant? One who would just understand our whims and likes? A personal shopping chaperone that would assess our needs based on our likes and dislikes. This is the reality in the world of Data Analytics. It is seen as a win-win for the retailer as well as the customer. It enhances the retailer’s perception of gaining necessary ingrowth into the market. It not only improves performance but also is seen as a method of risk management. Data analysis gives us an insight into all the aspects of retail such as customer behavior, sales, geographic performance, Operations, market trends, etc.
Deployment of data analysis techniques in retail has brought a paradigm shift, placing retailers on a roadmap to success. The process of analyzing inventory levels, supply chain, consumer behavioral patterns, demand, sales, ensures retailers gain an edge in the competitive market. Predictive analysis is widely used in the retail industry to assess past data and make projections for the future. Several areas in which predictive analysis is used are:
1. Behavioral analysis – Assessing a customer on their motives, buying patterns, channel usage etc. and using this data to have a more predictable positive outcome for retailers.
2. Price optimization – Dynamic pricing which will help retailers gather data on demand, inventory, competitor’s price etc. Data analytics helps identify mark down optimization which allows retailers to identify when prices should be dropped
3. Demand prediction / Trend forecast – Forecasting the trends in the industry and helping to adjust inventory accordingly. Retailers can also gather data from social media to understand changing preferences.
4. Operations and supply chain – Seamless supply chain and operations can be guaranteed with data analytics. Region wise sales projections and demand analysis can allow for assessing trend projections of particular areas.
5. Fraud detection – Retailers can also detect frauds and patterns in purchasing, inventory, accounts payable, sales projections, returns etc. using this technique. If similar patterns are identified, the system can throw up a red flag.
It is therefore pertinent that usage of technology and data driven analysis have become an indispensable factor in the retail industry. It has come to a point of ‘either perform or perish’. We are talking about large volumes of data which need to be gathered, sorted and simulated to make informed and useful decisions.
While all these are forays in the field, there is also a flip side in terms of security, privacy etc. The use of neuroscience to analyze cerebral systems to access data provided by emotional and cognitive aspects is a point to be noted. However, then weighing the pros from the cons, it can be rightly said that data aplenty is there with regard to retail industry. It is the manner in which it can be scrutinized through and interpreted that enhances the retailer to take judicious decisions for the success of the industry.
Nu-Pie has worked with global retail giants to design and implement their retail analytics powered strategy formulation and implementation practices. This has had a positive impact our clients Compounded Annual Groth Rate (CAGR) of over 40% and serves as a testimonial to the power retail analytics.
Author: Jerrin Thomas; Co-Author: Benila Jacob