Retail is a very big, competitive space. It is the sector that is facing lots of challenges in recent times due to shrinkage in demand and decreasing footfalls. The users are addicted to online shopping and are buying everything, literally, online.
This has made it important for the retailers to include such features in their outlets that can compel the buyers to come out of their comfortable spaces and find the second most comforting space for buying the things of need or entertainment.
Data science is the tool for developing business intelligence and its use in retail is changing its scene for the better. Taking cues from the conditions prevalent, listed here are the top retail analytics trends of 2020.
Using Camera Feeds To Find Ways To Drive Customer Behavior
All retail stores have one thing in common, i.e. a CCTV camera recording various portions of the store. The camera can be loaded with highly intelligent solutions like object recognition tools that can help the owner find very important information like:
- Items in high demand (found from depleting numbers at shelves)
- Reorder level setting and adjustments
- Objects’ storage arrangement if compatible with customers’ average height, etc.
- Consumer attitude towards the objects of various groups
These important information pieces are proving to be quite helpful in managing retail stores according to the customer’s expectations. These solutions can help in serving more customers per day by reducing the buying time with the help of shopping experience enhancement tools.
The camera feed is also going to allow the advertisers to gauge the impact of their promotional materials on shoppers. They can study the lingering time that customers spend on an ad they see. The visibility of ads and related customer responses can also be helpful in finding better promotional strategies.
Another most important use of camera feed data analytics will be in managing the queues at billing counters. Retail researchers can find the times when the queues are likely to go longest and deploy staff and counters accordingly. It helps stop opt-outs caused by the waiting time in billing queues.
Use Of Styling Suggestions For Cloth Shoppers
Let’s take a look at some company’s statistics that show how personalized styling suggestions creation has encouraged people to buy more from a particular type of dress seller.
- Stitch fix – This company is doing the service of home delivery of dresses after stitching them as per the body type of the customers. The company is making use of about 100 data scientists who use intelligent tools to find the preferences of the customers based on the bodily measurements that they provide.
Thus, it offers the best example of the use of data science for retail as the algorithmic models tell about the size part and styling intelligence takes care of the type of dresses that are most likely to get picked up.
- Mada: With a team size of about 2,600 brand partners, this multi-brand dress seller makes use of a style quiz to gather customer preference data and analyze it. The company may have registered good growth in terms of sales, but the sanctity of the quiz due to the possibility of untrue answers still remains questionable.
- Having said that, cloth retail space making use of data analysis is likely to score better in terms of delivery of the right options in the coming times.
Use Of Location Intelligence For Opening A New Store Or Making Changes In The Existing Store
Opening a store is a big decision. Location intelligence can help make the best decisions pertaining to launch. The data collection and analytics tool may tell the business owner about the probable number of footfalls. Purchasing attitude or window-shopping attitude analysis also helps understanding if the footfall is actually going to help or not.
Another important use of location intelligence can be in the food retail space. The data analysts can help in finding how menu options can drive customers numbers towards an outlet. They can also help in finding if the seating arrangement and ambiance and pamphlets, etc. are going to contribute to the outlet’s popularity or not.
So, these are some of the business intelligence use trends that recently shaped up the retail space and are likely to continue to rule in the year 2020 too.