In this global era of rising competition retailers are finding it hard to thrive. But they are getting access to a lot of data from stores, marketing campaigns, vendors and customers. This information is truly acting as a game changer for retail businesses. Data analytics is helping them to harness the power of this data to improve their performance as well as enhance customer experience helping them stay ahead of the competition.
So this growing need of analytics in retail means that 2018 brings with it new trends that can further help retail businesses to evolve. Here are 5 such trends that are likely to be witnessed in the upcoming year:
1. In-Store Analytics
In-Store analytics is the process of finding out useful insights from customer behavioral data. It helps retailers keep a close watch on their customers and help gauge the store performance.
In-store analytics takes into account how many shoppers entered the store, how they moved inside the store and what were the key areas they visited? This digitally available information can help the retail business to establish a connect between customer, store, products and customer buying pattern.
Most retailers are investing in various data collection platforms through video cameras, thermal imaging, 3D Sensors etc.Wifi analytics platform is providing valuable demographic data by asking the customers to opt in via a captive portal. This is expected to revolutionize in-store analytics in 2018.
2. Location analytics
As retail businesses are trying to expand and open new stores they are being confronted with certain questions like:
- Which region/state to expand in?
- Given a set of cities in a selected region, which localities to expand in?
- Within a selected locality, where should the store be opened (colleges/railway stations/hospitals)?
Location analytics is helping retailers to gain insight from the location or geographic component of business data. Through location analytics, retailers can have a more detailed understanding of their businesses-costs, profits, people, customer satisfaction and loyalty etc.
Location analytics can be primarily used to perform the following functions:
- Determine optimal strategic location for opening new retail stores
- Optimize sales and marketing mix
- Improve asset management
- Determine factors affecting new store location selection
- Identify high density, high spend locations for new stores
- Determine customer purchasing patterns
To find out more about Location analytics refer to this blog: www.transorg.com/blog/
3. Omni-Channel Data Integration
Retail businesses are witnessing huge inflow of data from different verticals and channels like supply chain data, customer demographics data, ERP data, Web data, and marketing campaign data. But this huge inflow of information has to be integrated at a single data mart so that the retailer can enjoy a more holistic view of the business. This eventually acts as a launching pad for meaningful retail analytics.
4. IOT for retailers
With the number of connected devices expected to grow exponentially IOT is proving to be an added advantage to retail analytics. With IOT, retail business can understand the context, time and place of the customer to identify what the customer desires thus enabling them to react to their demands instantly. For instance store traffic across different stores can be utilized to understand the entire shopping journey of the buyer. By monitoring the video and foot traffic the system can direct a support staff near the customer to assist him in real time.
5. Anticipating customer sentiment and behavior
Understanding customer’s needs has always been on the top of the priority list for retailers. They have been relying on market research surveys and campaign responses to gauge the customer’s sentiment towards the product and the brand.
But with the advent of social media, many customers talk about the product and the brand on social media handles. Some retailers have also started collecting feedback manually. This information has a huge potential by the virtue of which the business can understand the sentiment of the customers in real time, find out how the customers feel about the products on store shelves, store layouts and advertisements.
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