Data Analytics Top Trends For Retail In 2017
Retailers are in the midst of difficult times, with ongoing economic uncertainty, the rising power of the consumer, and an ever-growing influx of competitors meaning that they are having to constantly adapt. In the battle for survival, data is proving one of the most effective weapons in their arsenal. By using data properly, retailers can improve operating margins by in excess of 60%. The majority of retailers have realized this. In a survey of retail executives by JDA Software Group and PricewaterhouseCoopers (PwC), 86% of retail executives polled said they plan to increase investment in big data tools over the coming year.
The benefits that can be achieved from data in retail come in many forms. In a recent Forbes Insights report, ‘Data Elevates the Customer Experience: New Ways of Discovering and Applying Customer insights,’ respondents cited the most useful of these as improved revenue generation and lower cost reduction, better understanding of customer buying patterns and behaviors, and accelerated process efficiencies and quality improvements. Another recent study by FICCI, in association with PWC, found that analytics could generate in-depth insights in everything from procurement and supply chain through to sales and marketing.
In 2017, we are set to see retailers again increase their focus and investment in data analytics as they bid to stay ahead of the competition. Here, we’ve looked at some of the trends that data practitioners working in the retail space should be aware of this year.
Forrester estimates that the adoption of location analytics will increase to more than two-thirds of data and analytics decision-makers by the end of 2017, up from less than 50% last year. It can benefit businesses in a variety of ways, but retailers in particular stand to benefit. They can, for example, send geo-targeted push notifications to mobiles, which research has found to be 6-8 times more effective than other notifications. It can also be used in-store to help better understand people’s purchasing behavior. US fashion retailer Nordstrom, for example, has spent millions introducing technologies like sensors and Wi-Fi signals into its stores that enable them to track such information, and as IoT explodes the number of data points is only going to increase. One customer could generate more than 10,000 unique data in a single visit from various sensors placed throughout a store, indicating where they will go, at what point they make the decision to pick up an item, and so forth. This information could be used by the retailer to get an idea of where products and promotions can be placed to maximum effect.
There are a number of firms making this easier. Foursquare, for example, has recently released Foursquare Analytics, which CEO Jeff Glueck claims is ‘kind of the Google Analytics of the world’. It is a dashboard designed to provide retailers and restaurants with greater visibility into location intelligence, changing store visit patterns among demographics, and their share of consumer visits in relation to competitors. Another making waves is Euclid Analytics. Euclid Analytics is a US-based company that uses location analytics to monitor consumer traffic in shops and malls, using WiFi signals from smartphones to track and analyze everything from how many enter a store to how long they stay, and the number of times they return.
The key to enabling a better customer experience in-store is to incorporate as many technologies as possible to collect data, essentially by re-creating the online shopping experience. This is being greatly aided by two emerging technologies set for mass adoption in the coming years – Augmented Reality and IoT.
Augmented reality has been used in store for a number of years.
