In the past couple of years, the retail industry has been going through a paradigm shift. Most retailers today understand the need to monitor in-store analytics and are investing in various analytics platforms based on video cameras, beacons, thermal imaging, and 3D sensors. However, the data that is captured using these platforms is aggregated data that might not necessarily prove to be actionable. This is where appropriate in-store analytics come into the picture. Companies in the retail industry can make use of the latest analytics trends to understand their customers better. By understanding customer behavior using data insights from different channels, retailers can better execute marketing campaigns and personalize the shopping experience for their customers. Let’s take a look at the analytics trends in the retail industry that 2018 has in store for us:
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Rise of Wi-fi Analytics Platforms
Retailers will not be able to differentiate a first-time visitor, repeat visitor, or a loyalty member just by looking at them. An appropriate in-store wi-fi analytics platform can provide such precision. Using such a platform, retailers can identify each customer by asking them to opt-in via captive portal using their name, email, phone or loyalty number. This will provide companies in the retail industry with more accurate and authentic details of their customers. In fact, according to research experts, analytics trends such as wi-fi analytics are expected to rise from USD 2.94 Billion in 2017 to USD 10.72 Billion by 2022.
Predictive to Prescriptive Analytics
Predictive analytics is widely used in the retail industry for everything ranging from forecasting demand & footfalls to personalizing the customer experience. But with the increasing pressure from competition in the market, pricing remains one of the most significant challenges for retailers. With the help of analytics trends like predictive analytics, companies can overcome this challenge. Prescriptive analytics provides the best course of action for any given situation. Analyzing different types of data such as product availability, customer trends, resources, time, and geolocation, can help retailers to optimize profit margins and capitalize on available opportunities.
Product Assortment Analytics
Product assortment is one of the key analytics trends that has had a significant amount of impact on in-store conversions and sales. Earlier, retailers who have either neglected or poorly planned their product assortment have seen devastating results on their sales. Product assortment can be used to maximize sales by reviewing shopping patterns to understand correlated products that are bought together. In-store analytics will help players in the retail industry to integrate in-store customer behavioral data with purchase history from POS to discover shopping patterns.
Analytics and Loyalty Programs
Despite the growth of e-commerce in recent times, research suggests that retail stores still account for roughly 94% of the retail sales. This means that a large number of customers are still relying on brick and mortar stores. It also establishes the fact that beyond price discount, customers experience is what drives purchases. By understanding in-store customer behavior, brands are focusing on personalizing customer experiences to drive customer loyalty.