Understanding how to use retail data is key to success in today’s accelerated retail landscape. It should come as no surprise that retail analytics continues to play an ever-increasing role in how the industry competes, affecting which businesses enjoy significant growth and which suffer losses.
Data-driven decision-making presents retailers with new opportunities to determine what exactly drives shopper conversion in a rapidly changing industry landscape.
ShopperTrak retail data solutions empower leadership and front-line staff with valuable insights necessary to create momentum in a crowded environment. Leveraging retail data throughout an organization as the driving mechanism for superior performance, agility, and customer-centricity means that retailer departments have access to data-backed decision-making tools.
Here’s how retail analytics benefits:
Even before IoT and Big Data transformed retail analytics, retailers kept a watchful eye on key shopper behavior metrics. Historical trends and buying patterns have always provided helpful insights into what consumers expect, when they want it, and how they prefer to make purchases. Retail analytics software gathers, parses and compiles data on a single-pane window that delivers real-time numbers to support proactive management strategies. Whether is it empowering staff to quickly reallocate available associates to achieve favorable STARs or evaluating dwell time per department, organizational leaders make data-driven decisions based on KPI reporting.
Along with tapping retail data as an effective scheduling and cost containment tool, learning how to use retail data to reduce shopper abandonment is mission-critical.
Retail analytics data gives marketers the agility they need to rapidly adjust campaigns in response to consumer demand, supply chain hiccups, or other events that occur in relation to a promotion. Predictive analyses, based on purchase histories, allows retailers to offer highly personalized promotions or discounts in a customer-specific manner.
Key metrics for markets include: pass-by traffic, draw rate, and changes in traffic patterns following specific advertisements or promotional activities on social media. These types of metrics put marketing performance in context, compared to local trends and consumer spending behaviors. One children’s apparel store was able to boost in-store traffic by 4%, after implementing changes based on a draw rate analysis.
Retail leaders know that in-store sales start with effective merchandising. Optimizing product placements and properly allocating space are essential for increasing conversion rates. Traffic data insights ultimately enable merchandisers to develop reset planograms that are based on traffic counts and shopper flow patterns.
The real estate side of the retail industry isn’t only about increasing conversion rates, it’s also about managing overhead and creating higher revenue potential. Harnessing the power of retail analytics retailers to enter into informed negotiations on lease contracts, based on historical shopper traffic patterns. When armed with historical data demonstrating consumer engagement, traffic count-per-square-foot, and draw rate numbers, real-estate professionals can better identify high-performing shopping zones.
Seamlessly integrating eCommerce websites and brick-and-mortar locations minimizes a brand’s cannibalization risk. Retailers use traffic data to ensure webrooming activities drive in-store sales transactions, and that brick-and-mortar showrooms complement online sales strategies. Traffic analytics allow leadership to compare web transactions and traffic count ratios with brick-and-mortar numbers to make sure the total retail policies create a consistent omnichannel shopping experience.
The Importance of Learning to Use Retail Data Effectively
Ultimately, every retailer from the c-Suite to the showroom floor benefits from gathering, parsing and disseminating retail data. Data-driven shopper insights enable retailers to create personalized campaigns that boost revenue potential and enhance the shopping experience. Monitoring traffic numbers across all channels informs decision makers about changes in the retail environment in real time. Predictive, prescriptive, and diagnostic retail data analyses lay the foundation for creating better marketing campaigns, elevating customer experiences and improving the intersection between eCommerce sites and brick-and-mortar locations.
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