09 October 2015

Square unveils analytics tools for merchants

21 August 2014  |  3714 views  |  0 Source: Square

The world's largest retailers employ armies of statisticians and analysts to help them increase sales. Today, Square levels the playing field for merchants of all sizes by adding Square Analytics to its complete Register service.

The powerful reporting and analytics tool delivers sellers actionable data to increase sales and better serve their customers. Square Analytics integrates the full suite of Square Register products including Pickup, Invoices, and Appointments, making it the most robust point of sale service.

Expensive annual fees, tedious set-up processes, and irrelevant, generalized reports have traditionally excluded small business owners from useful information available to larger merchants. Building on the sales data to which Square sellers already have access, the new mobile-optimized Square Analytics delivers information including most-popular items and categories, busiest time of day, and a holistic view of customer spending.

Pam Turkin, owner of 17 Just Baked cupcake shops in Michigan and Ohio, determined her most efficient business hours with Square Analytics: "When I opened Just Baked in Detroit, I was guessing when customers would stop in for a cupcake. Square Analytics showed that this location's busiest hour was actually between 4:00 PM and 5:00 PM. We would have closed at 4:00 PM and missed out on sales if not for Square Analytics' hour-by-hour trends."

Square Analytics has a few key features:

  • The analytics homepage shows how a seller's business is performing in real time, including which items are the most popular, and how their business is performing compared to others in their industry.
  • Sales trends provide updates of sales hourly, daily, and monthly so sellers can consider later hours or stocking up on inventory to avoid missed sales.
  • Buyer insights show sellers useful customer information. Sellers can see new vs. returning customers as well as customer frequency, recency, and average customer spend. 

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