Main goals for a physical store
When we evaluate the management of stores, we often talk about five KPIs or key performance indicators: the total value of sales per hour, the average value of sales per customer (or the average ticket amount), the number of products per ticket, number of sales per seller and number of sales per square meter.
These data, which are absolutely useful and necessary, show us only a part of reality: that concerning the closure of sales, a merely economic figure. And what about lost sales? Do you know how many potential customers spend each day in front of your store and how many of them end up entering? Or how many people enter instead without buying anything?
When it comes to an online store, the question is clearer: the potential customers correspond to the visitors who enter the e-commerce home and the entrances are represented by the people who surf the various pages. Therefore, two key indicators to control the performance of an online commerce are the abandonment rate (% of visitors arriving on the home page of the web page and leaving without exploring it) and the conversion rate (% of visits ending with a purchase ). Other interesting indicators are represented, for example, by the average stay time, or the day and time of the week in which you sell the most (in anticipation of the launch of any campaigns or offers).
These indicators belonging to the online world are easy to monitor thanks to Google Analytics tools. In the physical world, however, it is necessary to rely on Retail Intelligence technologies. These traffic analysis tools allow us to know the number of potential customers that pass in front of our windows shop every day and end up entering, data from which it will be possible to obtain the penetration rate KPIs (% of people passing by to our windows shop, ends up entering in-store) and the conversion rate (% of people in the store who end up buying something).
In the same way, it is also possible to know the average turnout in the store at any time, and the average time spent by customers within the room or the duration of the purchase process, the time and day of the week with greater turnout etc.
With all this information, you can make decisions to optimize the performance of your store.
With these data, chain stores can measure and compare different parameters of customer behavior in their stores and identify opportunities to improve it by increasing profitability, commercial efficiency and customer service.