The big, scary world of analytics isn’t really that scary anymore, especially when you have the right analytics tool in place to do the heavy lifting for you. This is especially true for retail businesses, as there are now a multitude of affordable, easy-to-use retail analytics software options on the market. Here's a quick overview of these systems, including some product demos:
It's likely your competitors are taking advantage of this technology. Need proof? The overwhelming majority of your retail business owning peers are requesting analytic components from their new point of sale (POS) systems:
Sales reporting and inventory management are common retail analytics components that most modern POS systems offer in some capacity. They provide users unparalleled transparency into the inner workings of their business. This includes:
But analytics systems are not all created equal. Some are less granular but very easy to use, while others seemingly require a data scientist to make sense of the spreadsheets (that’s a slight exaggeration).
So, we’ve created this guide to help you understand the various retail analytics systems, to help you determine the features and level of complexity that are the right fit for your business.
Here's what we'll cover:
What Is Retail Analytics Software?
Common Functionality of Retail Analytics Solutions
Benefits of Retail Analytics Systems
Retail analytics software can be tough to pin down. It isn’t really any one thing, and you can technically find it in many software offerings. For the sake of clarity though, retail analytics for small businesses analyzes sales, inventory and customer data.
We’ve identified sales reporting, inventory management and customer management as three of the five must-have retail point of sale (POS) features for small businesses. All three of these features help you streamline operational processes, and make things easier for you, your employees and your customers. In addition there are valuable insights that can be gleaned from analyzing key data points collected through these features, such as:
Retail analytics software functions are pretty much the same whether you’re digging into sales, inventory or customer data. However, there are some nuanced capabilities based on the origin of the data that is being analyzed. Functionality shared among most analytics-enabled POS systems includes:
| Data collection | Automatic collection and organized storage of data following every transaction is particularly important. Imagine if you had to pull double duty by completing a task, then going back to record multiple specific details of that task that may or may not be valuable in the long run. Analytics software saves time by automating this process. |
| Reporting | Reporting capabilities in software store these details for future reference and analysis with the click of a button. More advanced reporting can actually take historical data and perform predictive analytics to identify potential future trends, vulnerabilities, opportunities etc. |
| Dashboards | Dashboards take reporting and make it even easier for you to get key takeaways. These features automatically articulate the key findings from reports into easy-to-digest, often interactive visual assets such as charts, graphs and tables. Many POS systems with analytic components even offer mobile dashboards for business owners to easily check sales, customer and inventory info, while on the go. |
We’ve conducted consumer research that articulates the benefits of comprehensive analytics insights with regard to retaining customers. For example, the stats below highlight the fickle nature of customer loyalty if their expectations aren’t met. These statistics may be quite shocking to some:
Retail analytics tools can help you address these issues by uncovering key insights such as peak hours, days and seasons and optimize your inventory. These insights are critical in ensuring stores are properly staffed to handle busy times and properly stocked to meet the demands of consumers.
There are many benefits to retail analytics capabilities in addition to the insights uncovered in the data above. These include:
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