Getting Started With Analytics: 3 Tips For Mid-Market Retailers
When it comes to sales forecasting, retail business intelligence helps mid-market retailers to get a better view of what’s beyond the horizon.
Some retailers are testing the waters of retail business intelligence, which involves using various data sources and analytics to evaluate goals and predict trends. This insight helps to give midsize companies a critical competitive edge in a changing business landscape.
Here are three tips for mid-market retailers looking to use retail business intelligence to improve their forecasting and growth:
Gather analytics that support organizational goals: Retail business intelligence is especially helpful in gauging how well you’re moving toward your organization’s goals. Defining the goals, strategy, mission and key performance indicators you want to focus on before collecting analytics is vital to ensure that you’re tracking the right data.
Keep in mind that goals will vary between retailers, which means the analytics to track are going to differ. For example, do you want to compare sales between your stores? Or are you more interested in finding out where more male or female shoppers patronize stores in a specific region?
Let’s say you’re a medical scrub apparel retailer and want to evaluate your marketing efforts targeting local medical offices and hospitals. You should gather analytics that drill down to the number of medical office and hospital employee vouchers redeemed at your store. That data would provide valuable insight into how well your marketing efforts are translating into sales goals.
The information possibilities are endless, but again, you need to have specific goals in mind before selecting the analytics to gather.
Evaluate the quality of collected data: The strength of retail business intelligence depends on the quality of data captured at the store level. Before you delve into crunching analytics, you’ll want make sure you have the right ERP tools to capture data. A retail ERP solution is vital to gathering and tracking the data, while a business intelligence (BI) tool analyzes the data.
- Use Big Data to predict trends: Retail business intelligence involves analyzing store-level data (such as sales transactions or seasonal product trends) and comparing it to complex sets of Big Data (such as economic indicators or other statistics collected outside a retailer’s capacity).
For example, you might try to identify a relationship between daily sales and outside temperatures. If sales of ice scrapers dramatically increase on days when the high temperature is below 25 degrees, you could use weather forecasts to ensure they’re stocked on those days. That’s where retail business intelligence becomes truly powerful — when store-level and Big Data analytics are used together to drive results.
Keep in mind that sometimes there might not be a correlation between in-store occurrences and Big Data trends. Store sales could remain stable despite outside trends that would signify otherwise. Or BI tools might reveal inconsistent patterns with no discernable correlation. That’s why it’s always important to carefully review your data and ensure you understand what it means.
These three tips should serve to help mid-market retailers get started in taking advantage of retail business intelligence tools. Just remember, before adding an analytics package to your retail ERP solution, be sure to identify the goals that you’re hoping to achieve.
Author: Wm. Matthew Street, Solutions Consultant/Retail Product Lead at ArcherPoint
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