7 Retail Analytics Examples to Visualize & Improve ROI
In today’s consumer market, retail stores benefit from making data-driven decisions. Gone are the days of relying on intuition for marketing, understanding consumer behavior, determining inventory decisions, and more. Instead, we’ve seen a rise in an area known as retail analytics. The goal of this post is to provide an overview of retail analytics, common use cases, and how this can be used to improve a company’s ROI.
What are retail analytics?
According to Shopify, retail analytics is the process of gathering and analyzing data related to a retail store in order to develop a business strategy. Since the overarching goal of the retail industry is to improve ROI, it’s important to understand how retail analytics can be leveraged to guide business decisions, bringing a company closer to success.
Types of Retail Analytics
One can conceptualize retail analytics as falling into four key areas, which are briefly described below:
- Predictive Analytics – using data to predict what will happen in the future
- Prescriptive Analytics – use real-time data to develop a strategy
- Descriptive Analytics – look at the results of a campaign, promotion, or launch to uncover what went well and what didn’t
- Diagnostic Analytics – examine why an event happened
It’s clear that retail analytics encompasses multiple data sources such as retail store sales data, marketing campaign data, point of sale terminals, consumer demand, inventory, and more. Therefore, one can surmise that the number of use cases for analytics in the retail industry continues to increase as new business questions and data sources arise.
Top 7 Retail Analytics Use Cases
Let’s look at some of the most common retail industry questions professionals seek to answer by applying retail analytics.
1. Customer Segmentation
By analyzing and visualizing Salesforce data, retail companies can better understand their customers. Specifically, customer segmentation involves categorizing customers and potential customers for marketing, forecasting, and targeting activities.
There are several different customer segmentation approaches that can be visualized in a dashboard to help make business decisions:
- Focused Approach – the company targets one specific segment
- Differentiated Approach – targeting at least two different segments Hypersegmentation – Includes up to thousands of different segments
- Based on the approach selected, a retail company might tailor marketing strategies and lead nurturing to each segment. This improves ROI by using the right strategies for the right customers – essentially marketing to target customers more efficiently.
3. Optimizing Inventory
How does a retail company decide which items to supply and in which quantity? Everyone knows supply and demand fluctuate, so having a data-driven approach to understanding inventory is crucial in improving ROI.
For instance, a clothing company might assume that it should have the largest stock of bathing suits in the summer. However, if they analyze their data and discover there is actually a higher demand for swimwear in the winter (potentially attributable to higher rates of vacations), this can allow them to optimize their inventory.
By combining data from multiple sources, such as Salesforce and Quickbooks, the finance and product teams can visualize their analyses in a clean dashboard to help make inventory decisions.
3. Marketing Personalization
When it comes to marketing, there isn’t a one size fits all solution if a company wants to maximize its ROI. Building off of the customer segmentation example earlier, a retail company might want to add Hubspot or Facebook Ads to the mix, in order to understand how to personalize their ads, emails, or brand messaging.
4. Location Intelligence
Analyzing customer data related to geography can also help retail companies make smarter marketing decisions. For instance, geofencing or geotargeting ads can be beneficial for A/B testing creatives for different locations.
Perhaps a company notices that creative asset A performs better in the southeast United States, whereas the Northeast prefers asset B or C. It’s possible to uncover this by simply analyzing multiple data sources and creating a cohesive visual.
5. Sales Forecasting
This might be the first thing people think of when it comes to retail analytics. Discovering trends in sales based on inventory, locations, marketing efforts, and more, allows companies to create more accurate forecasting tools.
By understanding what to expect from different segments and working toward a common goal, marketers can delegate the appropriate resources to the channels that are driving the most sales.
6. Dynamic Pricing
Dynamic pricing allows companies to review their current prices and optimize them throughout the day to match competitors. This technique relies on advanced analytics and automation.
It’s important to consider the pros and cons of dynamic pricing, but if this seems to be a strategy that can benefit your company, visualizing the data with a comprehensive dashboard can help evaluate the results.
7. POS Reporting
If a retail company uses Square or Stripe for its POS software, being able to analyze and visualize the data on a daily, weekly, monthly, or yearly basis allows for effective tracking. For instance, a company might want to see the top products or customers at specific times of the year. This can drive more personalized marketing efforts and improve ROI by better understanding trends and outliers.
Putting it All Together
The most important part of getting started with retail analytics is connecting all of your data sources. The power of being able to report on and visualize transaction, inventory, employee, and loyalty data in a single dashboard cannot be over-emphasized.
Luckily, DataLakeHouse allows your retail store to do just that. Through our connections to Shopify, Ceridian Dayforce, Salesforce, Hubspot, Snowflake, and most other data sources you would want in order to determine the effectiveness of marketing efforts, uncover operational inefficiencies, evaluate employee performance, utilize forecasting, and more.
And not only can you access every data source you need on one platform, but you can also view all of these metrics in one synchronized dashboard.
You have the power to make reporting easier and more effective than ever before.