Retail Analytics: Analyze Your Data to Improve Business

Jordan McGee

June 24, 2021

With the rise of online shopping, many retailers face fierce competition and changing consumer tastes. People can now buy a vast amount of products from different stores with the simple click of a button. So it’s more important than ever to leverage retail analytics to keep a competitive edge.

What is retail analytics?

Retail analytics is collecting and analyzing data from sales, inventory, and customers to improve business processes and marketing. By identifying trends and patterns, retail analytics helps businesses leverage data to make better decisions.

Benefits of retail analytics

Retail analytics takes the guesswork out of many business operations and puts them on autopilot. It helps predict product demand and trends, what customers want, and when they want it. All this allows stores to optimize their inventory levels and product prices.

Retail analytics also helps you manage in-store operations like staffing levels. Using live and historic retail data lets you know how many employees to put out on the floor.

Most importantly, retail analytics helps you understand your customers. After all, customer experience matters, and you can know their wants and needs by following the data. Then make the buyer’s journey as seamless as possible and raise customer lifetime value (LTV).

Types of retail analytics

Different retail operations call for different types of analytics. Here are the different kinds to know and what metrics they track:

  • In-store analytics measures things that happen within the store, like foot traffic, dwell time, and sales per square foot.
  • Inventory analytics measures operations behind the scenes, like stock return and sell-through rates.
  • Customer analytics measures customer satisfaction and loyalty through net promoter scores (NPS) and customer retention rates.
  • Web analytics measures online engagement through traffic, conversions, and sales.

Retail analytics in ecommerce

Web analytics is driven by ecommerce, which exploded during COVID-19. As businesses were forced to close, they put more products online. As shoppers were confined to their homes, they shopped more online. But even before the pandemic, ecommerce was taking over the retail industry, and it's predicted to just keep growing.

Ecommerce share of total global retail sales from 2015 to 2024:

Ecommerce Share of Total Global Retail Sales From 2015 to 2024,Ecommerce Share of Total Global Retail Sales from 2015 to 2024 from Statista

When it comes to analytics, ecommerce opens up a world of opportunity over brick-and-mortar retail. To begin, the amount of data and types of data available is much larger. Imagine knowing the exact time every customer walked in, which aisles they walked down, which products they touched, what items they put back, what they bought for what price, how long they stayed in your store, and even where they lived. That’s what is possible with ecommerce analytics. You just can't get the same amount of data from a physical store environment.

Of course, some brick-and-mortar strategies can be adapted for ecommerce. For example, you can implement a recommendation engine to imitate a friendly storekeeper. It can recommend impersonalized items like new, trending, or discounted products. Or it can make personalized recommendations based on consumer purchasing and browsing history.

Sometimes ecommerce analytics will change retail strategy. For example, product titles may need to be adjusted. Why? Ecommerce product titles need to match what online shoppers are searching for. Otherwise, they may never find your product, and you’ll lose valuable web traffic, which boosts ecommerce revenue in the long run.

Overall, retail analytics is essential for any ecommerce or hybrid business to thrive.

Challenges of retail analytics

Implementing retail analytics can also be challenging. For instance, you need to make sure to respect customer privacy concerns and comply with government regulations like the General Data Protection Regulation (GPDR) and the California Consumer Privacy Act (CCPA). These can make consumer data collection tricky.

As a rule, collect data securely and transparently. Most online shoppers don’t mind giving away their data. They just expect you to be upfront and responsible with it.

One way to collect consumer data is to collaborate with customers through games, quizzes, and surveys. Incentivize them to volunteer data by offering a reward in exchange. This way, you stay transparent and get their consent.

How to use retail analytics to improve your business

Once you are data security compliant, collect as much data as possible. Measure and track it consistently over the long term. Any retail analytics software should store historical data to help you do this.

Then, focus on data and metrics that matter most to your business. Massive amounts of information can be overwhelming, so narrow it down to what’s relevant to your objectives, business type, and current campaigns.

Next, leverage the data by identifying product gaps, segmenting customers for email marketing, or relating different metrics to each other for greater insights. Combine online and offline data. Any retail analytics software should integrate with other tools, so you can get the most out of all your data.

Finally, don’t rely exclusively on retail analytics. Use your human intuition to fill in the gaps that technology can’t. In the end, retail analytics is just a tool to help you run your business optimally.

Market for Retail Analytics

The retail analytics market is expected to expand at a rate of 18% and reach a value of $9.5 billion by 2025. Much of this growth can be attributed to retailers adopting cloud-based software, RFID tags, in-store WiFi, and Internet of Things (IoT) technology. Each offers new ways to track data, making retail analytics more valuable in the process.

One retail analytics trend not to miss is omnichannel analytics. Omnichannel analytics shares data across several stores, allowing you to know how analytics in one store or channel affects another. For example, your conversion rates at Walmart could impact how you approach SEO on Amazon. With omnichannel analytics, retail analysis takes a holistic view.

Working with Pattern

Here at Pattern, we have a suite of data to give you clear insights into what areas of retail analytics you are missing out on. Our data-driven ecommerce solution tracks what you need to grow. Request your demo today to learn about our platform, analytics access, and how to set yourself up for future success.

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