4 retail analytics best practices you need to know

Michael Poyser
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Retail has never been more competitive. Retailers have an ever-growing number of channels they can use to market to customers, and consumers have a wide variety of choices when deciding where to shop. The average shopper is well-informed by the time they make a purchasing decision.

So, how do retailers engage and retain their customer base with personalized content on the right channels? In short, you need to make the most of your data, and retail analytics can help.

What are retail analytics?

A retail analytics platform can gather data at point of sale (POS) and other customer touchpoints to inform you about your customers. POS data is the information that’s collected during a customer sales transaction. This could be in-store, online, or on your mobile app. This data provides a number of in-depth findings, including deeper insights on:

  • Product transactions
  • Product inventory
  • Customer preferences
  • Customer spend, basket size, and loyalty

Your retail analytics system processes this data in real-time. With this information, you can better understand customer behavior and product performance. This can be used to steer your decision-making, letting you strategize, create targeted marketing, and optimize your offerings.

Read the 4-step marketer's guide to retail data analytics. Discover how to  transform your data into targeted marketing. 

The importance of retail analytics

You wouldn’t throw a dart with your eyes closed, so why make targeted decisions without data?

Data is a rich resource that provides insights into your business and customers. By using it correctly, you can make smart decisions to grow your profits.

It’s likely your retailer is collecting a large amount of data every day. Retail marketing analytics can help make sense of raw data and turn it into valuable customer insights. Importantly, thought leaders agree that the way in which retailers use and execute analytics is critical to their success. When a retailer has an analytics platform that lets them monitor changes, like competitive shifts in behavior, they’re more prepared for future change. Additionally, retailers who are using advanced analytics outperform their competition by 68% in earnings.

If you’re looking for a retail marketing platform or want to optimize your existing one, here are our best practices for retail analytics success.

The retail analytics best practices

1. Data quality

Before you even get started with a retail analytics solution, your data quality must be up to scratch. Poor data quality can affect the accuracy of its insights.

Your POS systems, e-commerce payment systems, customer channels, and other touchpoints all collect data. This data can be delivered at different times and in distinct formats. It might also be delivered into separate places, or not collected at all. You could be missing out on vital insights if this is the case. A retail analytics system requires accurate and up-to-date data to be most effective.

2. Link up your data sources

Your retail analytics system should consolidate this data into one place. By linking up your data and the channels it comes from, you’ll achieve a more consistent view of data. Additionally, your retail analytics software should collect data in near real-time. This ensures you're obtaining the most up-to-date, accurate view of data. 

By linking up your data sources, you'll have a single source of truth. Data will be in the same format and within a centralized system, making it easier to understand. This helps your teams get insights faster and make smarter decisions. 

3. Get data expertise

Knowledge is power, and data puts it right into your hands. So it's no wonder why many retailers are looking to grow their in-house data science capabilities. However, this requires internal knowledge and resources, and setting up an analytics function is a time-consuming process, especially for retailers with a large customer base. 

A retail data analytics platform can help your business unlock the benefits of data using a pre-existing solution. The software is straightforward to implement and expert teams can support you with getting started, if you need it. This frees up time for your internal teams and makes sure you're following the right processes for retail analytics. 

4. Leverage real-time data

If you want to make the most of your retail analytics platform, it's important to set goals that are relevant for your business. You might want to consolidate data from in-store customers and online customers. Or you might want to keep better track of customer transactions, product popularity, or product stock. These goals will differ depending on your business.

You can use a retail analytics platform to help you react to changing information quicker than ever before. For example, real-time data can help you be alerted to out-of-stock events, and can help you target customers in the moment. The key is to have an intuitive platform, providing deeper insights and fueling your decision-making.

Retail analytics software gives you greater insights

Modern retailers have access to a rich amount of data. If you're not harnessing it now, you're missing out on customer and product insights that could differentiate your brand. By using retail analytics software, you'll gain greater insight into how and why your customers shop, helping you make more strategic decisions in the future. 

The 4-step marketer's guide to retail data analytics


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