RETAIL DATA SYSTEMS

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Integrate years of transactional and profile data from any system to create a clean, consistent, de-duplicated record of every customer.

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Engage customers with personalized, omnichannel campaigns by seamlessly warehousing, syncing, or activating your data in any platform.

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RETAIL DATA SYSTEMS

What are retail data systems?

There are a lot of moving parts in a business. Whether you’re a national chain with hundreds of stores or a local retailer with a single storefront, things are always moving. Customers enter your store or website, browse products, make decisions, buy things, tell their friends, use discounts, return items, leave reviews, check out the competition, and more. Yes, the daily hustle and bustle of retail can be crazy, and even overwhelming, but there is an upside to this confusion. Deep within all this complex motion and interaction lie the keys to a better and more lucrative business.

At its most basic level, all this movement is an expression of the needs, wants, and feelings of customers with respect to your business. This means that if you could look at and analyze the behaviors of each customer persona, you could figure out whether or not they feel happy with your prices, your products, your business and why.

This is what retail data systems do. These are complex and intelligent networks of data collection and customer analytics tools that look at all the movement and chaos (data) and figure out what it means (insights). With this, marketers and business leaders can better connect with their customer bases and work to build better shopping experiences. Increase customer satisfaction, and people will want to shop with you more often and buy more each time they do. This means increased profit and lifetime value growth.

Retail data systems, such as Customer Data Platforms (CDPs) are fast becoming a must-have for all markets and industries, helping companies to use the swirling information all around them to create better, more personalized experiences for their customers. These systems can focus on customer buying patterns, loyalty, ad preferences, product response, churn rate, and more. 

The bottom line is with the kinds of martech and software we have today, from retail data collector apps to forecasters and AI modeling within customer data platforms or CDPs, businesses of all kinds can achieve new benchmarks of success. Let’s take a look at how it all works.

 

Retail Data Services

The kinds of tools used to sift through all this customer data are complex. As a result, businesses aren’t expected to build and integrate these data systems themselves, but instead partner with software companies that develop them. The number of companies offering retail data services are as numerous as the kinds of data challenges out there.

Many companies specialize in data capture and collection. The first step in any retail data system is transforming the many interactions between customers and your business into information. This info can be found anywhere that you and customers make contact—at the register, on the sales floor, at your web store, and elsewhere online. Depending on the software, you can choose either to seek out a specific kind of information or focus on gathering all the available customer data from a specific location.

Other providers offer platforms where all this collected information can be stored, accessed, analyzed, and used for activation across channels. This is achieved with a customer data platform, or CDP. In the CDP, every new piece of data is sorted and matched to an individual customer profile to create a “single customer view.” This way everything stays organized and all the information about a specific customer can be called up at a moment’s notice for easy insights, segmentation, and targeting.

Another set of companies deals with customer analytics. These software tools help you scour the data to uncover hidden patterns and trends that may be of importance to you. Some of these programs also work on measuring and predicting how customers will behave in the future, such as their likelihood of churn. These predictive analytics capabilities help you prepare for new challenges and opportunities, such as preventing churn or capturing a second sale. 

Others work on dashboards—visualization programs which seek to condense the data and present only the most pertinent customer metrics to your team. Using tracking and measurement tools like these to see the big picture in a clear and simple way helps you make decisions and improvements faster.

These are only a few of the retail data services companies offer, and many provide tools even more specialized and unique than these. Some CDPs, like Lexer, are strong in both data collection and analysis and cross-channel activation. The most important part of building or implementing a successful retail data system is finding the right tools for your business.

How soon after an implementation can you expect to see results? Click here to read “Post-deployment timeline: What changes can you expect with a CDP?”

 

Types of Data Systems

Just as there are many different tools for dealing with data, there are many different kinds of systems that can be built from these tools.

Many of these are register or POS data systems. Checkout is usually the closest point of interaction between customer and business, and many different types of data can be collected here. Some systems simply track product data—what items are being bought and when. This helps businesses determine what to stock and what to market to consumers at different times of year. Many programs monitor customer purchase patterns—when specific shoppers visit and how much they buy. Other info about age group, gender, and location can also be picked up by systems which work on customer demographics, or by enriching your customer database with third-party data sources such as Experian’s Mosaic

Other systems rely on data coming from online retail stores and digital brand engagement. There, much of the same info about customer shopping habits is readily available, but with greater detail. Site traffic can be analyzed to determine all the different items customers view, how long they look at each of them, what they usually search for, and more. They can also learn what time of day online customers like to shop, where they’re located (shipping addresses), and how frequently they like to browse and purchase.

Many types of data systems focus on marketing and digital advertising. Analyzing data from physical ad media can be difficult, but online, there is a wealth of info to be gathered. By tracking how customers and other internet users interact with ads, data systems can determine which ad campaigns are succeeding and how others could be made better. What sites people are most likely to see your ads on, when and where they are most likely to interact with them, which search engine they use, and which ads they do and don’t respond to can all be tallied and recorded for continuous improvement. 

And this is just the beginning. There are systems out there, such as CDPs, that can monitor customer satisfaction to help you understand buying motivations and preferences, track churn rate to help you improve retention, collect zero-party data from forms and surveys, detect coupon usage, and much more.

 

Data Systems Examples

To get a better idea of how this whole process works in the real world, some data systems examples may be useful.

A supermarket customer data system is programmed to track the purchase habits of customers. It looks at the number and value of items purchased, how often individual customers come in, and what they actually buy—this type of analysis is known as RFM (recency, frequency, monetary) segmentation. Analytics programs look for patterns in the items bought to see whether certain items should be better advertised during some seasons or not carried during others. This helps optimize your advertising to improve acquisition, growth, and upsells. Purchase size and frequency are used to measure customer loyalty, and looking at how often people are coming in helps the business see how well it is satisfying customer needs. The system sees if it can find any correlation between customer retention and rewards program membership, location, items bought, and other factors. If it does, you should respond to this insight by increasing your funding and focus in these areas.

A clothing retailer sets up a customer data system to monitor its online store. The system keeps track of all the searches made by customers on their site to see which products people want to buy but which might not be available. The items that customers look at but do not buy are automatically displayed to them again each time they visit the store to increase the likelihood of a future conversion. The system also looks at customer loyalty and habits by monitoring purchase size, frequency, and content. The reviews left by customers on individual products are analyzed and sorted into positive and negative groups. Products which receive positive reviews are promoted and always kept in stock. The ones that receive negative feedback are brought to the attention of management and considered for removal, improvements, or discontinuation.

These examples only give a general overview of how these systems work, but they demonstrate how many different tasks they can perform simultaneously and how much they can tell you about the way your business works and what your customers want and need. 

 

Data Systems Management

Even with all the tech working behind the scenes to find, capture, store, and analyze this data, the task of making better business a reality will still fall to your team.

Marketers and business owners are already very busy people. What data systems can do is make the hardest and most important decisions easy by helping you easily and independently generate customer insights, perform advanced segmentation and cross-channel targeting, and track results. The CDP, analytics programs, and dashboards all come together to bring the right data in the right form to the right people at the right time. This way, knowing what to do next—how to increase revenue, how to market your brand, how to measure and grow customer lifetime value, and how to keep customers happy and loyal, is all made easy.

Data systems management is meant to make building a better company easier, but it does require some work. Data and dashboards need to be monitored by your team to watch for any changes in the way customers are buying, shopping, and generally interacting with your business. Keeping on top of the datastream helps keep your company agile, adaptive, and current. This way, you’re ready for any challenge and can take advantage of any opportunity. The result is happier customers, smoother operations, greater popularity, and higher sales.

The key to bringing your team up to speed on using these systems effectively is by choosing a CDP partner, as opposed to just a vendor. A CDP partner like Lexer can offer strategic guidance and consulting services to help you make the most of your retail data. If you’re not sure where to start, click here to read “Checklist: How to choose a customer data platform (CDP)

Retail data systems are becoming a bigger and bigger part of business, no matter what industry you’re in. If you’re looking to stay relevant and profitable in the coming decade, entering the world of data now is the best first step. With the right partner and the right tools, you’ll wonder how you ever did without them.

Click here to read the top 15 reasons customers choose Lexer as their preferred partner for customer data and experience management. 

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