A semi-brief discussion on some of the ways retailers can monetize their data.
Like every industry out there, retailers strive to achieve profitability. However, in retail, the competition is fiercer than ever (especially when it comes to e-commerce) and organizations often do whatever they can to stand out from all the others. Whether we’re talking marketing or any other areas of retail, it really boils down to developing and maintaining a competitive advantage. This can be in the form of operational efficiency, a strong and efficient supply chain, superior product offerings, favorable pricing, offering an excellent customer experience, etc.
With that being said, data-driven decision making is essential.
Technology has enabled us to collect and analyze more information than ever before. Retailers in particular, collect so much data in so many different ways, the possibilities of what they can do with it are probably endless. My marketing mindset tends to focus on all of the benefits data offers in that area (and there are an abundance), but in this blog post, I’m broadening my horizons and throwing in some additional benefits! Here’s what I’ve observed (in business interactions) and learned (through research), in terms of the benefits retailers can experience from putting their data to work:
- Effective Segmentation, Targeting, & Positioning
- Crafting Highly Effective Promotions
- Enhancing Consumer Experiences
- Determining Appropriate Pricing
- Implementing In-Store Optimization
- Supply-Chain & Distribution Optimization
- Effective Budgeting
- Improving Operational Efficiency
- Enhancing Service
- Guiding Product Design
- Measuring Success
And just to clarify, data utilized for retail purposes can come from a variety of sources. Here are a few of them:
- Credit card transactions
- Loyalty programs
- Geolocation
- IP addresses
- User log-ins
- Mobile applications
- Production information
- Social media activity
- Inventory tracking
- Reviews
- Browsing/search history
- 3rd parties (weather, census, economic, etc.)
So, to get into a little more detail, I’ll start off by discussing things from a marketing perspective and then I’ll try to tie in some of the benefits other departments can experience as well.
Uses for Retail Data
According to one of MarTech’s recent Intelligence Reports (developed with data, btw), Consumer Data Platforms: A Marketer’s Guide, the majority of consumers not only expect connected experiences and for companies to anticipate their needs, they also favor omni-channel shopping. They not only want to be able to purchase anything, from anywhere, at any time, they also want retailers to know what they like, show them similar products to buy, and remind them when it’s time to buy things they might be running low on (shampoo, toilet paper, peanut butter, etc..). By reviewing data on a retailer’s target consumers, marketers can develop the perfect omni-channel solutions (that remain consistent across channels) and present their audience with relevant communications.
But let’s take a step back for a minute….
Marketers are tasked with a variety of different objectives when it comes to retail, however, most of what they do is centered around getting a good idea of who the target customers are, what they want and need, when they’re likely to purchase those things, where they’re located and primarily shopping, why they select certain products and/or retailers over others, and how they can be reached best. Once they figure as much of that as they can, they can ensure a retailer’s products, pricing, promotions, and distribution all make sense. And absolutely all of this should be done by observing and thoroughly analyzing data.
Looking at demographic, psychographic, geographic, and behavioral data, marketers can learn all about a retailer’s target consumers and develop appropriate marketing strategies. The data shows marketers what they need to know to give the people (A.K.A. consumers) what they want! This means providing the right people with alluring messaging and relevant offers, when and where they want to view them (both initially and when retargeting). Data regarding consumers’ purchase and search history helps marketers identify their needs and interests to tailor both their shopping experiences and the communications they receive. Marketers can develop content that actually provides the target consumers with value and present them with personalized product recommendations and promotions that they’re likely to genuinely give a #$%^ about, therefore fulfilling that level of customized engagement that is now expected by most consumers. Understanding what matters to the target audience also facilitates accurate positioning that will place the retailer in a favorable light consistently throughout all marketing communications.
At a high level, market analyses (based on all kinds of different data) aid in strategic decision making. Marketers can monitor which products (both their own and competitors’) are selling at which prices, along with economic fluctuations, to easily implement dynamic pricing strategies. Data from inventory tracking, competitors’ sales, consumers’ social media activities, as well as feedback submitted directly and in online reviews allows retailers to track product performance and determine the best ways to fill the shelves. Additionally, candid comments made via social media can help marketers determine how customers really feel about products and organizations. This information can also show retailers which products they should be carrying.
Geotargeting, geofencing, and beaconing utilize consumers’ geolocations to give marketers the ability to reach consumers with marketing communications when they are within specific distances from, or within the retailer itself. This kind of data ultimately helps marketers keep a retailer top-of-mind for the target consumers. Data from similar technologies that track consumers’ shopping behaviors throughout stores enables marketing teams to make sure each store’s layout reflects the way consumers prefer to shop and products are showcased as they should be. This enhances the shopping experience by making it easier for customers to find what they are looking for (and some things they may not have known they needed/wanted).
In other departments, data allows retailers to optimize asset utilization, budgets, performance, service quality, and product design. Inventory tracking helps retailers keep products stocked adequately and keep up with the popularity of each product in real time. Not only can this information help the marketing department (as you can imagine), but it can also help streamline a retailer’s supply chain and ensure proper resource allocation (eg. increasing orders to keep up with demand and allocating trucks to support those additional orders). Data also allows forecasting that enables proper budgeting. Customer service can be enhanced, based on various feedback, as it has the ability to bring unknown issues to light. Reviews and other sources of feedback can alert retailers to issues with inadequate sizing and/or other issues that they can improve upon in terms of product design and production. Retailers can then turn to the data to measure the success of any changes implemented, determine their effectiveness, and make any necessary adjustments.
But what about the money?
When retailers effectively target their customers and provide them excellent customer service and offerings when and where they need them, they become repeat customers. These loyal customers not only stick around for a while (and spend more money over time), they also become raging fans of the retailer (A.K.A. brand advocates) who share their positive experiences with others, who then also become happy and loyal customers. Effective targeting also reduces customer acquisition costs, freeing up more marketing dollars that can be spent elsewhere. A 360-degree view of an organization’s supply chain and distribution can greatly reduce costs when efforts are directed in the right areas. And of course budgeting lets retailers know exactly how they’re performing and indicates areas that are cause for concern, so changes can be made. This all translates to greater returns on investment (ROI) and ad spend (ROAS), ultimately increasing both revenue and profit.
In Sum
Data keeps marketing teams in tune with the consumers they are targeting and other departments in tune with their own priorities. Access to real-time data also allows marketing (and other) strategies to be changed as necessary to ensure consumers are continuously being reached adequately (and everything else is running smoothly as well). All of which saves retail dollars to be allocated where they’re needed most.
How Your Organization Can Get With the Program:
A comprehensive view of the business requires unifying structured, unstructured, and semi-structured consumer data with a platform like Snowflake (our favorite!). With DataLakeHouse, you can pull all of that information together by extracting and loading it into Snowflake, giving your organization a single source of truth. From there, the data must be analyzed to uncover hidden patterns, correlations, trends, consumer insights, and other useful business information. An end-to-end analytics tool with advanced machine learning capabilities (cough cough, DataLakeHouse) can help retailers (among others) easily uncover high-level insights (like what goes on throughout the entire customer journey, the best places and times to reach consumers, specific information about top spenders and their actions, where customers are being lost throughout the process, etc.) that can effectively guide business decisions.
So go ahead and click below to find out how you can jump on the data-driven bandwagon and start to uncover insights that will contribute to your organization’s competitive advantage and result in better business performance overall.
