Beyond the Jargon: the Future of IoT and Retail

Cost savings play a major role in the IoT messaging of major software vendors. But in a recent survey, retailers valued IoT data analytics as a way to improve merchandising, not operations. What’s happening, and what does IoT data analytics offer retailers?

Survey Emphasizes Differentiation, Consumer Pricing

In a 2015 survey conducted by Boston-based Retail Systems Research, retailers were asked which challenges would persuade them to consider IoT solutions for their stores.

Given cost-, margin- and growth-based challenges, retailers chose growth. They gave top value to IoT data analytics to help them manage growth-related challenges. Differentiating their brands and monitoring consumer price sensitivity were their top-rated uses for IoT.

Beyond the Jargon: Data Analytics Technologies for Retailers

So, what does IoT mean to retailers? Modern technology gives us several ways to slice, dice and analyze retail data. The differences lie in data volume, speed of analysis and where the data comes from.

Technology

What it does

What it delivers

Capabilities

Big data analytics Uses high-speed, high-volume data handling methods and tools. Analyzes stored data. Turns huge volumes of data into actionable information. Can handle a wide variety of data such as database records, images, emails and digital documents.
Fast data analytics Uses big data technology and tools on smaller data volumes. Mines raw, stored data in real time. Information that retailers can use immediately to change prices or improve customer experience. Avoids the delay in analysis and visualization of big data analytics.
IoT data analytics Automatically gathers and analyzes streaming data from connected sources such as mobile phones, POS, video cameras and social media. Actionable information on customer preferences, products, pricing and the competition. Provides up-to-the-minute customer responses to prices, trends, in-store events and sales.

 

 

 

Connected to a network and the internet, these IT resources play an essential role in IoT data analytics:

  • IoT assets, such as mobile and connected devices, sensors and beacons. These gather streaming data and route it to the retailer network.
  • Data storage, which gives business users and analysts access to huge volumes of historical data.
  • Data analytics software, which in the context of retail analytics can be used to analyze and visualize streaming data, set digital alerts and automate report distribution and scheduling.
  • Data analytics platforms, which can be located on-premises or in the cloud. This centralized digital workspace processes IoT information gathered from many points on the internet and delivers actionable information to users.

Here are a few examples of how retailers can use these assets to monitor prices and differentiate their brand.

Keeping an Eye on Consumer Price Changes

Many RSR survey respondents were interested in using IoT data analytics to gauge consumer price sensitivity. Business users can do this with IoT data snapshots or set up and test pricing strategies.

Monitor customer response to price changes

Measuring customer reactions to recent retail price changes is a then-versus-now comparison. Business users can compare sales volumes related to stored data or information hot off the IoT wire. Either way, IoT technology makes it easy to gather, analyze, visualize and share information automatically.

Test an existing price strategy

Creating or updating your pricing strategy is another way to use price sensitivity information gathered on the IoT.

When you set up a statistically valid test, you’ll make sure that pricing is in line with your business model and target audience. The speed of real-time, streaming data analysis makes a series of what-if tests easy to set up, evaluate and use.

If you need more than one strategy, startup is easy. You’ll probably start gathering data from POS and many other devices you haven’t had access to before.

By using IoT platform and software capabilities, you can find the best product price range for specific audiences. Study customer buying patterns; IoT data gathering, analysis and sharing are automatic.


 

Using IoT to Make Your Brand Distinctive

Survey respondents also viewed the IoT data analytics as an excellent way to differentiate their brands. What better way for your business to distinguish itself as a place to get great prices, a delicious customer experience—or both?

When Numbers Rule: Differentiating by Price

Speed and agility are the main advantages of IoT data analytics. You can gather data from many locations and devices, monitor current conditions, change prices and test customer behavior quickly and often.

Use IoT data to measure sales behavior of targeted audiences before and after specific price changes. You’ll discover quickly whether a specific audience accepts that 10-percent price increase. If you don’t come out ahead? You can respond quickly without putting a serious dent into revenues.

Making Your Mark with Support Services
When it’s difficult or impossible to differentiate on price, you still have alternatives. Many resellers set their business apart by adding value-added services such as faster shipping, free returns or a fun-to-use mobile app that knows what you like.

IoT contributes to speedy shipping by gathering RFID data off your packages and sending it to tracking software in your logistics center. If customers return their goods, you’ll probably have stored personal and product information that helps you figure out what went wrong.

And that mobile phone app? More about that below.

Cultivating Personalized Shopping Experiences

IoT also helps retailers use customer preference and behavior data to create strong, long-term relationships. Here are some examples of IoT technology and how it creates appealing shopping experiences.

  • Use mobile phones to make customers happy. Help your customers find their favorite products and brands at your store, not down the street. Provide their mobile phones with apps filled with your store information. They can search for what they want, learn about sales and review in-store events with their friends. Use beacons to alert registered customers about their favorite products and services.
  • Make unique product recommendations. When you track customer preferences and get familiar with their buying habits, use that back-end data to identify likely future purchases. Track individual tastes, previous purchases and loyalty points to provide suggestions and prices that appeal to each customer.
  • Improve products and services. Gather in-store feedback or social media streams to tweak products based on direct customer responses and location data.

IoT Advantages: Speed, Agility and Lower Risk

With IoT data analytics, retailers can quickly gather, analyze, visualize and use huge volumes of data from many devices. Though this might make your IT pro’s heart flutter, there’s plenty of appeal from a business point of view:

  • Reduce market risk. Streaming IoT data helps you know, not guess what’s happening right now. And you can make changes and identify opportunities quickly before your market changes.
  • Avoid costs. You can test hunches without making costly business mistakes.
  • Control costs. Although new, IoT technology needn’t bust your budget. Available as a cloud-based service, IoT data analytics is often offered as a monthly subscription service.

Ilan Hertz is head of digital marketing at Sisense,

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