The Future of Retail Series: Laying the Foundation

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9 min read

Editor's Note: Watch our MapR and RCG Global Services experts in this complimentary on-demand webinar to learn why retailers need a data fabric to stay ahead of their customers & more.

In part 1 of my blog series on the future of retail, I shared details about digital imperatives essential for retail leaders to succeed amid a large industry transformation.

In this post, I’ll explore available technologies that help create the most effective customer experience. Before we look in detail at what these technologies are and how you might use them, let’s start with the big reason why retailers are struggling to leverage data to transform their business while keeping the customer in focus.

Why Are Retailers Struggling to Leverage Data?

The purpose of all this data is to be more responsive to customer needs. Retailers seek accurate and actionable intelligence in order to compete with experience, service, and urgency. However, many lack the systems and technologies to integrate siloed data and model data to produce insights that they can incorporate into their operations. For example, wouldn’t it be nice to be able to leverage every customer touchpoint to gain insights on how best to serve them to maximize profits and improve customer loyalty? With the right data platform, you can create more targeted promotions, tailor store assortments to specific clientele, and create a personalized shopping experience for customers at all stages of the buying cycle.

I’m not talking about any data platform that lets you build a data lake in which you put all your data. The concept of a data lake is effective only if you can ensure that important data assets are managed and secured throughout the organization. Given that data needs to be accessed by multiple users through several applications, it’s essential to have visibility into where the data is located, or being used, and to have fine-grained access control of the data. Attempting to deploy disruptive technologies, such as cloud, mobile, or analytics, without leveraging a converged data management system as the underlying platform will result in redundant systems, processes, and data.

Why Is a Data Platform Needed?

A converged data platform combines data management and application processing technologies to enable the creation of intelligent applications. That means easy ingestion of any kind of retail data–including sales data, customer traffic in stores or on websites, and mainstream and social media–into a single platform that scales to petabytes, and fast, efficient processing of the data in the same platform. And that’s where the MapR Data Platform comes in.

What’s unique about the MapR Data Platform is that it enables retailers to build a data fabric that addresses all the data silos and allows seamless data access around the globe. Think of this data fabric as the underlay for your applications, interweaving systems to store, manage, process, and analyze massive amounts of diverse retail data. The MapR Data Platform is the underlying robust and scalable platform that powers this fabric.

Another unique aspect about the MapR Platform is that it uses a global namespace, which greatly simplifies data management and access by giving it structure. With a single global namespace, IT can centrally manage permissions and access to data through a single pane of glass, and application developers, analysts, or store associates have a unified view and access of data, regardless of where the data physically resides.

The MapR Data Platform comes with built-in storage (MapR XD), real-time database capabilities (MapR Database), and an event streaming system (MapR Event Store), and easily integrates with Apache ecosystem tools. With this single, powerful platform, retailers can use data in real time to focus on the seamless experience of customers.

Here’s How It Works

I recently had an experience at a local Nordstrom store that shows how a holistic data and analytics strategy can lead to happy, loyal customers. At the store, I found the same blouse I had saved in my online shopping cart, and proceeded to checkout. After swiping my credit card, the store associate noticed a small hole on the sleeve while folding the sweater neatly on the counter. Unfortunately, that was the last sweater they had in that store. With confidence, she immediately checked their online inventory and inventory of other stores. When she found the same sweater in my size in another store, she asked if I would like to complete the transaction. With free shipping to my home, I happily said yes!

What makes Nordstrom stand out is that they tightly integrate all parts of their business with technologies that ultimately serve the customer. They make the shopping experience frictionless by keeping inventory updated in real time, empowering their staff with information, and unifying and tracking orders across all channels.

Other retailers can learn from Nordstrom and implement a digital strategy that makes the right data accessible and simplifies processes.

With MapR, retailers are empowered with capabilities and tools to unify and track all orders and keep inventory across all channels up-to-date. Tools such as the Network File System (NFS) protocol let you easily pull together data collected from point of sales transactions, inventory status and pricing, competitive intelligence, social media, and customers. In the case of streaming data, MapR Event Store (event data streams) can be used for collecting data such as weather, world events, and logistical data. When these event data streams are collected, Apache Spark can be used for real-time analysis of potential logistical impacts and rerouting of inventory.

Spark provides an API-powered toolkit, which data scientists and application developers can incorporate into their applications to rapidly query, analyze, and transform data at scale. Spark’s ability to store data in memory and rapidly run repeated queries also makes it a good option for training machine learning algorithms for predicting supply chain disruptions.

It’s not enough simply to pull orders and inventory together. Store associates must have easy access to the information in order to produce the best experience. With interactive SQL query tools like Apache Drill, retailers can use a wide range of visualization tools to explore, analyze, and visualize data in minutes. Apache Drill provides access to data on the MapR Data Platform through standard database access protocols, ODBC, or JDBC.

With MapR supporting your digital strategy, your customers can conveniently use any channel to shop and receive a consistent experience.

Become a Leader with the Right Technology Investments

The time is now to leverage these technologies. If retailers don’t take advantage of a converged data platform to store, process, and learn customer behavior online and offline, they will not be able to answer simple but critical questions, such as:

  • Why is she shopping at my store?
  • Why is she shopping at competitors’ stores and what for?

As competition gets tougher, online-only stores are increasingly seeking to open brick and mortar stores as another way to reach customers. Amazon is a great example of this shift. The company is making a big move into brick and mortar retail by agreeing to purchase organic grocery giant Whole Foods. As a loyal customer of Amazon, I appreciate the effort they put into learning about my habits and behaviors, making my shopping experience pain-free. Although no one is certain what Amazon’s purchase of Whole Foods means, I’m ready to experience another level of engagement in their stores.

Technology is advancing at a rapid pace, and it will only keep getting faster. Let’s take advantage of the digital advances and integrate data-driven insights into processes.

In my next blog, we’ll look at how some of our customers have applied data analytics in their operations to enhance the customer experience.

Additional Resources

This blog post was published July 20, 2017.

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