Research study after research study have all confirmed one simple truth – the explosion in consumer access to digital channels is having a profound impact on what products consumers buy and how they buy them. The proliferation of digital devices and channels have forever changed the shopping paradigm and are impacting almost every phase of the typical shopping journey, from research and awareness all the way to post-sale service.
Along with the explosion in digital channels, there is also an explosion in data. While most would welcome this additional insight, the reality is this data explosion is a double-edged sword. If implemented correctly, it can give consumer-focused organizations a massive competitive advantage. However, if implemented incorrectly, it can result in frustrated business users, failed projects and, even worse, lost customers. Taking the time to develop a customer loyalty strategy can reap significant benefits and help move the needle in today’s ultra-competitive retail environment. Some of the biggest opportunities include the following:
Creating a consolidated view of the customer. Many organizations have made considerable investments in building databases to house their customer information and associated campaign and analytic processes. Unfortunately, many of these solutions rely exclusively on data that the retailer has within its enterprise and fail to leverage the wealth of information available about these same consumers in the social space. To address this challenge, many companies are adopting social login across their branded sites as well as within mobile apps. This gives the organization access to the consumer’s social profile in a permission-based manner and enables them to augment the information they already have available. After all, a typical Facebook profile has a wealth of information that can be used by marketers to build the “Database of Affinity,” which Forrester refers to as a “Holy Grail” for marketers.
Establishing in-store location analytics for sales improvement. Retailers know how impactful proper product placement can be within a physical store. Looking to improve sales, they have been trying for decades to understand how shoppers move throughout the store and its correlation to buyer behavior. Unlike the physical store, in the e-commerce world retailers can analyze purchases relative to behavior in infinite detail. Unfortunately, the same thing just hasn’t been possible in the brick and mortar world. Retailers want the ability to track shopper behavior in the physical world, understand where buyers are spending the most (and least) amount of time in the store, and how that relates to their purchasing decisions. The good news is that the rapid adoption of Apple’s iBeacon technology and similar cell phone technologies will allow retailers to track shopper movement throughout their stores. Of course, this needs to be done in a permission-based manner and will require the consumer to download the appropriate app and give the merchant permission to track their movement through the store. Once activated, the retailer can then analyze the shopper’s movement and compare that to actual purchases in order to enhance product positioning.
Enable real-time mobile offers. Based on a shopper’s history, current shopping basket, and current in-store movements, suppliers can deliver targeted offers during the shopping experience, at checkout, or even post-visit for use on future shopping trips. Furthermore, as more consumers use their smartphones to pay instead of using cash or a credit/debit card, this scenario becomes even more feasible. One interesting and emerging example is within the quick-serve restaurant (QSR) space. In addition to supporting eWallets such as Apple’s iPAY, numerous QSR’s have rolled out their own apps that allow consumers to order and pay for their food via their mobile device. With this infrastructure already in place, the next logical step will be adding an analytics layer to deliver cross-sell/upsell suggestions as the order is being made.
Consumer-based Internet of Things. More and more home devices, such as thermostats, televisions, water heaters, video streaming devices, home routers, home security sensors, and garage door openers, are transmitting a stream of data back to the manufacturers. In most cases, the device manufacturers provide apps that the consumer can use to monitor and/or control the device. In the future, it is quite possible that new standards will emerge that will allow consumers to use a single app to control multiple in-home devices from a single app. When this occurs, there will be tremendous opportunity to leverage this information to not only learn more about consumers’ preferences, but also to deliver targeted, relevant messages to them. These messages could be marketing focused, informational in nature, or both.
While the opportunities are endless, the needs of each consumer-focused organization are, in fact, unique. However, two distinct similarities have emerged across nearly all use cases:
- The emergence of new digital/mobile technologies and/or social channels that have reached critical mass only within the last decade.
- The generation of massive volumes of data that can be analyzed to better understand the business, sometimes even in real time.
Suffice to say that traditional data management architectures are not optimal for each of these new digital use cases. Analyzing all the data coming from the digital space requires new solutions, and many organizations are considering enterprise Hadoop solutions instead of traditional RDBMS technologies. As a matter of fact, the thought process is evolving to “Why not Hadoop?” from the earlier “Why Hadoop?” mindset. In addition, there is a rapid emergence of ACID-compliant RDBMS on Hadoop platforms that allow end-users who are comfortable with SQL to use a familiar interface. This allows IT to start using Hadoop in a way that immediately drives value, such as reducing costs by hiding some of the complexities typically found in Hadoop.
Emerging use cases such as those described above, combined with a rapidly evolving technology landscape, are creating tremendous opportunities for organizations to differentiate themselves based on analytics. With that in mind, it is critical for organizations to evolve to the changing digital landscape and define their analytics strategy so they aren’t left behind by the competition or, worse, abandoned by their customers.
Duane Lyons is Practice Lead, Retail/CPG and Manufacturing at Clarity Solution Group, a data and analytics consulting firm.
Subscribe to Data Informed for the latest information and news on big data and analytics for the enterprise.