RPA, Analytics and Cloud: The New Game Changer in Customer Analytics
Emerging on the scene about 18 months ago, RPA’s initial appeal was the ability to reduce costs by automating more than 40 percent of routine and repetitive back office work traditionally performed by humans. RPA applications apply rules and logic to quickly and accurately execute routine and repetitive tasks such as month-end close, reconciliation, accounts receivable and HR compliance. These “swivel chair” processes that require entering the same data multiple times into different systems or applications are ideally suited to RPA functionality.
Beyond freeing up people from these traditional tasks and saving time and money, RPA is adding business value by enabling retailers to unify data from disparate systems and gain a more holistic view of the customer. Since today’s consumers pass through multiple channels on their path to a purchase, retailers have had to analyze data from multiple sources in order to personalize their shopping experiences. This requires analyzing huge volumes of data to predict and identify a buyer’s preferences, and then matching those preferences to available products, prices and delivery options. Retailers who have long struggled to gain insights from huge volumes of siloed big data can now apply RPA tools to rapidly process that data by linking multiple standalone systems, without the need for duplicate data input or analysis. By gaining key sales, inventory and customer data across different channels, merchants can execute their omni-channel initiatives more effectively.
According to digital marketing agency, AgilOne, more than 70 percent of consumers expect personalized experiences with the brands they interact with. Yet achieving this personal connection has been a challenge, as retailers have struggled to properly segment consumers and ensure that specific customers receive the right promotions, coupons, loyalty programs and mobile messages, based on their buying patterns and digital footprints.
The data collection and processing capabilities of RPA are helping retailers address this challenge by enabling more effective use of advanced analytical tools. By applying data centralized from multiple sources, retailers can now determine buying patterns, customer preferences and personalize the experience so that every consumer feels like he or she has a personal shopper to guide them through the store and offer expert advice. For example, to encourage in-store shopping, smart retailers are tracking a consumer’s digital footprints online and making his or her interests available in- store seamlessly. Additionally, recognizing that navigation in-store must be as easy as it is online, retailers can ensure that nothing that is available online cannot be found in-store.
In addition to RPA and advanced analytics, cloud-based computing is another key element empowering the new era of shopping engagement. The cloud allows retailers to scale quickly, store and access data from anywhere and get real-time insights into various aspects of their businesses. The value proposition of cloud is based on standardization, best practices and high-value delivery, and an opportunity to transition away from expensive, customized legacy systems. The cloud is ideally suited for specific capabilities like sales force automation and customer relationship management, and while some customers remain hesitant to use cloud for distribution and supply chain-type applications that support critical operations, evolving contract mechanisms and security standards are addressing traditional fears around cloud reliability, security and control.
The challenge for a retailer – or any enterprise – moving to the cloud is that the highly customized systems the cloud will replace are deeply entrenched, making a “rip and replace” strategy potentially risky. Another issue is managing organizational inertia and battling the “but this is the way we’ve always done it” syndrome. For many retailers, an optimal approach to cloud is a step-by-step transition, as part of a broader, long-term sourcing strategy guided by effective change and vendor management, communication, governance and transition processes and organizational design. While the retail industry has been slower in moving to the cloud than other industries, those who have made the transition are recognizing the key benefits of standardization, flexibility and scalability.
The advent of RPA, combined with analytics and cloud adoption, is emerging as a powerful triad in transforming the way retailers understand and engage with their customers. As progressive retailers embrace the nascent field of RPA and build it into their customer engagement strategies, stay tuned for an even greater shopping experience.
Jeff Seabloom, Chief Chief Revenue Officer, Alsbridge, is a leading technology and sourcing executive with demonstrated success in driving revenue, profit and shareholder value, as well as managing large and complex engagements in global enterprises involving the integration of people, processes and technology. During his career, Jeff has worked with +$100B enterprise software and technology organizations, including Oracle, i2, Manugistics and Hewlett Packard. An early pioneer in the ERP and supply chain markets, Jeff has continued as a student of how these areas can benefit from emerging technologies such as cloud and Robotic Process Automation.