Retailers must use AI to automate and deliver better decisions and make it possible for associates to be customer experience differentiators. Multichannel retailers are facing an existential crisis. Consumers’ buying behaviors and lifestyle choices are changing. Competitive pressures from disruptive pure-play e-commerce players are causing radical changes to antiquated business models, driving down prices and driving up costs. Ultimately, the impact of AI on retail will be manifold more than that of Excel’s reign. At first, by automating paper tasks and reducing the need for key punch or data entry, Excel provided some savings, but overall, more resources were required to, and certainly did, extract significant value from data using Excel. Retail corporate headquarters now employ hundreds or thousands of associates who spend the majority of their working day manipulating data in spreadsheets. Much of this work is repeated or reinvented week after week as they work to evaluate performance and solve problems, while also reacting to directives from top management. Consistency and quality are suspect, since from department to department, the knowledge base of the worker is varied. Overall, the crisis in retail, combined with increasing costs and a lack of consistent quality analytics, are drivers for change.
Emerging AI trends in retail:
- Customer insights and adaptive journey — Through natural-language processing and machine learning, AI systems can learn from the huge data created by customers, generating behavioral/usage insights and providing direction for product owners/retailers, which helps them gain a better understanding of their consumers and customizing their products, designs and shopping experiences around unique user needs.
- Chatbots and virtual personal assistants (VPAs) — Retailers are striving to achieve fully integrated omnichannel presence, focusing on personalization and seamless customer experience with AI-powered solutions.
- Predictive analytics for marketing, merchandising and hiring — Prescriptive and predictive modeling based on historical sales, marketing campaigns, website discounts, events and competitor data makes the marketing campaigns much more effective, which helps a firm to grow, engage and convert the audience, along with hiring the best candidates.
AI enables large retailers to create customer-centric experiences:
Gartner clients can read the entire research publication: Algorithmic Retailing: Using AI to Drive Smart Automation
Read Complimentary Relevant Research
Implementing Customer-Centric Merchandising and Marketing in Retail Primer for 2018
Retail CIOs must position the business to leverage algorithms for unified retail commerce supported by a foundation of high-quality customer...
View Relevant Webinars
Program and Portfolio Management Leadership Vision for 2018
Program and portfolio management leaders must look across all ongoing and planned projects to develop recommendations for management...
Comments or opinions expressed on this blog are those of the individual contributors only, and do not necessarily represent the views of Gartner, Inc. or its management. Readers may copy and redistribute blog postings on other blogs, or otherwise for private, non-commercial or journalistic purposes, with attribution to Gartner. This content may not be used for any other purposes in any other formats or media. The content on this blog is provided on an "as-is" basis. Gartner shall not be liable for any damages whatsoever arising out of the content or use of this blog.