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
Predicts 2019: Data and Analytics Strategy
Data and analytics are the key accelerants of digitalization, transformation and “ContinuousNext” efforts. As a result, data and analytics leaders will be counted upon to affect corporate strategy and value, change management, business ethics, and execution performance.Read Free Gartner Research
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