-
Generative AI–powered productivity enhancements and cost savings could boost retailers’ already thin margins
-
Personalized shopping initiatives, such as AI-powered conversational shopping assistants, could increase a retailer’s revenue by 5-10%
-
AI tools for content generation, software development, and employee support can increase productivity by up to 25-40%
Retailers have had access to generative AI (gen AI) tools for more than a year now time enough for almost all to see the new technology’s undeniable power. New research from Bain & Company shows how generative AI at scale will rapidly improve productivity, easing the industry-wide pressure on margins through an array of cost savings.
“From conversational search to personalized apps, gen AI is reshaping the retail landscape in a way that is going to be even faster and more transformative than the smart phone or the internet,” said Mikey Vu, partner in Bain & Company’s Retail practice. “A year into their journey, retailers have enjoyed some early successes. It will be critical for them to scale these use cases, with a focus on ROI, to keep pace with the evolving expectations of shoppers who are rapidly incorporating generative AI into their daily lives.”
Personalized shopping experiences
One highly promising use case centers on personalizing the customer experience through tools such as AI-powered conversational shopping assistants, enhanced search, and localized shopper recommendations. Bain found these use cases at scale have the potential to increase a retailer’s revenue by 5-10% overall. Underscoring this point is research from Bain showing consumers trust AI for personalized shopping recommendations more than any other use case they were asked about.
Automated marketing content generation
Retailers are likely to have experimented already with using generative AI to enhance and streamline their marketing efforts—with promising results. Bigger rewards now lie in store for executive teams that wrap these initiatives into a broader push to automate generation of marketing collateral in areas such as translation and repurposing of content, social media, and the creation of dynamic and personalized landing pages. We estimate that this broader family of use cases can deliver marketing productivity gains of 30% to 40%.
Supercharged employees
Bain estimates generative AI enhancements that reshape the way retail employees work on the front line, in warehouses, and at HQ could boost productivity up to 25%. This includes automated inventory checks and restocking alerts, and search assistants for real-time problem resolution.
The first year of the generative AI era has also caused retailers to think hard about its long-term impact. One worry is that big tech companies will muscle in on the early stages of the shopping journey, such as inspiration and curation. Another fear is of being shouldered aside by digital insurgents that are simply faster at implementing generative AI in a compelling way.
Read More:Â SalesTechStar Interview with Eran Hollander, Chief Product Officer at HungerRush
To fully capitalize on the promise of AI, retailers must ensure that their rollout passes tests in these three areas:
- Change management. Amid all this change, retailers need to note that jobs may need to be entirely redesigned, both on the front line and at the corporate level, and improvements made now should facilitate future evolution as well.
- Democratization. To successfully move from experimentation to scaled delivery, retailers need to put gen AI tools in the hands of all their employees, not just those in the tech department. At the same time, however, they need to centralize gen AI–related capabilities to avoid duplication of work and other inefficiencies.
- Talent. As best practices in gen AI implementation will often date quickly, retailers must help workers continually update their new skills in tech-related roles and across the organization by focusing on upskilling existing employees.
