August 31, 2023

5 Considerations to Adopting AI in Retail


ai in retail

Over the past year alone, it seems like almost everyone is using or at least talking about Generative AI. From college kids writing term papers to large corporations looking to scale fast, AI is just about everywhere these days. While 2023 might as well be renamed the “Year of GenAI,” many retail and other industry leaders want to dip their toe into the AI in retail pool, but aren’t sure how or where to start. 

If this is you, you’re in good company. It seems like there are new retail AI solutions each week. It’s normal to feel overwhelmed by the sheer volume of AI options promising to solve countless problems. 

Collaboration comes first when applying AI in retail 

AI adoption is inevitable. But, it can be hard to decide which business use cases to focus on first, especially as budgets become more stringent. Chances are there are also internal obstacles to AI adoption that retail brands need to overcome. For example, many retailers worry that AI will replace their team or conflict with their commitment to sustainability. But, the truth is contrary to these commonly held beliefs. Recent research from Upwork on Generative AI found that 49% of hiring managers will hire more independent talent and 49% will hire more full-time employees. AI needs humans to train it, supply new ideas, and set boundaries. For mission-based brands, AI helps achieve scale, which brings the brand’s message or mission to new audiences.  

The most impactful AI strategies put collaboration between humans and AI first. A 2023 Persado survey of 250 experienced retail marketing professionals found that combining human creative talent with AI-generated language and insights optimizes digital marketing effectiveness.

No matter how a retail brand begins their AI journey, human and AI collaboration should be at the center of AI adoption. While humans bring creativity and critical thinking skills to the table, AI can quickly process large amounts of data and perform more repetitive tasks. 

5 considerations before implementing AI in retail

There are countless ways retailers can begin using AI. From AI chatbots, to copy and image creation, to virtual try-ons, and even product and packaging design, the options for Generative AI in e-commerce alone are endless. Much of the e-commerce personalization software and cart abandonment tools available to retailers also use AI. 

With all of the options out there, where do retail teams begin? We outline five key considerations to look at when implementing AI in retail in today’s market. Getting started with AI that checks these boxes will make a retailer’s digital transformation toward AI more seamless and drive the most ROI on the path to more and better use of AI. 

1. Historically proven 

When first implementing AI, retailers should begin by considering solutions that already have a track record of delivering ROI for retailers. Solutions that have already shown their value and useability present less risk for retail and e-commerce teams. When considering AI solutions, look for applications that already work successfully with brands similar to yours.

Some examples of proven AI solutions for retailers include: 

  • Klaviyo offers AI tools to power email and SMS attribution, behavior forecasting, and more. 
  • AI-powered chatbots such as LivePerson or Simplr have a history of driving conversions and providing both pre and post sale support to top retail brands. Simplr is unique in that it provides a conversational chatbot alongside a Human Cloud Network of high quality customer service agents, backup in case the customer query requires a human touch. 
  • Trendalytics, a product intelligence and trend forecasting platform powered by AI, pulls data from Google Trends, social media, and the general e-commerce market to predict which trends are emerging to help retailers optimize how they buy and price products. 
  • Bloomreach Discovery drives revenue through industry-leading AI-driven product discovery. 
  • Persado Motivation AI is a specialized class of enterprise Generative AI used to develop digital marketing messaging that drives conversions. Offerings include Dynamic Motivation, which reduces cart abandonment by serving personalized language in the online cart, and Essential Motivation, self-serve Generative AI that creates high-performing digital marketing language across channels and is informed by more than ten years of Fortune 500 insights from real digital marketing campaigns. 

2. Simplicity  

Start by identifying the most immediate problem the team is looking to address and then consider which GenAI solutions can solve it. Make sure the goal is attainable and the ROI straightforward and quantifiable. When assessing Generative AI, some key capabilities to look for in order to achieve optimal results include automated experimental design, a motivation-aware knowledge base, and integrations for fast time-to-value. To learn more, check out our full report on the 5 Capabilities of Generative AI for the Enterprise

Once you have some momentum and impactful results, you can move on to the next area of interest. Retailers want to be able to measure the impact of individual initiatives to prove the business value of technology investments to the C-suite. If you run multiple AI experiments at the same time without clear lines of impact between them, you won’t know for sure what worked. 

3. Low risk 

Retailers should make sure the AI solutions they start out with are low risk. Low risk AI solutions have the highest standards of enterprise security and compliance. They also don’t require a large initial investment in budget and/or resources to set up. Perhaps, they offer a trial period. 

4. Fast ROI

If it’s going to take months or even years to see ROI from an AI solution, it may not be the best solution to start with. Retailers have short term sales and conversion KPIs they need to hit. So retailers new to AI should look to AI-powered solutions designed to drive ROI quickly. This way, teams can see almost instantly what is working or isn’t working and adjust their strategy accordingly. This allows retailers to learn how to use GenAI more efficiently and effectively in a shorter period of time. It also opens up the budget for additional AI more quickly as retail teams report positive results.  

5. Flexible billing options 

Retailers’ needs change fast. Budgets change even faster. So the ideal AI for retail brands in the testing phase is that the product can easily be turned on or off with no penalties. Look for solutions that have month-to-month billing options or bills based on use. Sign a long term contract once you have gotten the promised better results.

AI is transforming the shopping experience. Why? Because it’s essential for retailers looking to achieve omnichannel personalization, to bring in-store experiences online, to make real-time data-driven decisions, and more. Impactful online shopping experiences come from truly understanding shoppers and using those insights to bring added value to customers. AI in retail makes all this possible at scale. 

For more on how to make an impact through AI adoption, check out the CMO’s Guide to Generative AI

Top retail brands such as Kate Spade, Gap, and Marks & Spencer trust Persado Motivation AI to deliver digital marketing messaging proven to drive conversions and fast ROI – with flexible billing. Request a risk-free trial to explore more with zero commitments or constraints.