Generative AI is gearing up to transform the retail sector and its experiences through the automation creation of online storefronts to make it a more reliable means for the customer experience journey. But is this time best for retailers to get hold of this evolving technology?
We all know what made the retail industry grapple with this technology, certainly after the recent advances in the area of Generative AI, which can perform a lot of stuff such as generating images, videos, audio text, and code that never existed before.
Advanced generative AI systems can be utilized to optimize any function in the retail industry. It helps through its conversational and creative abilities, which includes
- Customer service
- E-commerce transactions
- Marketing creative
- Website navigation and much more
As far as the global consumer survey is concerned, consumers are overwhelmed with the use of Generative AI tools to make their e-commerce shopping experiences better and they are more likely to see new developments coming up to this.
"Are consumers Ready for Generative AI?" - Chirpn has initiated a survey of consumers in different regions to see how GenAI impacted. With brands in mind, this new technology can help generate a stream of possible revenue and, foremost, customer experience.
- Out of 87% of shoppers who have used GenAI tools are overwhelmed, and most likely, they want to know what more this can bring to their shopping experience.
- Out of 27% of shoppers, they are confident about the potential of GenAI's ability to bring improved real-time price comparisons and deal alerts along with overall online search results.
- Out of 25% of shoppers, they use the virtual Generative AI shopping assistant to curate and compare products to their lists.
- Out of 40% of shoppers who have used Generative AI previously, they believe the tool is worth everything.
Despite this, integrating conversational AI into the workflow and customer journeys creates a steep learning curve for employees, customers, and brands. But there are also risks associated with this evolving technology, such as inherent biases, lack of trust in customers, and often comes up with factual inaccuracies. However, this will take some time and effort from the retailers to deal with.
“How can we use this technology to catapult businesses into the next area of growth and comprehend inefficiencies and costs? And how do we do it ethically?”
What Generative AI Is - and What It Isn’t
Generative AI is a general term that refers to models of artificial intelligence that can generate new data samples similar to training data. Poems, factual articles, travel plans, motivational speeches, and answers to any prompt or question you give can be output from open-source models like GPT-4 and Google's Bard that use datasets as large as the entire internet.
Nevertheless, generative AI is not limited to chatbots, as initially evidenced by the breakthrough of ChatGPT's giant language model. Modern generative AI models can generate an infinite amount of contextualized content in any format. Research findings show no difference between text, code, and images created by artificial intelligence and those produced by people.
Generative AI Uses Probability, Not Human-Like Reasoning
Generative AI systems such as GPT-4, which is used to power apps like ChatGPT don't produce text by using logical reasoning or with any kind of human-like intelligence. Do they just generate answers that are most likely to be "correct" given the context as established in the dataset, i.e., what would be the next possible step in this sequence?
For example, let's say a store wanted to use AI to create personalized ads for customers with different demographics but no additional programming was done so a generative language model would simply use a probability distribution to predict what should come after based on some prompt and then output an ad that seems real.
How Retailers Can Take Advantage of Generative AI?
Conversational commerce: generative AI and the customer experience
Generative AI is quickly changing the way customers interact with retailers online.
The modality of online shopping interactions, and e-commerce interfaces themselves, may soon change. You're going to see a much better quality of search with more tailoring, customization, and efficiency.
Conversational Product Search
While most shoppers can use search bars to find the products they’re looking for, conversational commerce (powered by generative AI) accelerates the search process, potentially increasing conversion rates and average basket sizes for retailers.
Brands are implementing A/B tests of conversational product search bars to assist customers in finding specific products more efficiently, like searching for all of the ingredients in one recipe through a question or asking about each item of clothing in a full outfit.
Chatbot Support
Customer service chatbots powered by generative AI can reduce staffing needs and support agents by providing complex and engaging responses. While many chatbots currently have only 15 or 20 decision trees, advanced generative models open the potential for chatbots with infinite paths of conversation.
Retailers also have the opportunity to play around with conversational styles that match their brand and personalize interactions for customers, changing the negative perception of automated chatbot features.
Cross-selling and Upselling
Finally, generative AI can provide more intelligent shopping suggestions based on search history and other customer demographic data. While retailers currently use analytics and tags to monitor and enhance consumer experiences, generative AI could more automatically suggest the next logical purchase or step in a customer journey, without manual journey design.
Automated Content Generation: Generative AI and Back-end E-commerce
Front-end customer experience can be improved with the help of generative AI. Undoubtedly, it is also capable of automating workflow at the back end.
Even though creative outputs generated by generative AI models lack intricacy and subtlety, new systems are now able to effortlessly automate elementary content tasks on a human scale.
"Generative AI can accelerate commerce content creation," says many experts. "The next versions may probably have greater transparency and fewer mistakes; however, the information contained therein should still be checked for authenticity."
There are several e-commerce scenarios in the back office where generative AI already helps to create content.
Consistent Product Descriptions
Stores that existed before, use AI systems to test a variety of product descriptions and find the most effective one. Nowadays, stores use AI technology, which assists in writing consistent product descriptions for many sellers.
This allows for third-party sellers who often have widely disparate product information from different sources. Content writers do not need to hire people to rewrite such descriptions any longer; they can use AI to generate standard, accurate, and brand-friendly content.
Similarly, using artificial intelligence (AI) could enable businesses to analyze customer feedback on products, which will help them improve their listings and marketing strategies, thus enhancing the overall shopping experience.
Personalized Product Images
Product image creation is another area that generative AI can improve on, as it used to require photographers, designers, models, and other personnel. Using AI, stores can create tailored product images for clients by simply using text descriptions and image data from the past.
For instance, an athletic wear shop might generate an image of a collegiate student in a sports jersey on the college grounds for its 19-year-old client. Should customers give more personal information or their suggestions, AI could display items in different environments, such as a digital body of the customer.
Auto-fill Transaction Flows
The same usage occurrence could still work generally for full web pages, which would enable sellers to be able to lead their suppliers and purchasers through the buying process at an even earlier time. For now, most e-commerce site flows are canned or can only be adjusted based on simple elements like channel or time zone.
Through generative AI, retailers can provide short-form site experiences for every customer as well as every supplier, filling in product or store or customer information automatically at the back end.
Secondary Decision-making: Generative AI and Supply Chain Optimization
What about use cases other than those in the consumer interface? Many different types of human-to-human interactions and human-machine interactions can be improved with the talking capabilities of big language models.
The retail space has not yet seen much investigation into this one usage instance. The supply chain is an area that has not been explored as a use case that much. Costs could be lowered using generative AI as a mode of communication, thereby providing supply chain leaders with smoother, more efficient experiences, including faster decision-making at secondary levels.
The Drawbacks of Generative AI for Retailers
Despite the above examples of success, deploying generative AI processes and experiences in the early days of the technology is not without its risks and challenges, which retailers should be mindful of.
The person behind ChatGPT once remarked that it was a “mistake to be relying on it for anything important right now” because it tends to provide strikingly believable yet nonfactual answers without vetting or validating them—a capability that takes significant investment to code in.
ChatGPT's creator also says that "regulation will be critical and will take time to figure out." Before industry regulation, merchants aiming to create their own generative artificial intelligence models need to institute AI literacy sequentially and formulate ethical guidelines for staff members to avoid negative customer reactions concerning defective outcomes from generative AI.
How Generative AI Will Change the Retail Industry?
Although the initial excitement about generative AI may have waned, the traditional drop in excitement for new technologies does not mean that they are not valuable or relevant in the long term. Quite soon, in some years' time, generative AI could be central to e-commerce encounters.
Irrespective of their decision to include generative AI in their stores and businesses or not, retailers should plan for this possibility. What other thing?
Getting Started with Generative AI
“So, which segment of the business should retailers begin from if they want to try out some of their earliest engagements?”
Most people should start with chat commerce.
"It is how you would first enter into this area without going beyond your ecosystem," Mazumder tells me. "Apart from that, there are some questions that retailers will need to ask themselves to prioritize new use cases."
Where do salespeople spend most of their time?
What are the biggest missed opportunities for upselling or cross-selling?
How can staff access important internal information more effectively?
Where do customers and sales associates have the highest levels of frustration?
What are the frequently asked clients’ concerns?
