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Can AI Deliver on the Hype Promised for Shopping?
A global survey from the IBM Institute for Business Value found that only 9% of consumers are content with in-store shopping, and only 14% are content with online shopping. Emerging shopping technologies were found to not be living up to their hype.
The survey of 20,000 consumers across 26 countries found that over half of respondents are eager for artificial intelligence (AI) enhancements like virtual assistants (55%) and AI applications (59%) as they shop. Personalization and targeted offerings were also found to hold appeal, with 52% interested in receiving information, offerings, and advertisements from stores that are relevant to their specific interests.
However, the virtual assistant experience was found to be wanting. About one-third of those who have used virtual assistants are satisfied with the experience, with nearly 20% so disappointed they don’t want to use virtual assistants again.
At the store level, consumers surveyed want a greater variety of available products (37%), more information about products (26%), and faster checkout (26%). Showing the appeal of a digitally integrated experience, 65% are supplementing their in-store experience by using mobile apps while shopping.
Online, challenges cited in the survey included finding the products they want (36%), not having enough information about products (33%), and dealing with a cumbersome return process (33%).
IBM’s survey also found economic concerns, particularly inflation, to be influencing consumer’s dismal view on shopping expectations. Of the respondents, 62% cited price as a top reason they switch stores or brands.
Part of the technology challenge is a reluctance by many consumers to share personal data to take advantage of AI’s data-mining capabilities.
A survey last year from CI&T, the software and digital consultancy company, found that 58% of consumers “believe data sharing is necessary for brands to achieve personalization,” but 42% think retailers should be able to create a personalized shopping experience without gathering any personal information from consumers, whether intentionally or without permission.
The survey further found wide disagreement about what personal data was appropriate to share. The four pieces of information consumers are most open to retailers learning about are gender (14% openness), the city they live in (14%), how much they are willing to spend on an item (11%), and age (11%).
Salesforce’s Connected Shopper Report based on a global survey of 1,125 retail executives last year found that 92% of retailers are investing in AI more than ever to improve shopping experiences. Of the respondents, 59% are using AI to help store associates make product recommendations to shoppers, 55% are using AI to create a conversational digital assistant to help online shoppers find products, and 51% using AI to create personalized product bundles.
On the downside, Salesforce’s study found the top barriers to retailers’ retention and engagement efforts overall to be “a lack of customer insights for segmentation and targeting, followed by an inability to respond quickly to market opportunities.”
Discussion Questions
Have you become any more or less confident over the last year that artificial intelligence will elevate the in-store and online shopping experience? Where do you see AI exceeding as well as falling short of expectations as a shopping tool?
Poll
Loading …BrainTrust
Melissa Minkow
Director, Retail Strategy, CI&T
Paula Rosenblum
Co-founder, RSR Research
Solidly unchanged; and what am I unchanged from ?? Not expecting much. Oh, I’ve no doubt it will improve shopping – the experience – just that it won’t, indeed probably can’t, live up to the hype. Most of the problems with shopping – ranging from poor fit to inattentive sales staff to having your package stolen – are not ones I see AI helping much with. What we’ve seen so far, like linking searchs together under some single phrase, underwhelm me; admittedly it’s early, but stilll…
A.I. will eventually elevate the in-store experience, but despite the fury of activity, we’re still in the early innings of its evolution and in specifically how it gets implemented at store level. As the CI&T study revealed, it’s paradoxical that consumers want more personalization, but are reticent to share their personal information to get it. Personalize is a perfect use-case for A.I., but it can only be achieved with personal data to inform recommendations. However, there are myriad ways A.I. can be leveraged for retail operations from labor scheduling to inventory management, and so retailers should consider prioritizing these first.
Our data shows that consumers are skeptical of AI’s ability to improve the shopping experience, but when we ask them about different use cases, without telling them it’s AI that would do it, they believe it would make the experience better. So, it’s up to brands to leverage AI in a way that keeps consumers comfortable. There is no doubt AI will play a large role in the future of retail.
In the tech-bubble, AI is the be-all and end-all. Back in the real world among regular consumers people are not thinking about it all that deeply, and many are not thinking about it at all. I have no doubt that AI will play a bigger role in some aspects of retail, but it will be integrated into everyday functions such as answering questions, giving recommendations and so forth. What most consumers want from physical retail is a good experience. AI may be able to help with aspects of that, but there’s a lot of basic, everyday stuff that also needs to be focused on in which AI will play no role at all.
I found the following article interesting – basically retailers telling is that AI is not a savior for the labor shortage and that human talent is still vital. A good bit of balance in a world where there is too much AI hype:
https://www.glossy.co/fashion/great-talent-is-still-critical-retails-labor-shortage-cant-be-filled-by-ai-execs-say/
This article and many others like it, keep trying to paint AI as a savior to many retail problems, when the true solutions to most retail issues still resides in not fulfilling the retail basics from the beginning. Filling out of stocks, lowering prices, offering easier shopping (no lines), and better managing the consumer’s access to products within the store/online. Using AI to look for diverse solutions to obscure problems will not do this.
We are in the first inning of the game for the implementation of AI. Or the opening credits of the movie if you will. And I predict it’s going to get messy, very messy on the road to a smooth and seamless integration with shopping and buying. Sure, I’m old school, but at the same time I’d also appreciate anything that helps me shop and buy faster and smarter. But instead, I fully expect to be bombarded with “helpful” suggestions and ads and marketing and “personalized” whatever. It could very easily get to be too much of a good thing very quickly. As an individual, I can only hope for easily accessible opt-in and opt-out options.
AI has made incredible progress, especially in the last year. The insights and support to retail that AI can provide today is just scratching the surface. It will allow for better personalization in the form of understanding an individual customer’s habits, interests, buying patterns, and more. Personalization just got more personal!
For customers, it’s the same progress. AI will provide better suggestions based on the customers habits, interests, etc.
The future is now!
I am not sure that either the retailers or even the shoppers truly know what the ideal shopping experience is. We can execute survey after survey to determine the answer, but as Steve Jobs said, “A lot of times, people don’t know what they want until you show it to them.”
I am sure that AI will be a valuable tool in the shopping experience, but it will not be the determinant of what that ideal shopping experience is.
I’m with Craig. I think AI will prove to be HUGE in healthcare, and it has already been used in the supply chain successfully. Do I think it will help the in-store experience? NO. Do I think it will help the online experience? If the personalization is permission-based, yes.
We should not forget that the NY Times has sued OpenAI for “training” ChatGPT with the Times’ intellectual property. Everything must be permission-based, and permission-based means additional costs.
I think AI is profound. I do. When I have a complex question to ask I use ChatGPT, not Google. But retail still has basic rules of engagement. And retailers must work to reinvent large parts of their engagement models to please consumers without invading their privacy or “stealing” their information. I think back to Acxiom’s “About the Data” website, and how many wrong assumptions it had made about me because of one vacation, rather than my everyday life. Most people found it around 60% correct at best. Garbage in…still the same old story.
Disclaimer – I work for Microsoft and discuss these areas with customers regularly – points made here are my own views.
Artificial intelligence (AI) has the potential to significantly enhance shopping experiences, both in-store and online. AI’s successes already include personalization and targeted offerings, with great interest in AI-driven virtual assistants and applications. Shortcomings, however, are may appear with the dissatisfaction with virtual assistant experiences – perhaps based on frustration with older, less smart, versions.
Sharing personal may limit personalization capabilities. Retailer interest is strong, with some considering AI for product recommendations and digital assistants. Aside from consumer adoption, a key barrier many organisations face is access to the appropriate training data and ensuring that data security remains paramount.
Consumers want better product selection, help with choosing the item that meets their needs and they have price expectations. In store assistants can provide those services to an in-store shopper, but shopping online means that process needs to be computerized. If AI is the tool to develop that approach, it will used by brands and retailers to accomplish the objectives of consumer help. If AI is the wrong tool, it will not be used. The consumer does care about the technology, only the services.
AI is a strong tool for complex back office and supply chain opportunities, but on the customer side it should be applied and focused where there are obvious pain points in the shopping experience. Thinking like the customer must always be the place to start. Ask what hassles, extra steps and frustrations do they have? Saving time, finding solutions and making shopping truly about “me” will likely be the strong front runners.
AI is more than the latest innovation du jour. However, the hype is ahead of the necessary action to realize the promised customer benefits.
Most consumers dread grocery shopping. A recent focus group participant said, “I hate food shopping, rather abhor is a more appropriate description.” If AI, implemented by brands & retailers can address the many noted food shopping negatives, reality may supplant the AI hype.
Here is a interesting thought to consider, or to disregard as outlandish: Some experts say artificial intelligence will eventually eliminate 40 to 60 percent of US jobs. If so, how will these people earn enough money to shop the way they shop now?
In my opinion, my confidence in artificial intelligence (AI) improving the shopping experience has grown in the past year. It’s true that AI has the potential to enhance both in-store and online shopping through personalized recommendations and smooth processes. However, challenges persist, especially in virtual assistant satisfaction and data privacy concerns.
AI’s success lies in meeting consumer needs for product variety, information, and quicker checkout. It excels in creating personalized product bundles and assisting store associates in making recommendations. Despite these advancements, implementing AI faces obstacles like, a lack of customer insights and flexibility in responding to market changes. Although AI shows significant potential, continual enhancements are crucial to align with evolving consumer expectations and tackle existing challenges.
AI will absolutely have an impact. Let’s remember we are very early in this and as more use cases come to light and the technology catches up to the need, there will be impact. Doesn’t mean it will overtly do so, and in many cases, it is likely shoppers will have no idea AI is even part of the solution.
Color me very skeptical. Maybe in six, seven years. Maybe.
AI has already proven its value for retail innovation, especially in eCommerce applications. Its ability to parse data to deliver personalized search results and product recommendations based on intent and context far exceed anything possible from human intervention. What we’ll see more of this year is further integration of existing AI applications within brands’ tech stacks to enhance the customer experience.
Where AI currently falls short is a lack of transparency and customer understanding. For brands who are early adopters, many are implementing AI to improve the customer experience without explaining to the customer that the new experiences and features they’re using are powered by AI technology. For example, a customer might notice they’re getting more personalized, quality search results every time they visit a brand’s website without knowing that it’s because AI is powering those improved results and recommendations. Brands must better explain to customers what data it’s collecting and how AI is using it to improve their experience.
It’s less about confidence in artificial intelligence and more about understanding that AI can’t solve all the challenges facing the retail industry. Where AI excels is in enhancing efficiency, fueling innovation, and elevating the overall shopping experience for consumers and retailers alike. For consumers, AI-powered recommendation systems can analyze vast amounts of data – including past purchases, browsing history, and demographic information – to offer personalized product recommendations. This enhances the shopping experience by presenting relevant items tailored to each individual’s preferences and interests. For retailers, AI algorithms can forecast consumer trends and behaviors based on historical data, enabling them to anticipate demand, optimize inventory levels, and adjust pricing strategies accordingly. By leveraging predictive analytics, retailers can also minimize stockouts, reduce excess inventory, and maximize revenue.
There’s a disconnect between the practical ways consumers want AI (or any technology) to improve their buying or in-store experience and the exploration of new AI use cases by some technology vendors.
When a vendor asks retail executives for ways to improve shopping experiences, the responses are structured to reflect technology’s ability to impact. As the article references, retail executives are using AI to help store associates make product recommendations (59%), create an online conversational digital assistant (55%), or build personalized product bundles (51%). The challenge is that the in-store experience aggregates diverse activities and data threads that culminate in the store; it is a messy human problem, and no cookie-cutter solution or process can adequately address the variety of journeys.
Gen Z’s use of social media as a multi-experiential platform rendered marketing’s traditional linear “consumer” funnel obsolete. Similarly, retailers are looking for ways to understand consumers’ changing behaviors related to the in-store experience. We need to use AI more creatively at points of friction that matter the most to consumers and the ways they shop. Offering in-store excitement and theater works if the basics of having the right products in stock with an appropriate assortment range are in place; otherwise, the crafted experience will fall flat. Today’s customer journeys are many, with loops inside of loops full of inspiration, exploration, and sharing. They vary by context, situation, and an ever-shifting consumption identity. AI can help, but success requires a well-thought-out and connected journey that excels at every point of impact, especially in-store.