Retailers have the capacity to create a fine-tuned shopping experience for consumers based on personal information — but should they? Consumers currently do not feel comfortable sharing much beyond gender, what city they live in, how much they’re willing to spend on an item, and their age, according to a personalization survey conducted by CI&T in March 2023.
More than half (52%) of respondents said they prefer that a retailer personalize the shopping experience for groups of similar customers. 48% said they preferred that a retailer personalize the shopping experience to each individual.
Most customers (58%) said they believe data sharing is necessary for brands to provide a personalized experience. 87% of respondents want to be asked for their permission to collect personal data first. Only 13% said it was not important to them to be asked.
A significant portion (42%) of respondents said they do not believe sharing their personal information, whether intentionally or without permission, is necessary for a retailer to personalize their shopping experience.
CI&T, a software and digital consultancy company, surveyed 542 U.S. consumers in March 2023. Respondents were selected to be representative of the demographics of the U.S. population.
Consumers don’t want to share much information about themselves
Consumers are reluctant to share information beyond:
- Gender: 14%
- What city they live in: 14%
- How much they are willing to spend on an item: 11%
- Age: 11%
- Who they are shopping for: 10%
Only 8% said they’d be OK with a retailer knowing their shopping history at the retailer’s physical store, or their browsing history on the retailer’s digital channels such as a mobile app or website (7%).
Topping the list of what information consumers do not want retailers to know:
- Annual household income: 19%
- How large the household is: 12%
- Browsing history at this retailer’s physical stores: 11%
- Race: 11%
Consumers are more likely to share information related to what products they want to buy. When asked which of the following consumers wish retailers knew about them when shopping with the retailer:
- The sizes I usually fit in best: 17%
- The styles I prefer to wear: 16%
- The price point that is most aligned with how I spend: 15%
- What I’ve bought from them in the past: 13%
- The color scheme/schemes I prefer: 11%
According to survey author Melissa Minkow, director, retail strategy, “while there is sufficient demand for personalization, achieving it in the most-privacy-respecting way possible is imperative,” she wrote in the report.
While survey respondents said they wanted personalization geared toward similar groups of consumers rather than individual shoppers, 22% said they would share personal information in exchange for a product type, color or style developed just for them with the exact specifications they’d want. 21% said a search process that is quick and oriented to precisely what they are looking for would be an incentive to share data. And 20% cited a personalized price point.
“Consumers will gladly welcome ‘good’ prices,” Minkow said in the report.
Consumers want options
Respondents also said they do not want to miss out on options should they opt for a personalized shopping experience. 47% said they’d like to see the “same web page everyone sees, and then allow me to navigate to the type of item I’m looking for after I select a few filters,” such as price or color.
Only 15% said they’d want to see a retailer’s homepage with personalized options.
Categories that consumers said they would prefer to have a personalized experience:
- Apparel and accessories: 17%
- Personal care (body wash, razors, hair brushes): 13%
- Beauty (cosmetics): 12%
- Electronics: 12%
- Grocery: 12%
Human interaction vs. chatbot
Overall, consumers slightly preferred interacting with humans over artificial intelligence when it came to:
- Apparel/accessories: Fit and sizing experience.
- Electronics: Differences between brands.
- Grocery: Recipes and brands, or finding the least expensive ingredients.
Categories where consumers were comfortable interacting with a chatbot as much or nearly as much as a human:
- Household goods: Explanations of chemicals used in manufacturing.
- Furniture and appliances: Interior design consultations.
- Personal care consultations: Ingredient explanations and suggestions.
- Beauty consultations: Color match appointments for foundation and concealers recommendations, or makeup lessons.
- Pet supply consultants: Suggesting the right food or toys.
What retailers can do to entice shoppers to share information
Retailers can incentivize providing data by building exclusive content, creating limited product ranges, offering unique services, and launching early drops for shoppers who share more personal information, Minkow said.
“Right now, the best examples I’ve seen are Nike and Levi’s,” she said. Levi’s Red Tab loyalty program prompts shoppers to answer a few questions for Levi’s to suggest relevant products.
Levi’s engages with consumers through its Red Tab loyalty program by asking questions to tailor the shopping experience.
“The more consumers engage with these brands by giving up more information about them through their loyalty programs [as well as outside loyalty programs], the more tailored and interactive the shopping experience,” Minkow said.
Consumers want options. Minkow warns retailers to be careful not to suggest that the customer bypass certain products “because consumers seem to worry that personalization may lead to shortcuts that omit products they would want to see,” she said.
Instead, when asking for data, retailers could explain the benefits such as “this will allow us to show you more items you might be interested in.”
Or, for omnichannel shoppers interested in buy online, pick up in store (BOPIS), “if you’re solely open to picking up in store today, sharing your location with us will ensure we only show you items in stock at the stores within the amount of miles from you that you’ll accept.”
Using AI to personalize the shopping experience
Survey respondents are open to interacting with AI chat bots. Minkow said pricing models offering personalized discounts are another example of how technology can power the type of personalization consumers want.
“Sizing suggestions and styling recommendations leverage technology to facilitate personalization as well,” she said.
She warns that once a problem arises that cannot be easily resolved by a chatbot, the conversation should be handed to a customer service agent immediately.
“Too much friction can be created when a problem is handled by technology for longer than it should be, which would result in an abandoned shopping cart and/or not returning post-purchase to the retailer,” she said. “There should be an automatic threshold wherein if a customer has been interacting with technology for a certain amount of time, a service agent is automatically triggered to step in.”
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