Think Tank: The Personalization Conundrum, Data Overload
The retail industry is buzzing with the potential of applying personalization, artificial intelligence and big data to capture the Millennial consumer, and since they possess the largest annual spending power of any generation — a hefty $200 billion — we can understand why.
This digitally native cohort is shaking up the game. They are demanding personalized experiences but are concerned about data privacy. Many brands have yet to find the recipe that quells worries over privacy while delivering more meaningful one-to-one experiences.
This year, brands and retailers such as Nordstrom, Rent the Runway and Ann Taylor implemented on-point data-driven and digitally savvy strategies that delivered successes. But they are the exceptions. The majority of retailers are struggling to build the right technology stack that can capture, store and process meaningful data. In fact, upward of 54 percent of retailers rank their personalization strategies and omnichannel maturity level as “low,” according to a presentation by Meyar Sheik of Certona during Shop.org this fall.
While data collection is a fundamental part of creating more personalized experiences, the new question is, “What data should be captured?”
Personalization is table stakes, but poor execution equals poor results
U.S. consumer satisfaction is precarious with statistics from a recent Accenture report showing 44 percent of U.S. consumers are frustrated when companies fail to provide relevant, personalized experiences, and 41 percent said they ditched a company because of “poor personalization and lack of trust.”
The modern consumer wants fast, frictionless shopping sessions online and on mobile that they can feel confident about. In a recent qualitative study, Stylitics teamed with retail research firm NPD Group to take a closer look at the expectations and preferences of the Millennial female shopper to uncover what she wants, and what information she is willing to give for a better online shopping experience. The Millennial Mirror: Retail Personalization report confirms she wants and expects high levels of personalization, but is willing to give, to get.
The study explored four top personalization categories in the apparel and accessories categories:
Outfit and Styling Recommendations: featured as “Shop the Look” or “Ways to Wear It,” also customer reviews and photos.
Product Recommendations: a showcase of similar products to what a shopper is browsing such as “You May Also Like” or “Recently Viewed.”
Size and Fit Guidance: suggestions on what size apparel/shoes will best fit a customer, how big an item is in comparison to other familiar products based on feedback from previous purchasers.
Personalized E-mails and Advertisements: displays images of products the customer recently purchased or viewed while browsing the web or social media.
Retailers need to ask the right questions
To make personalization work, retailers need to ask the right questions. While privacy is important, the good news is female Millennial shoppers are willing to provide valuable information in exchange for more help and time-saving experiences. A majority, 95 percent will share size and body type, 75 percent will offer style and occasion preferences; 70 percent will share gender information, and 65 percent will provide details about her willingness to spend. All the gathered data points provide powerful information for a retailer who can better optimize their site to both capture and deliver these experiences.
Marketers need to be aware that things start to shift when they ask for e-mail addresses as only 35 percent of the panel said they would submit their e-mail address to make the experience more personalized. This rate continues to drop when asking for social media accounts, household income or race and ethnicity.
Making the data work
There are many ways retailers can make the data they do have work harder and smarter. For example, say a shopper is looking for a dress online, she is plus size and will be attending an evening wedding. She needs this dress within three weeks and is ready to purchase if she can find the right look. A smart, integrated online seller would offer up items that are in stock, in the right size range, are tagged as formal or evening attire, and may even know the seasonal outfit needs based on her location.
This type of responsiveness gets our shopper closer to a sale, but adding full outfit and style recommendations along with fit guidance and product recommendations such as “Recently Viewed” or “Shop the Look” can be a deciding factor — and it pays. Outfitting and styling advice opens an opportunity for retailers that is significant, and according to the study, she will buy one to two more items on average if she sees recommendations on how to wear her item.
This functionality also drives up consumer satisfaction and helps deliver that desired easy and frictionless experience while saving her hours of frustrating searches.
London-based Asos heard the call from their customers about size and fit guidance and is going the distance by showcasing the same product on three different-sized models, who represent “non-runway model” body types. This company has embraced body positivity and is capturing the hearts of their customers.
Rent the Runway recently rolled out style advice and outfitting functionality to show multiple ways to style rentals with pieces she might already own. Further evidencing they are a company that knows its customer well.
The adage of “give the customer what they want” has not changed, but the rules of how to do that have. It is time for retailers to realize that consumers view traditional experiences as time-consuming, inconvenient and impersonal. Hyper-relevance is the next wave for growing retailers and those who can find the balance between collecting data designed to understand the consumer’s needs and building trust by safeguarding privacy and giving customers full transparency and control over their personal data, stand to gain the most.
Rohan Deuskar is the founder and chief executive officer of Stylitics, an AI-powered digital visual merchandising and outfit recommendation platform for retailers and brands.
For more WWD business news, see:
“Art Versus Folly: Holiday Fashion Ads Underperform With Broad Audience”
“The Future of In-store Experiences, 2019 Edition”
“Returns as Diamonds in the Rough, Re-commerce Draws 11 Million Views?”
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