If you're working in retail technology, there's no doubt that improving the e-commerce shopping experience is a hot button topic. In fact, Shelley Bransten, Salesforce SVP of Retail and Consumer Goods Industry Solutions, recently said, “80% of consumers are saying they’ll switch brands not based on products or necessarily even services, but based on experience.”
Data Driving E-commerce Personalization
A recent article in RetailTouchPoints
highlights how four brands across different industries are using data to help improve e-commerce personalization. While each of these brands offers different products, the data-driven initiatives are something that all brands and businesses can learn from.
Melissa & Doug is a toy manufacturer, who focuses on the use of a content-first strategy. This strategy works to ensure the authenticity of content, and overall customer experience. Customer demand and increased expectations have been on the rise and ultimately led to the company’s adoption of this strategy.
focuses on mobile-shopping optimization
, which accounts for 60% of the makeup brand’s online traffic. Shoppable videos, product imagery and personalized promotional offers optimize the brand's focus on mobile initiatives.
is a wine brand working to provide customers with more personalized product offerings
through improved data analysis. Artificial intelligence helps companies break the barrier between the brand's perception and the customer's true wants and needs.
has implemented a "fan-centric" marketing initiative to ensure customers are receiving individualized recommendations
. Retailers can formulate similar algorithms to ensure their customers are provided information on relevant items they may be interested in purchasing.
Fashion Retail and
At True Fit, we believe that the key to improving the e-commerce shopping experience is rooted in understanding each customer. Finding one’s True Fit isn’t just about size, it’s about understanding the convergence of fit, personal style, and what flatters every body. Retailers and customers deserve more than just a simplistic size calculator or generic size chart.
"Finding one’s True Fit isn’t just about size, it’s about understanding the convergence of fit, personal style, and what flatters every body."
The combination of rich connected data and machine learning enables personal experiences for all fashion retailers. Artificial intelligence provides customers with recommendations through personalized style rankings that leverage a deep understanding of both users and garments. Customer-level data analysis can also improve browse, search, email marketing, retargeting, in store clientelling, and chatbots.
"The combination of rich connected data and machine learning enables personal experiences for all fashion retailers."
As e-commerce personalization popularizes, retailers are competing with one another, and finding the best ways to optimize data analysis of their individual customer base. The most successful companies analyze the true wants and needs of their customers to ensure that personalization efforts are worthwhile.