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December 1, 2020
Today’s retail reality shows that 87% of consumers begin their shopping journey digitally, since these technologies make online shopping simple and convenient. The average shopper’s journey may look something like this: See an advertisement on Instagram that is relevant to his or her personal style, swipe to check out the product in more detail, and ultimately purchase the product right in the app. Product recommendations now populate in shopper’s feeds, instantly.
The implementation of a data set and machine learning technologies can help retailers map shopper preferences, product details, and returns data, to scale personalization. Retailers who work to provide consistent and relevant offerings can assist their shoppers through the purchase process with ease, driving consumer satisfaction and loyalty.
The use of personalized ads, improved search capabilities, and emails are a few ways some of the leading retailers work to facilitate consumer acquisition. These additions help guide shoppers through the awareness stage with ease. The consumer wants to be inspired and find the styles they’ll love, and 77% of consumers expect personalized shopping experiences.
Next, is the consideration stage. Retailers can offer more relevant recommendations by using machine learning to populate styles that the individual shopper wants. Consumers are 82% more likely to do business with retailers who offer personalized experiences. The key to succeeding in this step is showing the shopper the products they want on the first page of results. This enables the shopper to find the styles they like with ease, and move towards the purchasing stage.
Once the shopper reaches the next stage, maintaining their confidence is where a comprehensive data set can help complete a purchase. 62% of US online adults have chosen, recommended, or paid more for a brand that provides a personalized service or experience. Data can help the retailer offer size filtering, details on an item’s fit, the ability to shop for others and more. By simplifying the purchase stage for the shopper, retailers can be confident that the styles purchased are ones that the individual consumer will love and keep.
Providing consumers with the same personalized experiences as those offered in-store, is a challenge that many retailers are working to overcome. 83% of shoppers need assistance while online shopping. Through artificial intelligence, retailers can increase the availability of chatbot, call centers, native apps and other technologies that help make ecommerce more personal.
The shopper journey extends past getting consumers to purchase products. An important final stage to the shopper journey is the loyalty stage. 52% of consumers are likely to switch brands if a company doesn’t make an effort to personalize communications to them. Delighting shoppers with personalized experiences the first time they visit a site increases the likelihood that they will come back to make future purchases.
Providing a truly personalized shopping experience is no easy feat. In order to succeed at delivering 1-to-1 experiences, retailers must look to data and how they can tap into key insights to drive the consumer through the shopping journey.
Retailers who overcome the five main challenges of personalization, analyze different types of data available, and use data to facilitate each touchpoint of the shopping journey are sure to win consumer satisfaction and loyalty.
