When it comes to e-commerce personalization, how do you know if you are truly delivering a personalized experience? As shoppers, we all have different likes, patterns, affinities, interests and trigger points that lead us to making purchases. In a physical store environment, an associate is well equipped to not only gauge the interest and patterns of their repeat customer, but also to inquire and learn what prompts that particular shopper to make a purchase. Is it a BOGO offer? Is it the ability to sample a new product with a purchase? Or is it the allure of purchasing an exclusive line solely available at that particular store?
In other words: What is the relevance and contextual value that drove the individual to complete the purchase and make repeated purchases with the retailer?
In the e-commerce realm, face-to-face interaction is lost and therefore the ability to offer a relevant and personalized experience to each shopper becomes ten times harder. Today’s digital-savvy shoppers know they have choices, yet typically choose a retailer based on the value an organization brings through an enhanced personalization strategy. The stakes for a personalized experience are high and consumers increasingly expect retailers to add contextual value for the individual shopper. But how do you offer a personalized experience online that creates relevant value for the individual without being creepy? It begins and ends with data.
Achieving contextual relevancy through data
The truth is, the majority of digitally enabled retailers may be offering a personalization experience to their shoppers, but it may not be personalized enough for that individual shopper. For example, in today’s market we tend to see segmentation rather than personalization. With segmentation, shoppers are grouped into various buckets due to previous purchases, demographics such as geography and household income as well as previous clicks. While segmenting may help uncover basic statistics about the shopper, it doesn’t go above and beyond in adding value to the individual shopper’s experience with the brand. Retailers can look to solve this pain point by utilizing data in the following ways:
Learn about real-time intent with each purchase
Consumers are willing to share feedback if they know that it will lead to an improved shopping experience. As such, capturing real-time intent data during a shopper’s e-commerce experience is critical. To do so, retailers should create a quick dialogue with each customer that arrives to the site, just as a store associate does. Digitally greeting the customer and asking them if there is anything you can help them find on your digital site can go a long way in identifying the shopper’s purpose and affinities, as well as create instant value for the shopper by helping them arrive at the product faster and discover new products that they may have not thought of purchasing prior to arriving at the site.
Solve for data relevancy
To deliver true digital personalization, retailers need to ensure they are implementing the right tools and procedures to solve for relevancy first. The subject of relevancy can have several different factors, including analyzing data and user-interaction data versus just practicing segmentation. To solve for relevancy, retailers need to look at the whole picture and combine product data, behavioral data and improved search capabilities to deliver true value to each shopper. With an enhanced data relevancy strategy, retailers can efficiently create one-to-one experiences across all of the individual shopper’s touchpoints.
Keep the voice of the shopper in mind
As consumers continue to shop online, retailers need to keep the voice of the customer in mind with each and every interaction. Today’s shoppers are using voice and text to look for products and retailers need to be able to answer in the way a shopper might search for an item in the store, as well as account for any errors or misspellings. For example, let’s say a shopper is either typing or giving the voice command of “I am looking for the perfect outfit for brunch.” In response, a retailer’s product data should quickly answer this query and take the consumer to the products they are searching for.
This is critical given that we live in an era of instant gratification that has changed the nature of online search. Retailers need to make sure their product data can answer and personalize for each of the shopper’s search queries. Since each shopper can search for a particular item in 100 different ways, an elevated machine learning component will need to be in place. This implementation will help the retailer solve for the countless ways the shopper looks to find the item as well as evolve with each search task to continue helping the retailer deliver a personalized experience.
To deliver true value, e-commerce personalization cannot be in silos. The ability for retailers to offer online shoppers value beyond just the product they sell will continue to be a true differentiator. To achieve this, retailers need to examine their data strategy and solve for real-time intent, relevancy and unique search queries to create a superior and unique customer experience for each shopper.
GroupBy provides product data, site search, personalization and analytics software for e-commerce sites.Favorite