Enhancing the Online Experience through Data Enrichment
The modern consumer relies on a continually increasing amount of information when shopping for items online. Needless to say, accurate and extensive product details are essential for a superior shopper experience.
As eCommerce continues to evolve, however, issues due to lack of this information or products associated with incorrect information are no longer acceptable.
One of the main reasons eCommerce has risen in popularity over shopping at a traditional brick and mortar store the ability for shoppers to quickly and easily purchase an item they are in search of from the convenience of their mobile device or desktop. In fact, according to a recent survey by comScore and UPS, 51% of consumers preferred to do “their shopping online, compared to the 48%” the year before. But while this may be the case, electing to go the eCommerce route can result in losing out on a few of the key elements that drive them to make a purchase, such as touch and feel, or the additional value of getting to “try” the product before they buy it.
Nonetheless, this is not to say that consumers cannot have an enhanced experience while shopping online if retailers and brands do their due diligence to provide each and every consumer with the ability to find exactly what they are looking for, and in some cases to help them find what they didn’t know they needed! But in order to offer these kind of enhance online shopping experiences, retailers must first be able to create an enriched product data environment. So, what does data enrichment entail? By definition, “data enrichment is a general term that refers to processes used to enhance, refine, or otherwise improve raw data.”
In the eCommerce world, retailers can use this approach as a strategy to provide the most memorable online shopping experience possible by considering the following best practices:
Start with a comprehensible site search experience
An enhanced eCommerce experience begins with giving shoppers the ability to easily and quickly find the product they are in search of. That said, a consumer’s search journey will not always follow the direct product description logged within your search engine. For example, while your product description may be labeled as “ivory sun dress,” consumers may type in “white sleeveless dress,” or for a more descriptive angle, “summer dresses for a Fourth of July picnic.”
In order to guarantee customers do not become frustrated with limited results, retailers must utilize their shopper’s historical search data and enable their eCommerce site to interpret every search query. From here, consumers will be able to effortlessly arrive at the product they are in search of. Traditional semantic classification and natural language models often fail to measurably improve search relevancy for eCommerce. With that in mind, retailers and brands should look to add a layer of recognition to their data queries that allows an increase in query complexity now necessary with the rise of mobile shopping and voice search devices.
Ensure your attribution is seamless
A good site search experience should be followed with good product data. For example, shoppers are more likely to abandon their carts if they encounter incomplete or incorrect product data across a retailer’s site. To provide better findability for their visitors, retailers must establish accurate titles and descriptions for each of their products. Additionally, retailers must make certain that all product are tagged correctly and in the correct order to boost SEO traffic and safeguard product integrity across all digital channels. To achieve this seamless attribution, retailers must automate product attribution across every department with comprehensive taxonomy so that every product is well-attributed and covered.
Create product relevancy
Compared to shopping at physical stores, eCommerce shoppers do not always have the opportunity to imagine how the product they are viewing can be valuable to their lives. As such, it’s important that product data and overall site experience provide the these individuals additional, contextual reasons as to why making the purchase is a good idea. For example, adding components such as videos and reviews, as well as showcasing additional scenarios in which the product can be utilized, can provide consumers more and more reasons to make the purchase, ultimately saving the sale.
Create an opportunity to upsell with personalized recommendations
Once product relevancy is established, retailers have an opportunity to upsell by identifying relevant products that fit in combination with the item the shopper has added to their cart. The key to executing this process successfully lies in making sure that each item recommendation is relevant to the individual and truly compliments the product the shopper was originally in search of. For example, if a shopper just finished adding a shower curtain to their cart, recommending additional bathroom items, such as bathroom rugs, curtain liners and soap dispensers can help the retailer make the a larger sale. On the other hand, this same retailer must not forget that if a shopper just finished purchasing a shower curtain, the last thing they want to see are additional recommendations for other shower curtains shoppers.
To achieve this—the ultimate shopping experience—retailers must have the ability to connect with each and every single one of their consumer data sets in real time. When this happens, they can begin to learn from previously viewed and purchased items, repeat purchases, or abandoned items left in shopping carts, adjusting the shopping journey accordingly and thereby connecting this data to tangible results. It is only through forming this connection and building unique profiles for each shopper that retailers and brands can make incredible product recommendations and deliver an online experience that competes with traditional, in store shopping.
While eCommerce may have its advantages and disadvantages in comparison to this brick and mortar experience, creating a data-rich and data-led eCommerce organization is the key to leveling the playing field and providing shoppers with a memorable, exciting and altogether superior experience. And as consumer expectations continue to rise, it has never been more important for brands and retailers to be sure their shoppers always find exactly what they are looking for. Without enriched data, none of this is possible. But with it, the possibilities are absolutely limitless.
About the Author: Roland Gossage is the CEO of GroupBy, which provides solutions for retailers to interact with their consumers online through data-driven commerce, media, and knowledge management software solutions.