Shoppers come to ecommerce sites with specific goals in mind. Whether that goal is to find a suit for an upcoming wedding or to be inspired to update their home office, retailers often underserve the shopper's goals when designing discovery and navigation experiences.
To truly cement loyalty and drive conversion, retailers must support their customers' desires and motivations.
Ideally, an ecommerce site will improve on the in-store experience by enabling each shopper to leverage intuitive interfaces instead of a store associate. Many think the missing piece is technology if this model fails but the cause is actually something more foundational and far-reaching: the product data.
Today's ecommerce solutions (site search, navigation, personalization, recommendations and SEO/SEM) are incredibly powerful and easy-to-use. However, without complete, accurate and enriched product data fueling the engines, these tools are less than effective.
Rich product data bridges the gap between what customers are looking for and how products are described. This critical connection allows retailers to cater to the wide-ranging goals of shoppers by curating products in a way that allows shoppers to control their journey to find the perfect product. With rich data, shoppers are empowered to tell retailers exactly what they are looking for, in their own words. In turn, retailers can interpret that sentiment and deliver relevant results.
Here are three steps for using product data to improve your discovery experience:
1. Improve the Quality and Consistency of Your Product Data
Ensuring that your products are described accurately is the first step to improving the discovery experience. This basic requirement, unfortunately, is also one of the most challenging for retailers. Developing and maintaining complete, consistent and accurately structured product attribution for hundreds or hundreds of thousands of products is a daunting and unglamorous task. Yet, it is critical to the success of your entire ecommerce investment.
Enriching product data to provide clarity around basic values like color, style and material will ultimately provide the shopper with more relevant search and filter results. It will also reduce the likelihood of shopper frustration and a lost sale that ends in a Google search pointing to a competitor.
2. Develop a Strategy for Improving Engagement
Retailers already pay close attention to how customers browse their website. Bounce rate, page visits and time on site are monitored regularly and influence the decisions to make updates to the ecommerce experience. Product attribute performance, on the other hand, is not frequently examined even though it can provide as much, if not more, critical insight into what shoppers are looking for and what impacts their ability to find it.
For example, let's say product attribute intelligence reveals that shoppers are searching for a "date night dress" and the results they are finding are underwhelming. In this case there is a clear disconnect between what customers want and the results the retailer is providing. Fixing this poor shopper experience could be as simple as changing how products are attributed. For example, rich product data ties the customer vocabulary (date night dress) to the product description (color: black, style: v-neck, item: dress), thus presenting the shopper with the products that meet her goals.
The insights gained from your shopper's interaction with your product data will inform data enrichment strategies that extend your product attribution in more creative and valuable directions. More importantly, these strategies will increase the likelihood that shoppers not only purchase from your site, but also feel inspired to come back again because they were successful in their search.
3. Execute and Continuously Improve
Retailers must continuously monitor and enrich product data to ensure the data fueling their site aligns to ever-changing trends and the vocabulary of their customers. As the example above demonstrates, it is pivotal to improving all dimensions of the ecommerce ecosystem.
As product data strategies are created and changed it is important to have a plan in place that efficiently scales attribution all the way down to the product level while also ensuring accuracy. This cannot be achieved with manual processes that rely on documents and spreadsheets. A big data problem requires an innovative solution based on technology that is driven by an experienced team.
Outsourcing the enrichment of your product data to a trusted partner not only ensures that the quality and speed of curation can support your ecommerce objectives, but it also frees up valuable internal resources for more strategic and professionally rewarding work.
Let's summarize:
An ecommerce website is a living and breathing system, so retailers should keep evaluating their product data to understand how it is converting, how much revenue it impacts and how shoppers are engaging. If the data falls down in one area, it should be immediately improved to prevent lost revenue.
By uncovering how customers use an ecommerce website, developing a strategy for improving engagement, and executing to make a difference, retailers have the ability to improve product findability and relevancy. That means, you guessed it, improved loyalty, increased conversion and more satisfied customers.
