If you’re an ecommerce retailer, you already know how hard it is to acquire new customers and drive sales while competing against the giants like Amazon, Walmart, and Overstock. But digital marketing for ecommerce is experiencing a huge shift—particularly in the way paid search experiences are delivered to the users in response to a search query.
Simply put, if you start making better use of data feeds to energize your product listings, you can prepare your business for an imminent shift in the ecommerce search space.
How new SERP structures revolutionize ecommerce
Search engines are moving away from the traditional keyword-based customer journey, wherein users search for a keyword, sort through text ad results, and click through to a website. With the emergence of more structured and segmented product feeds (also known as shopping feeds), search engines are now serving up SERPs that are personalized, localized, and conversational—with more actionable results.
The driving factor behind this paradigm shift (and other developments on the paid search horizon this year) is the increasing use of automated strategies powered by machine learning technology. But how do these automated strategies work? More importantly, how do they decide which product ad to show in response to a user query when we are not using keywords?
The answer is structure: product feeds act as mechanisms or bridges that help streamline access to the retailer’s entire product data set and related information. They are generated and managed in standardized file formats, which allows platforms or comparison-shopping engines—such as Bing Shopping (Bing Product Ads), Google Shopping (Google Product Listing Ads), and Amazon Marketplace—to market products from multiple retailers by accessing and correctly understanding products in the context of user preferences, search history, demographics, location, and other qualifiers. The result? Dynamic, personalized engagement in real time.
Richer retail experiences for the Digital Age
Product feeds are the first stage in an imminent sea change in ecommerce. The rise of such AI-powered strategies (coupled with machine learning) is enabling search engines to evolve into much more effective digital marketing partners. We now have the ability to share information via product feeds in a way that allows search engines to understand, compare, and contextualize product data, making it easier for retailers to connect with their potential customers throughout their online journey to purchase.
But there is still work to be done. In order to fully harness the power of major search engines and comparison-shopping engines, retailers have to optimize their product feed structure through effective data mapping, standardization, normalization, and cleansing. It can be complex, time-consuming work (as we know from first-hand experience with leading retailers like Clas Ohlson), but it’s the most effective way to take your product ads from A to A++.
If you want to drive performance in ecommerce—or you simply want to understand how to structure and optimize your shopping feed—we’re here to help. Contact DAC!
