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E-Commerce Content: Five Steps To Improve PLA Click-Throughs

  • Written by  John M. Pierre, Linguastat

VP site only Linguastat head shotGoogle Shopping Campaigns are expected to heavily influence holiday traffic as consumers compare pricing and look for specific items on the wish lists of friends and family members. Here’s how to make every PLA count.

Retailers and brand manufacturers alike know the importance of a great, eye-grabbing package design in the setting of a brick-and-mortar store. Now, the same emphasis on the visual is moving to the forefront in e-Commerce as well, especially with the growing influence of Google Product Listing Ads (PLAs) — now Google Shopping Campaigns. Introduced just two years ago, PLAs have become such a reliable source of click-through traffic that retailers are expected to dedicate a significant portion of holiday marketing dollars to the new shopping campaigns.

But simply spending more may not be enough to get shoppers to move beyond the ad. The science of creating PLA-friendly product content represents the “last mile” to winning the sale, and retailers will need to rely heavily on the power of images, combined with a few well-chosen words, to get shoppers to click through to a product landing page.

While an image may remain the same no matter where a PLA appears, the text can, and should, differ depending on variables such as what search terms the consumer used to get there, their recent browsing history, and their demographics. In addition, Google’s strict and evolving PLA rules require retailers to bring an even sharper focus to the descriptive content that accompanies each and every one of their product images.

So the challenge for retailers seeking to optimize their online advertising, search and sales results is the need to create targeted, Google-friendly descriptions for their entire range of products. But it can be done.

Here are five key steps to creating content that drives PLA results by working well within the new world of Google Shopping Campaigns and other comparison engines.

1. The first three words matter most. While every word in a product title can increase search relevance, only the first few words have a chance to catch the fast-roving eye of an online consumer. In trying to influence a click decision within a narrow two-second time frame, the first three words of the product name have to count at a particular moment in time, for a particular person using a particular device.

2. Think beyond the product name. Unfortunately, to be effective, retailers can no longer succeed by simply repurposing web site product titles from their product catalogs. With just three or four words to get a shopper to click on the PLA, the product descriptor should reflect an understanding of the consumer’s search terms, where they’ve shopped recently, what they purchased before and whether they are using a mobile device or desktop computer. The consumer may already know the product they are looking for and, given just a few words, may choose to narrow their selection by moving right to the PLA that indicates the right brand, color or size.

3. Leverage analytics to deliver the right content. It’s not just the words but the order they appear in that can make an enormous difference in click-through rates, and it will be different for different shoppers. For example, a consumer in the market for a strong brand name HD television set will have used this brand name as part of his search query. For this shopper, seeing results that read “[BRAND NAME] HD TV” will create a smooth click-through path.

But for an off-brand TV set, the brand name will be of less importance than information regarding screen size and other features. In this case consumers will better respond to a product title that reads “72-inch HD TV” as opposed to one that prominently features an off-brand name. New e-Commerce technology helps deliver the right content based on the most important attributes to consumers for each and every SKU instead of using a one-size-fits-all approach.

4. Adhere to current requirements of Google and other search engines. Google shopping and other comparison shopping engines have very specific usage rules that can cause product descriptions that would otherwise be appropriate and desirable for web site display to be rejected. This includes the use of upper-case letters, trademark or other symbols, and language that is overly promotional. These requirements change periodically, so retailers must stay current. At the same time, product information needs to be optimized for PLA while maintaining tight synchronization and relevance to the product landing page.

5. Regularly refresh copy. As consumer preferences shift over a period of weeks or months, retailers can sustain and grow their click-through results by adapting content to appeal to trending colors and functionalities. The few words that accompany PLAs offer an opportunity to differentiate an offering and capture consumer demand as new favorite features emerge.

PLA-Friendly Content Helps Drive Sales

In the increasingly image-oriented world of e-Commerce, it’s important to make the few words attached to each product really count. It’s a tall order for retailers with catalogs consisting of tens or hundreds of thousands of individual SKUs. To handle the volume and complexity of the problem, some retailers are tackling the problem using predictive analytics and algorithm-based solutions such as those used in natural language generation.

Advances in Artificial Intelligence and Natural Language Generation have made it possible for retailers to rapidly and automatically create optimized product titles, along with content descriptions, for their entire catalog. In addition, this dynamic content can be continuously refined and targeted, based on metrics such as search queries, site traffic, and conversion rates. In the increasingly image-oriented world of e-commerce, such solutions can make the few words attached to each product image really count.

No matter how retailers approach the challenge, they must find a way to create compelling, unique content that meets Google requirements and, more importantly, appeals to shoppers across mobile, desktop and tablet formats.

John M. Pierre is co-founder and CEO of San Francisco-based Linguastat, which uses patented Natural Language Generation technology to automatically transform data into optimized product descriptions for mobile and e-commerce channels. Pierre has more than 15 years of industry experience developing new technologies and products and has published several papers in automated classification and text mining. Linguastat provides e-Commerce content creation and optimization services to over ten percent of the top 100 retailers in the Internet Retailer Top 500.

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