Search Query Management for Google Shopping improves the cost/sale of retailers’ campaigns by matching spend to the value of search queries
PHILADELPHIA – Sidecar for Google Shopping now includes a new capability called Search Query Management to improve the efficiency of Google Shopping campaigns. Sidecar’s Search Query Management analyzes the performance of search queries and matches spend to them based on their value to a retailer’s business.
The technology works by identifying the individual words that affect the value of queries. It uses these words to segment queries into groups and assign spend accordingly. The technology continuously evaluates campaign performance and structure, making adjustments as needed to maximize efficiency.
“The performance of one query — among the hundreds, thousands, or more — in a retailer’s Google Shopping account is a statistically insignificant amount of information from which to create any kind of optimization strategy,” said Dave LeDonne, Director of Product for Sidecar. “But retailers can gain statistically significant data by aggregating the performance of many similar queries according to the words they contain.”
Unlike negative keywords, Search Query Management captures all queries at a value appropriate to a retailer’s business model.
Sidecar analysis has shown that when Search Query Management was applied to a top-500 retailer’s Google Shopping account, cost/sale decreased by 12% month-over-month while revenue remained steady. In addition, the higher value queries generated two-thirds of total Google Shopping revenue.
Part of the genesis of Search Query Management is to overcome issues with negative keywords. Although they are a way to prevent products from showing for irrelevant queries, negative keywords can cause retailers to forfeit search traffic that could convert. Unlike negative keywords, Search Query Management captures all queries at a value appropriate to a retailer’s business model.
Search Query Management is also future proof. Sidecar’s machine learning engine is continuously analyzing and optimizing query performance, no matter how consumer behavior or Google’s algorithms change over time.
Sidecar is an e-commerce marketing technology that uses machine learning to solve the complex, data-intensive process of connecting consumers to relevant retail products, in all paid marketing channels where consumers shop. Sidecar takes relevance to the next level, allowing retailers to display the right product ads to the consumers most likely to purchase them, at the right moment.
The technology considers an average of 1.2 million data points each day to analyze and index every product in a retailer’s catalog, to ensure profitable growth out of paid customer acquisition channels across all devices.
Retailers that use Sidecar drive millions of dollars of new, measurable revenue and save time and internal resources, while maximizing ROI and improving the conversion journey for customers. Brands including Newegg, Boscov’s, Serena & Lily, and Bealls count on Sidecar to optimize their product advertising campaigns. Sidecar retail customers average an 87% increase in YoY channel revenue and a simultaneous 15% growth in return on ad spend.
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