Sidecar’s latest technology automates paid search management for every product in a retailer’s catalog by leveraging cross-channel data in a brand new way
PHILADELPHIA – Sidecar today released a new technology for retail marketers who manage paid search on Google and Bing. The solution, Sidecar for Paid Search, introduces two retail-specific datasets to paid search management: a retailer’s product feed and search queries from Google Shopping campaigns.
Sidecar for Paid Search ingests this data, in addition to a retailer’s historical keywords, paid search queries, and competitive metrics from Google. The data, collectively called the Sidecar Retail Index, drives paid search automation—including campaign creation, keyword list creation, keyword bidding, ad copy development, landing page management, and ongoing testing and optimization.
Sidecar for Paid Search is a machine learning technology that leverages shopping-centric data to create campaigns and set bids at scale, taking into account new products, promotions, and shifting consumer search behavior.
“When shopping ads emerged several years ago, marketers finally gained insight into the one-to-one match between a product and how a consumer discovers it,” said Mike Perekupka, Product Manager for Sidecar. “At the same time, the product feed is the #1 source of information about current products, including titles, descriptions, and other attributes that marketers often use to craft successful paid search ad copy. Yet marketers have had no way to use this data to drive paid search campaigns. Today they do with Sidecar for Paid Search.”
RIPE FOR INNOVATION
Paid search is a marketing stalwart, with long-established tools and processes. The channel hasn’t changed much over the past several years in terms of features and capabilities, yet it remains no less important to digital marketing strategy. Retailers have invested similar spend in paid search and Shopping over the past 12 months, according to Sidecar’s analysis.
However, challenges continue to plague retail marketers who manage paid search. Building keyword lists is a matter of inference and A/B testing. Ad copy writing and testing are often manual processes. The channel has many moving parts that are cumbersome to align—including keywords, ad copy, bids, and match type.
With so many variables, many marketers remain overly focused on tactics and have little time left to cultivate strategy. Often, marketers invest the majority of their paid search effort in their top products, while other products remain under-promoted and under-targeted. The result is inefficient ad spend and sub-optimal revenue and ROI.
THE RIGHT CROSS-CHANNEL DATA
Sidecar for Paid Search is a machine learning technology that leverages shopping-centric data to create campaigns and set bids at scale, taking into account new products, promotions, and shifting consumer search behavior. The technology:
- Organizes keywords into tightly knit campaigns and ad groups based on a retailer’s existing feed taxonomy.
- Creates, evaluates, and optimizes keywords for every brand, category, and product in a retailer’s catalog.
- Continuously mines data to look for new positive and negative keywords, reducing the need for ongoing manual keyword testing, analysis, and management.
- Analyzes performance and dynamically adjusts keyword bids to ensure spend is focused on the most important keywords.
- Uses feed attributes and ad copy best practices to automatically generate and test copy for every product, eliminating the need for manual drafting and A/B testing and helping drive stronger click through.
- Analyzes site search data to choose the most appropriate existing landing page URL or generate a new one to serve with a retailer’s ads.
Sidecar for Paid Search is the latest solution in Sidecar’s lineup, which also includes Sidecar for Shopping and Sidecar for Social. The company developed its paid search solution in response to customer feedback. Retailers of all sizes value Sidecar’s technology and team, and have seen double- and triple-digit growth in their Google and Bing Shopping campaigns throughout their partnership.
Digital marketing in retail requires a balance between technology, data, and people. Technology should build bridges between ever-evolving, cross-channel datasets, driving automation that lets people bring their expertise to bear in increasingly strategic—not tactical—ways.
At the same time, many of Sidecar’s customers wanted to unite their paid search and Shopping approaches to drive more cohesive strategy. Sidecar recognized that it could apply its dedicated experience and expertise in Shopping to solve challenges that its customers were facing in paid search.
“Digital marketing in retail requires a balance between technology, data, and people,” said Andre Golsorkhi, founder and CEO of Sidecar. “Technology should build bridges between ever-evolving, cross-channel datasets, driving automation that lets people bring their expertise to bear in increasingly strategic—not tactical—ways. This combination is the heart of how marketers will deliver experiences more tightly aligned to the shopping journey. We are excited to introduce this approach to the paid search space with today’s release of Sidecar for Paid Search.”
Sidecar’s leadership in performance marketing has led to an expanding customer base in the U.S. and Europe. Sidecar acquired twice as many customers in 2017 compared to 2016. The company’s team has tripled in the past three years to fulfill its commitment to helping retailers grow.
- Overview of Sidecar for Paid Search
- Webinar introducing Sidecar for Paid Search
- Guide to developing a cohesive search + shopping strategy on Google
Sidecar is a technology company dedicated to retail. Our mission is to maximize the value of performance marketing. By combining deep data, knowledgeable humans, and inspired technology, Sidecar is the magic behind retail’s smartest marketing campaigns.
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