Sidecar announced several technology updates to Sidecar for Paid Search and Sidecar for Shopping. These solutions now use new applications of natural language processing (NLP) and artificial intelligence (AI) to increasingly improve the performance of retailers’ paid search and shopping ad campaigns on Google and Bing.
Amid these developments, the number of retailers managing their paid search and shopping campaigns with Sidecar has increased by 40% in the past quarter. This adoption is a testament to Sidecar’s combination of intelligent technology and services.
“Sure, retailers can automate search marketing,” said Mike Perekupka, Product Manager for Sidecar. “But it’s the next phase of automation that becomes valuable in performance marketing today—and that’s intelligence. With this in mind, Sidecar’s latest technology updates let retailers automatically execute a greater number of best practices for search marketing success, all paired with the guidance and counsel of Sidecar’s channel experts.”
Sidecar for Paid Search and Sidecar for Shopping can now:
- Build and evolve keywords and ad groups with natural language processing. A core part of Sidecar technology is the Search Query Manager. This feature analyzes words and phrases in consumer search queries to automatically identify and categorize new positive and negative keywords, and assign the right bid to them.Now, using natural language processing, Search Query Manager organizes those hyper relevant words and phrases into tightly knit ad groups that help retailers drive down CPCs. Without Sidecar, keyword management is manual and inefficient. Because of this, ad groups are usually not as relevant or intelligently structured as possible, and fall out of date quickly as consumer search behavior changes, leading to wasted ad spend.
- Target a cost per acquisition (CPA) goal. While many marketers measure their performance marketing success by return on ad spend (ROAS), some are increasingly focused on CPA as an alternative or additional KPI. Sidecar’s CPA Goal Bid Algorithms now give retailers the option to use custom, automated bidding approaches that tailor the technology to meet a CPA goal instead of or in addition to a ROAS goal.Retailers can use multiple custom goal algorithms in their account to align each segment of their product catalog to specific data-driven goals. Unlike automated bidding tools created by search engines, Sidecar pairs its technology with its team. The company’s channel experts work with retailers to guide them in goal setting and ensure those goals remain aligned to changes in their business, seasonality, and other factors.
- Monitor stock levels. Products go in and out of stock frequently in e-commerce. Marketers typically have little to no time to sustain a constant awareness of stock levels. This often creates situations where their ads are promoting out-of-stock items, leading to poor shopping experiences.By contrast, Sidecar’s Automatic Stock Monitoring incorporates a retailer’s stock levels within the technology. If a product goes out of stock, Sidecar technology restricts related keywords from receiving bids and wasting spend. Once the product is back in stock, Sidecar technology re-enables the keywords. Automatic Stock Monitoring eases the pain of aligning marketing efforts with product availability and demand, especially during holidays and promotions.
- Adjust bid modifiers. A click is usually worth more or less on a certain device, at a particular location, or during a specific time of day. Marketers commonly—and manually—use bid modifiers to adjust bids based on this criteria.Sidecar’s Bid Modifier Optimization now handles this task. It continually analyzes performance data and automatically adjusts bid modifiers to drive campaigns to meet the retailer’s return goal. Sidecar technology adjusts all major modifiers, including device, geotargeting, and dayparting.
Sidecar will continue developing its solutions to help performance marketers in retail approach shoppers with a more compelling and relevant experience on any channel or device. These developments will continue to merge automation with a collaborative understanding of retailers’ goals, product catalogs, and competitive landscapes.