Kenshoo Supports Instacart Advertising with Data-Driven Insights to Optimize the Endless Aisle
“We made it easier to profitably scale Instacart advertising independently or alongside campaigns on other top E-commerce marketplaces,” said Nich Weinheimer, general manager, Ecommerce for Kenshoo. “With COVID-19 accelerating already-robust online grocery sales, CPGs understand that growth in 2020 and moving forward will be won or lost online.”
U.S. online grocery sales grew 22% in 2019 and stand to surge about 40% in 2020, with Ecommerce expected to reach roughly $38 billion this year, according to Coresight Research and Supermarket News.
Instacart provides consumers with a convenient and affordable way to have fresh groceries, household essentials, and more delivered or picked up from their favorite local retailer in as fast as an hour. The company partners with more than 400 retailers to deliver from more than 30,000 stores across 5,500 cities in the U.S. and Canada.
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Expanding beyond the native user interface, marketers leveraging Kenshoo to support Instacart advertising campaigns enjoy a unified view of keywords, ad groups, and campaigns on Instacart; the ability to measure performance across the marketplace; and different ways to structure and optimize these campaigns to boost results.
With rules-based alerts, advertisers managing Instacart campaigns with Kenshoo can receive notifications to prompt bid, budget, or other adjustments when various criteria are met: when campaigns outperform their target ROI or run out of budget, for example, or if sales from a high-performing keyword drop. Kenshoo’s dimensions and categories enable Instacart advertisers to apply custom labels (brand vs. non-brand, categorical, promotional, etc.) to ad groups, ads, and keywords across Instacart and other E-commerce marketplaces that enable granular-to-aerial views of ad performance across channels. Also simplifying the otherwise complex task of comparing performance across channels, Kenshoo’s True North Custom Metrics bridge the gap between differing attribution and auction models.
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