Vermont Teddy Bear Company owns four highly seasonal brands—Vermont Teddy Bear, PajamaGram, PajamaJeans, and Vermont Brownie Company. The retailer wanted to reallocate its Google Shopping budget to acquire new customers, and not overspend on those who already know and trust its brands.

But the retailer had no way to do this with its agency, which had limited Google Shopping knowledge and no technology to advance channel performance. That’s when Vermont Teddy Bear Company partnered with Sidecar.

Vermont Teddy Bear Company has its eyes set on efficiency in Google Shopping. The retailer defines revenue and cost/sale targets monthly, aiming for especially aggressive goals during its busy seasons. Those include Valentine’s Day and year-end holidays for all its brands, except PajamaJeans, which peaks in the spring and fall.

“We have the conflicting goals of trying to earn as much revenue as possible, but at a very efficient ad cost,” said Donnie Ager, Digital Acquisition Marketing Manager for Vermont Teddy Bear Company. “And we’re responsible for carrying that out across not one, but four sites.”

Initially, the retailer outsourced Google Shopping management to a digital agency, which took the traditional approach of adjusting bids manually and structuring campaigns by product type. But Ager found that the manual management was too slow, and the agency struggled to understand his business and develop Google Shopping strategy for it.

“We often had to go into Google Ads ourselves and point out areas that needed to be improved,” he said. “Performance had been the same for a while, and we really wanted to grow the channel. We thought that if we had better account management, and technology to automate our efforts, we could drive much greater success on Google Shopping.”

Ager also felt he was overpaying for high-intent traffic. “We market across digital, TV, radio, and catalog,” he said. “We know the exposure spurs consumers to Google our brands, with the intent to visit our sites directly to make a purchase. We wanted to reduce Google Shopping spend on these consumers since we were already winning them through other means, and focus on acquiring new customers.”

Ager researched the market for an advanced approach that would meet his goals. It was critical to find a technology solution that would save money and time, build revenue, and scale across all sites, as well as a team that would develop channel strategy in lockstep with Ager and his business objectives.

“That’s when I found Sidecar for Shopping,” he said. “I spoke to people who are directly related to the company’s machine learning technology. They explained how it would continuously use product performance data and search queries to optimize each bid. The approach was innovative and made perfect sense. I was convinced.”