Bissell

A Marketing Story by Rank Crankers about BISSELL

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BISSELL

Increase Sales

Challenge

CLIENT OVERVIEW Bissell is a household cleaning equipment and solutions manufacturing company in ecommerce. As strategic consultants, Rank Crankers is continuously testing new initiatives to push our client’s business forward and increase sales year over year. This project was centered around the testing of a new Google Ads Shopping campaign to increase revenue and sales while maintaining a specific ROAS goal. Why Smart Shopping? Save Time: With Google’s machine learning we are able to fully automate our bidding, ad placements, and save time. Higher Relevancy: Google’s automatic product feed correlation feature allows remarketing highly relevant product images to users. More Revenue: Google machine learning serves an optimal combination of an image and text across different networks to generate more sales and revenue. Be Present in the Moments That Matter: Helps to stand out and drive revenue during peak shopping times. Google automatically adjusts the ad to fit within all the different ad formats across different Google marketing platforms. PROJECT GOAL Increase revenue and sales while maintaining a specific ROAS goal. Challenges Limited Visibility: Smart shopping campaigns will not display as “limited by budget” and therefore need to have a much higher daily budget during peak shopping times. The campaigns spent twice the daily budget on Black Friday, meaning there was room to push them further. This led to opening the campaign budgets throughout the weekend, and Cyber week. Cookie Window: ROAS will appear low during high shopping days but will increase due to the cookie window. During the peak holiday shopping weekend, Smart Shopping ROAS was well below the target goal early in the day. However, they ended above the target due to the cookie window. Limited Reporting Abilities: While this campaign is fully automated by Google and you would not be able to optimize it, Google limits reporting features so you can’t apply learnings to other campaigns. We were also unable to see what networks it is performing the best on (Search, Shopping, YT, GDN, Gmail) and unable to see performance by device, audience, demographics, etc. Limited Management Abilities: From a branding perspective, this campaign is tough as you lose the ability to control branding standards. In order to segment out specific products, you have to add custom labels (as opposed to being able to bid by SKU). This is a more difficult approach than Standard Shopping as it requires additional parameters than the standard shopping feed.

Solution

Our Approach Start Small: Before giving the control over to Google, we tested the machine learning capabilities on smaller accounts. Allow Google to Learn: We didn’t limit the campaign with budget so the machine could learn and do its work. Keep Testing New Opportunities: After 3 months of continuously exceeding goals without a ROAS target, we wanted to test if a decline in efficiency would allow us to get closer to our ROAS goal and generate more revenue. We tested lowering Target ROAS goals in the Smart Shopping campaigns to drive more revenue at the account target ROAS goal. We also expanded to test across the strongest campaigns in the client’s main account. Spread the Success: As Smart Shopping was meeting set revenue goals it allowed us to test further; across other campaigns while still maintaining our ROAS goals. The max conversion bid strategy was successful in Smart Shopping, which drove us to implement a max conversion bid strategy across our search campaigns.

Online Advertising