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The client is a leading US-based subscription-based sports apparel and accessories company. Their two main business assets include an e-commerce site and a subscription platform for online delivery services. They also run an SMS platform where flash deals are texted to users; the deals redirect the users to purchase products via a Shopify store.
Retail
Our team of PPC advertising specialists focused on driving sales and subscriptions through advanced shopping campaigns, branded search, display, shopping, and retargeting campaigns with Google Ads. We conducted continual A/B testing by testing headlines, ad copy, creatives, and call-to-actions to identify ad variants that worked significantly better on Facebook Ads. These efforts fueled an increase in return on ad spend and revenue, while helping the client to achieve their pay-per-click advertising goals.
We started by analyzing the client's historical search terms, audience categories, and product performance. Keyword research was done using syndicated tools such as Keyword planner and SEMrush. Search terms based on Google Ads suggestions were also included in the keyword list, which helped serve as a guide for restructuring the campaigns. Based on the attribution model, we set separate targets for high-assisting keywords. Google Search and Google Shopping campaigns were restructured and segmented to enable better bid and budget management. The high-level research and analysis done by the team facilitated strategic use of the ad budget.
The launch of non-branded campaigns enabled them to reach customers who would not otherwise have entered the marketing funnel. These campaigns helped increase the customer base and created more opportunities to create loyal customers. While bidding on non-branded terms, we discovered new search terms that had the potential to garner more traffic and generate new customers. We incorporated these search terms in the non-branded campaigns.
We noticed that the display campaigns lacked the potential needed to drive conversion volume. Looking at the location-wise performance of the campaigns, we identified locations that outperformed others. We modified the location-based bid modifiers for all the campaigns and developed a location-based bid modifier strategy for each state which was adjusted as the seasons changed. Similarly, we identified the timings and days of the week during which sales were high. The bid was modified to pick up as much traffic as possible during these times and also to pick up any lost opportunities.
For Facebook, click and reach-focused campaigns were run to increase customer reach. We worked on developing a rich audience base and excluded people who did not spend time on the site. Look-alike audiences were created based on the category of subscription, the recency of users, and the frequency with which they visited the site. Ad sets were split based on the subscriptions being promoted. We created a testing strategy for each placement – this included unique creative, offerings, and messaging as user experience/intent differs by placement. Rather than continuing to add ads to existing ad sets, we duplicated winning ads into new ad sets to run against new creatives.
For reporting marketing activities, the client wanted to build actionable and interactive reports for the executive, operational, and marketing teams. Using Google Data Studio, we built a fully automated consolidated reporting dashboard with real-time marketing data from various channels such as website, social, search, and PPC. Automated reporting enabled them to reduce the time spent on building reports and invest more towards developing and implementing data-driven insights. Faster workflows and more precise insights helped optimize campaigns and increase ROI.
We started by analyzing the client's historical search terms, audience categories, and product performance. Keyword research was done using syndicated tools such as Keyword planner and SEMrush. Search terms based on Google Ads suggestions were also included in the keyword list, which helped serve as a guide for restructuring the campaigns. Based on the attribution model, we set separate targets for high-assisting keywords. Google Search and Google Shopping campaigns were restructured and segmented to enable better bid and budget management. The high-level research and analysis done by the team facilitated strategic use of the ad budget.
The launch of non-branded campaigns enabled them to reach customers who would not otherwise have entered the marketing funnel. These campaigns helped increase the customer base and created more opportunities to create loyal customers. While bidding on non-branded terms, we discovered new search terms that had the potential to garner more traffic and generate new customers. We incorporated these search terms in the non-branded campaigns.
We noticed that the display campaigns lacked the potential needed to drive conversion volume. Looking at the location-wise performance of the campaigns, we identified locations that outperformed others. We modified the location-based bid modifiers for all the campaigns and developed a location-based bid modifier strategy for each state which was adjusted as the seasons changed. Similarly, we identified the timings and days of the week during which sales were high. The bid was modified to pick up as much traffic as possible during these times and also to pick up any lost opportunities.
For Facebook, click and reach-focused campaigns were run to increase customer reach. We worked on developing a rich audience base and excluded people who did not spend time on the site. Look-alike audiences were created based on the category of subscription, the recency of users, and the frequency with which they visited the site. Ad sets were split based on the subscriptions being promoted. We created a testing strategy for each placement – this included unique creative, offerings, and messaging as user experience/intent differs by placement. Rather than continuing to add ads to existing ad sets, we duplicated winning ads into new ad sets to run against new creatives.
For reporting marketing activities, the client wanted to build actionable and interactive reports for the executive, operational, and marketing teams. Using Google Data Studio, we built a fully automated consolidated reporting dashboard with real-time marketing data from various channels such as website, social, search, and PPC. Automated reporting enabled them to reduce the time spent on building reports and invest more towards developing and implementing data-driven insights. Faster workflows and more precise insights helped optimize campaigns and increase ROI.