Paid Search and Paid Social Advertising

• Identify and scale campaigns that can efficiently convert and subsequently expand to other opportunities from a budget management perspective.
• Launch non-branded campaigns by identifying high-performing terms, along with good distribution of match types using search query reporting and keyword research.
• Orchestrate a low-cost traffic-driving mechanism for display campaigns to build up audience and cookie pools for remarketing.
• Scale remarketing campaigns on Facebook using look-alike audiences and split testing.
• Build a fully automated reporting dashboard with real-time data that can help streamline communication within the team.

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.

• Performance Summary Dashboard presents a consolidated view of the entire business and displays data on key performance indicators such as spend, revenue, ROAS, and profit.
• Channel Summary Report displays data on key performance indicators across each of the channels/platforms under management.
• Daily Progress Report tracks the clicks, impressions, cost, conversions, and CPA for each channel on a daily basis. Users can compare figures for the present day, week, and month with the previous period. The differences are indicated using colored up/down arrows.

• High-level keyword analysis and attribution modeling facilitated strategic use of ad budget and improved the efficiency of Google Search and Google Shopping campaigns.
• Non-branded campaigns strengthened the customer base growth rate and created more opportunities to build loyal customers.
• Location-based bid modifiers and maximum bidding on the identified high sales periods doubled the display campaigns' CTR and conversion rate.
• Look-alike audiences created based on user behavior, as well as continual split testing with creatives, offerings, and messaging helped scale remarketing campaigns on Facebook.
• The automated Google Data Studio reporting process significantly reduced time and effort.
• Faster insights into KPIs helped to quickly analyze campaign performance and identify top converting areas.
• Data-driven insights led to informed decision-making that helped optimize campaigns and increase ROI.
• Business teams could easily explore and analyze data, extending the value of data throughout the organization.

• Google Ads
• Facebook Ads
• Google Analytics
• Google Data Studio