Panoramic: Paid Social Marketing Benchmarks

Anonymized benchmark performance across multiple social media platforms.

Description:

Panoramic’s Benchmark DataFeed provides users with an exhaustive, comparative dataset with which to contextualize their marketing performance across key channels.

Samples/tables included:
Partner Performance Benchmarks highlighting metric norms over the previous year for Facebook, Snap, Google Ads & Twitter

Fields Included:
– DATA_SOURCE
– OBJECTIVE
– PUBLISHER
– COST_PER_ENGAGEMENT
– COST_PER_LIKES
– COST_PER_LINK_CLICK
– COST_PER_SHARE
– COST_PER_THOUSAND_IMPRESSIONS
– COST_PER_VIEW_COMPLETION
– VIDEO_VIEW_RATE

Example Use Case:
Comparing and contrasting KPIs with industry benchmarks is central to evaluating the costs and outcomes of digital marketing campaigns (i.e., the cost-efficacy). Panoramic Benchmarks Data Feed facilitates these analyses by providing robust averages that can be compared to real-time metrics.

Example insight that can be derived while leveraging this data:
Over the weekend, Company X received a $10.21 cost per share on their Facebook campaigns. On the surface, this number doesn’t mean much. But, 25% of the campaigns had a VIDEO_VIEWS objective with a $2.89 cost per share and 75% of the campaigns were REACH campaigns with a $39.04 cost per share. Comparing these results with the Benchmark DataFeed would indicate that VIDEO_VIEWS campaigns are over performing and the REACH campaigns are underperforming. Additionally, if the media buyers wanted to optimize shares, it would be reasonable to shift the efforts more towards VIDEO_VIEWS campaigns.

 

About the Provider:

Panoramic is a unified data analytics layer that sits on top of your existing data warehouse. The platform was built by marketers for marketers to address the key pain points experienced as a result of today’s complex ecosystem of disparate data sources. Panoramic streamlines cross-channel data cleaning, mapping, modeling, and visualization, and fosters collaboration among teams for faster, smarter decisioning.

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