#marketing-analytics

#marketing-analytics

Not just any algorithm, mind you, but the most devilish metric devised to date. Because it finally translates the old publicity strategy of fame once governed by unquantifiable guesswork into money. No, it isn't (black) magic, just computerized math: by analyzing and comparing quantitative and qualitative data, the program in question calculates and assigns an economic value to these star appearances based on their public performance.

Over the past decade, marketers have invested in dozens of creative data solutions to measure attention, emotion, distinctiveness, brand recall, and more. Yet these data sources remain disconnected, with brands switching between dashboards to gather creative intelligence. This means valuable insights can't be scaled, merged, or operationalised fast enough for modern marketing.

Instead, interaction data - the digital breadcrumbs left behind by real users - has become a vital lens for understanding audience behavior. Consider how Netflix fine-tunes its recommendation interface. Every hover, pause, and scroll through a content row contributes to decisions about what shows to highlight or which thumbnails perform best. Similarly, Airbnb uses journey tracking to identify where users abandon booking flows, helping them streamline page layouts and increase conversion rates.

Advertisers working with one of LinkedIn's certified B2B Attribution and Analytics partners now better measure campaign impact with insights from Company Intelligence API. Aggregated company-level engagement data from LinkedIn, like paid and organic impressions or clicks, can now be viewed directly within existing reports and dashboards alongside additional campaign insights, with no extra setup required. Partners ingest this data and combine it with CRM outcomes and other channels to deliver attributed metrics, like pipeline impact and ROI.

76% of U.S. consumer marketers who invested in a sports sponsorship in 2024 struggle to calculate the return on that investment (ROI), according to Forrester.

Google's slow updates to Performance Max allows advertisers to see channel-level breakdowns across various platforms, but without the ability to act on the data.

"Conversion lift testing helps determine how many conversions can be attributed directly to a specific marketing campaign or channel, rather than other factors."