What is the methodology for Analytics?

Learn more about Creative Analytics' methodology

Hilary Smith avatar
Written by Hilary Smith
Updated over a week ago

Creative Analytics is powered by AI, which leverages computers and machines to mimic the problem-solving and decision-making capabilities of the human mind.

3 Types of AI Leveraged

Computer Vision: Machines are able to process and detect every visual element in every frame of the media being analyzed.

Natural Language Processing: Through NLP, the algorithm understands the text and spoken words in the media, such as call-to-action and copy.

Speech Recognition: Using speech recognition, the AI converts the voice-over to written format to identify the ad’s spoken CTAs.

Step 1: Tagging Creative Elements

The Creative Analytics tagging feature makes it easy to see and act on all of this information.

Tagging happens automatically once a client connects their ad accounts to VidMob’s platform in a matter of hours.

Then, using all of the AI components mentioned, the program adds tags to each piece of creative in the ad account – from spoken words per second, to text density, to human emotion.

Step 2: Overlaying Media Metrics

VidMob pulls in the media metrics that are made available via the platforms API, which are 1st party media metrics (Brand Lift coming soon!).

Because of the granularity of data (creative level) that is received through our partners APIs, VidMob is able to automatically overlay 1st party KPI metrics across each element tag to understand what that individual element’s KPI performance was.

Step 3: Performance Comparisons

Based on a number of filtering options dictated by clients (listed below), an ad account average is assigned in which the elements performance is compared against using the standard % increase formula: % increase = 100 x [(final – initial)/initial]

Creative Analytics Filters:

  • Time Frame

  • Objective

  • Media Type

  • Ad Type

  • Campaign

  • Ad/Ad Set

  • KPI

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