The Business Case for Solving Visual Search with Computer Vision

Empower Users to Find Objects in Your Media Archives Quickly

What it Does Icon

What it Does

Visual search (VS) extracts information from digital media via computer vision algorithms and machine learning models. The metadata from the media is used to describe, search, and trigger actions.

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  • Increase productivity by 25% to 50% when searching within media.
  • Improve video content sharing across the organization by 25% to 50%.
  • Drive online shopping conversion rates by 20% to 30% by including search results of similar items.
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HIGH: Worth immediate action if your business processes entail capturing video for record keeping, commerce, quality checks, or detecting anomalies.

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Risk Level

MEDIUM: Risk factors include inadequate operational processes, information leakage impacting security, and unacceptable performance of computer vision algorithms and models to identify objects.

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30/60/90 Plan

Identify use cases, VS vendors, and key performance indicators, then conduct vendor trials and POCs while assessing workflow integration challenges. Once a VS solution is acquired, draw out plans for expanded use and configure metrics to show benefits over time.

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Time to Value

The value of integrating visual search into a solution should be realized within three to six months.

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