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Real-time Image Annotation for a Retail Tech Developer

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m9439dbe

Real-time Image Annotation for a Retail Tech Developer

PDF

Real-time Image Annotation for a Retail Tech Developer

Machine Learning (ML) has quickly proven to be a helpful tool for both consumers and tech business owners. With split-second decisions needing to be made in an ever-changing tech environment, ML solves this pain point by allowing companies to gather and analyze data rapidly and improve their customer experience (CX)1.

The Challenge

Our client, a US-based interactive retail technology developer, provides retailers with end-to-end automation solutions for their operations. They allow their customers to create better and more efficient stores, lower their costs, and increase their profitability.

They needed a flexible workforce infrastructure, reliable support in creating training materials on real-time image annotation and tagging, and an improved quality assurance system.

The Solution

TaskUs identified three main factors that will address the client’s pain points:

  1. Workforce Management

We provided the client with the flexible workforce they needed to accomplish the required data tagging/annotation work.

  1. Quality Control

We established a comprehensive quality infrastructure by implementing basic auditing and quality scoring baselines and setting expectations for performance.

  1. Learning Experience

We developed blended agent training on two lines of business for maximum productivity. 

The two keys to achieving your business growth are efficient workforce management and performance and quality management. Along with better ML models, our client was able to specify the transactions they need from Us, which also helps them better manage their costs.

Download the full case study, Real-time Image Annotation for a Retail Tech Developer, to know more about saving unnecessary costs, mitigating revenue loss, and exceeding your target average monthly quality score.

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    Real-time Image Annotation For a Retail Tech Developer

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