The client is a web labeling company based in Israel. The company aims at giving advertisers a greater control over their brands and budgets for web advertising. The company is founded by a group of Israel's elite intelligence unit.
The client has incorporated advanced machine learning algorithms, next-level NLP (Neuro-Linguistic Programming) capabilities, and sophisticated anomaly detection modules into its platform to battle negative brand content and fake bot traffic. They have developed a prevention platform that analyzes negative content and identifies fake users in less than 20 minutes.
The client required an outsourcing partner to label 45,000 websites. The labeling tags included OK, Negative, and Sensitive. O2I had to update this information onto the client's custom tool. The client wanted to pass this information onto its customers to help them identify the most appropriate websites for their digital advertising.
The key challenges faced during the project were -
O2I analyzed the client's requirement and offered a free quality test (trial). The client remotely trained one data entry operator for three business days. O2I ensured that the resource had an immense knowledge of current events and an unbiased approach.
Post the training, we analyzed 500 URLs (60 URLs per hour) using the tool as a trial. The tool was adopted as an extension. Each website was analyzed, labelled as OK, Negative, or Sensitive and then updated onto the client's tool.
The Negative Category included websites that promoted xxxxx. The Sensitive Category included websites that promoted: xxx. The OK Category included websites that did not fall into the above categories. O2I ensured the resource assigned to the project was unbiased and maintained a neutral approach while categorizing the websites.
On O2I's completion of the first batch, the satisfied client signed a long-term contract with Outsource2india to label the remaining websites.
O2I categorized the websites according to the clients' requirement accurately and within the stipulated time. The satisfied client expressed appreciation at the timely delivery and cost savings, accurate labeling, unbiased approach to labeling, and professionalism.
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