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E-Commerce

Sentiment analysis and annotation best practices helped to increase efficiency 5 times

Industry and use case:

Retail and e-commerce, sentiment analysis

Data:

200,000 customer reviews

Project duration:

30 days
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Challenge:

The client wanted to develop a neural network that could help determine customer reviews’ topics and perform sentiment analysis. They contacted Training Data to annotate 200,000 customer reviews

Solution:

The 40-person team from Training Data classified 10+ topics and 5+ sentiments. The personal manager was in touch with the customer 24/7, making it possible to quickly discuss and change the original project scope and labelling requirements. In addition, the team helped to redesign the work of the customer service team to improve efficiency

Outcomes:

  • High-quality data accelerated customer support processes 5 times
  • Real-time identification of negative reviews and instant follow-ups
  • Automatic sentiment analysis and review classification
The annotators and project manager not only quickly labelled a large quantity of data but also redesigned a process that improved the entire work of our department. Very efficient and professional team!
Mark T.
ML Team Lead in a Bank

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Stages of work

  • Application

    /01
    Leave a request on the website for a free consultation with an expert. Th e acco unt manager will guide you on the services, timelines, and price

  • Free pilot

    /02
    We will conduct a test pilot project for you and provide a golden set, based on which we will determine the final technical requirements and approve project metrics

  • Agreement

    /03
    We prepare a contract and all necessary documentation upon the request of your accountants and lawyers

  • Workflow customization

    /04
    We form a pool of suitable tools and assign an experienced manager who will be in touch with you regarding all project details

  • Quality control

    /05
    Data uploads for verification are done iteratively, allowing your team to review and approve collected/annotated data

  • Post-payment

    /06
    You pay for the work after receiving the data in agreed quality and quantity

Timeline

  • 24 hours
    Application
  • 24 hours
    Consultation
  • 1 to 3 days
    Pilot
  • 1 to 5 days
    Conducting a pilot
  • 1 day to several years
    Carrying out work on the project
  • 1 to 5 days
    Quality control
You pay for the work after you have received the data
in the established quality and quantity

Why
Training Data

  • Quality Assurance:
  • Enhanced Data Accuracy
  • Consistency in Labels
  • Reliable Ground Truth
  • Mitigation of Annotation Biases
  • Cost and Time Efficiency
  • Data Security and Confidentiality:
  • GDPR Compliance
  • Non-disclosure agreement
  • Data Encryption
  • Multiple data storage options
  • Access Controls and Authentication
  • Expert Team:
  • 6 years in industry
  • 35 top project managers
  • 40+ languages
  • 100+ countries
  • 250k+ assessors
  • Flexible and Scalable Solutions:
  • 24/7 availability of customer service
  • 100% post payment
  • $550 minimum check
  • Variable Workload
  • Customized Solutions
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Tell us about your project!

    Choose interested services:

    Select an option

    • Data labeling

    • Data collection

    • Datasets

    • Human Moderation

    • Other (describe below)