Annotation Labs

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Understand Customers Better with Annotation Services for Retail & E-Commerce

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Retail & eCommerce Data Annotation for AI & Computer Vision

Need of data annotation in e-commerce and retail

Retail & E-Commerce players are increasingly adopting AI-based solutions to tackle the rise in competition, reduction in customer loyalty, and ever-changing trends. It has become paramount to adopt a customer-first approach and find innovative ways to improve consumer satisfaction. Tools such as content moderation, in-store Retail AI, social media sentiment analysis, & brand perception map models require high-quality annotated & labeled data sets to train the machine learning and AI Computer Vision models.

How is data labeling used for autonomous vehicles?

Content Moderation & Chatbot Training NLP
Sentiment Analysis & Text Annotation of Brand Reviews

NLP models to train content moderation and chatbot tools

Sentiment Analysis & Text Annotation of Brand Reviews

Text extraction on social media to analyze consumer trends and brand reviews

Understand Consumer Preferences using Sentiment Analysis & Perceptual Maps
Annotations for Consumer Preferences in Store using AI & ML

Sentiment analysis to understand customer perceptions about brands, products & services

Annotations for Consumer Preferences in Store using AI & ML

Polygon annotation to identify in-store customer preferences for targeted marketing

Image Annotation to understand Product Categorization & Operations
Annotation for Automated Retail Footfall Count & Shopper Movement AI

Bounding Boxes to manage in-store product categorization

Annotation for Automated Retail Footfall Count & Shopper Movement AI

Annotation for shopping mall AI footfall count (number of people) and time spent analysis

Annotation tools used in e-commerce and retail industry

We specialize in personalizing our data annotation services to meet your Brands and Platforms needs.

Our beliefs behind each annotations

Core Value: Data Security & Privacy

Data Security & Privacy

Core Value: Fast Delivery & High Accuracy

Fast Delivery with High Accuracy

Core Value: Low Cost Pricing

Cost Effective Pricing

Core Value: Scalable Solutions by Expert

Scalable Solution by Experts

What is content moderation?

Content is the practice through user-generated content, and submissions are monitored, pre-determined applied to determine whether the said content is permissible or not. In simple terms, content moderation is defining if certain content goes against set communication guidelines in a platform or if it is acceptable to be broadcast or viewed by other people.

What is a facebook moderator?

A Facebook moderator is a person who moderates user-generated content on the Facebook platform. A Facebook moderator ensures that posts, comments, replies, and every other part of user content are not against the Facebook guidelines. That includes ensuring the content posted on the platform is not abusive, promotes violence, disturbs public order, or is offensive towards certain groups or any other category defined by the platform’s guidelines.

How to become a tiktok moderator?

To become a TikTok content moderator, you must visit the TikTok careers page and apply. You need at least one year of experience in content moderation, be familiar with internet regulations and laws, have a passion for internet content and be comfortable understanding what the task entails.

How to be a social media moderator?

Applicants must have at least some college education and background experience working with social media to become social media moderators. Some companies will require a minimum of one year in content moderation, while others allow new applicants to learn on the job. You are also needed to be dynamic, can make justifiable decisions, and possess strong communication and interpersonal skills. You can get job openings on the company’s career page or other job listing sites.

How are chatbots trained?

Chatbots are trained to predict what the users will say and how to respond. Training requires proper purpose definition by having a specific use case/cases. Next, the chatbot AI is trained to understand the many ways a customer could make a query, including the tone, mood, and nuances and how to respond to each case. That should be followed by validation and retraining if necessary.

How to train chatbot?

Training a chatbot is a laborious, procedural process. You start by defining the specific use cases of your chatbot. Next, ensure your intents are distinct and that several utterances for each plan are available. Next is to train the chatbot AI using the various instances of each intent. Continue training the AI until it can identify and respond appropriately to each intent.

What exactly does a virtual assistant do?

Intelligent virtual assistants are AI-powered machine learning software that performs the function of a virtual human assistant. They assist humans in completing tasks faster, such as helping them find relevant information more quickly or create lists easily. Virtual assistants also serve as personalized personal assistants assisting individuals in maintaining schedules, meetings, calendars, etc. Some examples include Siri, Alexa, and google assistant.

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