Detect the intent behind any   text interaction e-mails sentences

Detect and classify the unstructured text data based on the intent of the author by analyzing the language they use. Compile and analyze large volumes of data to uncover actionable insights.

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Bytesview Intent Detection

What is Intent Detection ?

Intent detection is the process of analyzing the text data to identify the intent of the author. Much of human behavior and actions are based on intentions,and understanding intentions can help you interpret these behaviors.

It can help your business understand their customers and predict their future course of action. Intent detection can identify the customer's intent ahead of time and help in plotting the future course of action.

BytesView's cutting-edge intent detection and classification techniques can help you analyze and classify based on the intent expressed in the text by the user.

Detect the intentions of current and prospective customers and plan the future course of action accordingly.

Compile and analyze large volumes of text data to detect the intention of users with ease.

Intent Detection Demo

Result

Positive
Neutral
Negative

Result

Accuracy

Topic Label

Result

News

Feedback

Promotion

Query

Spam

Result

Relatedness

Result

Angry

Fear

Happy

Sad

Love

Neutral

Result

Result

Result

BytesView Feature Extraction Technical Specifications

Technical Specification of sentiment Analysis
Deployment Availability
BytesView Server
BytesView Cloud
Amazon Web Server
Plugins
Google Spreadsheet
Zendesk
Zapier
Bindings
Curl,
Python,
Php,
Java,
Curl,
R,
Ruby,
C#,
Node.JS
Supported Languages
English
Industries
Specific INTENT DETECTION Model Developed For
Customization
Customized solution as per your need

How can your business benefit from a Intent Detection tool?

Discover your customers intentions

Use intent analysis to analyze textual data to identify the intentions of your customers. Classify users based on intent such as purchase, issue, query, complaints, etc. to increase efficiency and user experience.

Discover your customers intentions
Generate leads that convert

Generate leads that convert

Analyze large volumes of customer data and identify users that are interested in what you offer. Use intent analysis to create lists of users that are actually interested in purchasing your product.

Plan targeted campaigns

After you identify the right target audience with intent analysis you can use the insights to plan marketing campaigns targeting users that are actually interested in your product and increase customer satisfaction

Plan targeted campaigns

How to access BytesView Intent Detection tool ?

Given below are the steps to access the BytesView Intent Detection API . You can either gather the data by yourself in an excel/CSV format or ask us to do so.

  • Gather pieces of text and documents from multiple sources
  • Compile the gathered text data in an Excel/CSV file or Google spreadsheet
  • Install the BytesView plugins on Google spreadsheet and open the add-ons tab to locate it.
  • Create a demo account or Purchase a subscription plan that suits your requirements and get an API key.
  • Paste the given API key on the BytesView plugin to activate it
  • Select the cells you want to analyze and the machine learning model you want to use. Click run to start analyzing your data.
  • For more information on intent detection models, go through the video.
access sentiment analysis

Now build and train custom Intent Detection models as per your need

build custom sentiment analysis

Now train custom intent detection models with data related to your organization to further increase accuracy of the output.

  • Collect the data you want to analyze and export them as a CSV or Excel file. Use a web scraping tool or let us do it for you.
  • Go on the BytesView dashboard and click on “create a model” and chose between a classifier or an extraction model.
  • Click on classifier and then select intent detection model.
  • Import your data and select which column you want to analyze if there is more than one.
  • Tag a few of the data units as Positive, Negative, or Neutral to train your model. The model will begin making its own conclusions after a few tags.
  • Name and Test your model to see how it is working.
  • Once your model is trained, you can upload the whole data set to get results.

Get started with BytesView

Let BytesView platform helps you solve all your text analysis needs

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