JOB MARKET & HR

Company Reviews Monitoring

Track employee reviews, ratings, and employer brand sentiment across review platforms. Understand what employees are saying.

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Employer Brand Matters

Employee reviews on Glassdoor, Indeed, and other platforms shape how candidates perceive your company. Negative reviews can hurt recruiting, while positive sentiment attracts top talent.

Monitoring reviews manually across platforms is tedious. You need automated collection and analysis to track sentiment over time.

WebScraping.AI Solution

  • Multi-Platform Monitoring: Track reviews across Glassdoor, Indeed, and more
  • Sentiment Analysis: AI-powered analysis of review sentiment
  • Trend Detection: Identify emerging themes and issues
  • Competitive Intel: Compare your ratings against competitors

Review Intelligence Features

Comprehensive employer brand monitoring

Ratings Tracking

Monitor overall ratings, category scores, and rating trends over time.

Sentiment Analysis

AI analysis of pros, cons, and overall review sentiment.

Theme Extraction

Identify common themes like culture, management, compensation.

Competitor Comparison

Benchmark your employer brand against competitors.

Code Examples

Extract company review data

Extract company ratings & review summary
curl -G "https://api.webscraping.ai/ai/fields" \
  --data-urlencode "api_key=YOUR_API_KEY" \
  --data-urlencode "url=https://review-site.com/company/tech-corp/reviews" \
  --data-urlencode "fields[company_name]=Company name" \
  --data-urlencode "fields[overall_rating]=Overall rating out of 5" \
  --data-urlencode "fields[total_reviews]=Total number of reviews" \
  --data-urlencode "fields[recommend_to_friend]=Percentage who recommend" \
  --data-urlencode "fields[ceo_approval]=CEO approval rating" \
  --data-urlencode "fields[culture_rating]=Culture & values rating" \
  --data-urlencode "fields[worklife_rating]=Work-life balance rating" \
  --data-urlencode "fields[compensation_rating]=Compensation & benefits rating" \
  --data-urlencode "fields[career_rating]=Career opportunities rating" \
  --data-urlencode "fields[management_rating]=Senior management rating"
# Response:
# {
#   "company_name": "Tech Corp",
#   "overall_rating": 4.2,
#   "total_reviews": 1547,
#   "recommend_to_friend": "78%",
#   "ceo_approval": "85%",
#   "culture_rating": 4.3,
#   "worklife_rating": 3.8,
#   "compensation_rating": 4.1,
#   "career_rating": 4.0,
#   "management_rating": 3.7
# }
# pip install webscraping_ai
# https://pypi.org/project/webscraping-ai/
from webscraping_ai import Client

client = Client(api_key="YOUR_API_KEY")
result = client.fields(
    "https://review-site.com/company/tech-corp/reviews",
    fields={
        "company_name": "Company name",
        "overall_rating": "Overall rating out of 5",
        "total_reviews": "Total number of reviews",
        "recommend_to_friend": "Percentage who recommend",
        "ceo_approval": "CEO approval rating",
        "culture_rating": "Culture & values rating",
        "worklife_rating": "Work-life balance rating",
        "compensation_rating": "Compensation & benefits rating",
        "career_rating": "Career opportunities rating",
        "management_rating": "Senior management rating",
    },
)
print(result)
# Response:
# {
#   "company_name": "Tech Corp",
#   "overall_rating": 4.2,
#   "total_reviews": 1547,
#   "recommend_to_friend": "78%",
#   "ceo_approval": "85%",
#   "culture_rating": 4.3,
#   "worklife_rating": 3.8,
#   "compensation_rating": 4.1,
#   "career_rating": 4.0,
#   "management_rating": 3.7
# }
// npm install webscraping-ai
// https://www.npmjs.com/package/webscraping-ai
import { WebScrapingAI } from 'webscraping-ai';

const client = new WebScrapingAI({ apiKey: 'YOUR_API_KEY' });
const result = await client.fields({
  url: 'https://review-site.com/company/tech-corp/reviews',
  fields: {
    company_name: 'Company name',
    overall_rating: 'Overall rating out of 5',
    total_reviews: 'Total number of reviews',
    recommend_to_friend: 'Percentage who recommend',
    ceo_approval: 'CEO approval rating',
    culture_rating: 'Culture & values rating',
    worklife_rating: 'Work-life balance rating',
    compensation_rating: 'Compensation & benefits rating',
    career_rating: 'Career opportunities rating',
    management_rating: 'Senior management rating',
  },
});
console.log(result);
// Response:
// {
//   "company_name": "Tech Corp",
//   "overall_rating": 4.2,
//   "total_reviews": 1547,
//   "recommend_to_friend": "78%",
//   "ceo_approval": "85%",
//   "culture_rating": 4.3,
//   "worklife_rating": 3.8,
//   "compensation_rating": 4.1,
//   "career_rating": 4.0,
//   "management_rating": 3.7
// }
<?php
// composer require webscraping-ai/webscraping-ai-php
// https://packagist.org/packages/webscraping-ai/webscraping-ai-php
require 'vendor/autoload.php';

use WebScrapingAI\Client;

$client = new Client('YOUR_API_KEY');
$result = $client->fields('https://review-site.com/company/tech-corp/reviews', [
    'company_name'        => 'Company name',
    'overall_rating'      => 'Overall rating out of 5',
    'total_reviews'       => 'Total number of reviews',
    'recommend_to_friend' => 'Percentage who recommend',
    'ceo_approval'        => 'CEO approval rating',
    'culture_rating'      => 'Culture & values rating',
    'worklife_rating'     => 'Work-life balance rating',
    'compensation_rating' => 'Compensation & benefits rating',
    'career_rating'       => 'Career opportunities rating',
    'management_rating'   => 'Senior management rating',
]);
print_r($result);
// Response:
// {
//   "company_name": "Tech Corp",
//   "overall_rating": 4.2,
//   "total_reviews": 1547,
//   "recommend_to_friend": "78%",
//   "ceo_approval": "85%",
//   "culture_rating": 4.3,
//   "worklife_rating": 3.8,
//   "compensation_rating": 4.1,
//   "career_rating": 4.0,
//   "management_rating": 3.7
// }
# gem install webscraping_ai
# https://rubygems.org/gems/webscraping_ai
require 'webscraping_ai'

client = WebScrapingAI::Client.new(api_key: 'YOUR_API_KEY')
result = client.fields(
  'https://review-site.com/company/tech-corp/reviews',
  fields: {
    company_name:         'Company name',
    overall_rating:       'Overall rating out of 5',
    total_reviews:        'Total number of reviews',
    recommend_to_friend:  'Percentage who recommend',
    ceo_approval:         'CEO approval rating',
    culture_rating:       'Culture & values rating',
    worklife_rating:      'Work-life balance rating',
    compensation_rating:  'Compensation & benefits rating',
    career_rating:        'Career opportunities rating',
    management_rating:    'Senior management rating',
  }
)
puts result.inspect
# Response:
# {
#   "company_name": "Tech Corp",
#   "overall_rating": 4.2,
#   "total_reviews": 1547,
#   "recommend_to_friend": "78%",
#   "ceo_approval": "85%",
#   "culture_rating": 4.3,
#   "worklife_rating": 3.8,
#   "compensation_rating": 4.1,
#   "career_rating": 4.0,
#   "management_rating": 3.7
# }
// go get github.com/webscraping-ai/webscraping-ai-go/v4
// https://pkg.go.dev/github.com/webscraping-ai/webscraping-ai-go/v4
package main

import (
    "context"
    "fmt"

    webscrapingai "github.com/webscraping-ai/webscraping-ai-go/v4"
)

func main() {
    client, _ := webscrapingai.NewClient(&webscrapingai.Config{APIKey: "YOUR_API_KEY"})
    result, _ := client.Fields(context.Background(), &webscrapingai.FieldsOptions{
        URL: "https://review-site.com/company/tech-corp/reviews",
        Fields: map[string]string{
            "company_name": "Company name",
            "overall_rating": "Overall rating out of 5",
            "total_reviews": "Total number of reviews",
            "recommend_to_friend": "Percentage who recommend",
            "ceo_approval": "CEO approval rating",
            "culture_rating": "Culture & values rating",
            "worklife_rating": "Work-life balance rating",
            "compensation_rating": "Compensation & benefits rating",
            "career_rating": "Career opportunities rating",
            "management_rating": "Senior management rating",
        },
    })
    fmt.Println(result.Result)
}
// Response:
// {
//   "company_name": "Tech Corp",
//   "overall_rating": 4.2,
//   "total_reviews": 1547,
//   "recommend_to_friend": "78%",
//   "ceo_approval": "85%",
//   "culture_rating": 4.3,
//   "worklife_rating": 3.8,
//   "compensation_rating": 4.1,
//   "career_rating": 4.0,
//   "management_rating": 3.7
// }
// Maven: ai.webscraping:webscraping-ai:4.0.0
// https://central.sonatype.com/artifact/ai.webscraping/webscraping-ai
import ai.webscraping.Client;
import ai.webscraping.Config;
import ai.webscraping.option.FieldsOptions;
import ai.webscraping.result.FieldsResult;

Client client = new Client(Config.builder().apiKey("YOUR_API_KEY").build());
FieldsResult result = client.fields(FieldsOptions.builder()
    .url("https://review-site.com/company/tech-corp/reviews")
    .addField("company_name", "Company name")
    .addField("overall_rating", "Overall rating out of 5")
    .addField("total_reviews", "Total number of reviews")
    .addField("recommend_to_friend", "Percentage who recommend")
    .addField("ceo_approval", "CEO approval rating")
    .addField("culture_rating", "Culture & values rating")
    .addField("worklife_rating", "Work-life balance rating")
    .addField("compensation_rating", "Compensation & benefits rating")
    .addField("career_rating", "Career opportunities rating")
    .addField("management_rating", "Senior management rating")
    .build());
System.out.println(result.getResult());
// Response:
// {
//   "company_name": "Tech Corp",
//   "overall_rating": 4.2,
//   "total_reviews": 1547,
//   "recommend_to_friend": "78%",
//   "ceo_approval": "85%",
//   "culture_rating": 4.3,
//   "worklife_rating": 3.8,
//   "compensation_rating": 4.1,
//   "career_rating": 4.0,
//   "management_rating": 3.7
// }
// dotnet add package WebScrapingAI
// https://www.nuget.org/packages/WebScrapingAI
using WebScrapingAI;

var client = new WebScrapingAIClient(new WebScrapingAIClientOptions { ApiKey = "YOUR_API_KEY" });
var result = await client.FieldsAsync(new FieldsRequest {
    Url = "https://review-site.com/company/tech-corp/reviews",
    Fields = new Dictionary<string, string> {
        ["company_name"] = "Company name",
        ["overall_rating"] = "Overall rating out of 5",
        ["total_reviews"] = "Total number of reviews",
        ["recommend_to_friend"] = "Percentage who recommend",
        ["ceo_approval"] = "CEO approval rating",
        ["culture_rating"] = "Culture & values rating",
        ["worklife_rating"] = "Work-life balance rating",
        ["compensation_rating"] = "Compensation & benefits rating",
        ["career_rating"] = "Career opportunities rating",
        ["management_rating"] = "Senior management rating",
    },
});
Console.WriteLine(result.Result);
// Response:
// {
//   "company_name": "Tech Corp",
//   "overall_rating": 4.2,
//   "total_reviews": 1547,
//   "recommend_to_friend": "78%",
//   "ceo_approval": "85%",
//   "culture_rating": 4.3,
//   "worklife_rating": 3.8,
//   "compensation_rating": 4.1,
//   "career_rating": 4.0,
//   "management_rating": 3.7
// }
Surface sentiment themes from recent reviews
curl -G "https://api.webscraping.ai/ai/question" \
  --data-urlencode "api_key=YOUR_API_KEY" \
  --data-urlencode "url=https://review-site.com/company/tech-corp/reviews" \
  --data-urlencode "question=What are the most common positive and negative themes in recent reviews? What do employees like most and complain about most?"

# pip install webscraping_ai
# https://pypi.org/project/webscraping-ai/
from webscraping_ai import Client

client = Client(api_key="YOUR_API_KEY")
answer = client.question(
    "https://review-site.com/company/tech-corp/reviews",
    question="What are the most common positive and negative themes in recent reviews? What do employees like most and complain about most?",
)
print(answer)

// npm install webscraping-ai
// https://www.npmjs.com/package/webscraping-ai
import { WebScrapingAI } from 'webscraping-ai';

const client = new WebScrapingAI({ apiKey: 'YOUR_API_KEY' });
const answer = await client.question({
  url: 'https://review-site.com/company/tech-corp/reviews',
  question: 'What are the most common positive and negative themes in recent reviews? What do employees like most and complain about most?',
});
console.log(answer);

<?php
// composer require webscraping-ai/webscraping-ai-php
// https://packagist.org/packages/webscraping-ai/webscraping-ai-php
require 'vendor/autoload.php';

use WebScrapingAI\Client;

$client = new Client('YOUR_API_KEY');
$answer = $client->question(
    'https://review-site.com/company/tech-corp/reviews',
    'What are the most common positive and negative themes in recent reviews? What do employees like most and complain about most?',
);
echo $answer;

# gem install webscraping_ai
# https://rubygems.org/gems/webscraping_ai
require 'webscraping_ai'

client = WebScrapingAI::Client.new(api_key: 'YOUR_API_KEY')
answer = client.question(
  'https://review-site.com/company/tech-corp/reviews',
  question: 'What are the most common positive and negative themes in recent reviews? What do employees like most and complain about most?'
)
puts answer

// go get github.com/webscraping-ai/webscraping-ai-go/v4
// https://pkg.go.dev/github.com/webscraping-ai/webscraping-ai-go/v4
package main

import (
    "context"
    "fmt"

    webscrapingai "github.com/webscraping-ai/webscraping-ai-go/v4"
)

func main() {
    client, _ := webscrapingai.NewClient(&webscrapingai.Config{APIKey: "YOUR_API_KEY"})
    answer, _ := client.Question(context.Background(), &webscrapingai.QuestionOptions{
        URL:      "https://review-site.com/company/tech-corp/reviews",
        Question: "What are the most common positive and negative themes in recent reviews? What do employees like most and complain about most?",
    })
    fmt.Println(answer)
}

// Maven: ai.webscraping:webscraping-ai:4.0.0
// https://central.sonatype.com/artifact/ai.webscraping/webscraping-ai
import ai.webscraping.Client;
import ai.webscraping.Config;
import ai.webscraping.option.QuestionOptions;

Client client = new Client(Config.builder().apiKey("YOUR_API_KEY").build());
String answer = client.question(QuestionOptions.builder()
    .url("https://review-site.com/company/tech-corp/reviews")
    .question("What are the most common positive and negative themes in recent reviews? What do employees like most and complain about most?")
    .build());
System.out.println(answer);

// dotnet add package WebScrapingAI
// https://www.nuget.org/packages/WebScrapingAI
using WebScrapingAI;

var client = new WebScrapingAIClient(new WebScrapingAIClientOptions { ApiKey = "YOUR_API_KEY" });
var answer = await client.QuestionAsync(new QuestionRequest {
    Url = "https://review-site.com/company/tech-corp/reviews",
    Question = "What are the most common positive and negative themes in recent reviews? What do employees like most and complain about most?",
});
Console.WriteLine(answer);

Why Monitor Company Reviews

Employer Branding: Understand and improve your employer brand.
Early Warning: Detect issues before they become widespread.
Competitive Intel: Benchmark against competitors.
Recruiting Support: Address concerns candidates may have.
Culture Insights: Understand employee sentiment trends.

Monitoring Use Cases

HR & People Teams

Track employee sentiment and address issues

Talent Acquisition

Understand candidate perceptions

Investor Due Diligence

Assess company culture before investing

Competitive Intelligence

Monitor competitor employer brands

Related Use Cases

More HR and review monitoring solutions

Job Listing Aggregation

Aggregate job postings from multiple boards.

Salary Benchmarking

Collect compensation data from job postings.

Social Media Monitoring

Track brand mentions across social platforms.

Start Monitoring Company Reviews

Get started with 1,000 free API credits. No credit card required.

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