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10 Best Data Extraction Tools in 2023 For Your Business

Extracting data from various sources, including websites, APIs, and databases, requires efficient and accurate tools. These tools can help businesses save time and resources by automating data collection. When companies need to collect and analyze large amounts of data quickly from a variety of sources, data extraction tools can be beneficial, because they can provide insights into customer preferences, trends, and other data points that can help them make better business decisions. 

Using the tools featured in this guide, you can automate data extraction processes for various uses.

Why do businesses need data extraction?

Data extraction involves obtaining information from various sources and then transforming it into a structured format to make business decisions and gain insights. By using the features of data integration tools, you can unify different data sets and consolidate data flows.

Businesses need tools for data extraction to save time and resources by automating the data collection process. Automatic data extraction tools can also provide a more accurate and comprehensive view. Such instruments can be particularly useful for businesses that need to collect and analyze large amounts of data from various sources in a short amount of time. This is because they can help businesses gain insights into customer preferences, trends, and other data points that can inform business strategies.

To better understand, analyze, and communicate the underlying patterns and trends, specialists can use data visualization, the process of creating graphical representations of data sets. 

There are many ways that extracted data can be applied to visualization, including:

  • Dashboards. Extracted data can be used to create real-time dashboards to explore different data points through graphs, charts, maps, and tables.
  • Data visualization tools. These tools can be used to create a wide range of visualizations, such as line graphs, bar charts, and heat maps.
  • Business intelligence software. Extracted data can be imported into business intelligence software and used to create customer segmentation maps, performance metrics, etc.
  • Spreadsheet. Extracted data can be imported into Google Sheets, and used to create a variety of visualizations.

After extracting data from a source, you may need to filter out irrelevant information, fill in missing values, or manipulate the data so that it fits the desired format. At this stage, take advantage of data transformation tools. The next step is to select an appropriate visualization method (choosing a chart type and selecting specific design elements). The final stage is to create and fine-tune the visualization. The resulting data and combined dashboards can then be shared and discussed with others to make informed decisions.

What data types you can extract

  • Sales data. Data about purchases can be obtained from Salesforce or an e-commerce website and put into a program for analyzing information for insights. Also, this approach will be beneficial in gathering information for market research
  • Financial data. Information on your money, like what you’re making and spending, can be obtained from accounting programs or a bank account. This is so you can use it to plan a budget or figure out what your future financials might look like.
  • Customer data. Such information as purchase history or contact data from CRM systems might be used for marketing purposes. This category also involves collecting data for business intelligence and analytics platforms for better visualization.
  • Social media data for marketing purposes. Influencers and bloggers often use it to analyze their followers’ public data, to understand their attitudes and feelings, what they’re discussing, and how they feel about certain topics.
  • Training data. Extracting data for use in machine learning or artificial intelligence applications.

How do data extraction tools actually work

Data extraction tools automate the process of extracting data from a specific source and transforming it into a more usable and easier-to-understand format. To extract data using one of these tools, you typically need to specify the source and specific data you want. 

The tool will then access the source and retrieve the data, often using web scraping or other methods to gather and parse the information. Once the data has been collected, it can be stored in a structured format. Some data extraction tools also offer additional features, such as the ability to transform or clean the data and scheduling options for automatic extractions at regular intervals.

The process typically involves the following steps:

  1. Identification of the source of the data.
  2. Definition of the data points to be extracted. This may involve selecting specific elements or attributes on a webpage or defining specific fields in a database or API.
  3. Extracting the data. The extracted data is typically stored in a structured format, such as a spreadsheet or database table.
  4. Organizing the data. This data may require some cleaning and organizing before it is ready for analysis. This may involve removing duplicates, formatting the data correctly, or eliminating any errors.
  5. Export of the data. Ready-made datasets can be exported in various formats, including CSV, Excel, and JSON. The format is determined by the purpose (analyzing the data in a BI platform, or using it to train a machine learning algorithm).

Code vs. no-code data extraction tools

There are two main categories of data extraction tools: code-based tools and no-code tools.

Code-based tools require users to write code to extract data. These tools also need a certain level of programming skill and technical expertise. Examples of code-based data extraction tools include:

  • R packages: R is a programming language commonly used for statistical analysis and data visualization. It has a range of packages and tools for data extraction.
  • Python libraries: Python has a wide range of libraries and tools for data extraction, such as Beautiful Soup.
  • Java libraries: Java has a range of libraries and tools for data extraction, such as JSoup and Apache HttpClient.

Data extraction tools that do not require users to write code are called no-code. Unlike code-based tools, these tools are typically easier to use, more user-friendly, and may be less powerful. Examples of no-code data extraction tools include data integration platforms, such as, which offer a range of connectors and tools for extracting data from a variety of sources without the need to write code; web scraping tools, such as Octoparse to extract data from websites by specifying the data and the website; spreadsheet software, which offers a range of features and tools for extracting data from various sources.

An API data extraction algorithm generally works by sending requests to an API and receiving responses in a particular format, like JSON or XML. After parsing the response, the algorithm can extract the desired data points. To extract API data, algorithms use various techniques, such as:

  • JSON parsing. If the API returns data in JSON, you can extract specific data points from the JSON object.
  • HTML parsing.
  • Regular expressions. Using regular expressions, you can extract data points that follow a particular pattern.

For APIs that return large amounts of data in multiple pages or batches, data extraction algorithms may also use pagination techniques.

The main types of data extraction tools

The type of data extraction tool that is best suited for a particular task will depend on the source and format of the data. In addition, such a choice will rely on the specific data points that need to be extracted.

There are several types of data extraction tools available:

  • Webscrapes. These tools are designed for extracting data from multiple web pages or websites.
  • E-mail scrapers. Such data extraction tools can be used to collect data from email inboxes or other email repositories (addresses, subjects, text).
  • API extractors. API extractors can be used to import API data into databases for analysis or use.
  • PDF extractors. These tools can be used to extract images from PDFs and may also offer OCR (optical character recognition) to retrieve text from scanned documents.
  • Database extractors. An extractor can be used to obtain specific data points, entire tables, or datasets from a MySQL or Oracle database.

These tools work with a wide range of data sources. The following are a few of them:

  • APIs: Application Programming Interfaces permit two software applications to talk to one another and retrieve data from a wide range of sources.
  • Web scraping measures the HTML or XML of a website to gather data unavailable through APIs.
  • Data mining, extracts patterns and deductions from large quantities of data, frequently necessitating specialized programs.
  • Data integration, the process of collating data from several distinct sources and formats into a single, cohesive view. Data transformation and data mapping can be utilized to compile data from multiple sources. 
  • SQL (Structured Query Language) is a programming language used to query data stored in databases. SQL queries can be utilized to acquire the desired data points or records. 

Some tools include some data processing and are known as ETL tools. ETL stands for Extract, Transform, and Load. It refers to a process in data warehouses where data is extracted from various sources. The data is transformed to fit a specific format or structure and then loaded into a target system, such as a data warehouse.

Benefits of using data extraction tools

Data extraction instruments can offer significant benefits in terms of time and resource savings, accuracy, customization and flexibility, and scalability. Here are some advantages of using data extraction tools:

  • In comparison to manually collecting and organizing data, data extraction tools can help save time and resources by automating the process of collecting and organizing data.
  • Data extraction tools can be useful in ensuring the accuracy and completeness of the data collected. It is possible to customize the tool to your own specific requirements and data points, as well as set up an automated extraction schedule for convenience. 
  • Many of these tools are designed with user-friendliness in mind, with easy-to-understand interfaces, tailor-made features, and extensive documentation.

Anyone who collects and analyzes large amounts of data from various sources can benefit from data extraction tools. These tools can be used by individuals and organizations alike, including:

  1. Companies that conduct market research. These companies utilize data extraction tools to learn about consumer behavior, competitors, and market trends.
  2. Researchers can use data extraction tools to gather data for analysis and research purposes in economics, sociology, and political science.
  3. Data scientists and analysts can collect and clean large amounts of data for machine learning or artificial intelligence applications.
  4. Students and educators can use these tools to collect data for projects and assignments and learn the basics of data extraction and analysis.

Top 3 data extraction tools

We have selected the 3 leading data extraction tools from the top 10 you should consider in the first place. These tools are helpful not only for data extraction but also for integrating and transforming data.

FeaturesPricingPros & cons
A data automation and analytics platform
  • Automatic data refresh
  • Data stitching
  • Webhooks
  • Data consulting service
  • From $49 per month
    14 days of a free trial.
  • Pros: the ability to pull in data from multiple sources, auto-update feature, clear interface, no extra charge for team mode. It is easy to combine data from Airtable or BigQuery, and start visualization.
  • Cons: there is no ability to edit multiple importers at once at the moment.
  • Version control
  • Multiple environments
  • Wide range of integrations
  • Charging is based on actual usage. There are 2 types of credits: API and Database. From 0.75$ per execution.
    14 days of a free trial.
  • Pros: role-based access control, a wide range of integrations available, offers scheduling options, and a development environment.
  • Cons: not easy to configure some parameters, and not all features are well-documented.
  • Octoparse
  • Data export to CSV, Excel, and various databases
  • AJAX, JavaScript parsing ability
  • Automatic IP rotation
  • From 89$ per month.
    A free plan is available.
  • Pros: 5 day money-back guarantee for pricing plans. The free plan is available and easy to use for simple data extraction tasks.
  • Cons: Limited functionality for more complex tasks.
  • Treat this comparison of 5 data transformation platforms as an appetizer to the main course of top 10 solutions that are introduced below.

    Best 10 data extraction tools in 2023

    #1 –

    11 coupler logo is a data automation and analytics platform that provides a comprehensive ETL tool to get your data from multiple sources to three destinations. To use for data extraction, choose the data connector and configure it to connect to the desired data source. offers a range of connectors that can extract data from specific sources, such as Shopify, Clockify, and Jira. You can use Google Looker Studio, PowerBI, or Tableau for further data visualization, custom dashboards, and charts. allows users to easily connect to various data sources, including popular databases, SaaS applications, and CSV files, and extract data using customizable queries. Data can then be transformed using different options, such as filtering, mapping, and merging, before being loaded into a database, BigQuery as a data warehouse, or spreadsheet. With, users can save time and effort by automating their data integration processes and taking advantage of a range of powerful features. features

    • Scheduled data extraction: lets users schedule their data extraction processes to run automatically and regularly.
    • Append import mode: can collect historical information by instructing it to pull the updated data and append it to the end of your working sheet or table.
    • JSON API connector: to automate data exports to Google Sheets, BigQuery, and Excel from REST APIs.
    • Webhooks: supports both incoming and outgoing webhooks to cover different business cases, such as building a sequence of importers to run one after another, triggering events after the importer’s run, sending notifications about importer’s run, etc. 
    • Data consulting service that covers a variety of data transformation and visualization cases. pricing comes with a 3-tier pricing model to meet every need. All tiers come with a 14-day free trial and you can even save 20% on every plan by paying annually:

    1. Starter: This tier works best for individuals with a limited data integration needs. It costs $49 per month and grants you 500 runs with 10,000 rows per run. All data sources are available.
    2. Squad: Ideal plan for small teams who collaborate on multiple sources. It costs $99 per month providing 4,000 monthly runs with up to 50,000 rows per run. Additionally, you can schedule an automated data refresh every 30 minutes.
    3. Business: The largest tier which is perfect for companies with multiple teams. With $249 per month, you can have 10,000 runs per month with more than 100,000 rows per run and you can schedule your automated data refresh to run every 15 minutes.

    Who can benefit from

    • Data analysts and data scientists. allows them to focus on analyzing and modeling the data rather than spending time on manual data tasks.
    • Marketing teams. The tool can help to extract data from marketing platforms (Google Analytics4, Google Ads) and transform it into a needed format.
    • Sales teams and SMB (small and midsize business) owners can extract data from CRM systems like Salesforce or HubSpot and transform it to create KPI dashboards.
    • Developers can automate data extraction and integration processes as part of applications.
    • Product managers. offers a batch of essential tool integrations for these specialists.

    #2 – is a data integration platform that allows users to extract, transform, and load data from various sources. It offers a range of data cleaning, deduplication, and normalization features, as well as support for scheduling and automated data flows.

    This ETL platform offers collaboration and sharing features that allow users to collaborate on data integration projects and share their work with others. Data prep, cleaning, and transformation are performed in the database with the help of different features, saving time and technical resources. 

    The tool charges based on actual usage, not the number of rows, allowing you to scale tasks flexibly and transparently. features

    • Data integration from various sources — a huge amount of pre-built connectors.
    • Data scheduling and automation.
    • Customizable data pipelines using API and CLI (command-line interface). pricing

    As part of the tool’s RPU credits system (Rivery Pricing Unit Credit), there are credits for sources charged for each execution of a data pipeline or database or file storage sources charged for the amount of data transferred.

    Rivery’s free trial includes access to all of the professional plan features for 14 days or 1,000 free credits (worth $1,200) of usage.

    When your trial period ends, you can continue using one of the following plans: 

    • Starter: $0.75 per RPU credit
    • Professional: $1.20 per RPU credit
    • Enterprise: custom

    Who can benefit from

    The ETL tool is more popular among current business lines, such as E-commerce, AdTech, Pharmaceuticals, and Real Estate.

    Rivery can be useful for:

    • Data analysts for consolidating data from multiple databases into a single dataset.
    • BI professionals to clean and standardize data from various sources.
    • Developers who need to create automated data pipelines for data integration and transformation.

    #3 – Octoparse


    Octoparse is a web scraping and data extraction tool that allows users to extract structured data from websites and other online sources. It offers a visual interface for building web scraping tasks and advanced features for handling AJAX, JavaScript, and CAPTCHAs.

     It can be used for tasks such as price comparison, contact information collection, and data mining. The tool features a user-friendly interface and requires no coding skills, making it suitable for people with little or no programming experience. It also offers advanced options for users who want more control over the scraping process. Octoparse can be used to scrape data from almost any website and supports multiple languages.

    Octoparse features

    • Data export to CSV, Excel, and various databases
    • AJAX, JavaScript parsing ability
    • Automatic IP rotation to get a website for parsing

    Octoparse pricing

    Octoparse offers a free version with limited features and paid plans:

    • Standard: $89 per month
    • Professional: $249 per month
    • Enterprise: custom price

    Who can benefit from Octoparse?

    Octoparse can be helpful for professionals who need to extract data from websites and online sources.

    The most common use cases, based on the business niche, are:

    • Extracting product data from e-commerce websites.
    • Scraping real estate listings from property websites.
    • Gathering market research data from online sources.

    #4 – Bright Data

    bright data

    Bright Data offers a range of features for data cleansing, enrichment, and transformation, as well as support for scheduling and automation. The platform provides a service called Web Unlocker, which is best for use cases involving web scraping. Instead of manually dealing with CAPCHAs, blocks, and other restrictions, Web Unlocker does the unlocking with 100% success rates. The other services are SERP API to get user search results for any keyword on every major search engine and Proxy Network — the proxy infrastructure with huge GEO coverage.

    Bright Data features

    • Proxy services (ISP proxies, mobile proxies, datacenter network of multiple IP types).
    • Web Scraper IDE (Integrated development environment) to collect mass data from any geo-location built on Bright Data’s proxy infrastructure and patented web unlocking technology.
    • Data lineage tracking.

    Bright Data pricing

    Bright Data offers a 7-day free trial and paid plans starting at $500 per month. There is also an option of the “Pay per use” pricing.

    • Proxy Network Pricing: from $15/Gb and $500 per month to $2 000 and custom plans.
    • SERP API Pricing: from $3 CPM and $500 per month to $2 000 and custom plans.
    • Web Unlocker Pricing: from $3 CPM and $500 per month to $2 000 and custom plans.

    Who can benefit from Bright Data?

    This platform will be useful while enriching data with additional information from external sources. Bright Data includes a range of no-code data solutions utilized by business owners and a robust infrastructure. The most common use-cases are:

    • E-commerce representatives: to optimize products and pricing strategies
    • Marketing specialists: to collect social media data
    • Technical specialists: to request public web data from a collection of pre-made dataset templates or using customization or proxy

    #5 – Fivetran


    Fivetran offers a range of features for data integration, including support for real-time data synchronization, scheduling, and automation.

    The tool is designed to make it easy for businesses to extract and centralize their data in a single location, such as a data warehouse, for analysis and reporting. Fivetran offers pre-built connectors for a wide range of data sources, making it easy to set up and maintain connections. The tool also features automatic schema detection and data transformation, ensuring that data is correctly formatted and structured for analysis.

    Fivetran features

    • Cloud extraction
    • Real-time data synchronization
    • Scheduling and automation
    • Collaboration and sharing

    Fivetran pricing

    Fivetran has a usage-based pricing model. You will be charged for the MAR (monthly active rows). A 14-day free trial is available. 

    Who can benefit from Fivetran?

    Fivetran is a suitable tool for companies looking to improve their data management and analysis capabilities, especially in FinTech and MarTech. This ETL tool will be helpful for:

    • Analysts
    • Data Engineers
    • Business Intelligence Teams

    #6 – ScrapingBee


    ScrapingBee is an ETL tool with a large proxy pool, which allows you to bypass rate-limiting websites, and lower the chance to get blocked. 

    The platform allows users to schedule the data extraction processes to run automatically at specific intervals, eliminating the need for manual data management tasks.

    ScrapingBee can handle websites that use AJAX, JavaScript, and CAPTCHAs, making it easier to extract data from dynamic and interactive pages. With JavaScript rendering, a simple parameter enables you to scrape any web page using React, AngularJS, or Vue.js.

    ScrapingBee features

    • Data extraction using CSS or XPATH selectors
    • Code samples in Java, Python, Go, PHP, curl, and JavaScript
    • Google search API: search results with API call

    ScrapingBee pricing 

    • Freelance: $49 per month
    • Startup: $99 per month
    • Business: $249 per month
    • Enterprise: $999+ per month

    1 000 free API calls are available as a testing option.

    Who can benefit from ScrapingBee?

    Data analysts, marketers, researchers, and others who need to extract data from websites can benefit from ScrapingBee.

    #7 – Stitch

    10.Stitch data

    Stitch or Stitch Data is an ETL service for businesses of all sizes. The platform allows users to extract data from various sources, including databases, SaaS applications, and CSV files. Using Stitch’s features, you can synchronize data in real time, ensuring that the destination data is always up-to-date.

    Users can configure the data extraction process by setting up custom data pipelines that extract data from the source and transform it into the desired format. This platform will be helpful in supporting multiple environments, transferring data, or maintaining a hybrid data stack.

    Stitch features

    • Reporting using data visualizations (charts and graphs)
    • Data extraction from the designated source like relational databases, JSON files, and XML files
    • Connectors for a huge amount of data sources such as databases like MySQL and MongoDB

    Stitch pricing 

    Stitch Data offers a 14-day free trial. The pricing plans available are:

    • Standard: from $100 per month
    • Advanced: $1250
    • Premium: $2500, Advanced and Premium plans are billed annually. These packages allow you to add rows and destinations to customize your plan.

    Who can benefit from Stitch?

    Use cases for Stitch include consolidating data from multiple databases into a single dataset, cleaning and standardizing data from multiple sources, and automating data integration and transformation pipelines.

    The platform will be more suitable for:

    • Product teams: to understand what drives new product growth by integrating data from diverse analytics platforms and get insights.
    • Marketing teams: to analyze ROI and other valuable metrics by integrating all marketing data. 
    • Sales analytics team: integrating data from the CRM, sales automation, and payments into a cloud data warehouse.

    #8 – Docparser


    Docparser is a data extraction and conversion tool that allows users to extract structured data from PDF and other document formats. It offers a range of features for extracting data from invoices, receipts, contracts, and other types of documents, as well as support for data validation and transformation.

    Docparser features

    • Extraction of structured data from PDF and other document formats based on OCR and ML.
    • Docparser allows users to customize their data extraction rules and automate the data extraction process.
    • The tool can be integrated with other instruments, such as CRM systems and accounting software, allowing users to transfer extracted data into these systems easily.

    Docparser pricing

    Docparser offers a free trial for 21 days. There are 4 types of pricing plans:

    • Starter: $39 per month
    • Professional: $74 per month
    • Business: $159 per month
    • Enterprise: custom plan

    Who can benefit from Docparser?

    Docparser can be useful for businesses and organizations that need to extract and convert data from PDF and other document formats. Some examples of use cases for Docparser include extracting data from invoices for accounting purposes, extracting data from contracts for legal review, and extracting data from receipts for expense management.

    Among the specialists using this service are:

    • Sales & Marketing consultants
    • Logistic sector representatives
    • Finance operations specialists
    • Developers

    #9 – enables users to convert the mass of data on websites into structured, machine-readable data with no coding required. The point-and-click interface transforms websites into data. The platform allows customers to process 1,000s of URLs and access millions of rows of data with JSON REST-based and streaming APIs and integrations. To ensure all data is gathered, the platform can collect images, data from lists, nested categories, and hidden content and follow pagination structures like get more, next, and infinite scrolling. automates data extraction processes, reducing the need for manual data management. features

    • Extraction of structured data from websites: can extract specific data fields from websites, such as product prices, ratings, and reviews.
    • Data extraction methods capturing fully loaded quotes, including all add-on fees, for more accurate pricing comparison.
    • Support for AJAX, JavaScript, and CAPTCHAs. pricing 

    The prices for different plans start at $299 per month. A free trial is available.

    Who can benefit from

    Customer data, images, and reporting are used for price monitoring, investment research, gathering images and descriptions for online marketplaces, machine learning, and artificial intelligence.

    The tool will be a better choice for: 

    • Product teams and brand managers;
    • Travel and hospitality business representatives;
    • Retailers, SMBs in E-commerce.

    #10 – Astera


    Astera is a data integration and automation platform with multiple data-driven tools. Astera ReportMiner is an automated data extraction solution and an ETL engine. It helps businesses streamline the extraction, transformation, and integration of data trapped in complex documents and unstructured data files.

    The data extraction features support real-time data synchronization, scheduling, and automation. The data extraction process can be customized by setting up custom data pipelines to extract and transform data.

    Astera features

    • Real-time data synchronization: Astera can synchronize data in real time, ensuring that the destination data is always up-to-date.
    • The ability to construct reusable extraction templates without coding and extract documents in bulk as they are received.
    • Multi-channel capture with its support for a range of unstructured documents

    Astera pricing

    Plans aren’t provided in official sources. Contact Astera directly for pricing details. A 14-day free trial is available.

    Who can benefit from Astera?

    Astera is helpful for Small and Medium Enterprises (SMEs) and large enterprises in the energy, financial, manufacturing, education, healthcare, and retail industries.

    The list of the most common industries and uses-cases:

    • Healthcare: extracting data from electronic medical records and integrating it into a patient management system.
    • Energy: to extract data from invoices and contracts and integrate it into an accounting system for billing and payments.
    • Education: extracting data from course management systems and integrating it into a student tracking and analytics system.

    How to choose the best automatic data extraction tool?

    Before selecting a data extraction tool for your business, it is important to research and determine which solution will best meet your current needs. There are several factors to consider when choosing a data extraction tool. Let’s highlight the main ones:

    1. Data source. The first step is to determine the source or sources of the data you intend to extract (databases, SaaS applications, CSV files). This will help narrow down the options and ensure that you select a tool that is compatible with your data sources. 
    1. Data format. Consider the format of the data you want to extract and ensure that the tool you choose can handle it. 
    1. Data transformation. Does the tool offer features for cleaning, deduplicating, and transforming data into the desired format?
    1. Scheduling and automation. Make sure the tool allows you to schedule data extraction processes to run automatically at specific intervals if needed.
    1. Pricing: Consider the cost of the tool and whether it is within your budget. Some tools may use freemium mode or have a free trial period, while others may require a subscription or one-time fee.

    Subscription-based pricing is a standard pricing model used in SaaS products. But using some platforms, you should pay a recurring fee regularly (such as monthly or annually) to access the software. And in the case of the pay-per-use pricing model, customers pay for the specific features or services they use rather than a flat fee. This can be an attractive option for businesses using the software sparingly.

    1. Data points: Ensure that the tool you choose extracts specific data points. Some tools may be limited in their capabilities.
    1. Usability. If you are not a technical person, you may want to choose a tool with a user-friendly interface and clear documentation.
    1. Customer support. Consider the level of support offered by the tool, including documentation, forums, templates, use-cases, and other training resources.

    By carefully considering these factors, you can choose an ETL tool that is well-suited to your business needs and will help you effectively extract, transform, and load data from various sources. It may also be helpful to try out multiple tools and see which one works best for your particular use case.

    In conclusion, the top 10 data extraction tools we’ve discussed in this article can help you make informed decisions using your data. By choosing a powerful ETL tool, such as, you can save time on data extraction, transformation, and management and use it to uncover valuable insights to improve your data-driven business and drive its growth. Remember that this list is not exhaustive, and you may find other solutions that better suit your specific needs. Best of luck in finding the right tool for you.

    • Zakhar Yung

      A content manager at whose key responsibility is to ensure that the readers love our content on the blog. With 5 years of experience as a wordsmith in SaaS, I know how to make texts resonate with readers' queries✍🏼

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