3 Steps For Choosing The Right Data Collection Tool

Once you have a specific dataset in mind that you are targeting (i.e. organic weight loss journey social media posts), and your capabilities are clear (i.e. you do not have the technical personnel to perform in-house data collection) then choosing the right solution becomes very straightforward
5 min read
7 Steps for choosing the right data collection tool

In this article we will discuss 3 easy steps that will help you choose the right data collection solution for your business:

Step one: Set your goals 

Many business managers get very flustered when first setting their data collection goals. They know that they need, and want data in order to become more efficient, and increase Return on Investment (ROI). Typically however they think of data in terms that are way too generalized. For example:

  • We need social media data 
  • We should be collecting all of our eCom competitor’s data
  • We could benefit from real-time financial data on inflation

But in order to be successful with data collection, businesses should be refining this, and be specific about what datasets could benefit them most (even if you are not sure, these hypotheses can be tested). Here is how the previously mentioned examples can be refined:

  • We want to collect organic social media posts of users in the New York City metropolitan area who are writing about their weight loss journey so that our algorithms can analyze real-time user needs, and target them with tailored, geo-specific marketing campaigns
  • We are currently selling a GPS on multiple marketplaces and want to collect consumer reviews of our competitors’ products so that we can identify shortfallings, and make our success in those areas the centerpiece of our product listings (e.g. high speed shipping)
  • Our business is specifically centered around Fast Moving Consumer Goods from China which is why we plan on collecting alternative satellite imagery data of the speed with which Chinese production plants are resuming activities post-COVID. This will help us understand, and prepare for supply-chain shortages more efficiently   

Step two: Define needs, and capabilities 

Once you know which datasets you are targeting, the next step is defining your needs, and capabilities. For example the following companies may define themselves using this criteria:

Company A 

  • We are a digital fashion brand that wants to focus primarily on our niche and less on data
  • So we need data to inform our production lines, marketing campaigns, SEO etc but we prefer that the data we need, be collected on our behalf and fed periodically to team members
  • We have no in-house data collection personnel, nor do we have the technical infrastructure or know-how to manage large-scale data collection projects 

Company B

  • We are a tool that helps investors gain access to real-time market data. We offer them a full-suite dashboard where they can check stock daily volume, relevant news items, as well as trending social media posts discussing a given company for social sentiment trends
  • We have in-house technical staff, and data collection infrastructure that feeds our algorithms data
  • Our key challenge is collecting datasets from tough target sites, such as competing investor tools that distort their open-source data to make it harder for competing entities to collect pertinent information

Company C  

  • We have a platform where travelers can search for vacation rentals
  • We have our own data infrastructure and personnel in order to perform real-time price comparison and vacation bundle offers
  • Our key challenge is that we have trouble collecting geo-specific data from a user perspective and often find that data points are skewed as we collect this information from the wrong geographies (i.e. we try to collect pricing data from a competitor for properties located in the U.S. using British IPs)

Step three: Identify the right data collection solution

Once you have this information down pat, then choosing a solution is pretty straightforward:

Company A 

Considering the above-described scenario, company A would be best suited choosing Bright Data’s Web Scraper IDE. The reasoning behind this is that it is a solution that:

  • Automates the entire data collection process
  • Requires zero technical know-how
  • Requires no in-house data collection infrastructure
  • Enables companies to focus on their core business rather than on data collection
  • Designated datasets are delivered directly to team members, and algorithms in the pre-defined format and on a predetermined (albeit flexible) data collection schedule

Company B 

Considering the above-described scenario, company B would be best suited choosing Bright Data’s Web Unlocker. The reasoning behind this is that it is a solution that:

  • Guarantees a 100% success rate – if your request is not successful, you don’t pay a penny
  • Unblocks the toughest of target sites using sophisticated retry logic, and CAPTCHA-resolving tech that will change settings based on target site recalibrations
  • Has complete user environment emulation. For example, at the browser-level, it offers full-suite cookie management and browser fingerprint emulation (e.g. fonts, audio, canvas/webgl fingerprints, etc)

All of these features will nicely compliment company B’s existing data collection infrastructure and drive success rates through the roof. 

Company C 

Considering the above-described scenario, company C would be best-suited choosing one of Bright Data’s four proprietary proxy networks, in this case our Residential Network would be best suited. The reasoning behind this is that it is a solution that:

  • Utilizes a real-peer global network of IPs
  • Has country/city-specific geotargeting
  • Enables the highest levels of reliable data retrieval (think of the fact that you are now routing requests to competitor sites as a real individual in your locale of choice (for example, you are checking vacation rental prices for apartments located in Dallas using an IP located in Austin). 

The bottom line

Whatever your company’s unique challenges or data collection goals are, Bright Data has a solution that can help you attain them. The most important thing is being specific about your goals, which datasets have the highest likelihood of serving you best and then correlating your capabilities with what that specific product has to offer. 

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