Articles on: How to use Mailerfind
This article is also available in:

How analysis work


Analyses are the starting point inside Mailerfind. This is where you define what type of leads you want to obtain and from which source.


From there, the platform takes care of collecting the public data of those users so you can use it in your lead generation strategy.


1. Create a new analysis


To get started, go to the “Analysis” section within the platform and click on “New analysis”.


This is where you choose what type of data you want to obtain and from where.


Mailerfind allows you to run analyses on several platforms:


  • Instagram
  • Twitter
  • Google Maps


Each one has a different approach, but the goal is the same: obtaining qualified leads.



2. Available analysis types


Instagram


This is the most used source and where you have the most segmentation options:


  • Followers → users following an account
  • Following → users followed by an account
  • Comments → people who commented on a post or reel
  • Hashtag → users who posted using a hashtag
  • Location → users who posted in a specific location


This allows you to target highly specific audiences (competitors, niches, interests, etc.), which is exactly where the value lies.



Twitter


Similar options to Instagram:


  • Followers
  • Following


More limited, but useful depending on the business type.



Google Maps


Here the approach changes: instead of users, you obtain businesses.


Practical example:


  • Area: downtown Madrid
  • Business type: hair salons


Mailerfind will search for businesses matching those criteria and collect their data.


This type of analysis is usually slower at the beginning, but then stabilizes.



3. Configure the analysis


The process is quite straightforward:


  1. Select the analysis type (for example, Instagram followers)
  2. Enter the input (username, hashtag, location, etc.)
  3. Select the correct option from the list
  4. See an estimated volume (e.g. number of followers)
  5. Click “Start”


From there, Mailerfind automatically starts collecting the data.



4. What happens during the analysis


When you start an analysis:


  • The system scans the target profiles
  • Extracts available public information
  • Processes and organizes the data


It is important to understand this:

not all users will have all data available (email, phone number, etc.).


That’s why the result is always a combination of:


  • Complete data
  • Partial data
  • Users without direct contact information


Even so, the volume compensates for it, and that’s why the system works.



5. What to do with the leads obtained


Once you have the data, you have several options:


Export the data


You can download it in formats such as:


  • CSV
  • Excel


You can also integrate it with external tools.



Use them in campaigns


You can:


  • Import them into platforms like Meta Ads
  • Create custom audiences
  • Launch cold email campaigns directly from Mailerfind


This is key: analysis alone does not generate revenue — what generates revenue is what you do afterward with the data.



6. Filter the results


Inside the analysis, you can use filters to better segment your leads.


Example:


  • Show only users with email
  • Filter by available data type


This allows you to work only with more actionable leads.



7. Data enrichment


If you want to obtain more information about users, you can use the data enrichment feature.


This expands the available data and improves lead quality.


To understand it in depth, we recommend checking the specific article about enrichment.



8. Important considerations


  • Mailerfind works only with public data
  • You do not need access to your Instagram account
  • There is no ban risk
  • The quality of the results depends on how you structure the analysis


This is where many people fail: it is not a magic tool, it is a powerful tool.

If you define the input poorly, you will get poor-quality leads.



Conclusion


An analysis in Mailerfind basically consists of:


  1. Defining an audience
  2. Extracting their public data
  3. Using it to acquire customers


Simple in structure, but very powerful in execution.


The real difference is not in running an analysis, but in choosing the right audience to analyze and how you use that data afterward.

Updated on: 08/05/2026

Was this article helpful?

Share your feedback

Cancel

Thank you!