Interacting with the followers of big accounts in your niche is a great place to start finding your own potential followers! However, as you grow, you will realize that having control of your audience demographics becomes just as important as follower count. Are you an influencer? Then brands will be very keen on seeing your audience metrics, not just whether your followers are real, but whether your followers will purchase their product. Are you a business? Then 10 potential local customers as followers have way more intrinsic monetary value than 1000 low quality followers across the globe.

Let’s go through a generic use case together, and hopefully by the end, you will be able to apply the principles and methodology to your own niche and goals.

For this use case, let’s pretend you are a fitness studio (business) or personal trainer (individual) with the following data:

Product Sold = Muscle Gain & Weight Loss

Consumers’ Demographics = Must live in New York City

Consumers’ Behaviors = Majority weight loss customers

Now, as mentioned above, the most common practice to grow would simply be finding a large/popular fitness account, and engage with their followers. Although you will gain steady followers with this method, the followers will oftentimes be low quality, and you are unable to control your audience demographics.

To combat this, you will be curating your own lists of tens of thousands users to engage with, almost ALL in NYC and recently trying to lose weight. Let’s get to it:

  1. In order to create these lists, you will need scraping software. I highly recommend IG Scraper by imristo. These programs can scrape lists of usernames and hashtags based on specific filters i.e. bio words, hashtags used, follower/following count, and more.
  2. Now, focus on your audience requirements (demographic & behaviors). You need people living NYC and they need to be looking to lose weight.

  3. Beginning with DEMOGRAPHICS. How do you find people living in NYC? Well, first, boot up your scraper, and:
    • Scrape all county/boroughs i.e. “New York, Manhattan, Brooklyn, Bronx” etc.
    • Scrape all high traffic local hot spots i.e. popular bars, restaurants, etc
    • DO NOT scrape high traffic tourist spots i.e. Statue of Liberty, Times Square, etc.
  4. DEMOGRAPHICS (Cont)
    • In this example, we only touch on location. But the methodology extends to age and gender as well.
    • Age: If targeting 20–40 year old females, look at high-end department stores, i.e. Barneys, Bergdorf’s Goodman, etc.
    • Gender: Most automation services will distinguish between male and female accounts automatically based on first name or ML image recognition.
  5. From all the geolocations, you’ve scraped a list of 200,000 potential NYC users.

  6. Adding and combining the BEHAVIORS element.
    • Think of hashtags users would use who are currently trying to lose weight.
    •Ex: #weightlossjourney #bikinibodygoals #summerbody etc.
    •Scrape and compile a lists of users who have used the hashtags within 30 days (this number is up to you).
  7. Results: 200K users scraped from geolocations & 350K users scraped from hashtags
  8. Plug the two lists into a simple online script and output all MATCHINGnames: http://www.molbiotools.com/listoperations.html
  9. Results: 55K Users currently living in NYC, trying to lose weight

Now why is this so powerful? Not only is this is FREE but TARGETED advertising, this is also only the tip of the iceberg. With multiple filters available per scrape job, your ability to target users becomes limited only by your creativity and ability to associate instagram data with consumer behavior. How can you infer user categories based geolocations, or hashtags, or even bio words?

Think of users interactions — following, liking, commenting — as ads (notifications) and profile views are store visits. You have a limited amount of ‘ad budget’ (interactions per day), to get people into your store. Now, will you want a crowd of people in the store buying nothing, or a few people checking out at the cashier. That’s the difference between curating your own lists of targets versus letting the quality of a popular account’s audience and luck determine your customer conversion. You take control.

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