How to run Facebook ads using Data Science (Facebook for Business)

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Facebook is today’s mainstream social media application with more than a billion people using it. This means that if you are a marketer, Facebook is your playground for influencer marketing as well as targeted paid ads and so in this article, you’ll discover how to run Facebook ads using Data Science.

How to run Facebook ads using Data Science (Facebook for Business)

Here is a step-by-step guide on how to run Facebook ads using Data Science under the Facebook for Business plan:

1. Identify your primary Facebook audience

Baby boomers constitutes a large chunk of the active users on Facebook, however, they might not be your primary audience. The first thing you have to do is figure out if your primary audience is on Facebook or not and if you actually want to spend money on the platform.

Identify your primary Facebook audience

Here are some questions you should answer to identify your primary audience:

  • Gender: What gender are they?
  • Age: What age group do they fall in?
  • Location: Which location are they situated in?
  • Interest: What are their interests?

2. Research Facebook Statistics

Once you’ve identified your primary audience, the next step is to find if your primary audience is in one of Facebook’s ad-supported regions or not. Facebook is yet to release the paid ad feature globally and if you’re looking to run ads for a primary audience that resides in out-of-support reasons then you are out of luck.

Research Facebook Statistics

Also, it is a good idea to know the general statistics of users on Facebook since if you’re looking for 1000 Ph.D. level professors to advertise on Facebook, you might have to think twice.

3. Run Facebook ads using A/B testing

You’ve made a great marketing video and you’re in excitement to run your first ad. Do you spend all your marketing budget on it? No. The correct way to spend your marketing budget on Facebook ads is to do so by performing A/B testing.

Run Facebook ads using A/B testing

A/B testing (also known as split testing or bucket testing) is a method of comparing two versions of a Facebook ad against each other to determine which one performs better. For example, the ‘A’ version of your Facebook ad may highly focus on a subset of your primary audience characteristics and the ‘B’ version may focus on the entire primary audience characteristics itself.

Running both the ‘A’ and ‘B’ versions of your Facebook ads will help you determine the best performing ads in between the two while staying low on budget. You can also experiment with campaign changes such as changing the location, shifting the age ranges, and much more.

In Conclusion

Now you know how to run Facebook ads using Data Science. The trick is simple: Gather market data before you run your own Facebook ads and once you starting running your own ads, just gather your own data and optimize.

How to run Facebook ads using Data Science (Facebook for Business)How to run Facebook ads using Data Science (Facebook for Business)

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