What is synthetic data from a content marketer's standpoint?

Synthetic data is a term marketers will better get used to in 2025. Here is why.

What is synthetic data?

Let me try to explain synthetic data in a way that's easy to understand.

Imagine you're playing with LEGO blocks. You can build all sorts of things with them, right? Well, synthetic data is kind of like building something new with LEGO blocks, but with information instead!

Let's say you want to practice being a weather reporter, but you don't have real weather information. You could make up (or "synthesize") pretend weather data that looks and acts just like real weather data. You might say "Monday was sunny and 75 degrees, Tuesday was rainy and 68 degrees" and so on.

Here's another example: Think about those video games where you can create your own character. The game lets you make up a person who isn't real but looks and acts like they could be real. That's similar to synthetic data – it's created by computers to look and work just like real data.

The cool thing about synthetic data is that we can use it to practice, learn, and test things without needing to use real information. It's like having a practice playground where it's okay to make mistakes because we're not using real data.

Some real life example of synthetic data

How is synthetic data used in real life? A few examples:

In Healthcare:

• Hospitals create synthetic patient records to train new medical software

• Researchers use synthetic health data to study diseases without compromising real patient privacy

• Medical students practice diagnosing using synthetic patient cases

In Financial Services:

• Banks use synthetic transaction data to test fraud detection systems

• Insurance companies create synthetic claim scenarios for training assessors

• Trading algorithms are tested using synthetic market data

In Retail and E-commerce:

• Companies create synthetic customer profiles to test recommendation systems

• Synthetic sales data helps predict seasonal trends

• Testing new store layouts using synthetic customer behavior data

How do synthetic data apply to marketing?

It actually applies in every part of marketing:

• Campaign Testing: marketers can create synthetic customer profiles to test different marketing messages. Or they can simule customer responses to email campaigns before sending to real customers. A/B testing can also be made using synthetic engagement data.

• Market Research: Marketers can generate synthetic survey responses to identify potential trends or create synthetic focus group data to test new product concepts.

  
  

• Social Media Marketing: Marketers will test post performance with synthetic engagement data or simulate follower growth patterns to optimize posting strategies

• SEO and Content Marketing: Marketers could generate synthetic search queries to test keyword strategies

or create synthetic website traffic patterns to test content performance.

Among others examples. So many other applications could be made.

Is AI-Generated Content considered as Synthetic Data?

The answer to this question is (unfortunately) YES!

Yes, AI-generated content published on websites can be considered a form of synthetic data, but with some important nuances:

Like synthetic data, AI-generated content is artificially created rather than produced by humans. It is also generated to mimic real-world content/data patterns and created using algorithms and models trained on real data.

However, there's a key difference in how it's used and presented:

• Traditional synthetic data is typically created explicitly for training, testing, or development purposes, with everyone involved knowing it's synthetic ;

• Whereas AI-generated website content is often created to be consumed as if it were real content, sometimes without clear disclosure that it's AI-generated ...

Which IS a big deal!!

This raises some ethical considerations:

- Transparency: Users should ideally know whether they're reading AI-generated content

- Quality: The content might contain inaccuracies or hallucinations from the AI

- Data ecosystem: When this AI-generated content gets published online, it can potentially be scraped and used to train other AI models, creating a kind of "synthetic data loop"

This question is actually the real (concerning) one when it comes to the risks and dangers of synthetic data. And it directly applies to content marketing.

The following one could be what will the web look like when most of its content will be made of ... synthetic data.

#ugh #HappyNewAIMarketingYear 😕

What do you think?

Do you think Synthetic data is the upcoming major risk for AI Marketing and especially content marketing?

Ps: the way I see our new LLM content model ⬇️