AI and Marketing: Synthetic Data is the Future
AI isn't just changing creative tools, but it is also changing the way we use data in marketing.
Most of us are familiar with anonymised data, but a new frontier is emerging, and that is synthetic data powered by AI.
In this episode of The Marketing Guy, I break down:
(a) What is synthetic data, actually, and what does it mean for marketing
(b) How it compares to anonymised data
(c) And why it becomes the backbone of targeted, simpler, and privacy-friendly campaigns
Chapters:
00:00 - Problem scenario
00:58 - Intro to solution, synthetic data
01:51 - Role of GAN and VAE models
02:31 - Why anonymised data isn't the solution
04:08 - Real-life based example showing the use case of synthetic data
05:32 - Why is synthetic data needed today
06:25 - Risks and limitations of synthetic data
07:37 - Tips to start using synthetic data
Notes from the podcast
(1) MostlyAI (www . mostly . ai) specialises in synthetic data. Their platform helps brands create these realistic data sets, mirroring your real data, that you can play around with. All that data is safe to use and can unlock insights without exposing the real customer data you have.
(2) Podcast on cookiesLook for "Goodbye Cookies, Marketing's Biggest Shift Explained" from my channel. Link in comments as well.
(3) What models does synthetic data use?
(i) GAE stands for Generative Adversarial Network, and it is not something that LLMs use. There are essentially two neural networks in it. (a) Generator. This makes fake data, and (b) Discriminator. This checks if the data is real or fake. With enough training, the generator creates data that is almost indistinguishable from your real data. It's used heavily in deep fakes.
(ii) VAE stands for Variational Autoencoder, and it has two parts as well. (a) Encoder. This essentially compresses the data you feed. (b) Decoder. This then rebuilds that compressed data into something new, slightly different outputs.
#AIMarketing #AnonymisedData #SyntheticData #marketingstrategy #themarketingguy
AI isn’t just changing creative tools, but it is also changing the way we use data in marketing.
Most of us are familiar with anonymised data, but a new frontier is emerging, and that is synthetic data powered by AI.
In this episode of The Marketing Guy, I break down:
(a) What is synthetic data, actually, and what does it mean for marketing
(b) How it compares to anonymised data
(c) And why it becomes the backbone of targeted, simpler, and privacy-friendly campaigns
Chapters:
00:00 – Problem scenario
00:58 – Intro to solution, synthetic data
01:51 – Role of GAN and VAE models
02:31 – Why anonymised data isn’t the solution
04:08 – Real-life based example showing the use case of synthetic data
05:32 – Why is synthetic data needed today
06:25 – Risks and limitations of synthetic data
07:37 – Tips to start using synthetic data
Notes from the podcast
(1) MostlyAI (www . mostly . ai) specialises in synthetic data. Their platform helps brands create these realistic data sets, mirroring your real data, that you can play around with. All that data is safe to use and can unlock insights without exposing the real customer data you have.
(2) Podcast on cookiesLook for “Goodbye Cookies, Marketing’s Biggest Shift Explained” from my channel. Link in comments as well.
(3) What models does synthetic data use?
(i) GAE stands for Generative Adversarial Network, and it is not something that LLMs use. There are essentially two neural networks in it. (a) Generator. This makes fake data, and (b) Discriminator. This checks if the data is real or fake. With enough training, the generator creates data that is almost indistinguishable from your real data. It’s used heavily in deep fakes.
(ii) VAE stands for Variational Autoencoder, and it has two parts as well. (a) Encoder. This essentially compresses the data you feed. (b) Decoder. This then rebuilds that compressed data into something new, slightly different outputs.
#AIMarketing #AnonymisedData #SyntheticData #marketingstrategy #themarketingguy
