Artificial audiences: Navigating marketing with synthetic data
Explore synthetic data and the potential in marketing: benefits, challenges, privacy concerns, and its role in shaping the future.
A game-changer for marketers or just a passing trend?
Data is the raw material fueling much of today’s progress in artificial intelligence, producing fresh insights and new discoveries everyday. As its demand increases in the modern economy, so does the challenge to gather and label real data due to stricter privacy laws and larger AI models.
This is where synthetic data comes into play – artificially generated information that mimics the properties of real data.
In this blog post, we’ll unravel this tool, and explore its potential impact on your business. And we’ll also look at the challenges it brings, and the exciting opportunities it offers.
Ready to delve in? Let’s get started.
What is synthetic data?
Often, people see synthetic data as a less good option, used only when getting real data is hard, costly or limited by rules. But this view doesn’t capture the full power of artificial data. In fact, Gartner predicts that by 2030, synthetic data will completely overshadow real data in AI models.
Synthetic data (or artificial data, fake data, simulated data) is any information generated artificially which is not sourced from events or objects in the real world.
Put another way, synthetic data is created in digital worlds rather than collected from or measured in the real world. It leverages AI and computer algorithms to simulate real-world customer information.
It can be a powerful marketing asset, especially when granular data is difficult to obtain. And it facilitates access to more extensive data sets, allows data sharing, helps reduce biases, and enables the execution of A/B tests for marketing initiatives.
Despite its potential, the truth is, not a lot is known about synthetic data and how well it respects privacy. But as marketers start to use artificial data more for their work, it is becoming increasingly important to get the whole story.
Why is synthetic data important for your business?
Synthetic data has broad applications that extend beyond traditional uses in creative generation. With the power of artificial intelligence (AI), artificial data is reshaping the landscape of marketing and customer engagement. Here are some essential benefits of leveraging this type of data in your business:
- Scenario forecasting
One of the most important applications of synthetic data is scenario forecasting. It enables businesses to test and predict the potential outcomes of various decisions before they are made. This ‘what-if’ analysis helps in making informed strategic decisions, thus significantly reducing the risks associated with new initiatives.
Example: consider a retail company planning to launch a new product. Using artificial data, they could simulate how different pricing strategies for the product might affect sales and customer retention.
- Algorithm testing
Algorithm testing is another crucial area where synthetic data comes into play. AI and machine learning models need extensive data for training, and artificial data provides an abundant, controllable, and secure source for this.
Example: suppose a tech company has developed an AI system designed to recognise fraudulent transactions in online banking. Instead of using real customer data, which could have privacy and ethical implications, the company can create synthetic data that mimics the characteristics of genuine and fraudulent transactions.
- Audience segmentation
Synthetic data can also play an essential role in audience segmentation. Businesses often need to expand into new customer segments, but the lack of relevant real-world data can be a hurdle. Synthetic data can mimic the behaviour of the new audience segment, providing businesses with the information they need to develop suitable marketing strategies.
Example: a video streaming service aiming to attract older audiences might not have enough data about their viewing preferences. Synthetic data, in this case, can help simulate the behaviour of this demographic, enabling the service to better tailor their content and marketing efforts to attract the intended audience.
- Data enrichment
As businesses are phasing out third-party cookies due to privacy concerns, there’s a growing need for other ways to obtain detailed data. Synthetic data can fill this void by simulating detailed user behaviour, providing businesses with the granular insights they need without violating user privacy.
Example: a news website could use synthetic data to understand more about users. For example how they interact with different types of content, what kind of articles lead to more time spent on the site, and which layouts drive the most engagement. These insights can inform content strategy, website design, and other important business decisions, while respecting the privacy of the users.
Synthetic data, privacy and the mitigation of bias
Synthetic data offers a unique advantage for brands, acting as a digital disguise to anonymise personal information. In industries handling vast quantities of sensitive customer data, such as healthcare, generative AI can create artificial data that masks the real data.
One of the significant advantages of synthetic data is its ability to address and rectify biases present in real data. For example, if a data set skews heavily towards one demographic, say “90% male and 10% female”, the potential for bias in the model is high. By incorporating artificial data, you can balance out this demographic distribution and mitigate the bias.
Yet, it’s important to remember that artificial data is a mirror of real data, an artificial reproduction of the real world. As such, it carries with it the potential to contain biases. This is also true for generative AI models like ChatGPT as well. Their outputs are based on real-world data, and consequently, can potentially bear the biases present in that data.
Synthetic data, combined with generative AI, offers significant potential to marketers. It can aid in ideation, initiate projects, and offer a response to the gap left by third-party data.
However, it’s not a silver bullet solution. The fast-paced evolution of this technology also means we should expect to see frameworks and regulations put into place. This is a trend that’s already starting to take place in Europe. Marketers need to remember that synthetic data is not always clear-cut in origin or accuracy. Thus, it’s crucial that it forms part of a broader strategy and is always validated by human experts for accuracy and compliance.
If you want to unlock the power of your data, get in touch with our team.
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