5 reasons marketers must explore synthetic data

Opinion

Use of synthetic data is only set to grow and success depends on marketers’ ability to balance innovation with ethical considerations and consumer trust. Here are some key considerations.

In the competitive landscape of digital marketing, synthetic data has emerged as a powerful yet controversial tool.

As privacy regulations become more stringent and consumer trust becomes increasingly valuable, marketers face a pivotal moment. Synthetic data offers innovative opportunities, but its adoption comes with significant challenges that require careful consideration.

The synthetic data market is set for substantial growth. Gartner has projected that 60% of data used for AI and analytics projects would be synthetically generated in 2024. This significant shift will reshape marketing strategies, offering new avenues for insight generation while potentially enhancing consumer privacy protection.

But this comes with some implications for marketers.

1. Privacy-compliant personalisation: Promise vs ethical considerations

Synthetic data enables personalisation without compromising individual privacy. However, recent research suggests that it may not always provide the perfect balance between privacy protection and data utility. More research needs to be done in this area.

Marketers should develop a clear communication strategy about synthetic data usage in personalisation efforts. Create customer-facing resources that explain how synthetic data enhances privacy while enabling tailored experiences.

2. Predictive analytics: Enhanced capabilities vs potential for bias

While large synthetic datasets may improve model accuracy and predictive power, there’s a possible amplification of biases present in source datasets.

Implement a comprehensive testing programme comparing marketing campaign performance using synthetic versus real data. Monitor key metrics such as conversion rates, customer engagement and return on investment to quantify the impact of synthetic data on predictive accuracy.

3. A/B testing: Unlimited scenarios vs risk of unrealistic data

One advantage of synthetic data is that it allows for more extensive testing scenarios. However, it should be acknowledged that insights from synthetic environments may not accurately reflect real-world consumer behaviour.

Develop a staged A/B testing strategy. Begin with low-risk elements using synthetic data, gradually expanding to more critical components while continuously validating against real-world results.

4. Niche market exploration: Solving scarcity vs ensuring authenticity

Synthetic data potentially facilitates deeper understanding of underserved segments. The challenge? Ensuring authenticity and reliability in synthetically generated niche market data.

Best practice would be to create synthetic personas for niche markets based on limited real data. Use these personas to guide content creation and campaign strategies. Validate effectiveness through small-scale, real-world pilot campaigns before full implementation.

5. Regulatory compliance: Navigating uncertain terrain

In complex regulatory environments, synthetic data may help reduce reliance on personal information. But a word of caution: the UK Information Commissioner’s Office warns that some synthetic data may be considered pseudonymised rather than fully anonymous. In such cases, it remains subject to data-protection laws. Marketers should carefully assess whether their synthetic data truly anonymises information.

One proactive measure marketers can take is to establish a cross-functional team to develop guidelines for synthetic data usage in marketing activities. Create a governance framework outlining approved use cases and potential risks, ensuring compliance with data protection regulations even when using synthetic data.

Key considerations

The synthetic data generation market is likely to continue evolving. While the potential is significant, marketers and their data counterparts must approach synthetic data with a critical eye.

Here are five things chief marketing officers should do.

>> Campaign effectiveness: Regularly assess campaign performance metrics between synthetic and real data-driven initiatives
>> Brand trust: Monitor customer sentiment regarding synthetic data usage through surveys and social media analysis
>> Cost-benefit analysis: Conduct periodic reviews of synthetic data implementation costs against marketing performance improvements
>> Innovation opportunities: Identify new marketing strategies enabled by synthetic data, such as scalable personalised content
>> Cross-functional alignment: Establish regular meetings with legal and data science teams to stay updated on synthetic data capabilities and compliance requirements.

Navigating an evolving landscape

The applications of synthetic data in marketing will continue to expand as pressures around consumer privacy evolve and the need for training data for hungry algorithms appears insatiable. Success in this environment will depend on marketers’ ability to balance innovation with ethical considerations and consumer trust.

Marketers should take the lead in implementing synthetic data strategies, focusing on customer-facing aspects and campaign performance. However, close collaboration with data science teams is essential for technical implementation, bias detection and data quality assurance. Regular workshops and clear communication channels between marketing and data teams will ensure a comprehensive approach to synthetic data adoption.

In this evolving landscape, those who can effectively utilise synthetic data while maintaining authenticity and transparency will emerge as leaders.

Try tackling these questions and consider what role synthetic data can play in the answers:

• What critical marketing challenges are you facing that current data practices struggle to address?
• How can you balance the demand for personalised experiences with growing consumer privacy concerns?
• In an era of rapidly evolving data regulations, what strategies are you developing to maintain marketing effectiveness while ensuring compliance?

Cecilia Dones is founder and chief data officer at 3 Standard Deviations