Search engines such as Google continue to move towards more privacy-focused marketing models. Although the full removal of third-party cookies in Chrome has been delayed, the long-term direction is the same. Organisations must reduce their reliance on third-party data and adopt tracking methods that are both compliant and respectful of user privacy.
To maintain strong performance in this environment, businesses need to prioritise data quality, protect their traffic from invalid activity, and use targeting strategies that work even when traditional data signals are limited.
Managing Invalid Traffic and Ad Fraud
Invalid traffic (IVT) and bot activity can distort analytics, waste budget, and compromise campaign decisions. This is a growing challenge for organisations that run ppc management at scale, especially in competitive industries.
Using a tool such as Lunio helps filter out bot clicks and fraudulent impressions, ensuring your ad spend reaches genuine users and improving the accuracy of your performance data.
Smarter Targeting Approaches
With less tracking data available, targeting needs to be more deliberate and grounded in secure, permission-based methods.
- Manual placements let you choose trusted, brand-safe environments.
- Programmatic advertising works best when driven by high-quality first-party data and clear audience controls.
- Contextual and interest-based targeting delivers strong results without depending on personal identifiers.
- AI-assisted targeting helps identify patterns and intent even when data is limited.
These approaches help maintain reach and relevance while respecting user privacy.
Benefits of a Privacy-Focused Approach
A privacy-focused approach does more than meet regulatory requirements. It supports stronger, more sustainable digital activity across the organisation.
- Stronger compliance with GDPR and other global privacy regulations reduces legal risk and protects customer data.
- Greater user confidence, driven by transparent data practices, helps build long-lasting trust.
- Access to modern targeting methods, including contextual targeting, server-side tagging, and predictive analytics, supports effective campaigns without relying on intrusive tracking.
- A more resilient long-term strategy, as privacy-friendly methods are less likely to be disrupted by future browser or platform changes.
Challenges to Consider
Privacy changes introduce some practical challenges that organisations need to plan for.
- Reduced data visibility can make trends harder to detect without a strong first-party data foundation.
- Less certain attribution occurs when cross-site tracking is limited.
- Initial investment may be required for new tracking tools, data platforms, or analytics setups.
These challenges are manageable with the right support. Taking time to strengthen first-party data, improve measurement frameworks, and review tracking setups helps maintain consistent performance.
Marketing and AI Data Protection
Generative AI tools such as ChatGPT, Gemini, and Perplexity are now widely used to support content creation, research, and optimisation. These tools provide clear advantages, but it is important to use them responsibly to protect your organisation’s information.
Free AI platforms may retain the information entered into them and use it to help train their models. This means inputs can influence future outputs. If confidential or identifiable information is included, there is a risk of exposing details that should remain private.
Should you stop using free AI tools?
For any work that involves sensitive or internal information, it is safer not to use a free AI platform. Paid versions often include privacy controls that prevent your inputs from being used for training.
Should you avoid generative AI entirely?
No. Generative AI can be a valuable part of your workflow when used thoughtfully. It can support content creation, save time on repetitive tasks, and help maintain consistency across digital channels.
How to use AI securely?
- Choose paid plans with clearly outlined privacy settings.
- Avoid entering customer information or confidential internal data.
- Use AI-generated content as a starting point and refine it with your own knowledge.
- Use originality and quality checkers when appropriate.
- Use trained or customised models where possible to keep data within controlled systems.
Marketing vs AI Data Breaches
Generative artificial intelligence has quickly become part of everyday business life. Tools such as ChatGPT, Gemini, and Perplexity are now widely used to speed up content creation, research, and optimisation tasks. ChatGPT alone reports hundreds of millions of active weekly users, yet only a small proportion use a paid plan with enhanced privacy controls.
However, it’s important to understand the risks. Free AI tools may use the information you submit to help train and improve their models. This means any text you enter could be retained, learned from or potentially resurfaced in future outputs. If sensitive or confidential data is included, there is a genuine risk of unintentional exposure.
Should you stop using free generative AI?
For sensitive information, yes! Suppose you don’t have that layer of protection from a subscription; in that case, you should not put sensitive information into the platform that you don’t want to access outside your organisation.
Should I not use generative AI full-stop?
Absolutely not! With the advancements we have experienced in the last few years alone, AI can reduce time and resources, increase output volume, obtain valuable insights, and maintain the quality of website content, emails, ads, presentations, and more.
How do I use AI securely?
Here are some of the methods we use to keep our data secure and make the most out of AI:
- Purchase a paid subscription
- Avoid using customer/company data
- Build upon generative content – don’t copy
- Use trusted AI/plagiarism checkers
- Train your AI model
Take Control of Your Privacy-First Marketing Strategy
Privacy and performance do not need to be in conflict. At ExtraDigital, we help organisations modernise their SEM strategies with compliant tracking, AI-safe workflows, and high-quality data practices.
We can support your shift to a more resilient and privacy-focused marketing model.
If you would like guidance on applying privacy-focused and secure working practices to your marketing, development, or content processes, contact ExtraDigital to speak with our team.
Frequently Asked Questions
What is privacy-focused search engine marketing?
Privacy-focused SEM refers to strategies that respect user data by reducing dependence on third-party cookies and intrusive tracking. It prioritises compliant, first-party data and contextual targeting to maintain campaign performance while protecting user privacy.
Why is Google phasing out third-party cookies?
Google aims to improve online privacy and comply with global data protection regulations. Phasing out third-party cookies reduces unauthorised tracking and shifts advertisers toward more transparent and consent-based practices.
Can AI tools compromise marketing data security?
Yes, especially free generative AI tools, which may retain and use submitted data for model training. Using paid plans with clear privacy settings, avoiding confidential data input, and deploying private AI models helps mitigate this risk.
