How ITP and Privacy Features Affect RLSA & Dynamic Remarketing in Google Ads

Online advertising has changed a lot in the last few years. One of the biggest reasons is the growing push for user privacy. Major browsers like Safari, Firefox, and even Google Chrome are introducing tools and restrictions that limit how advertisers can track users.

While this is good news for privacy-conscious users, it creates challenges for advertisers who rely on remarketing — especially RLSA (Remarketing Lists for Search Ads) and Dynamic Remarketing campaigns in Google Ads.

In this article, we’ll explain in detail:

How ITP & Privacy features affect RLSA and Dynamic Remarketing
How these changes affect your campaign performance
And finally, what can you do to overcome this ?

Let’s dive in.

What Are RLSA and Dynamic Remarketing?

Before we get into the challenges, let’s quickly recap how these two campaign types work:

RLSA (Remarketing Lists for Search Ads)

This feature allows you to customize your search campaigns for people who have already visited your website.

Example:

Someone visits your online store and checks out a pair of shoes.
A few days later, they searched on Google for “best running shoes.”
Because they’re on your remarketing list, you can bid higher or show them a more tailored ad than you would for a brand-new user.

Dynamic Remarketing

This takes remarketing a step further. Instead of showing a generic ad, Google uses the products or services the person looked at on your site and shows them personalized ads.

Example:

A user browses a red handbag on your site but doesn’t buy it.
Later, they see a Google Display Ad featuring that exact red handbag, reminding them to come back and complete the purchase.

Both strategies rely heavily on cookies and tracking tags to recognize the same user when they come back. And this is where ITP comes in.

What Is ITP (Intelligent Tracking Prevention)?

ITP is a privacy feature created by Apple for Safari. Similar protections exist in Firefox (Enhanced Tracking Protection, or ETP) and will soon be fully rolled out in Google Chrome under the Privacy Sandbox initiative.

The goal of ITP is simple:

To stop advertisers and third parties from tracking users across websites for long periods of time.

It does this by:

Limiting how long cookies can last

In Safari, first-party cookies created by scripts (like Google Ads tags) often expire in just 7 days or even sooner.
Third-party cookies (from ad networks) are blocked entirely.

2. Blocking third-party tracking cookies by default

Many remarketing systems need cross-site tracking to work, which becomes impossible.

3. Stripping URL tracking parameters

This removes identifiers (like gclid in Google Ads) that help connect a click to a conversion.

4. Preventing trackers from running at all

Ad blockers and browser privacy settings can completely block the remarketing tag from loading.

On paper, these sound like small technical details, but the impact on advertising is huge.

How ITP & Privacy Features Technically Affect RLSA and Dynamic Remarketing

Impact on RLSA (Remarketing Lists for Search Ads)

Shortened Cookie Expiration

Normally, Google Ads Remarketing Tags can set a 30-day cookie (or longer) to keep someone in a remarketing list.
Under Safari ITP, JavaScript-set first-party cookies expire in just 7 days (sometimes 24 hours if they’re linked to cross-site tracking).
This means:
- Day 1: User visits your site.
- Day 8: That cookie is already gone — so the user “falls off” your list, even though you set the list duration to 30 days in Google Ads.

2. Blocked Third-Party Cookies

If your remarketing tag tries to drop a third-party cookie (from net or googleads.g.doubleclick.net), Safari/Firefox block it instantly.
Result: These users are never added to your RLSA list at all.

3. Cross-Device and Cross-Browser Tracking Breaks

Without persistent cookies, Google can’t link the same user across mobile + desktop (unless they’re logged into Google).
Example: User searches on mobile → visits your site → later searches on laptop. Without login data, Google treats them as two different users.

Impact on Dynamic Remarketing

Loss of Product-Level Tracking

Dynamic remarketing relies on event tags (e.g., view_item, add_to_cart) + product IDs sent via cookies.
If cookies are gone:
- Google Ads receives the visit but can’t tie it to a specific product.
- Instead of seeing “red handbag you viewed,” the user just sees a generic brand ad.

2. Audience List Shrinkage

With 7-day cookies, long buying journeys (like travel, cars, B2B software) suffer most.
Example: User browses vacation packages → waits 3 weeks → cookie is expired → they never see your remarketing ads when they’re ready to book.

3. Click Parameter Stripping

Safari strips URL identifiers like gclid (Google Click ID) after 24 hours if cookies are considered tracking-related.
Without this, Google Ads struggles to connect ad clicks → remarketing tags → conversions.

In short:

RLSA lists become smaller and “leak” users quickly.
Dynamic Remarketing loses personalization, turning into generic ads.

How to Fix or Reduce These Issues

Now let’s look at the practical steps you can take.

1. Move to Server-Side Tagging

The problem with client-side tagging (default):

Google Ads tags run in the browser.
Safari sees them as “trackers” → applies ITP → short cookie lifetime or total block.

Server-side tagging solution:

Instead of sending data straight from the browser to Google, the browser sends it to your server/domain first.
Example:
- User visits → browser sends it to https://tracking.yourdomain.com.
- Your server processes it → forwards it to Google Ads/GA4.

Why this works:

Because the cookie is dropped by your own domain, it is considered first-party and not flagged as cross-site tracking.
Cookies can last much longer (e.g., 90 days instead of 7).

Tools you can use:

Google Tag Manager Server-Side (sGTM) hosted on Google Cloud or your own server.
Google Tag Gateway (via Cloudflare) for easier implementation.

2. Use Enhanced Conversions

The problem: When cookies fail, Google Ads can’t always connect a click → to a conversion → to a remarketing list.

The fix (Enhanced Conversions):

Collect first-party identifiers during checkout or lead form submission (like email, phone, or address).
Send these values to Google Ads in hashed (encrypted) form.
Google then matches these with signed-in Google accounts.

Result: Even if Safari blocks the cookie, Google can still match “John who clicked the ad” with “John who made a purchase.”

3. Encourage User Sign-Ins

Why this helps:

Cookies may fail, but Google can still track users if they’re logged into their Google account (via Gmail, YouTube, Chrome).
If you encourage logins (e.g., loyalty programs, gated content, exclusive offers), users are more often signed in → remarketing lists become more accurate.

4. Adjust Remarketing List Durations

The issue: Safari expires cookies after 7 days.

The solution:

Instead of setting remarketing lists for 30–90 days, create shorter lists (e.g., 7–14 days) for Safari/Firefox-heavy audiences.
Use “fresher” remarketing windows that capture people while their cookies are still valid.

Example:

Instead of “All site visitors (30 days),” create “All site visitors (7 days).”
Layer urgency-based messaging like discounts or “low stock” offers to push faster decisions.

5. Diversify Audience Sources

Since you can’t rely only on cookies anymore:

Customer Match → Upload CRM/email lists into Google Ads → remarket to known users.
GA4 Audiences → GA4 uses modeling + signals (beyond cookies) to sync audiences into Google Ads.
In-App Events → If you have an app, app events feed directly into Google Ads audiences and aren’t affected by browser ITP.

This spreads risk and ensures you’re not over-relying on cookie-based web data.

Final Takeaway

From a technical perspective, ITP and other privacy features cut off the tracking chain at the cookie level:

RLSA loses users when cookies expire early.
Dynamic remarketing loses personalization when product-level data isn’t tied to the visitor.

But with server-side tagging, Enhanced Conversions, login strategies, shorter remarketing lists, and diversified audience sources, you can rebuild that chain in a privacy-safe way.

The future of remarketing isn’t about “tracking more” — it’s about tracking smarter with first-party data.

The Bottom Line

Privacy updates like ITP are here to stay. They reduce both the size and accuracy of your remarketing audiences, making it harder to reach past visitors with tailored ads.

To keep RLSA and Dynamic Remarketing working well, you’ll need to adapt — focus on first-party data, invest in server-side tracking, and use multiple audience sources. That way, you can still deliver relevant ads to the right people, even in a more privacy-focused web.

anees@oriben

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How To Use First-Party Data in Customer Match & Enhanced Conversion For Fueling Smart Bidding

Remarketing has always been one of the most powerful tools in digital marketing. It lets you reconnect with people who already know your brand —

For years, remarketing worked by following people around the internet using cookies. But times are changing. Privacy laws are stricter, browsers are phasing out cookies, and users want more control over their data.

This affects the performance of Automated AI powered campaigns and bidding strategies. The RLSA and Dynamic remarketing capabilities make the Pmax and TROAS/TCPA campaigns powerful.

So here we make a plan to use the First Party data in Customer match and Enhanced conversion to fuel the advanced campaign types with the data it was missing from Cookie loss.

1. Customer Match: Turning First-Party Data Into Audience Power

Customer Match allows you to upload customer details (like email, phone number, or address) into Google Ads so you can create highly valuable audiences.

How to use first-party data in Customer Match:

Upload customer lists
- Prepare your first-party data (e.g., CRM, purchase history).
  Format it into Google Ads’ accepted CSV template (email, phone, country, zip).
- Upload in Google Ads → Tools & Settings → Audience Manager → Customer Lists.
- Google matches them with users logged into their Google account.
  You can then target these people across google
- In order to power customer match the smart bidding, you need to enable “Smart Bidding and Optimized Targeting” in Customer Match → Account settings

2. Build audience segments
Once Google matches the uploaded data with signed-in Google users, you can:

- Retarget past buyers with new offers.
- Exclude existing customers when running acquisition campaigns.
- Create Similar Audiences (lookalikes) to expand reach.

3. Apply in campaigns

- Attach these audiences to Search, YouTube, Display, and Discovery campaigns.
  Combine with bid adjustments or let Smart Bidding handle it.

How Google’s Customer Match Algorithm Works with uploaded data

Google “hashes” the data for security.
- Before uploading, or during upload, the information is encrypted using SHA256 hashing.
- Hashing converts your customer’s personal info into a string of numbers/letters.
- Example: customer@example.com → 5f4dcc3b5aa765d61d8327deb882cf99 (hashed form).
- This way, Google never sees the raw customer data.
Google compares hashed data with its own
- Google already stores hashed versions of emails, phone numbers, etc., for billions of logged-in users.
- The system cross-checks your uploaded list against its own database of hashed user info.
When a match is found
- If the hashed email/phone user uploaded matches the hashed data of a logged-in Google account, that user is added to your Customer Match audience.
- If no match is found, that record is discarded.
- After processing, you get an audience list of all matched Google users.
- These people can then be targeted across Google Search, YouTube, Gmail, and Display Network.
Updating & refreshing
- Google recommends uploading updated lists regularly. This keeps your Customer Match audience aligned with your real customer base.

Why this matters for bidding:
Customer Match feeds Smart Bidding with audience signals. Google knows these matched users are more valuable, so your bidding strategy can prioritize them automatically.

2. Enhanced Conversions: Feeding More Accurate Conversion Data

Conversions are the signals that Smart Bidding optimizes towards. But if tracking isn’t complete, Smart Bidding is running blind. That’s where Enhanced Conversions comes in.

How to set it up:

Enable Enhanced Conversions in Google Ads → Conversions → Settings.
Pass hashed customer data (email, phone, name/address) through your website tags or Google Tag Manager.
Google uses this data to match conversions more accurately to your ad clicks.

Example:

A user clicks your ad → browses → purchases later via another device. Normally, this may not be attributed. But with Enhanced Conversions, the system uses hashed first-party data (like their email at checkout) to connect the dots and give credit.

Why this matters for bidding:
Enhanced Conversions ensure every possible conversion is tracked and attributed, making Smart Bidding smarter. Instead of missing half the picture, your bidding models are trained on complete and precise data.

3. Smart Bidding: Letting Google Optimize With Better Signals

Smart Bidding strategies like Target CPA, Target ROAS, and Maximize Conversions thrive when they receive rich signals.

Here’s how first-party data plays a role:

Customer Match audiences → Tell Smart Bidding who is valuable.
Enhanced Conversions → Tell Smart Bidding what actions really happened.

Together, they supercharge Google’s machine learning.

Practical ways to use first-party data with Smart Bidding:

Prioritize high-value segments
Example: Apply Customer Match lists of loyal buyers. Smart Bidding learns these users have higher conversion probability, so it will bid more aggressively when they search again.
Refine conversion value for ROAS
If you’re running Target ROAS, Enhanced Conversions help ensure higher-value sales aren’t undercounted, letting the bidding system allocate budget more efficiently.
Improve lead quality in CPA campaigns
For lead gen businesses, Enhanced Conversions for leads (with CRM data) can connect offline sales back to Google Ads clicks. This helps Smart Bidding optimize not just for “form fills,” but for real revenue-generating customers.

Example Workflow Putting It All Together

Let’s imagine an e-commerce brand selling organic spices:

Customer Match
- Upload past buyers → Target them with new festive offers.
- Exclude them from generic awareness campaigns.
Enhanced Conversions
- Pass customer emails from checkout to Google Ads → Track even cross-device purchases.
Smart Bidding
- Run a Target ROAS campaign.
- The system learns from accurate sales data (Enhanced Conversions) + high-value buyers (Customer Match).
- The budget is automatically directed to the best customers at the best bids.

Result will be: More sales at a better ROI, with less wasted spend.

Final Takeaway

By using first-party data in Customer Match and Enhanced Conversions, you give Smart Bidding the right signals to work smarter. Customer Match helps you focus on the most valuable audiences, Enhanced Conversions ensures accurate tracking, and Smart Bidding uses both to optimize your bids automatically. Together, they create a powerful system that drives better results and maximizes your ad spend.

Customer Match = Identify and prioritize valuable audiences.
Enhanced Conversions = Capture every conversion signal.
Smart Bidding = Optimize bids with Google’s machine learning.

The key is not just having first-party data—but using it in the right places inside Google Ads. Do this well, and you’ll give Smart Bidding the best chance to work at full power.