As AdTech evolves, we’re committed to prioritizing privacy and user consent by helping brands build first-party data and implementing opt-in policies. At fullthrottle.aiTM, we prioritize your privacy and put action behind our belief that transparency is key. That's why our technology is opt-in to ensure that end-users have control over how their data is used. What people share should be their conscious choice. This approach ensures targeted, effective advertising campaigns that respect user privacy and comply with regulatory requirements. The technology behind fullthrottle.aiTM collects first-party data directly from user interactions, guaranteeing accuracy and relevance without infringing on privacy. By adopting opt-in policies, we empower users to decide how their data is used, fostering trust and compliance with privacy regulations like GDPR and CPRA.  

Our platform is SOC 2 compliant, demonstrating our dedication to security and privacy. We emphasize transparency in our data collection practices, providing clear information to users so they can make informed decisions about their privacy. With fullthrottle.aiTM, you can confidently build marketing strategies on a foundation of privacy, user consent, and trust, ensuring long-term success in the ever-changing world of AdTech.

If you are interested in our Privacy Hub, click here.

What Do You Mean When You Say Cookieless?

We mean there’s no part of our technology that tracks a user across websites without their permission — we don’t use mobile ad IDs, IP tracking, or fingerprinting. When you install the fullthrottle.aiTM platform on your site, it will ask users whether they want to opt into sharing data with us. If they say yes, we use our patented AdTech to identify and help you market to them. The tracking starts and ends with that user, on that site, for as long as they actively agree to share their data with us. We then send you that data through our Data Clean Room to ensure end-to-end security. You own that data — we simply deliver it. 

Cookie retargeting was once effective in helping businesses reach their target audience – and provided a silver bullet to immediately remarketing to your website visitors. Cookies can track users across multiple websites and collect personal information through subtle opt-out popups or with no consent at all, which can be concerning for many people. These developments led to a wave of cookie deprecation as regulators, end consumers, and companies like Google and Apple decide to move beyond cookie tracking methods.  

But it’s not just about privacy — it’s also about one thing no one in the AdTech industry seems to want to talk about: match rates. Cookie retargeting methods simply aren’t as effective at identifying site visitors as the cookieless method we’ve built our platform around.  

First-Party vs. Third-Party Cookies: What's the Difference?

first-party cookie

First-Party Cookies

  • These cookies are created and stored by the website a user is visiting, enhancing user experience by remembering preferences and tracking behavior on that specific site.
  • They offer better privacy, are less likely to be blocked by ad blockers, and align with privacy regulations like GDPR and CPRA.
third-party cookie

Third-Party Cookies

  • Created by domains other than the visited website, third-party cookies are used by advertisers and tracking services to collect information about users' browsing habits across multiple sites, enabling targeted ads based on user interests.
  • They face criticism for privacy concerns, vulnerability to ad blockers, and are being phased out by major tech companies in favor of privacy-centric solutions. 

Examples of Cookie-Based Methods


Fingerprinting is a technique that identifies and tracks users by collecting unique characteristics of their devices, such as screen resolution, browser version, or installed plugins. This information is then used to build a "fingerprint" of the device, which can be used for targeting and attribution purposes. 

How Did Fingerprinting Start?  

Fingerprinting was initially implemented as a solution to counter the limitations of cookies, such as their inability to track users across different browsers or devices. By utilizing device-specific characteristics, fingerprinting provided a more persistent and comprehensive way to identify and track users for ad targeting and analytics. 

Why Fingerprinting Isn’t Working 

Fingerprinting is seen as invasive by many, as it can be used to track users without their consent. Additionally, it has become less effective due to browsers implementing anti-fingerprinting measures and the increasing use of VPNs and other privacy tools. With growing awareness of privacy issues and the rise of regulations, fingerprinting is quickly becoming an outdated and unreliable method for user identification. 

Mobile Ad ID

Mobile Ad IDs (MAIDs)

Mobile Ad IDs (MAIDs) are unique identifiers assigned to mobile devices, such as smartphones and tablets. Advertisers use MAIDs to serve personalized ads to users based on their behavior and preferences. 

How Did MAIDs Start? 

Mobile Ad IDs were introduced to help advertisers effectively target users on mobile devices, where traditional cookies were less reliable. MAIDs enabled advertisers to access a wealth of user data, such as app usage and location, for better targeting and measurement of campaign performance on mobile platforms. 

Why MAIDs Aren’t Working 

MAIDs have been criticized for the same privacy concerns that plague cookies and fingerprinting. Additionally, major players like Apple have introduced changes that limit the use of MAIDs for ad targeting. With the increased adoption of privacy-centric features and user consent requirements, the effectiveness of MAIDs as a targeting method is rapidly diminishing. 

IP Address Retargeting

IP address retargeting is the process of serving ads to users based on their IP addresses, which can be used to approximate their geographic location and identify the devices they use. 

How Did IP Address Retargeting Start?  

IP address retargeting gained traction as a simple and cost-effective way to target users based on their location, without relying on cookies. It allowed advertisers to serve localized ads and content. 

Why IP Address Retargeting Isn’t Working 

IP address retargeting is inherently imprecise and can lead to irrelevant or misplaced ads, resulting in wasted ad spend. Additionally, the widespread use of VPNs and dynamic IP addresses reduces the accuracy of IP-based targeting. As with other cookie-based methods, privacy concerns and regulatory pressures make IP address retargeting an unsustainable approach to attribution and retargeting. 

Are IP Address Retargeting & Geo-Targeting the Same Thing?

While both IP address retargeting and geo-targeting use IP addresses to some extent, they are not the same thing. Geo-targeting involves determining a user's location to tailor content or ads, while IP address retargeting serves ads to users based on their previous actions, such as visiting a website or abandoning a shopping cart. The former is used to reach a broad audience in a specific location, while the latter is used to target a smaller, more specific audience based on their behavior or interests. Additionally, geo-targeting can also use GPS, Wi-Fi, and device information to determine a user's location, so it's not always using IP addresses.

IP address retargeting
Location Sharing

Location Sharing

Browser-based location sharing is a feature that enhances the online experience by providing personalized content and services tailored to a user's geographic location. These services often include local weather forecasts, news, and shopping recommendations. 

What is Browser Location Sharing?

When a user consents to share their location with a website, the information may be stored on the user's device or on the website's servers, depending on the site's privacy practices. Users can manage their location sharing preferences directly through their browser settings, ensuring an additional layer of privacy protection. 

Is Location Sharing the Same as Cookie Tracking? 

Short answer: no.  

Browser-based location sharing and cookie tracking methods are distinct approaches to collecting user data online. Location sharing involves users granting websites access to their geographic location, enabling personalized content based on the user's whereabouts. Cookie tracking, on the other hand, uses small text files stored on users' devices to record browsing history and preferences across multiple websites.

Opt-Out vs. Opt-In

The concepts of opt-in and opt-out play a crucial role in determining how users' information is collected, used, and shared. As the AdTech industry adapts to changing regulations and privacy expectations, understanding the differences between opt-in and opt-out consent models is vital for businesses and advertisers. 

Opt-Out: Implied User Consent 

The opt-out model assumes that users consent to data collection and usage by default, unless they explicitly choose to opt out. In this model, users' data may be collected and used without their knowledge or explicit consent, until they decide to take action and opt out of these practices. 

Opt-out models are often criticized for their lack of transparency and potential for abuse, as users may not always be aware of their options or understand the implications of their data being collected. As a result, privacy regulations and consumer expectations have been pushing the industry towards more opt-in-centric practices. 

Opt-In: Explicit User Consent 

The opt-in model requires users to provide explicit consent before their data can be collected or used for any purpose, such as ad targeting or personalization. In this model, users must actively agree to the terms and conditions or select specific preferences, ensuring that their data is only collected and used if they choose to allow it. 

Opt-in consent has become more prevalent due to increased privacy awareness and the introduction of regulations like the General Data Protection Regulation (GDPR) in the European Union and the California Privacy Rights Act (CPRA) in the US. The opt-in model is considered more privacy-centric, as it puts users in control of their data and requires clear communication about data collection practices. 

fullthrottle.aiTM requires active opt-in and does not track shoppers across different sites and organizations. Our technology leverages the website browser's location-sharing functionality available through any installed consent management platform to capture website visitor opt-in consent.

opt-in vs opt-out

1st-, 2nd-, 3rd-Party Data: What's the Difference?

First-Party Data

Data you collect directly from your customers from your website, CRM, databases, etc.

Second-Party Data

First-party data bought directly from industry specialists, conquest solutions, third party.

Third-Party Data

Programmatic Data aggregated for specialized audiences such as demographic credit-based category-specific intenders for products and services.

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