What is your biggest MarTech adoption challenge?

Overcome key challenges that hinder adoption and ROI.

UPCOMING MASTERCLaaS

OCT 19: Tealium AudienceStream CDP MasterCLaaS.

UPCOMING MASTERCLaaS

OCT 19 LONDON:
Tealium AudienceStream
CDP MasterCLaaS. 

Identity Resolution Essential Guide Featured Image

Identity Resolution – An Essential Survival Guide for the 2024 Cookiepocalypse

Identity Resolution Essential Guide Featured Image

Table of Contents

Understanding and managing customer identities has become a critical aspect of successful marketing strategies. Identity resolution, the process of integrating identifiers across various touchpoints and devices, has become indispensable for marketers seeking to create a cohesive and addressable consumer profile for analysing and targeting customers with personalised experiences. In 2024, this practice will be even more crucial than ever as marketers face greater challenges arising from privacy regulations, the explosion of digital touchpoints and the impending third-party “cookiepocalypse”.

 

 

Cookiepocalypse? The New Era of User Identification

The year 2024 is poised to witness a significant shift in the way customers are identified, tracked and targeted due to this impending depreciation.

If you haven’t heard already, Google is officially planning on rolling out their plan to depreciate third-party cookies in 2024. Starting January 4, Google will start testing its new tracking protection feature on 1% of the population that will eventually restrict website access to third-party cookies by default. By the second half of 2024 (Q3), they plan on phasing out third-party cookies for the entire population.

This transition poses challenges for advertisers and publishers who heavily rely on these cookies for tracking user behaviour, targeting and republishing.

 

 

 

Consequences of the Third-Party Cookie Phase Out

While the phase out of third-party cookies is a step in the right direction for improving user privacy and compliance with evolving regulations, offering users greater control over their data, there are several implications for brands. There are several that advertisers and publishers need to consider and address.

 

This table highlights the key challenges and implications that advertisers and publishers are facing with the cookie depreciation.

Implications Advertisers Publishers
Loss of user tracking
Difficulty in tracking users across websites.

Limited data on user interactions outside their site.

Challenges in retargeting efforts.
Reduced ability to provide targeted ads based on user behaviour.

Lower effectiveness of targeted advertising campaigns
Impact on cross-device tracking
Complexity in tracking users across multiple devices.
Challenges in delivering a seamless cross-device user experience
Limitations in frequency capping
Frequency capping becomes less precise.
Risk of overexposing users to ads due to inaccurate frequency capping.
Challenges in audience segmentation
Difficulty in creating precise audience segments
Reduced ability to segment audiences for targeted campaigns
Reduced ad personalisation
Struggles in delivering highly personalised content

Challenges in understanding user preferences
Limited ability to provide personalised ads to users

Reduced personalisation in content
Impact on cross-domain analytics
Difficulty in analysing user behaviour across domains

Challenges in gaining a unified view of customer journeys
Fragmentation in understanding the complete customer journey

Reduced ability to provide comprehensive cross-domain analytics
Attribution
Challenges in determining the contribution of various marketing channels.

Optimisation models like ROAS will be impacted.
May see variations in ad revenue attribution.

Customer Fragmentation

Customer fragmentation, the dispersion of customer data across various platforms and touchpoints, is a prevalent challenge and will only intensify with the depreciation of third-party cookies in addition to the non-stop explosion of digital touchpoints.

A report by Forester found 77% of marketers struggle to maintain an accurate customer ID over time and through changes. Many also say that they struggle to understand how much of their addressable audience is active and reachable online.

Explosion of  Digital Touchpoints

We are seeing a steady increase in the number of devices and touchpoints the average person uses, causing signficant fragmentation. According to a study by Statista, the average number of connected devices per person in 2023 globally was 3.6. This was up from 2.4 in 2018 and this trend is not expected to slow down, only continue rising in 2024.

As these cookies have traditionally played a crucial role in tracking user activities across the web, their diminishing effectiveness will lead to a more fragmented view of customer identities. With users engaging across multiple devices and channels, the absence of a universal tracking mechanism will contribute to disjointed customer profiles.

Navigating the Cookiepocalypse with Identity Resolution

The impending changes and implications demand a re-evaluation of how marketers approach customer targeting and personalisation. Identity resolution is one such solution that shines as a way to connect and consolidate user information, and can become the linchpin of not only sustaining effective marketing strategies in cookie-depleted landscape but also improve the way that users are delivered personalised and engaging experiences.

What is Identity Resolution?

At its core, identity resolution is the strategic amalgamation of various identifiers associated with individual consumers, transcending different platforms and devices. The objective is to create a unified and comprehensive consumer profile, enabling marketers to gain deeper insights into user behaviour, preferences, and engagement across diverse digital touchpoints.

Identity Resolution and ID Graphs

An integral component of identity resolution is the formation of an ID graph. This interconnected web of user-level and device-level identifiers allows marketers to piece together a holistic view of an individual’s digital footprint. Essentially, the ID graph acts as a bridge, linking the dots between disparate data points and weaving a coherent narrative of a user’s online journey.

The Benefits of Identity Resolution

Unified Customer View:

Identity resolution allows businesses to create a unified view of individual customers by connecting and consolidating data from various touchpoints and devices. This comprehensive view enables a deeper understanding of customer behaviour and preferences.

 
Improved Personalisation:

With a more accurate and detailed understanding of customer identities, businesses can deliver highly personalised experiences. Personalisation extends across marketing messages, product recommendations, and user interfaces, enhancing customer engagement.

 
Cross-Channel Consistency:

Identity resolution facilitates consistent experiences across different channels and devices. Whether a customer interacts with a brand through a website, mobile app, or other touchpoints, identity resolution ensures a cohesive and seamless journey.

 
Segmentation and Precise Audience Targeting:

Marketers can leverage identity resolution to create precise audience segments based on demographics, behaviours, and preferences. This precision enhances the effectiveness of targeted marketing campaigns, leading to higher engagement and conversion rates.

 
Cross-Device Tracking:

Identity resolution addresses the challenge of tracking users across multiple devices. By linking various identifiers associated with a user, businesses can maintain continuity in tracking user journeys, regardless of the devices they use.

 
Enhanced Marketing Analytics:

Businesses gain access to richer and more accurate data for marketing analytics. Identity resolution enables detailed insights into customer interactions, allowing for more informed decision-making and optimisation of marketing strategies.

 
Optimised Customer Journey:

Understanding the complete customer journey becomes more feasible with identity resolution. Businesses can identify touchpoints that contribute most to conversions, enabling them to optimise the customer journey for a more seamless and satisfying experience.

 
Consent Management:

Identity resolution often involves managing user consent effectively. Businesses can ensure compliance with privacy regulations by obtaining and managing user consent transparently, fostering trust with customers.

 
Efficient Resource Allocation:

By accurately identifying and targeting specific audience segments, businesses can allocate resources more efficiently. Marketing budgets can be optimized based on insights derived from resolved identities, ensuring a higher return on investment.

 
Reduced Data Fragmentation:

Identity resolution helps to overcome data fragmentation challenges by consolidating information from various sources. This reduction in fragmentation leads to a more holistic and coherent understanding of customer data.

 
Improved Customer Retention:

The ability to understand and respond to individual customer preferences fosters stronger relationships. By delivering personalised experiences and offers, businesses can enhance customer satisfaction and loyalty, contributing to improved retention rates.

 
Adaptability to Changing Regulations:

Identity resolution systems can be designed to adapt to evolving privacy regulations. This adaptability ensures that businesses remain compliant with changing data protection laws, reducing the risk of regulatory non-compliance.

 
Personalised Targeting: 

Identity resolution empowers marketers to move beyond broad strokes and deliver highly personalised experiences by understanding user preferences and behaviours.

 
Cross-Channel Consistency: 

With an ID graph in place, marketers can ensure a seamless and consistent user experience across various channels and devices, fostering a sense of continuity in consumer interactions.

 
Precise Audience Activation:

Resolved identities enable targeted marketing campaigns, ensuring that the right message reaches the right audience at the right time.

In essence, identity resolution not only serves as a solution for overcoming third-party cookie depreciation challenges, it empowers businesses to deliver more personalised, consistent, and effective experiences to customers

The Process of Identity Resolution

The journey to improved customer match through identity resolution involves a systematic process: 

01
Identify
Recognising and collecting user-level identifiers, encompassing email addresses, phone numbers, and other relevant data.
02
Connect
Establishing robust connections between user-level and device-level identifiers, creating a comprehensive ID graph.
03
Match
Overcoming challenges such as multiple cookies and varied device usage to accurately link relevant identifiers.
04
Validate
Ensuring the accuracy and reliability of the resolved identities, validating the effectiveness of the identity resolution process.
05
Activate
Leveraging the resolved identities for targeted marketing initatives and personalised messaging.

Types of Identity Resolution: Probabilistic and Deterministic 

Two primary approaches to identity resolution are probabilistic and deterministic resolution, each offering distinct methods for establishing user identities. 

Deterministic Resolution 

Deterministic matching operates by consolidating customer information only when two or more identical identities are present. This method is inherently conservative to maintain data integrity. 

 

Key Characteristics:
  1. Known Identifiers: Relies on verified and direct identifiers for precise matches. 
  2. Login Information: Leverages user logins as a primary source for identity resolution. 
  3. Customer-Provided Details: Uses information provided by users during registration. 
  4. Accurate and Reliable: Provides a higher degree of accuracy and reliability. 
  5. Single Identity Across Touchpoints: Creates a unified identity for consistent tracking. 
Example Scenarios of Deterministic Resolution
  • User Login Matching – Social media platform uses login information for precise identity matching.
  • Customer Registration Data – Retailer relies on customer-provided details during registration for accurate identity resolution.
  • Subscription with Verified Identifiers – Streaming service uses verified email addresses as direct identifiers for identity matching.

Probabilistic Resolution

Probabilistic matching seeks to combine customer profiles when a direct match is unavailable by analysing alternative signals. Examples of these signals include statistical modelling, machine learning algorithms and behavioural patterns to make educated guesses about user identities. It assigns a score to the strength of these signals and establishes rules for merging data based on these scores. The ultimate goal is to achieve scalable personalisation.

 

Key Characteristics:
  1. Behavioural Analysis: Analyses user behaviours to establish associations and patterns.
  1. Pattern Recognition: Identifies patterns in interactions across devices and touchpoints.
  1. Device Fingerprinting: Utilises device-related information for unique user identification.
  1. Cross-Device Tracking: Aims to connect user identities across multiple devices.
  1. Algorithmic Guesswork: Involves making educated guesses based on behavioural data.
Example Scenarios of Probabilistic Resolution
  • Behavioural analysis – E-commerce platform analyses user behaviour without logins to create a probabilistic identity. 
  • Device fingerprinting – Mobile app uses device-related info for cross-device tracking through probabilistic resolution. 
  • Ad click pattern recognition – Advertising platform identifies ad click patterns to form a probabilistic user profile. 

A table summarising and comparing the differences between deterministic and probabilistic resolution. 

Consideration Deterministic Resolution Probabilistic Resolution
Use case considerations
Preferred for precise identity matching
Suitable for cross-device tracking
Data privacy and compliance
Aligns more closely with data privacy regulations as it relies on verified and authenticated data
Requires careful consideration of user consent and privacy concerns
Accuracy vs. scale
Provides higher accuracy but may pose challenges in scenarios with sparse direct identifiers
Offers scale but it involves a degree of uncertainty in identity matching
Implementation accuracy
Implementation may be more straightforward relying on known identifiers
Generally involves complex algorithms and statistical modelling
Single identity across touchpoints
Aims to create a unified identity for consistent tracking across various touchpoints
Challenges in creating a single, unified identity across touchpoints due to the probabilistic nature

Choosing between probabilistic and deterministic resolution depends on the specific goals of the identity resolution strategy, the available data landscape, and the desired balance between scale, accuracy, and compliance with privacy regulations. In many cases, a hybrid approach that combines elements of both methods may be optimal. 

A Hybrid Approach

Combining Deterministic and Probabilistic Resolution 

Often a hybrid approach using a combination of deterministic and probabilistic will be best. By leveraging the strengths of both approaches, organisations can achieve improved customer matching, ensuring accurate and personalised interactions. The probabilistic component enables scalable analysis of user behaviours across various touchpoints, accommodating scenarios where direct identifiers may be limited. On the other hand, deterministic resolution ensures precision in identity matching when verified data is available, enhancing data integrity and compliance with privacy regulations. 

Example Scenarios Involving A Hybrid Approach

 

Scenario 1 – Telecommunications Subscriber Management:  

A telecom company adopts a hybrid identity resolution approach to manage subscriber information. Probabilistic analysis helps identify usage patterns across devices, and deterministic resolution is applied when customers register their accounts or provide additional information. This hybrid method ensures accurate billing and personalised service offerings. 

 

Scenario 2 – Multi-Channel Retailer 

A retail brand employs a hybrid approach by combining probabilistic analysis of customer interactions across various touchpoints (in-store, online, mobile) with deterministic resolution when customers log in or provide personal details during transactions. This comprehensive strategy allows the retailer to deliver a personalised and seamless shopping experience. 

Challenges and Opportunities

While the benefits of identity resolution are substantial, it is not without its challenges. Marketers must grapple with data fragmentation, the proliferation of devices and touchpoints, and the intricacies of privacy regulations. However, adept navigation of these challenges unlocks unparalleled opportunities for marketers to refine their targeting strategies and foster deeper connections with their audiences. 

 

Want to enable unified customer profiles for your organisation? Get in touch. 

What do you think?

Leave a Reply

Your email address will not be published. Required fields are marked *

[likebtn theme="custom" icon_size="40" icon_l_c="#0a0a0a" icon_l_c_v="#8aade1" icon_d_c="#0a0a0a" icon_d_c_v="#8aade1" brdr_c="#ffffff" show_like_label="0" popup_position="left"]

What to read next

Leave a Reply

Your email address will not be published. Required fields are marked *

top
Adobe

Adobe Analytics
Adobe Target
Adobe Audience Manager
Adobe Experience Manager
Adobe Campaign Manager
Adobe Real-Time CDP

Google

Google Analytics (GA4)
Google Analytics (360)
Google Optimize
Google Tag Manager

Tealium

Tealium AudienceStream CDP
Tealium EventStream
Tealium IQ

Segment
Quantum Metric
MoEngage
CleverTap
MixPanel
OneTrust
Playrcart
VWO
Optimizely