Part 3: Identity Resolution - What is Identity-Driven Marketing?

Identity Resolution - What is Identity-Driven Marketing? Deeper dive into identity resolution to uncover a game changer that revolutionizes marketing personalization strategies in today's era.


Welcome to the next installment of my series on identity resolution! So far, we've dived into the significance of identity resolution and examined the five technological methods that make it possible. Now, let's dive deeper into identity resolution and uncover how it goes beyond being an advancement in merging data profiles to a game changer that revolutionizes marketing strategies in today's era.

Because businesses understand the importance of ID resolution fundamentals for precision and personalization use cases like Cart Abandonment(an overused one) -- they are now looking for ways to elevate their marketing efforts to new heights with more advanced use cases. The ultimate goal is transitioning from single or multi-channel marketing to Omnichannel approaches - ID RES becomes the linchpin driving towards that goal. If you want to catch up on what we discussed on Omnichannel, check out Part 1, Part 2, and Part 3.

Businesses crave persuasive strategies and highly targeted personalized use cases that profoundly impact KPIs like revenue, real-time price elasticity adjustments, churn, and all levels of campaign optimization coordination. They reap benefits when they embrace identity resolution automation for new CX Personalization use cases beyond the simple CART ABANDONMENT use case noted above. Now that the profile is unified, it releases the Marketers with released time toward CX Personalization development. This article will explore how identity resolution can enhance marketing(top-to-bottom efforts) by making it more perceptive, compassionate, and practical.

These are the two sides of Personalization activated with ID RES within the CDP by McKinsey. I would probably modify this a bit, but for the most part, all the CDP vendors are approaching it in this way.

What is Identity-Driven Marketing?

Identity-driven marketing is a paradigm that utilizes verified customer identity data(aka a known profile user), transforming it into the fuel that powers highly personalized, resonant marketing campaigns. To better connect with customers, it's important to sift through their data and uncover valuable insights used to communicate in a way that truly resonates and elicits a response. It's like diving deep into an ocean of information to find the pearls to help you speak their language.

Personalization to the known user based on behaviors and attributes that can be used in Real-time after the user's identity has been merged and resolved. Sometimes, it may not need to be merged with other records, only added to over-time during the customer journey.

Understanding customers has emerged as a critical component in the contemporary data-driven world. More than basic information such as name and age is required. Identity-driven marketing focuses on the deep journeys into customers' behavior, preferences, desires, and needs to create personalized marketing strategies that resonate with them. This approach's significance lies in anticipating customers' needs, tailoring methods, and refining interactions. By prioritizing personalized communication, marketers can create a symphony of whispers(touch points) that speak directly to each unique prospect or existing customer. We will explore how real-time updates, refined segmentation, and acute personalization can culminate in a marketing tapestry that is seen, heard, felt, and remembered.

Omnichannel Experience

The omnichannel personalization experience is about ensuring consistency and seamlessness across multiple platforms and devices, and this is where Generative AI and Traditional ML models can be indispensable.

Seamless Transitions

Customers frequently switch between various devices and platforms. Identity resolution fortified with Generative AI or Traditional ML strategies ensures that the experience remains seamless and consistent across all channels. It does this by analyzing and understanding individual user behaviors and preferences across different platforms, adapting the user experience in real-time to meet the customers' expectations and needs.

Consistent Messaging

Consistency in messaging is critical in an omnichannel approach. Integrating Generative AI with the Traditional ML strategy approach discussed below helps maintain consistent and relevant messaging across all platforms and channels. It can automatically generate content that aligns with the brand voice and customer preferences, ensuring that customers are clear of mixed messages and receive a unified and harmonious brand experience, regardless of the channel or platform they interact with.

In essence, the infusion of these two combined approaches into omnichannel campaign initiatives ensures more cohesive and customer-centric experiences, helping brands to establish stronger connections with their audiences and adapt to their evolving preferences and expectations.

Building Customer Profiles

Comprehensive Data

In the sprawling landscape of digital identities, building a customer profile is akin to assembling a multifaceted puzzle, each piece a shard of data echoing with the whispers of individual customer stories. Identity resolution is not just the art of linking disparate IDs to a singular customer; it is the craft of weaving myriad data points into a coherent tapestry, revealing the vivid portrait of who the customer truly is. It involves gathering diverse shards of information – from browsing behavior to purchase history, from social interactions to content engagement – to craft comprehensive profiles that breathe the lifeblood of individual customer journeys.

High-level ERD for the Profile. This is a generic representation. It's a mix of several models taken from Adobe XDM, Salesforce CIM, Algonomy, and Microsoft CDM. 

At its foundational level, Identity is constructed using signals sourced from three distinct layers:

  1. Terrestrial: This foundational layer incorporates traditional data about an individual, including physical location, personal details, and identifiable information such as names and addresses. This set of data constitutes what we term the "terrestrial identity."
  2. Device: Every individual within a household engages with one or more devices. While some individuals might exclusively use personal devices like smartphones and tablets, others might share devices among family members. Such patterns give rise to the device's distinct identity.
  3. Digital: Certain digital platforms allow users to assert their identity. These self-declared digital identities serve as anchor points, connecting profile data with behavioral patterns.

The ultimate objective is to craft a cohesive strategy encompassing these three dimensions. The three can be mixed and represent data from what is traditionally considered offline sources - in reality, those offline sources are mixed metaphors of one or more of the three named here. Organizations can effectively manage and optimize their consumer insights by integrating this data and housing it in a centralized and structured repository – be it a marketing database, a customer data platform, a data lake, or any consumer intelligence tool.

(NOTE: The final paragraph above was inspired and rephrased from a book or article I, unfortunately, lost track of. The original content was outstanding. If anyone recognizes it, kindly inform me so I can give appropriate credit.)

Real-Time Updates

The technological marvel of identity resolution is its ability to breathe in the dynamism of the ever-evolving customer journey. Customer profiles are not static snapshots; they are living, breathing entities pulsating with the rhythms of real-time customer interactions. As customers dance through their journeys, interacting, exploring, and experiencing, the identity resolution technologies are the maestros orchestrating the continuous symphony of updates, ensuring the customer profiles reflect the customers' evolving stories, needs, and desires. This process does not mean the profile was resolved in real-time. Rather, it is made available after it is resolved or re-resolved based on a missed merge/match. This means it should then be forwarded to a real-time repository, aka CDP, to be updated continuously with event data so it can be activated when needed - the Data management and ID RES process for great matching and merging should sit in front of the CDP. Each component with a distinct function and feature in a composable manner. Some vendors like to promote their real-time resolution capabilities, but this is misconceived and often impairs the profile's accuracy.

Courtesy of Algonomy/RichRelevance

The image above depicts the "Real-Time User Profile" of a shopper, illustrating how various interactions, behaviors, and historical data of a user are tracked and integrated into a unified profile, which can be used for marketing personalization through machine learning (ML) models. This is how Algonomy's Rich Relevance personalization and recommendation engine is used when it consumes profiles from the Algonomy CDP.

Let's break it down - from the top, counter-clockwise:

  1. Interactions & Behavior:

    • Browsed & clicked: These interactions show the specific products the user has browsed and clicked on, such as different types of Michael Kors products. Timestamps indicate the exact time the user viewed each product.
    • Purchases: This area highlights a past purchase made by the shopper, including the product's name, image, and it's price.
    • Searches: The user has performed a specific search ("orange and white"), showing the types of products or colors they may be interested in.
  2. Real-Time Events:

    • Events like "viewedBrands" and "ItemView" are recorded in real-time, showcasing the user's most recent interactions on the platform.
  3. Segmentation/Characteristics/External Data Sources:

    • The profile is segmented based on certain attributes and preferences like 'Loyalty' and 'STELLA'. This data can be sourced from internal behavior tracking and external data sources.
  4. Shopper Profile:

    • The avatar, representing the shopper, is labeled "SHOPPER 1234", noting that each user has a unique identifier or code. aka Profile ID.
  5. Profile Augmentation:

    • The User's profile is constantly updated in real-time based on various interactions like geolocation, referral sources, page loads, clicks, and purchases.

In the context of ML models and personalization:

  • ML Models: These models can analyze real-time and historical data to predict future behavior, recommend products, or tailor marketing messages to the individual. For instance, if a user frequently views a particular brand or product type, ML algorithms can suggest similar products or offer deals that align with those interests.

  • Personalization Process: By integrating this rich profile data with 100's ML strategies or one large AI Deep learning or LLM, businesses can craft more personalized shopping experiences. For example, the next time the user visits the website, they might be shown personalized product recommendations based on their search history, viewed brands, and past purchases.

Overall, this image emphasizes the importance of capturing and analyzing every touchpoint in a shopper's journey to offer a more personalized and effective marketing experience.


As mentioned above, segmentation is often more of a business rule than the standard approach. ML takes on more of the audience segment responsibilities via 1:1 automation. However, marketers find the rhythm to segment their audience with a scalpel's precision within the orchestrated harmony of resolved identities for other campaign initiatives - not all vendors have full 100% omnichannel ML personalization capabilities, and not all campaigns can be leveraged with ML.

By diving into the depths of these rich, dynamic customer profiles, they can sculpt their audiences into highly defined, hyper-targeted groups - some vendors will call this micro-segmentation. This type of segmentation is not merely about clustering demographics; it's about aligning symphonies of individual customer narratives, behaviors, journeys, and preferences. It's the art of tuning the marketing messages to the individual. As with the above, deeper insight can be surfaced with AI and ML tools, and automation can be applied. I would like to dive deeper into those areas in subsequent articles. Or at least I hope I can find the time. Keep looking for ideas around this area as it is emerging as a key component within the CDP to accelerate audience creation so marketers can spend more time on the creative processes. I think there is a huge opportunity to improve and automate this area of data orchestration that is hugely neglected by vendors. Let's briefly dive into some of it below.

Personalization in Marketing

Personalization is crucial in marketing, as noted above with RichRelevance's diagram, turning ordinary interactions into meaningful and relevant experiences.

In this dynamic relationship, advanced AI deep learning models or basic and traditional ML models acting individually or in ensemble approaches can act as conductors orchestrating unique and insightful encounters. The image below depicts how Algonomy applies ML, but this could be achieved in many composable ways.

Companies purchasing CDPs must realize that the CDP is not a personalization engine, nor can it provide personalization capabilities like many often claim. The CDP's sole purpose is at the crux of many debates in this realm. Personalization is a composable component fed profile IDs, profile data updates, or audience segments natively or by the CDP in batch or real-time with a new event. Many personalization engines like the one below house a copy of the profile. Its dB updates from another service or through its native capability. In other cases, it can access the profile from an EDGE CDN mirror, a newer approach, especially for IoT devices and services personalization initiatives. Adobe Target has this more recent capability. Be careful as a customer of CDP vendors saying their CDP is a personalization activation tool. In most cases, they need to catch up in this regard.

Courtesy of Algonomy. Note that tools like Dynamic Yield work similarly.

This image sheds light on how businesses could use various ML strategies and decision-making processes to personalize customer experiences. It further illustrates the infrastructure supporting these strategies and how machine learning (ML) underpins the entire personalization approach.

Breaking it down:

  1. ML Strategy Library:

    • Multiple strategies are available as a 'library,' emphasizing the diversity of potential approaches businesses can use.
    • Some highlighted strategies include:
      • Content-Based: Uses metadata, images, and text from user interactions.
      • Collaborative Filtering: Finds patterns by aggregating user behavior.
      • Hybrid Approaches: A combination of different strategies, tailored for personalization based on individual user behaviors or item properties.
  2. User Profile:

    • A user's unique ID, demographic data (like age segment), browsing history, and purchasing details form the core of the user's profile. This profile acts as a foundation for all subsequent personalization strategies.
  3. AI-Based Strategy Selection - Ensemble Method:

    • ML models evaluate the user's profile data against the strategy library to select the most suitable strategies.
    • The ensemble method suggests that multiple models or algorithms might be used in tandem to optimize the strategy selection.
  4. Personalization Engine & Model Optimization:

    • The central hub is where all data and strategies are processed. This engine uses ML for optimizing models, ensuring the best results for personalization.
    • Key performance indicators include CTR (Click Through Rate), Conversion (Conv.), and Revenue.
  5. Real-Time Recommendations:

    • Dynamic content and offers are generated in real-time based on the user's profile and selected strategies.
    • The visual representation of a smartphone showcases that these recommendations are delivered on-the-go, keeping user interactions dynamic and fresh.
  6. Business, Brand, & Merch Rules:

    • Beyond the AI and ML strategies, business rules and constraints should be considered, such as legal constraints, margin objectives, and inventory realities. These shape the final recommendations, ensuring they align with business objectives and compliance standards.

Per the image and processes above, these personalization engine vendors can optimize and manage the content for the profile in several distinct areas. they include but are not limited to:

  • Customized Offers and Discounts
  • Content Personalization
  • Geo-Location Targeting
  • Recommendations
  • Content Testing and Experimentation

Enhancing Customer Loyalty and Retention

Recognizing High-Value Customers

Acknowledging and appreciating each customer's value is imperative to nurture the bond between brands and customers. Identity resolution is the harbinger of recognition, allowing brands to identify high-value customers and envelop them in layers of appreciation and rewards. Customers feel seen and cherished through this intricate dance of recognition and value acknowledgment, anchoring them firmly to the brand and fostering a terrain of loyalty and mutual growth. The ability to discern and distinguish high-value customers ensures that brands can tailor their appreciation, creating an ecosystem of personalized gratitude where customers feel their worth is recognized and rewarded.

Predicting Customer Behavior

Predicting the next move is pivotal in the dynamic ballet of consumer interaction. Here, identity resolution intertwines with machine learning to decipher the patterns and predict future customer behaviors with heightened precision. This synthesis of technology and insight carves pathways to proactive engagement, allowing brands to anticipate needs, desires, and preferences. In this anticipatory dance, brands can align their movements with customer expectations, ensuring a harmonious interaction that resonates with individual needs and fosters a profound connection, reinforcing the bonds and mitigating the chasms of disconnect.

Timely Retargeting

When recapturing the essence of a customer, timing is critical. Identity resolution empowers brands to retarget customers precisely and synchronously with real-time behavior, curating timely and relevant interactions. Through this amalgamation of timing and relevance, brands can rekindle the waning embers of connection, drawing customers back into the harmonious ballet of exchange and revitalizing the relationships that might be veering toward the shadows of disengagement.

Enhancing customer loyalty and retention is a meticulous symphony of recognizing value, predicting interactions, and crafting timely engagements, all orchestrated by identity resolution. It's a continuous ballet of mutual appreciation and anticipatory interactions that fortify the bonds between brands and customers. It creates a resonant, enduring, and profound harmony, making every interaction a step towards a lasting dance of loyalty and shared growth.

Measuring Campaign Effectiveness

Accurate Attribution

Measuring the impact of marketing campaigns hinges on accurately attributing interactions and conversions to the appropriate initiatives. Identity resolution emerges as a pivotal tool in this realm, meticulously linking customer interactions to specific campaigns, thereby unraveling the threads of customer journeys. This meticulous attribution enables marketers to dissect the nuances of campaign interaction, discerning which elements resonate and which fall flat and, in turn, refining their strategies with precision. Accurate attribution is more than just a measurement; it's a compass guiding marketers through the labyrinth of customer interaction, illuminating pathways to enhanced resonance and connection.

ROI Calculation

Return on Investment (ROI) is the melody of success in the economic symphony of marketing. It is imperative to calculate the ROI accurately to gauge the effectiveness and financial viability of campaigns. Identity resolution is the maestro in this symphony, orchestrating a coherent view of how individual consumers traverse through the sales funnel, linking interactions and conversions to monetary outcomes. By correlating the journey with the outcomes, it unveils the economic landscape of campaigns, presenting a clear panorama of investment returns. This calculative coherence allows marketers to tune their strategies, aligning their initiatives with the beats of financial viability and impact, ensuring every note played resonates with economic harmony.

Regulatory Compliance


The regulation landscape in today's digital age is multifaceted, with laws such as HIPAA, GDPR, and CCPA governing data privacy and protection. It is paramount for identity resolution technologies to align with these regulatory compasses, navigating the waters of compliance with precision. Configuring identity resolution technologies to be compliant safeguards marketing strategies from inadvertently breaching legal frameworks, ensuring that the pursuit of marketing excellence is anchored in ethical and lawful grounds. Compliance is not just about adherence; it's about embedding integrity and responsibility within the DNA of marketing, fostering a culture of respectful interaction with customer data.

By adhering to such stringent regulations, marketers uphold legal standards and cultivate trust among their user base, establishing a foundation of credibility that transcends transactional interactions. In marketing, trust is the currency that fuels long-lasting relationships, and regulatory compliance is the mint where this currency is forged, embedding value within every interaction and communication.


Identity resolution is the linchpin of the modern marketing ecosystem, synthesizing a spectrum of customer data into coherent and actionable insights. It transcends the conventional boundaries of marketing, offering a 360-degree view of the customer that empowers unparalleled personalization, seamless omnichannel experiences, and heightened customer loyalty. The journey through identity resolution is one of discovery, revealing the multifaceted dimensions of customers and paving the way for marketing strategies that resonate on a profound level.

As technology continues to evolve, the role of identity resolution is set to burgeon, shaping the future marketing landscape with its nuanced understanding and analytical prowess. It is about resolving identities and weaving the threads of interaction, experiences, and connection to improve marketing excellence. In this ever-evolving dance of innovation and connection, identity resolution stands as the choreographer to allow marketers to craft sequences of interaction that resonate with depth, relevance, and impact, sculpting the future of marketing with every step.

Sources and Citations

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