How can Syntasa help companies cope with a cookie-less world?

by Charmee Patel

In our previous post, we discussed the monumental shift facing companies as third-party cookies phase out. With cookie-based tracking on its way out, organizations must rethink their approach to collecting, managing, and leveraging customer data.

This transition presents a unique opportunity for businesses to embrace more privacy-centric methodologies. Rather than relying on intrusive tracking methods, companies can tap into their first-party data and consent management platforms to deliver personalized experiences.

In this post, we will dig deeper into best practices for collecting, managing, and connecting data in this new environment. Finally, we’ll highlight how Syntasa’s data transformation accelerator enables seamless data integration and governance. By leveraging Syntasa’s solution, companies can future-proof their data stacks to allow marketing activation and analytics use cases to yield better results.

The key is to see this major shift not as a challenge but as an opportunity to create better, more meaningful customer experiences grounded in trust and transparency. Let’s explore how.

What are data collection, data management, and stitching of data?

To successfully collect, manage, and stitch data, businesses need to first understand these key aspects:

1. Data collection

Data collection is the process of gathering information from various sources to gain insights and drive decision-making. Companies collect data to understand customer behaviours, identify trends, personalize experiences, and optimize operations. Having clear objectives is crucial to steer effective data collection efforts.

Cross-functional teams, including marketing, product, engineering, and analytics, typically collaborate to determine what data needs to be collected. They identify relevant first-party and third-party data sources that can provide the information needed to meet the defined goals. These teams also decide on appropriate collection methods such as surveys, interviews, web analytics, and more.

Effective data collection requires clearly defining the objectives and questions you want the data to answer, choosing suitable data sources that can provide relevant information, and employing the right collection methods to gather the data. When done right, data collection provides the necessary fuel for deriving customer insights and guiding strategic business growth.

There is also an opportunity to enrich existing data where gaps lie through strategic data partnerships. With proper consent and governance in place, leveraging external data sources can provide a more holistic view of the customer. 

2. Data management

Data management is organizing and storing data securely to enable easy access and usage. Proper management makes information readily available for analysis and actionable insights. 

Database administrators, data engineers, and other IT specialists typically design and maintain secure storage systems through backups, access controls, and integrity checks. A well-organized structure is established to facilitate easy retrieval and utilization of data. Measures like regular backups and checks are implemented to prevent data distortion.

This allows companies to easily access and use information to generate insights and make data-driven decisions. Ongoing maintenance of storage infrastructure protects data integrity and security over time.

3. Data stitching

Data stitching involves combining customer data from different sources into a unified view through identity resolution. Companies leverage customer data platforms and integration tools to link disparate data sets.

A key capability is an Identity Graph (ID Graph) – a database that stitches customer records from all data sources to create a Unified Customer Profile. The ID Graph uses identifiers like usernames, emails, phone numbers, cookies, and offline identifiers to match records belonging to the same individual.

With an ID Graph, a customer’s information across your e-commerce platform, CRM, email tool, and ad platform can be unified into one profile. This provides a complete view of each customer versus fragmented, siloed data. 

Cross-functional data teams first determine the relevant sources to integrate. Then, they standardize disjointed data for compatibility before bringing it together. Technical teams then utilize CDPs or manual scripts to combine first-party data seamlessly. Extensive validation checks ensure accuracy as integrated data feeds business intelligence and customer experience initiatives.

In addition to these considerations, businesses must also prioritize data privacy by adhering to regulations and ensuring compliance in data collection and usage. Data quality checks, including cleansing and validation, are crucial to maintaining accurate and reliable data. Implementing robust data security measures, such as encryption and access controls, is essential to protect data from unauthorized access or disclosure.

Why are Data Collection, Management and Data Stitching beneficial?

1. Clean Data Enables Insights:

Transitioning away from a cookie-less world benefits businesses by enabling them to obtain cleaner and more reliable data sets. By shifting their focus from fragmented cookie data, organizations can leverage alternative methodologies such as first-party data, contextual data, or permission-based data to gain profound insights into customer behavior and preferences. 

The availability of clean data establishes a robust foundation for precise analysis and empowers the Data Science team to derive accurate and meaningful insights. This, in turn, supports informed strategic decision making and enhances the overall effectiveness of data-driven initiatives.

2. Activations Based on Clean Data:

In a cookie-less world, businesses need to rely on alternative data sources and signals to activate their marketing efforts. This can include leveraging first-party data collected through user registrations, subscriptions, or interactions on owned platforms. With clean and reliable data, companies can create more targeted and personalized marketing campaigns, improving customer engagement and conversion rates.

3. Importance of Clean Data for Customer Data Platforms (CDPs):

CDPs play a crucial role in ingesting, unifying, and activating customer data across various touchpoints. Clean data is essential for the effective functioning of CDPs. Unclean data, on the other hand, can have downsides and pose challenges for businesses.

When data inputs to CDPs are inaccurate or unreliable, it can result in incomplete or misleading customer profiles. This can hinder the ability to accurately segment customers, personalize experiences, and execute targeted marketing campaigns. Inconsistencies or errors in data can lead to flawed analysis and decision-making, compromising the overall effectiveness of data-driven initiatives.

To mitigate the downsides of unclean data, businesses need to prioritize data quality and implement robust data cleansing and validation processes. By ensuring accurate and reliable data inputs, businesses can leverage CDPs to create comprehensive customer profiles, enabling better segmentation, personalization, and targeted marketing campaigns.

4. Unifying Data for Informed Choices

Effective data stitching connects siloed data to reveal full customer journeys. This powers strategic decision-making and tailored engagement. With the right solutions, companies can securely stitch consent-based data to deliver superior experiences without third-party cookies.

A key benefit is the ability to track a customer across the funnel to identify what’s working and what isn’t working. This cross-funnel visibility informs strategy and planning by pinpointing effective marketing and sales tactics versus those needing optimization. 

How Does Syntasa Enable Companies to Cope With The Cookieless World?

The Data Transformation accelerator, powered by Syntasa, is an ace up the sleeve for companies navigating the cookieless landscape. This innovative solution kills two birds with one stone – it streamlines data collection and management while stitching together disparate sources into a unified customer view.

Deployed within a customer’s cloud infrastructure, including popular platforms such as Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP), Syntasa operates behind the firewall to allay any data privacy or compliance fears. Its operation is confined to the customer’s dedicated VPC, which establishes a secure and segregated environment. This implementation approach empowers organizations to maintain data ownership and exercise full control over their datasets.

Syntasa casts a wide net to capture relevant behavioral and transactional data from every customer touchpoint. This could include website clicks, mobile purchases, support tickets, CRM interactions – you name it. The accelerator connects these far-flung data dots to reveal the full picture of each customer journey.

With all hands on deck, Syntasa consolidates first-party data across channels to drill down into customer segments and uncover actionable insights. The unified profiles serve as fodder for personalized experiences and targeted campaigns aimed right at the bull’s eye.

Here is an example to illustrate how Syntasa can help a company in the cookieless world:

Consider an online retailer looking to deepen customer relationships without third-party cookies. By implementing Syntasa, they can consolidate behavioral data from their website, mobile app, email campaigns, and call center interactions.

When a customer contacts support, the agent has a comprehensive view of that individual thanks to synthesized data in Syntasa. The agent sees the customer recently abandoned an online purchase, frequently uses the mobile app, and responds to cart abandonment emails.

Armed with these insights, the agent can have a highly personalized conversation and proactively address the customer query. and lead to conversion and loyalty through a positive customer experience. They recommend products based on past browsing, advise on mobile discounts, and remind the customer about email coupons to complete their purchase. This increases the probability of conversion and loyalty through a positive customer experience.

This tailored service delights the customer and gets them excited about the brand. The retailer gains revenue they would have otherwise lost. Multiply such individual experiences across thousands of customers, and Syntasa gives this company an edge despite disappearing cookies.

By seamlessly stitching data, the platform empowers personalized engagement that builds loyalty and trust. It’s a future-proof solution as the cookie crumbles.

How does a Data Transformation accelerator work?

Here’s a breakdown of how the data transformation accelerator works:

Ingestion of data: 

The data transformation accelerator is a real workhorse when it comes to unifying customer data. Right off the bat, it pulls double duty by ingesting information from all corners of the business – no data source gets left behind. Like a sponge, Syntasa soaks up structured data from databases along with semi-structured and unstructured data from websites, apps, and social channels.

Cleansing and Transformation: 

Once data is ingested, the accelerator initiates cleansing and transformation procedures. This entails rigorous identification and elimination of inconsistencies, errors, and duplicates within the data. Moreover, the accelerator performs standardization, normalization, and enrichment of the data, augmenting its quality and usability for downstream operations.

Identity resolution: 

Identity resolution is a pivotal step facilitated by the data transformation to establish a unified customer view. Leveraging advanced techniques, it resolves identities across multiple data sources. This involves using both deterministic and probabilistic modeling to match and link customer records. 

Deterministic matching links profiles with 100% certainty based on unique identifiers like hashed emails, phone numbers, or logged-in usernames. Probabilistic matching relies on attributes like IP addresses, device types, browsers, and operating systems to statistically match profiles, though not with complete certainty. 

For example, tracking IP addresses can identify devices likely used by the same individual connecting from different networks throughout the day. While not an exact match, combining probabilistic signals from various algorithms enables more comprehensive identity resolution. 

What is the Output of the Data Transformation accelerator?

Armed with this 360° understanding, companies can read customers like a book. Granular profiles and journey visualization enable hyper-personalized engagement while illuminating new revenue opportunities. It’s a feast for customer analytics that nourishes stronger brand affinity.

In the cookieless future, unified first-party data is king. With the data transformation accelerator in your tech stack, fragmented information transforms into total customer intelligence. This is the slice of data that will take your customer experience initiatives to the next level. 

The data transformation accelerator provides a unified customer view, the foundation for extensive analysis and personalization endeavours. It empowers companies to conduct in-depth journey analysis, measure the efficacy of marketing campaigns, and gain insights into customer preferences and behaviour.

Here are some ways in which the organization can leverage this customer data:

  • Marketing teams can access the data in CRM, DMP, CDP, and paid media platforms to create targeted campaigns and personalized experiences based on full customer insights.
  • Data analytics teams can incorporate unified profiles into modelling and analysis to uncover new trends and opportunities.
  • Business intelligence tools can connect to the data for improved reporting and dashboards with cross-channel visibility.
  • Front office operations can leverage the customer-centric view to deliver superior engagement during sales, service, and support interactions.
  • User behaviour can be tracked across touchpoints to understand the full journey and optimize experiences.
  • An amalgamation of demographic data, transaction history, browsing patterns, and other pertinent information to provide a holistic understanding of each customer. 
  • New systems can readily tap into the unified data foundation to drive innovation.


Leaning on Syntasa, organizations can hit the ground running with future-proofed data practices despite the cookieless shake-up. They gain an inside track of customers that cements loyalty and boosts the bottom line. It’s a win-win that respects privacy while driving growth.

Don’t let cookie-based tracking hold your CX(Customer Experience) initiatives back. Our experts are ready to evaluate your tech stack, data infrastructure, and use cases to craft a tailored solution. Reach out today to schedule a demo and discuss how Syntasa can help you thrive in the cookieless world.

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Charmee Patel

Head of Innovation and Data Science, Syntasa

Charmee Patel leads Product Innovation activities at Syntasa. She has extensive experience synthesizing customer, visitor, and prospect data across multiple channels and scaling emerging big data and AI systems to handle the most demanding workloads. This experience guides her work helping clients deploy innovative ways to apply AI and Machine Learning to their marketing data and developing the next generation Marketing AI Platform.