77: Boris Jabes: Decoding the composable CDP, the future of data activation and AI in marketing

What’s up folks, today we’re extremely privileged to be joined by Boris Jabes, the Co-Founder & CEO at Census.

Summary: In our conversation with Boris Jabes, we navigate the future of marketing where Composable Customer Data Platforms (CDPs) — agile, customizable data handlers — mark a seismic shift in martech. Census sits at the helm of this revolution, fostering a symbiotic relationship between data and marketing teams while transforming complex datasets into actionable data points. As the future brings us closer to AI integration, mastering the balance between automation and data integrity becomes the paramount performance every marketer must ace. It’s not a story of Census vs CDPs; it’s the dawn of a unified, flexible data ecosystem.

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About Boris

  • Boris is originally from Ottawa, Canada where he went on to study Computer Science at the University of Waterloo 
  • He got his start at Microsoft where he spent 7 years in various Program Manager roles leading C++ and 3D graphics for Visual Studio
  • He then moved to SanFrancisco to co-found a password manager tool called Meldium, backed by Y Combinator 
  • In 2014 he sold the startup to LogMeIn where he became a Senior Director for a year and a half – before jumping into Angel Investing in which he took part in startups like Canvas, Endgame, Lambda and Reflect
  • In 2018, Boris Co-founded Census where he’s also CEO today.
  • Census is a reverse ETL tool that allows marketers to activate customer data from their data warehouse 
  • Boris is also a podcaster, in 2021 he and his team launched The Sequel Show which counts over 30 episodes with some of the smartest minds in data and is one of the greatest resources to help marketers bridge the gap with data teams

The Thread Connecting Password Management and Reverse ETL


Boris’s first venture was into password management, but it wasn’t out of love for passwords. It stemmed from a frustration with the scattered nature of employee identities across numerous apps. Each login seemed to represent a different version of oneself. The solution? A first-of-its-kind enterprise-grade password management tool designed for teams, aimed at streamlining the login process for any office application.

Boris describes this as a quest to create a federated version of oneself – a concept known as Single Sign-On (SSO). Behind the tech jargon, the aim was simple: to make people’s lives easier by reducing the friction caused by hundreds of passwords.

His journey then led to Census, a reverse ETL venture. Again, the core issue was fragmented identities, but this time, it was the customers’ identities in question. Why were these identities inconsistent across different divisions within a company?

Just as with the password management venture, Boris saw the need for a central place from which customer identities could be federated. He was addressing the same problem but from a different angle.

Boris’s focus has always been on alleviating the pain points created by disparate data. From password management to reverse ETL, he continually seeks to resolve identity disparities, a testament to the power of innovation that lies at the intersection of distinct yet interconnected problems.

Takeaway: Boris’s journey showcases his quest to untangle the web of fragmented digital identities. Starting from creating a unique password management system for unified employee logins, to innovating with Census, a reverse ETL project aimed at centralizing customer identities, Boris proves innovation lies in finding and solving related problems from diverse angles. Essentially, his story emphasizes the power of iterative, angle-shifting solutions to common pain points in the digital world.

Experiencing the Pain Point Firsthand: The Genesis of Census

It was when Boris’s first startup was acquired that he truly felt the problem Census would later solve. Joining forces with LogMeIn, a larger company with a keen interest in their software and user base, illuminated a stark issue. The marketers and salespeople at LogMeIn wanted to engage with the users and cross-sell the software, but they struggled. The key issue? They didn’t seem to have a clear understanding of what the users were doing.

Despite the availability of tools to connect data, none seemed to coalesce the company around a single version of reality. The tools used by marketers were different from those used by salespeople. These fragmented solutions failed to bring everyone onto the same page, especially considering that product behavior was becoming an increasingly important driver.

The seed for Census was thus sown. Boris and his team envisioned a solution that would work at scale, bridging the gap between different divisions and providing a unified view of customer data. The challenge was technical, but the ultimate goal went beyond that. They aimed to empower various stakeholders – marketers, salespeople, product teams, finance – to take action based on reliable, trustworthy data.

Census was born out of the need to solve a real problem – to provide a single version of truth that would allow different divisions within a company to understand and act upon user behavior efficiently and effectively. This venture underlines Boris’s ability to observe, understand, and respond to the intricate problems arising from fragmented data, paving the way for more streamlined operations and decision-making within organizations.

Takeaway: The inception of Census highlights Boris’s knack for problem-solving. He recognized a critical issue – disjointed customer data causing confusion across company divisions. The solution? Census, aiming to unify customer data and streamline decision-making across teams. Essentially, Boris’s experience proves that innovation blossoms from understanding and addressing complex, real-world challenges.

Unraveling the Concept of the Packaged Customer Data Platform

As we delve deeper into the realm of martech, there’s no escaping the maze of terminology and definitions, especially when it comes to the concept of the Customer Data Platform (CDP). From a distance, it might seem like yet another acronym tossed into the complex landscape, but understanding it is essential.

In Boris’s view, the packaged CDP is a lineage of software specifically designed with marketers in mind, most often serving B2C companies (at least initially). But what does it really do? It performs three critical functions:

  • It helps collect events from your website and applications.
  • It serves as a source of truth for that data specifically for the marketing team.
  • It enables the segmentation and personalization of targets based on this data into other marketing tools.

Whether it’s channeling information into advertising platforms or feeding into an email or direct mail tool, a packaged CDP is designed to facilitate these processes with an all in one solution.

Takeaway: In Boris’s perspective, a Packaged Customer Data Platform (CDP) is designed to streamline end-to-end data management for marketers. It stands for the essential need to use data efficiently to create valuable, problem-solving tools, highlighting the ongoing evolution in the marketing technology landscape.

Building a Composable Stack: The Shift in the Martech Landscape

Boris highlights the major shift in the martech landscape, specifically focusing on the evolution of customer data platforms (CDPs). When examining the traditional packaged CDP model, it’s clear that these platforms often duplicate data from existing company databases, such as a data warehouse. However, this model assumes that all companies have a data warehouse, which is not always the case, especially for smaller startups.

In recent years, there’s been a considerable increase in companies investing in data warehouses or other forms of data platforms. These platforms, such as Google, Snowflake, Amazon, or Databricks, can store a massive amount of data and are used to answer a wide array of questions. Therefore, duplicating this data to solve problems seems counterproductive.

With this in mind, Census was built differently. It was designed from first principles, focusing on giving marketers more trustworthy data without contributing to unnecessary data duplication. The tool connects directly to a company’s existing data warehouse, eliminating the need to recreate a separate customer database. This, in turn, saves both the data and marketing teams a significant amount of time.

This shift is part of a broader trend towards composable solutions. Composability, in this context, refers to a philosophy where components of a system are designed to work together seamlessly, fostering flexibility. Each piece of the system can be customized and interacts fluidly with the others.

Today’s customer journey is more complex than ever, spanning across multiple touchpoints and channels. Add in the added complexity of privacy regulations and it’s clear that marketers require more flexible, adaptable tools to handle their customer data effectively. This evolving landscape necessitates a shift towards a more composable stack of tools centered around the data warehouse.

Takeaway: Boris identifies a critical shift in martech, moving from traditional, duplicative data platforms to composable solutions that streamline data use and improve adaptability. Census exemplifies this shift, connecting directly to existing data warehouses and removing unnecessary data duplication. This evolution underlines the growing need for flexibility and efficiency in managing the ever-complex customer journey.

Defining the Composable CDP: Flexibility, Scalability and Customizability

When we dive into the world of Composable Customer Data Platforms (CDPs), it can feel like stepping into an intricate labyrinth. Navigating this complex terrain involves understanding the key facets that differentiate it from traditional packaged CDPs.

A Composable CDP can be best defined as a marketing system that integrates diverse, best-in-class software components. Each component caters to a specific function or data task, resulting in a highly tailored and flexible solution designed to meet unique business needs. This modularity gives marketers the agility to switch components as and when their business requirements evolve.

The core advantage of the Composable CDP lies in its flexibility. As our fellow marketer pointed out, traditional CDPs often enforce limitations on the number of custom attributes or on the complexity of data manipulations, creating a ‘one-size-fits-all’ solution. In contrast, Composable CDPs empower marketers with unlimited attributes and advanced customization possibilities, even accommodating nuanced SQL operations.

This leads us to a secondary, yet vital, benefit – the ease of integration. Composable CDPs are built to work seamlessly with existing systems, such as data warehouses, forming the backbone of marketing operations. The fear factor associated with these complex systems is mitigated through intuitive user interfaces, rendering them accessible to a wider marketing audience.

Now, to the economic aspect of it. With Composable CDPs, marketers are no longer bound by the constraints of a user or event-based payment structure. Given that these platforms leverage existing storage resources, costs are dramatically reduced.

Finally, Composable CDPs serve as a holistic source of truth, capable of assimilating data from a wide range of systems like point-of-sale, billing systems, data science models, and even offline data. This approach results in faster implementation timescales, from months to mere days or even hours, depending on the state of your data warehouse. The Composable CDP is scalable, adjustable, and most importantly, built to work for you, not the other way around.

As the era of large internal martech teams building in-house solutions fades into the annals of marketing history, the rise of the Composable CDP opens the doors to a world of infinite possibilities, ready to be harnessed by marketers of today and tomorrow.

Takeaway: Stepping into the realm of Composable Customer Data Platforms (CDPs) is to embrace flexibility and customization in handling data needs. Unlike traditional, restrictive CDPs, Composable CDPs bring agility to marketers by integrating diverse components for highly tailored solutions. They cut costs, easily integrate with existing systems, and provide a holistic, scalable source of truth for data. Essentially, Composable CDPs represent the dawn of a new era in martech, ready to be leveraged for infinite possibilities.

Bridging the Gap: Collaboration Between Marketing and Data Teams

There’s a prevalent notion within the industry that data warehouses and marketing teams operate on different spectrums, leading to friction when attempting to implement tools such as Customer Data Platforms (CDPs). Yet, it’s crucial to reassess this standpoint as data increasingly becomes an integral part of marketing strategies.

The idea of data teams and marketing teams operating in silos is gradually fading. Forward-thinking businesses encourage their data teams to construct the stack and equip the marketing team with the necessary data for use cases. This collaborative approach paves the way for smoother communication and facilitates a more holistic view of the data.

Furthermore, this cooperative model propels a change in teaching and learning dynamics within the organization. For instance, data analysts are educated about the real-world applications of data in marketing strategies, such as segment creation, email targeting, and personalizations. On the other hand, marketers get insights into the intricacies of data tools, transformations, and models. These cross-functional insights lead to a synergistic relationship that enhances the overall functioning of the business.

While packaged CDPs are marketed as tools that don’t necessitate a data engineer, the reality can be quite different. Even technically adept marketers often find themselves needing the assistance of engineers to navigate the complexities of tools like Segment. Thus, acknowledging the interdependence of these roles can facilitate a more efficient and cost-effective implementation of CDPs.

Ultimately, fostering better relationships between marketing and data teams is a win-win scenario for all parties involved. Not only does it mitigate potential conflicts, but it also streamlines regulatory and compliance procedures, ensures consistency in metrics, and increases the flexibility of the business’s data operations. As such, bridging this gap offers a more seamless and efficient approach to utilizing data in marketing strategies.

Takeaway: A collaborative approach between data and marketing teams fosters cross-functional understanding, leading to more effective use of tools like Customer Data Platforms (CDPs). This synergy not only streamlines operations and compliance but also enhances the flexibility and efficiency of data use in marketing strategies, proving the value of interdependence in these roles.

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Embracing the Composable Stack and reverse ETL

The journey towards a cohesive and integrated work environment between data and marketing teams is undoubtedly a gradual process. However, the strategic advantage of aligning everyone around the shared objective of growing the company significantly outweighs the time investment.

Reflecting on the evolution of startups and marketing technology over the past decade, there was a time when these departments operated without a dedicated data team. Instead, marketing and engineering teams manually built individual integrations with each tool through APIs, a process that was time-consuming and often complex.

Fast forward to today, and marketers can now readily partner with data teams, thereby streamlining the process and maximizing data utility. This evolution highlights the emerging trend of the composable stack, which involves unbundling tools and functionalities to create a more tailored and efficient workflow.

The shift from conventional packaged CDPs to a more composable stack approach is gaining momentum. Tools like Census, for instance, offer a compelling alternative to traditional CDPs by interfacing directly with data warehouses like Redshift. These tools allow data teams to build or leverage existing transformations seamlessly and without the need for managing individual APIs or worrying about bi-directional syncing.

In essence, tools like Census handle the heavy lifting behind the scenes by fitting data into what downstream tools like Iterable or Salesforce require. This includes navigating challenges such as adhering to API quotas and managing system failover, which are notoriously complex to build internally.

The concept of ‘reverse ETL’ encapsulates this process, allowing marketers to get more data at their fingertips and enabling them to personalize the customer experience more effectively. However, it’s not just about better data access; it’s about reducing the grunt work for data teams, work that often goes unnoticed and unrewarded.

In conclusion, the future of data and marketing integration lies in embracing the composable stack and reverse ETL. These innovations not only enhance operational efficiency but also pave the way for more personalized and data-driven marketing strategies.

Takeaway: The shift to a composable stack marks a significant evolution in the symbiosis between data and marketing teams. By reducing manual workload and increasing data access for marketers, tools like Census are leading the charge towards more efficient, personalized, and data-driven marketing strategies.

The Etymology of ‘Reverse ETL’

The term ‘Reverse ETL’ first started to gain traction nearly five years ago, amidst the complexities of explaining a new and unfamiliar product. Its emergence was less a strategic branding decision and more a byproduct of early-stage product pitches, wherein the technical intricacies of data extraction and loading could seem somewhat disconnected from the more compelling value proposition – personalizing marketing campaigns.

During early customer interactions, when the product’s relevance to a marketing context was presented too abstractly, it often resulted in confusion. Therefore, shifting the focus towards describing what the product did, rather than its implications, seemed more effective. That’s when users from the data world started comparing the tool to existing ones, like FiveTran and Stitch, but in reverse.

Though this comparison seemed overly simplistic, it did help customers understand the flow of data. Soon, the term ‘Reverse ETL’ began circulating among data teams, first appearing in a Notion document someone had shared about intriguing tools.

The term’s widespread use, however, didn’t truly take off until it was picked up and propagated by venture capitalists via industry thought pieces. Given the excitement for the product was primarily born out of data teams, the term ‘Reverse ETL’ quickly became synonymous with the new category of tools designed to empower marketing teams with better data.

Regardless of its etymology, the term ‘Reverse ETL’ is less about who coined it and more about what it represents – the technical means for providing marketers with a higher degree of customer targeting and personalization. It has helped establish a clear and efficient route to manage data across multiple platforms.

Despite its widespread acceptance, it’s important to remember that the primary aim of ‘Reverse ETL’ is not the technology itself, but its capacity to facilitate marketers to tailor their campaigns more effectively. As the number of data destinations increases, maintaining the efficiency of these operations can be a challenge. By successfully bridging this gap, ‘Reverse ETL’ helps marketers personalize their approach, leading to improved customer experiences and less ‘Dear unknown’ type of communications.

Takeaway: Despite its technical roots, the essence of ‘Reverse ETL’ is not about the technology, but its ability to empower marketers with better data, facilitating more effective and personalized campaigns. As the landscape of data destinations expands, ‘Reverse ETL’ ensures efficiency, bridging the gap between data and its application, ultimately refining customer experiences.

The Role of Reverse ETL Tools in the CDP Landscape: Enhancing Data Activation, Not Replacing Legacy Systems

The terms ‘Reverse ETL’ and ‘Data Activation’ often go hand in hand, especially when it comes to technical marketers and DevOps teams. In the world of data flow, these teams often use ETL workflows to understand and map out how data moves around. Therefore, when they require a tool that helps them get data from the warehouse to other areas, the phrase ‘Reverse ETL’ resonates quite effectively.

There are critics of the composable route for Customer Data Platforms (CDPs) who argue that the discussion is rooted in an attempt to repackage Reverse ETL tools in a way that appeals to marketers but ends up causing confusion. Some vendors of Reverse ETL tools claim their solutions can replace a legacy or packaged CDP, which can potentially mislead marketers.

At Census, they neither replace a traditional CDP nor claim to do so. In fact, many of their customers have been using Census in combination with a CDP for years. They adopt a philosophy of composability – building tools that integrate seamlessly with others, providing users with more trustworthy data in more places without adding complexity or creating new data silos.

In the discussion around composability, a crucial point is that it allows the user, whether that’s a marketer or a data team, to work with the data seamlessly. In the software world, composability is a well-accepted principle – savvy engineers design their software not to break when combined with other software.

If your organization has a tool that does identity resolution, whether that’s a CDP or another tool, then they aim to make it seamless for you to use that in tandem with Census. Their goal is to benefit everyone, not just the marketing team.

The sales team, finance team, privacy and compliance team – they all need access to that identity resolution too. Therefore, our philosophy of composability is not about Census versus CDPs but about creating a more connected, efficient and user-friendly data environment.

Takeaway: Rather than being positioned as a direct replacement for traditional Customer Data Platforms (CDPs), Census stands as an advocate for a seamlessly integrated data environment. Embracing composability, it facilitates the amalgamation of data tools, extending the benefits not only to marketing but also sales, finance, and compliance teams. This isn’t a case of Census vs CDPs—it’s about creating a holistic, efficient, and user-friendly data ecosystem that enhances the data utility across an organization.

Could Warehouse-Native Tools Eliminate the Need for Data Pipelines?

Let’s step into the fascinating world of warehouse-native tools, where conversations often teeter on the edge of existential questions like “Do we even need data pipelines?” This isn’t about futurology. This is about the data landscape we’re navigating today, and the possible turns it could take tomorrow.

The term ‘warehouse-native’ may have recently entered the tech vernacular, but Boris has been living it through his work with Census, an enterprise that prides itself on its warehouse-native DNA.

The proposition Boris put forth is as audacious as it is appealing. In an ideal world, customer engagement platforms would sit natively on top of data warehouses, rendering separate data pipeline solutions redundant.

“Wouldn’t that be fantastic?” he pondered, adding that it would essentially mean less data duplication and greater consistency – the holy grail for data practitioners. But the pragmatic part of him warned against prematurely packing away your data pipeline toolkits. 

Census, which began its life as a warehouse-native solution before it was cool, is a testament to Boris’s extensive experience in this arena. The product natively connects to data warehouses and activates your data, enabling marketers to employ it in customer engagement platforms. In essence, Census is what you might call a ‘translator’, morphing complex datasets into comprehensible, actionable insights for marketers.

But the challenge doesn’t end at merely connecting. Boris highlighted the fundamental prerequisite for this system to operate seamlessly – “you need perfect data in your warehouse to begin with.”

Here’s where things get tricky. Warehouses are optimized for storing tables of data. Yet, platforms like Marketo don’t operate on tables of data; they work with users, contacts or similar entities. So, a considerable part of Census’s work revolves around shaping the data into a usable form for these platforms.

Boris candidly admitted, “I think the need for data pipelines will reduce over time, and that will be a great day. I don’t care about data pipelines. But it’s like the same way Apple doesn’t really try to talk about the megahertz or whatever, it’s like, what is the thing you can do?”

Looking to the future, Boris envisions an ecosystem where every application acts as a “lightweight cache on the core data warehouse.” While that day may not be here yet, there’s no denying we’re steadily moving towards it.

So, next time you find yourself pondering the relevance of your data pipeline solution, remember Boris’s words. We may not be ready to discard them just yet, but the tide is certainly turning.

Takeaway: In the realm of warehouse-native tools, the concept of customer engagement platforms sitting directly atop data warehouses is both bold and enticing. It paints a picture of reduced data duplication and improved consistency. However, this vision requires flawless initial data. While the relevance of data pipelines persists, Census, a leader in warehouse-native solutions, translates intricate datasets into digestible insights. We’re on a journey where data pipelines might become obsolete, but we’re not quite there yet. The wind is indeed shifting in favor of warehouse-native solutions.

Navigating the AI Labyrinth: The Path to Replacing Marketers

Artificial Intelligence (AI) is a game changer for every industry, including marketing. While some sectors have been quick to adopt and reap its benefits, there are challenges that need to be overcome for AI to fully replace human marketers. We’ve been deep down the rabbit hole on AI, we recently did a 4 part series that covered a few AI topics including how to parse out the gimmicky AI tools from the valuable tools marketers should be trying. 

We talked about things like predictive analytics and propensity models. And we also talked about How fast could AI change or replace marketing jobs

AI has long been a silent partner, behind the scenes, helping marketers place their advertisements strategically on Google and Facebook. By augmenting content generation and fueling these platforms with an increased quantity of options, AI has significantly enhanced efficiency. Those who aren’t utilizing AI in this aspect of marketing are falling behind in the race.

However, despite its numerous advantages, AI’s journey towards replacing human marketers isn’t a smooth sail. Boris’s take is that the critical challenge lies in our ability to trust AI. The data AI uses and generates can be a double-edged sword. It’s hard enough to trust raw data, and AI adds another layer of complexity by making its results subject to its interpretation or, in some cases, its “hallucination.”

For instance, when addressing critical customer queries or dealing with sensitive issues such as ADA compliance, you wouldn’t want AI to provide “hallucinated” answers. It’s crucial to restrict and guide these systems, ensuring they deliver correct and safe responses.

There’s no doubt that smaller companies, driven by the thrill of innovation, might dive headfirst into using AI. Yet, larger enterprises may proceed with caution, driven by the need to maintain data trust and correctness. This presents a golden opportunity for solutions that can help marketers harness the power of AI without compromising on data integrity and reliability.

While the notion of AI replacing marketers seems harsh, the future of marketing lies in the balance between automation and human expertise. Marketers who aren’t engaging with AI in one form or another are on a risky path. Therefore, embracing AI, yet maintaining a keen eye on data trustworthiness, is a delicate but necessary dance in today’s marketing world.

Takeaway: The fear is not AI’s potential to replace marketers, but rather the integrity and reliability of the data it uses and produces. Despite this, the balance between automation and human expertise will shape the future of marketing. And in this dance, avoiding AI isn’t an option – mastering the harmony of embracing AI while preserving data trustworthiness is the performance every marketer needs to ace.

The Secret to Balancing Success and Happiness: People First

In the fast-paced world of entrepreneurship, it’s easy to lose sight of what truly matters. But not for Boris Jabes, co-founder, CEO, investor, speaker, podcaster, and sports enthusiast. He’s a man who wears many hats, and yet, he seems to have found the secret to maintaining happiness and success amidst a sea of responsibilities.

The answer, it turns out, is quite simple and deeply human – it’s all about the people you surround yourself with. According to Boris, the people in your life, whether they’re coworkers, friends, or your spouse, have the capacity to uplift you. The power of a supportive network should not be underestimated; it’s these connections that energize him and push him to achieve more, all while keeping him grounded.

When he walks into his office, it isn’t a sense of duty that keeps him motivated, but the anticipation of being around those he respects and admires. These relationships offer more than just professional advantages – they fuel his drive, provide emotional support, and ultimately, make his career journey enjoyable and fulfilling.

In Boris’s perspective, success doesn’t exist in a vacuum. It’s cultivated through meaningful relationships, camaraderie, and shared experiences. So, while many are still seeking work-life balance, Boris has found his equilibrium in the people he surrounds himself with. It’s a thought-provoking approach, one that truly highlights the importance of nurturing relationships in the pursuit of a happy and successful career.

Takeaway: In the dynamic arena of entrepreneurship, Boris, a man of many roles, reminds us of a simple yet profound truth: success and happiness are people-oriented endeavors. It’s not about balancing work and life, but rather weaving them into a rich tapestry of connections. Those you respect, admire, and share experiences with don’t just offer professional growth but fuel emotional vigor. In essence, the secret sauce of thriving in this whirlwind venture is not the pursuit of work-life balance, but fostering relationships that interweave personal fulfillment and professional ambition into a gratifying whole.

Strengthening Bonds: Bridging Marketers and Data Teams

In the vast, intricate world of marketing, Census is constantly innovating. They are on a mission to redefine the relationships between data teams and marketers, to create a more harmonious, efficient, and fruitful collaboration. In an ever-evolving ecosystem, their primary focus remains on understanding the nuances of data teams, their aspirations, their challenges, and how we can bridge the gap for better synergy. 

One of the unique aspects of Census is its dedication to improving collaboration. To make this possible, they are on the brink of launching a set of features aimed at reducing the burden on the engineering teams, making it less of a colossal task to manage. Their goal? To help those who have experienced frustration and feel cornered by the overwhelming demand of data management. 

On a personal note, as the CEO, Boris is always open for discussion, and eagerly awaits your queries, suggestions, and insights. Despite the company’s growth, the communication lines remain wide open. So, reach out, connect, and unravel the complexities of data management and marketing together.

Census’s visual Audience Hub empowers marketers to unify, segment, and activate audiences with the 360° customer data in the warehouse. We’re more than excited about their ongoing community survey for data professionals, so stay tuned for the results!. At Census, they believe in the strength of connections, not just between data and marketing teams, but also with their users. Because ultimately, we’re all in this together, shaping a more dynamic, responsive, and effective marketing landscape.

Takeaway: Census is on a mission to improve synergy between data teams and marketers. They’re launching features to ease data management burdens, fostering a more efficient collaboration. They maintain open lines of communication, eager for community input. Key highlights: their Audience Hub and a community survey, demonstrating their commitment to connectivity. Watch this space as Census continues to shape a more dynamic, responsive marketing landscape.

Episode Recap

In this episode, Boris opened a window into the dynamic world of martech, revealing the pivotal shift from traditional Customer Data Platforms (CDPs) to flexible, composable solutions. We’re embracing Composable CDPs, a collection of efficient tools designed to streamline data management, and marking the dawn of a new era where marketers can tailor data-centric solutions to their unique needs. Exemplifying this trend, Census connects directly to existing data warehouses, diminishing data redundancy and enhancing adaptability.

Boris also navigates us through the complex dance between data and marketing teams, underlining the critical importance of synergy for effective tool utilization. And let’s not forget ‘Reverse ETL’. Despite its techie roots, it’s an empowering force for marketers, bridging the gap between raw data and its application, paving the way for personalized campaigns. Amid these seismic changes, the elephant in the room is AI. But the goal isn’t to dodge AI; it’s about mastering the blend of AI and human expertise, ensuring data reliability while pushing marketing to new frontiers.

Listen to the full episode now.

And don’t forget to follow Boris and Census:


Intro music by Wowa via Unminus
Cover art created with Midjourney

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