The Shifting Landscape of Customer Data Platforms: Can't See the Wood for the Trees
In the ever-evolving world of marketing technology, few solutions have garnered as much attention and investment as Customer Data Platforms (CDPs). Once hailed as the panacea for all customer data woes, today's reality paints a different picture. While the promise of CDPs remains undeniable, their actual impact often falls short of expectations. As the dust settles on the hype, it's crucial to understand the current state of CDPs and chart a strategic path forward.
Where is my ROI?
First and foremost, it's evident that many organisations are grappling with the gap between expectation and reality when it comes to CDPs. Despite significant investments and widespread adoption, Gartner's recent Magic Quadrant report for CDPs revealed a sobering truth: only a fraction of marketers report high utilisation of their CDP platforms. While 67% of respondents to Gartner's marketing technology survey reported having onboarded a CDP, only 17% of marketers indicated high utilisation. This discrepancy underscores a fundamental disconnect between the perceived value of CDPs and their actual impact on marketing operations.
From experiences working with many clients, I see 5 common factors contributing to CDP implementation failures:
1. Attempting to do too much at once: Overambitious implementation plans often lead to spreading resources too thin and diluting focus. Trying to tackle multiple activation cases, data sources, audiences, and events simultaneously can overwhelm teams and hinder progress.
2. Lack of cross-department buy-in: Successful CDP implementation requires collaboration and buy-in from multiple departments, including IT, analytics, marketing, and finance. Without alignment across these functions, achieving consensus on goals, priorities, and implementation strategies becomes challenging.
3. Poor data quality: Data quality issues can significantly impact the effectiveness of a CDP. You all know the mantra: garbage in, garbage out. Prioritising data hygiene and quality assurance is crucial before integrating data into the CDP.
4. Complex requirements and processes: Complexity in requirements and processes can impede the smooth integration and utilisation of the CDP. Attempting to force-fit existing dysfunctional processes into the new CDP framework often leads to inefficiencies and suboptimal outcomes. Adapting processes to align with the capabilities of the CDP is essential for success.
5. Lack of internal training: CDPs are complex tools that require extensive internal education and training.
Why hasn’t MS Excel announced its CDP product yet?
Moreover, the CDP market itself is in a state of flux. With market consolidation and the emergence of cloud data infrastructure providers, standalone CDPs face increasing challenges in delivering differentiated value. As mega-vendors like Salesforce, Adobe, and Oracle bolster their offerings and cloud providers centralise data management services, the competitive landscape for CDPs is undergoing significant transformation.
Adding to this complexity, some vendors are generating hype around concepts such as composable CDPs and lakehouse CDPs. These vendors often rebrand themselves with these trendy terms, primarily for marketing purposes and to create a sense of urgency and fear of missing out (FOMO) among potential buyers. Almost all vendors have added an AI layer on top of their CDP, usually in a black box, making it unclear what exactly happens and how. This increases the complexity of making the right choice, as many vendors are still trying to determine where AI can truly make a difference.
While these new terms may sound innovative, they often serve more to repackage existing capabilities rather than deliver genuinely transformative solutions. As Timo Dechau aptly remarked, "Why hasn’t MS Excel announced its CDP product yet?" In his post 'Everyone is a CDP now,' he highlights the absurdity of the current landscape where every email tool, ETL tool, and even analytics tool proclaims itself to be a CDP. This marketing-driven nomenclature can further confuse organisations already struggling to realise the value of their CDP investments.
However, amidst these challenges, the importance of CDPs in enhancing customer experiences across channels cannot be overstated. At their core, CDPs play a pivotal role in identifying customers across touchpoints and enabling personalised interactions at scale. By unifying customer data from disparate sources and delivering actionable insights, CDPs empower marketers to create seamless experiences that drive engagement and loyalty. In an era where customer expectations are higher than ever, leveraging the full potential of CDPs is imperative for staying competitive in the market.
Start small and grow
In light of these dynamics, exploring innovative approaches to CDP adoption becomes increasingly essential. Starting with a "CDP light" (or the “CDP as a Service” by MultiMinds) approach seems to resonate with the need for a clearer value proposition and a more tangible return on data. This approach prioritises delivering immediate value while laying the groundwork for future scalability and expansion. By focusing on addressing specific use cases or pain points and gradually expanding capabilities as needed, organisations can better align their CDP initiatives with their strategic objectives and drive tangible outcomes.
In conclusion, while the current state of CDPs may not fully meet expectations, the journey is far from over. As the market continues to evolve and new challenges emerge, strategic adaptation is key to unlocking the true potential of CDPs. By embracing innovative approaches, organisations can navigate the complexities of the modern marketing landscape and harness the power of customer data to drive meaningful business outcomes.
I would personally recommend you take three actions to ensure success with your CDP project:
1. Set the right expectations: Align stakeholders on the primary goals and objectives of the CDP project, considering the organisation's unique strategy and goals. Clearly define the scope, measurable outcomes, and success criteria to ensure alignment and manage expectations effectively.
2. Choose the right approach: Take a thoughtful approach to selecting the implementation strategy for the CDP project. Consider a mix of use-case-driven and foundational MVP approaches, focusing on enabling capabilities that align. It's better to start small and grow your maturity.
3. Design a Target Operating Model (TOM): Design a robust operating model for managing and leveraging the CDP effectively. Define clear processes, roles, and responsibilities for data management, governance, and utilisation, ensuring alignment across departments and stakeholders.