In today’s fast-paced digital landscape, understanding and utilizing customer data is crucial for businesses. A Customer Data Platform (CDP) plays a pivotal role in achieving this, by unifying customer data from multiple sources to provide a comprehensive view of the customer journey. While the temptation to build a custom CDP might exist, particularly for companies with strong technical teams, this approach is often fraught with challenges. Instead, leveraging open-source CDP solutions can often be a more effective strategy. Here are three compelling reasons why building your own CDP might not be the best decision:

What is Customer Data Platform

A Customer Data Platform (CDP) represents a critical asset in the business technology stack, enabling organizations to centralize, understand, and activate customer data efficiently, by collecting behavioral and non-behavioral data from different sources. As businesses strive to build a Customer Data Platform, they leverage this powerful database software to assimilate first-party data (leaving third-party data behind)) from an array of sources, ensuring a holistic 360-degree view of customer profiles.

For enterprises committed to enhancing data management and data quality, the CDP stands out as an essential tool. Unlike a traditional data warehouse, a CDP is designed specifically for marketing data management, focusing on collecting, cleaning, and consolidating customer-centric information into actionable unified profiles. This process of data collection is critical for creating a unified customer database that prevent data silos,  supports advanced data management practices and adheres to stringent data compliance standards.

Building your own platform

Building a Customer Data Platform involves a meticulous approach to integrating disparate first-party customer data, and employing robust management strategies. The goal is to develop a comprehensive view of the customer by merging information from diverse data sources, including transaction records, offline data, customer service interactions, and digital engagement metrics. 

A well-architected CDP not only serves as a customer management platform but also empowers organizations to maintain data compliance, data consistency, etc. By centralizing data, businesses can achieve a single source of truth for customer information, enabling more effective and targeted marketing strategies, and improve customer experience.

Furthermore, the strategic integration of a Customer Data Platform within the business infrastructure facilitates the enrichment of customer profiles. This enrichment process is vital for enhancing data quality and ensuring that the data management platform supports real-time decision-making and predictive analytics.

Steps of Building a CDP

Building a Customer Data Platform (CDP) is a strategic process aimed at centralizing real-time customer data to give businesses a detailed understanding of their customers. This comprehensive approach enhances both customer insights and engagement. Below is a structured method for developing a CDP, along with its core elements:

1. Data Collection and Integration

Objective: Bring together all customer data into a unified database with unique customer profiles, creating this way a single customer view from various touchpoints and data sources.

Process: Tackle the issue of fragmented data by connecting different sources and systems, ensuring all customer information is centralized. This includes data from both online and offline channels, offline sources, CRM systems, social media interactions, transaction records, and more.

2. Data Organization

Objective: Apply quality control measures to prepare data for analysis.

Process: After integrating the data, cleanse it to correct or remove inaccuracies, delete duplicates, and verify completeness. This crucial step enables accurate customer segmentation and a deeper understanding of their behaviors and preferences.

3. Identity Resolution

Objective: Attribute data from various sources to individual customers to create unified customer profiles.

Process: Achieve data unification by linking disparate data to specific customer profiles. This grants a holistic view of each customer’s interactions with the business across multiple touch points.

4. Customer Segmentation and Activation

Objective: Utilize the CDP’s ability to segment customers based on distinct attributes and behaviors for enhanced marketing personalization and targeting.

Process: Employ AI and machine learning to generate dynamic customer segments. Predictive scoring enriches customer profiles, providing marketing teams with detailed insights for developing targeted audience strategies. The CDP’s segmentation tools also enable identification of brand advocates, prediction of customer churn, discovery of cross-sell and upsell opportunities, orchestration of the customer journey, and delivery of personalized recommendations. Integrating Business Intelligence (BI) and data analytics tools into the CDP augments the capacity to analyze, understand, and act on customer data, facilitating informed strategic decisions.

5. Data Availability

Objective: Ensure seamless data sharing with external service providers, such as marketing platforms, Customer Relationship Management (CRM) platforms, customer support systems, and customer engagement platforms.

Process: This involves data orchestration, standardizing and transforming data for easy accessibility and use by external systems. Data orchestration enables a smooth exchange of information between the CDP and other tools, promoting a cohesive approach to managing customer data across different platforms. Making data available in a structured, standardized format allows external services to effectively leverage CDP insights, thus enhancing marketing efforts, customer service, and overall engagement tactics.

Benefits of Customer Data Platform

Customer Data Platforms (CDPs) offer significant advantages to marketing teams and businesses, centralizing and enhancing the understanding of customer data for customer engagement strategies. Key benefits include the creation of unified customer profiles from diverse sources, eliminating data silos for a comprehensive view of customer interactions. This unified view aids in delivering highly personalized experiences,  bigger customer loyalty, aand increasing engagement. Moreover, CDPs ensure data privacy compliance while optimizing data usage for increased revenue through tailored marketing efforts. They also improve omnichannel customer experiences by utilizing data from every interaction point, thus increasing overall efficiency and customer satisfaction. Additionally, CDPs are versatile, catering to both B2C and B2B marketing needs with a single platform. These platforms not only streamline data management but also empower businesses to act on real-time insights, significantly enhancing customer experiences and driving business growth.

Why building custom CDP from scratch may be a not solution.

Diversion from Core Business Focus

When companies seek a CDP, they are generally looking to solve specific problems: a lack of comprehensive customer understanding, a need for personalized customer journeys, and a desire to utilize customer data for better engagement. Building a custom CDP, however, is analogous to starting a bus company for a single trip to visit your parents – it’s a massive investment in an area that is not your core business.

Time and Effort Misallocation

Developing a CDP requires a significant investment of time and resources, which could be better spent on your primary business activities. The development process involves solving numerous challenges unrelated to your core goals, which can divert attention and resources away from customer activation and engagement strategies.

Financial Implications

The cost of developing a high-quality CDP is often underestimated. Initial perceptions may suggest that creating a CDP is not excessively expensive or time-consuming. However, the reality is quite different.

High Development Costs

Developing a functional CDP can cost anywhere from $300,000 to $1 million in programming fees alone. Stopping at the lower end of this budget range often results in a product that doesn’t fully meet your needs. In contrast, commercial fees for open-source solutions, which offer customization and extendibility, are significantly more economical. For instance, running a commercial open-source system like Tracardi for 25 to 50 years could be much more cost-effective than building a custom solution.

Technical Challenges

On the surface, coding a CDP might seem straightforward, but the reality is far more complex.

Scalability and Robustness

A CDP quickly becomes central to a business, particularly in the era of big data and AI. It needs to handle potentially billions of events annually, even for small businesses. Creating a system capable of this scalability is a monumental task. Established vendors have already navigated these challenges, ensuring their solutions are robust and reliable.

Technical Complexities

• Distributed Systems: Handling large amounts of data from diverse sources in various data formats, and mobile apps requires a sophisticated distributed system.
• Profile Merging: This involves challenges like handling locks, unique profile identifiers, resolving merge errors, managing inconsistencies, and dealing with latency and out-of-order profile stitching.
• Maintenance and Data Integrity: An error in a custom-built platform can lead to corrupted customer data, posing a significant risk to business operations.

Why not SAAS Solution

Opting for a SaaS solution for a Customer Data Platform (CDP) can seem appealing at first due to its convenience and the speed at which it can be deployed. However, there are several considerations that suggest it may not be the most advantageous choice for businesses in the long run.

Vendor Lock-In

One significant concern with SaaS CDP solutions is the risk of vendor lock-in. This happens when a business becomes overly dependent on a single vendor’s technologies and services, making it difficult and costly to switch to another provider in the future. Over time, companies might find that their SaaS CDP doesn’t adapt well to evolving business needs or technological advancements, yet migrating to a new platform could entail significant disruption and expense.

Cost Concerns

While SaaS solutions often have the allure of lower initial costs and quick setup times, they can become financially burdensome over the long term. Subscription fees can accumulate, and as a business grows, the cost of scaling the SaaS solution to match increasing data volumes or to integrate with new data sources can become prohibitive.

Data Regulation Compliance

The legal landscape surrounding data privacy and protection is continually evolving, with regulations increasingly shifting the responsibility for customer data security back to the data owners themselves. Laws such as the General Data Protection Regulation (GDPR) in the European Union place strict limitations on how customer data can be processed and where it can be stored. Relying on a SaaS CDP might complicate compliance with these regulations, as businesses have less control over how their data is managed and protected on external servers. This could lead to situations where companies are forced to repatriate their customer data to their own systems to ensure compliance, rendering their investment in a SaaS solution effectively wasted.

Long-Term Strategic Flexibility

Investing in a SaaS CDP solution might limit a company’s strategic flexibility. As businesses evolve, their data management needs can change dramatically. A SaaS solution that seemed adequate at one point may become a constraint, unable to accommodate new data types, sources, or analytical capabilities required by the company. Additionally, integrating a SaaS CDP with other business systems can introduce complexities and inefficiencies that hinder rather than help operational agility.

Comparison with Open-Source Solutions

In the scenario of comparing Customer Data Platforms (CDPs), open-source solutions present several compelling advantages over their proprietary, Software as a Service (SaaS) counterparts, particularly in terms of cost, customization, and flexibility.

1. Cost-effectiveness: Open-source CDPs typically have a lower total cost of ownership than SaaS solutions, which often charge based on the volume of data collected or the number of data points processed. This makes open-source CDPs more accessible for businesses of all sizes, especially for those with large volumes of data who wish to avoid the steep costs associated with data collection and processing in SaaS models.
2. Customization and Control: With their customizable nature, open-source CDPs allow businesses to tailor the platform to their specific needs without being constrained by the features and limitations of a proprietary system. This flexibility ensures that the platform can evolve alongside the business, incorporating new technologies or adapting to changing market demands more seamlessly than might be possible with a SaaS solution.
3. Avoidance of Vendor Lock-in: One of the critical benefits of open-source CDPs is the prevention of vendor lock-in. Businesses are not tied to a single provider’s roadmap, pricing structure, or technological ecosystem. This freedom enables companies to switch providers or modify their solutions as needed without significant disruptions to their operations or costly migrations.
4. API-First Approach and Composability: Open-source CDPs, particularly those designed with an API-first approach, facilitate easy integration with existing systems and enable the composition of a customized tech stack. This approach allows businesses to leverage best-of-breed solutions and ensures that their CDP can work seamlessly with other tools, enhancing the overall utility of their technology investments.
5. Accessibility and Community Support: The open-source nature of these CDPs means that businesses have access to a broad community of developers and users who contribute to the software’s continuous improvement. This community can offer support, share best practices, and provide custom solutions to unique challenges, enhancing the platform’s value beyond what a proprietary vendor might offer.

Conclusion

In essence, developing a custom CDP diverts valuable resources from a company’s core business, incurs significant financial and time costs, and presents complex technical challenges. Open-source solutions offer a more viable, cost-effective, and lower-risk alternative, allowing businesses to leverage the power of a CDP without the pitfalls of developing one in-house. The focus should remain on utilizing a CDP to enhance customer understanding and engagement, rather than getting entangled in the intricacies of building and maintaining one.