The Broken World of Third-Party Data: A Call for First-Party Data Leadership

Solving the One-Size-Fits-All Approach: Crafting Relevance in a Sea of Data

Introduction: Hey there, data enthusiasts! In my previous post, we explored the economics of customer data. Today, we're diving deeper into the messy world of third-party data (3PD) and why it's crucial to prioritize first-party data (1PD) in our data strategies.

Background: The Promise of Data-Driven Insights

We've all heard the hype: data is the new oil, the secret sauce for business revolution. There's truth to that, but with a crucial caveat. The real value of customer data emerges when you have a complete, easily unified picture from various third-party sources, tailored to your needs. This contrasts sharply with the current broken, one-size-fits-all approach to data sets.

Data marketplaces initially emerged to support database-driven marketing, Customer 360 pursuits and, subsequently, to feed data-hungry models and AI. While data marketers have been buying and renting 3P data for marketing purposes, data scientists and analysts increasingly seek this data to build models, especially when internal data is insufficient.

Recognizing this need, modern data platforms like Snowflake, Databricks, and even Customer Data Platforms (CDPs) and Master Data Management (MDM) systems have launched marketplaces. These aim to integrate hundreds of 3P data providers on a self-service basis.

When used effectively, data can transform customer understanding, optimize operations, and drive competition. However, not all data is equally valuable to every business. The subjective value of your customer data increases dramatically when you can seamlessly integrate relevant third-party data with your first-party data, enhancing insights rather than adding to governance chaos.

Unfortunately, the current third-party data landscape often complicates rather than clarifies. The true promise of data-driven insights lies not in more data, but in having the right data, properly integrated within your unique business context. This realization calls for a critical examination of current practices and a shift in our approach to both first-party and third-party data augmentation.

The Problem: An Antiquated Data Buying Process In 2024, you'd think acquiring 3PD would be as simple as ordering a latte on your phone. Unfortunately, it's not. In fact, it's even more challenging than buying ads was in the early 2000s. No dearth of volume again, 3rd party data vendors are all around us. There are over 300k data providers in the US alone.

Source: Author

So let's break down the issues:

1. Discovery Challenges

   • Awareness Gap: Many businesses are unaware of how 3PD could benefit them.

   • Limited Creativity: Finding innovative data sources requires out-of-the-box thinking.

   • Inadequate Search Tools: Data marketplaces often have outdated search functionalities.

   • Schema Complexity: Understanding data structures often requires specialized expertise.

2. Procurement Hurdles

   • Non-Standardized Buying Process: Purchasing 3PD is more akin to haggling at a bazaar than a straightforward transaction.

   • Licensing Maze: Navigating data licenses is complex and often confusing.

   • Multiple Contracts: Dealing with various providers complicates the procurement process.

3. Integration Nightmares

   • Engineering Bottlenecks: Integrating new data with existing systems is often resource-intensive.

   • Utility Uncertainty: The usefulness of data is often unclear until after purchase and integration.

   • Operational Challenges: Synchronizing data that updates at different frequencies creates ongoing issues.

A Path Forward: First-Party Data Foundation with Strategic 3PD Integration While many enterprises are working towards better data management through Customer Data Platforms (CDPs), Master Data Management (MDM), and data platforms, the integration of 3PD remains problematic. Here's a strategic approach to address these challenges:

1. Prioritize Your 1PD Strategy

   • Invest in collecting, organizing, and analyzing your own customer data.

   • Implement robust data governance practices including ID Management to ensure deduplication, data quality and compliance.

   • Example: Retail/CPG company launched verified ID system to unify data of each customer who has ever interacted with them

2. Use 3PD Strategically

   • Identify specific gaps in your 1PD and use 3PD to fill them.

   • Regularly assess the value and accuracy of your 3PD sources.

   • Example: B2B company used a waterfall enrichment company to buy all third party data instead of directly buying from data vendors

3. Demand Better from Data Providers

   • Push for standardization in data formats and delivery methods.

   • Seek providers who offer transparent data lineage and quality metrics.

   • Negotiate flexible contracts that allow for data testing before full commitment.

4. Invest in Data Literacy

   • Develop training programs to improve data understanding across your organization.

   • Create clear data dictionaries and semantic models for each team.

   • Foster a culture of data-driven decision-making at all levels.

5. Consider Data Intermediaries not brokers but tech solutions

   • Explore partnerships with companies that can aggregate and vet 3PD sources.

   • Look for intermediaries who can provide value-based pricing and quality comparisons. Including waterfall enrichment but own data quality.

Learning from the Advertising Industry The evolution of the advertising industry over the past two decades offers valuable lessons for the data world. From the rise of Demand-Side Platforms (DSPs) and Supply-Side Platforms (SSPs) to the shift towards cookieless approaches, we can draw parallels to the current state of the data industry.

Key Challenges to Address:

1. Commercial Challenges:

   • Standardizing data licensing practices

   • Developing fair and transparent pricing models

   • Balancing the interests of data marketplaces and buyers

2. Technical Hurdles:

   • Improving semantic type detection and data discovery

   • Enhancing data joining and field-level extraction capabilities

   • Implementing secure data sharing methods (e.g., federated learning)

The Road Ahead: Embracing a New Data Paradigm The current state of 3PD and data marketplaces presents significant challenges, but it also offers tremendous opportunities for innovation. By focusing on building a robust 1PD foundation and strategically integrating high-quality 3PD, we can create a data ecosystem that drives true business value.

As an industry, we must collaborate to tackle these challenges head-on. Recent AI breakthroughs provide us with powerful tools to revolutionize data management and utilization. The future of data-driven decision-making is bright, and it's up to us to shape it and own, maintain our persistent customer intelligence.

Call to Action: Are you ready to be part of this data revolution? Share your thoughts and experiences in the comments below. How is your organization navigating the complexities of 1PD and 3PD integration?

Stay tuned for my next post in this 3 part series, where i will explore the evolution from Customer 360 to Customer Observability and its impact on the industry.

Thanks for reading!