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Navigating the Challenges of DSPs and Data Marketplaces - Part 1

#DaaS-CEOs Digital Round Table

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World of DaaS
September 04, 2024


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The World of DaaS #daas-ceos Slack channel brought together over a dozen execs from leading data companies to address pressing issues surrounding the sale of data to Demand-Side Platforms (DSPs) and data stores. The conversation centered on ensuring data liquidity while safeguarding the value of premium data, a task that grows increasingly complex as DSPs expand their offerings and capabilities.

The Commoditization Conundrum

One of the primary concerns voiced by participants was the commoditization of premium data by DSPs. Several CEOs shared experiences of DSPs replicating and undercutting their unique data segments. One participant lamented, "The DSP was happy to take literally the exact taxonomy we created, branded, and replace it with their own." This practice not only erodes the perceived value of premium data offerings but also creates a race to the bottom in terms of pricing.

The issue is further complicated by DSPs' mission to drive down CPMs (Cost Per Mille) for advertisers. As one CEO noted, "DSPs have a mission to drive CPMs down, which often puts us in their crosshairs from a pricing perspective." This focus on cost reduction often comes at the expense of data quality and uniqueness.

Technical and Operational Challenges

The integration and management of data across various platforms and marketplaces present significant challenges for data companies. One participant highlighted the resource-intensive nature of this process: "The engineering effort, the KTLO (Keep The Lights On) effort, the constant need to adjust schemas—it's a significant overhead."

Moreover, the lack of standardization across data companies in terms of ID graphs and schema construction adds another layer of complexity. This inconsistency makes it difficult for buyers to compare and evaluate different data offerings effectively.

Pricing Strategies and Auditing

The roundtable discussion revealed diverse approaches to pricing and auditing. Some companies struggle with the toggle between CPM and percentage of media pricing models. As one CEO explained, "We don't find in our space generally that the percent of media is very accepted. People are so used to CPMs or comfortable CPMs."

Auditing and verifying usage on major DSP platforms remains a challenge for many data companies. While some rely on internal DSPs as a source of truth, others use year-over-year and month-over-month comparisons to identify anomalies in revenue reports - though discrepancies are hard to rectify.

Proposed Solutions and Strategies

1. Data Alliances and Standardization

Several participants proposed the idea of forming alliances or consortia among data companies to establish common standards.The concept of a "trust registry" or accreditation body was also discussed as a potential solution to help data companies compete with the power of large platforms.

2. Leveraging Unique Data Attributes

To combat commoditization, data companies are encouraged to focus on creating unique data sets that are difficult for DSPs to replicate. This could involve adding digital signatures or cryptographic proofs to establish provenance and uniqueness.

3. Exploring Alternative Platforms

The potential for non-DSP-centric platforms was discussed as a way to prioritize data quality and provider interests. However, some participants cautioned against relying on a single platform, advocating instead for a more diversified approach.

4. Direct Customer Relationships

Some CEOs emphasized the importance of maintaining direct relationships with customers. As one participant noted, "The value is having your data integrated directly into where the actual consumption happens. From an analytical perspective, data is not something that's discoverable in a purely packaged form."

Next Steps

The roundtable concluded with a consensus on the need for continued collaboration among data companies. Participants expressed interest in organizing further discussions to explore the formation of a consortium or working group to address the challenges identified.

Key action items include:

  1. Establishing a common way to benchmark reach and coverage for data assets.

  2. Prioritizing and ranking the pain points identified during the discussion.

  3. Exploring the formation of a data alliance or consortium.

  4. Investigating technological solutions that could facilitate standardization without compromising proprietary data.

In the words of one participant, "We've definitely got another conversation of folks like-minded, figuring out how we align interests."

Stay tuned for part 2!

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