IDC

Region Focus: Worldwide

Data Clean Room Technology
for Advertising and Marketing Use Cases 2023–2024 Vendor Assessment

December 2023 | us51047323e
Lynne Schneider

Lynne Schneider

Research Director, Data as a Service & Location and Geospatial Intelligence

Product Type:
IDC: MarketScape
This Excerpt Features: Habu, recently acquired by LiveRamp

IDC MarketScape: Worldwide Data Clean Room Technology 
for Advertising and Marketing Use Cases 2023–2024 
Vendor Assessment

Capabilities Strategies Participants Contenders Major Players Leaders

Leaders

Epsilon

HabuFeatured Vendor

LiveRamp

AppsFlyer

Major Players

Acxiom

Amazon Web Services

Decentriq

InfoSum

Snowflake

TransUnion

Optable

IDC MarketScape Methodology

IDC Opinion

Data clean rooms mean many different things to many different people. The concept — that there should be a privacy-protected environment where multiple parties in the advertising, marketing, and customer experience realm can come together to safely collaborate with their customers and property-derived data — is not new. What is new is:

  • The burning platform — prior ways of identifying web, app, phone, and physical traffic that are being replaced
  • Replacement of trusted intermediary with trusted technology solution
  • Utilizing technology to replace a trust-but-verify audit motion when it comes to the use of personally identifiable or sensitive data

Enterprises want to engage in data sharing but need special technologies to protect privacy and trade secrets and ensure trust between parties. Data clean rooms allow collaboration and matching of data while preserving privacy and ownership. They can de-risk the practice of data collaboration and exposure of customer information or trade secrets and permit insights not previously possible.

The most mature set of use cases for this relatively new technology addresses common consumer data transformation and analytics, including data enrichment, audience creation, activation, and measurement. To maintain privacy of both the individual consumer data and each enterprise’s knowledge assets, the solutions need to address the data collaboration life cycle, from making the data accessible to the data clean room environment to quality checks and transformation, through queries and analysis and ultimately purging of this data where it has been retained.

Because none of the collaborating parties have full visibility to the data, it can be very challenging to ensure that the data being contributed is of high quality and consistency. Variation in formats, definitions, and choices in how to match the data sets on a common identifier can make results unreliable and undermine the value that is to be gained by collaboration.

Data clean room technologies add to the technology portfolio without necessarily taking something away, so buyers are trying to minimize the amount of data duplication and movement that is necessary for data collaboration. The setup requires expertise in data privacy, security, and data analytics, so organizations without the necessary expertise may struggle on the technical side to get the proper data governance in place to avoid confusion, data misuse, and/or disputes. These can be avoided with planning on the part of the buyer because once the guidance exists, the rules can be built into the collaboration agreements within the software.

The methods for maintaining privacy and security vary across the landscape today. There’s currently variance in the need or ability to replicate data, where the data is housed, how queries are constructed and monitored, and what types of outputs can be distributed. However, all of these technologies allow collaboration with control.

Whether in a simple partnership between two entities or a wide-ranging industry ecosystem, a data clean room technology can be deployed to allow data to be used for shared — or unique — insights where each party involved has control over what data is accessed, who can access the data, and how that data can be used.

Tech Buyer Advice

Data clean room technologies are a relatively new component in many enterprises’ advertising, marketing, and data analytics technology portfolios. They represent an opportunity to create better data-informed processes and a new frontier for collaboration in the advertising and marketing ecosystem in a way that can better serve customers.

Vendors included in this study range from start-ups to some that have been in business for decades. However, all of the data clean room technologies have existed in their current form for little more than five years. Each vendor and product have unique origins based on vendor legacy, regardless of the vendor being a market incumbent or a young company.

To ensure the best fit, prospective buyers should start with assessing both their specific business and technical operating environments and objectives. Regulatory as well as enterprise ethical guidance on the approach to privacy and confidentiality should also be assessed in this phase. Solutions in this study include tailoring to advertising and marketing use cases and some other features that can help buyers move quickly from installation to value realization. Specific criteria might come from the detailed criteria in IDC’s analysis shown in Tables 1 and 2 in the Strategies and Capabilities Criteria section of the Appendix.

Unique dynamics of the market today that should inform technology buyers include:

  • Data clean room technologies are in a period of rapid enhancement. Most of the technologies covered in this study are releasing enhancements each month. It is important to evaluate the technologies available at the time your enterprise is ready and not rely too much on prior evaluations.
  • Collaboration and partnership are central to success. This is not just with the planned data collaborators; it extends to the technology vendor team as well. IDC asked current buyers of data clean room technology how well the vendor’s vision fit with their own and how much of the technology road map is being built out by the vendor suggesting new functionality versus the technology buyer approaching the vendor with needs. Customers do not always need to be led, but they do need to be listened to.
  • Marketers and data scientists may use a clean room differently. For marketers or other less technical roles, it can be helpful to have a library where they can choose from prebuilt analytical models. On the other hand, data scientists as users can call for more sophisticated and complex analytical capabilities. Not all data clean room technologies offer both, and they are not generally honed to the same degree. It will be important to select a solution that matches your enterprise’s target audiences.
  • Non-technological issues should not be underestimated. Both vendors and end users told IDC that the factors that extended the time frame from selection to first proof-of-concept deployment centered around concerns from legal departments and business partners and getting agreement in place between the focus customer (orchestrator of the collaboration) and the other data contributors. All the technologies were relatively simple to get installed; it was the rules, agreements, and human change management that took up the bulk of the timeline.
  • Technical and specific use case needs are not a popularity contest. While being listed in the Leaders category or gaining significant market traction might suggest superiority across the board, “long tail” vendors may offer niche capabilities targeted to your specific needs. Don’t exclude (or include) a vendor just because it is not in the uppermost right position of the chart (or used by most companies in the market). However, if your planned data collaborators are already using a data clean room technology (or multiple technologies), it will be a higher threshold to get them to consider an additional data clean room technology.

Featured Vendor

This section briefly explains IDC’s key observations resulting in a vendor’s position in the IDC MarketScape. While every vendor is evaluated against each of the criteria outlined in the Appendix, the description here provides a summary of each vendor’s strengths and challenges.

Habu

Habu was recently acquired by LiveRamp to strategically expand its collaboration network, and drive further adoption of LiveRamp’s core identity and connectivity solutions. Together, they offer an interoperable platform for data collaboration across all clouds and walled gardens globally.

Habu is positioned as a Leader in this 2023–2024 IDC MarketScape for data clean room technology for advertising and marketing use cases.

Founded in 2018, Habu solely focuses on data clean room technology. The firm’s founders bring expertise from the technology and data industry. Habu does not sell data, but its data clean room software can provide access to third-party data sets.

With Habu data clean rooms, identity can be resolved by the technology or with the addition of third-party data sets. The platform includes the ability to pseudonymize data and inject noise along with the capability to create synthetic data sets. All of these functions help create insight while preserving data privacy.

The Habu technology brings analytics and modeling to the data, and collaborators do not need to move data from where they have it. Queries can be written in natural language and converted to SQL using AI or written natively in SQL or Python. This provides flexibility for different personas. In addition, users have the ability to iterate on their analytics. The integrated genAI capabilities also provide suggestions for new use cases to end users, as well as help implement them.

Habu has participated in many activities to shape the market, including the definition and promotion of data clean rooms, along with being a significant contributor to the IAB Tech Lab.

Quick facts about Habu include:

  • Financial structure: Habu, a private company with a number of venture capital investors including Snowflake Ventures
  • Top use cases/industries: Audience analysis and activation, planning, measurement, and CCTV
  • Pricing: Subscription with unlimited users/processors/usage (no variable component); subscription with prepaid credits to use with product usage (e.g., each data transformation); pay-as-you-go consumption priced with a per-product usage (e.g., each data transformation); only the data clean room “orchestrator” required to have a license

Strengths

  • High customer satisfaction
  • Broad partnerships and interoperability, including AWS, Azure, Databricks, Google Cloud Platform, and Snowflake
  • Query flexibility while providing an interface geared toward a variety of personas and a library of prebuilt use case templates

Challenges

  • Some limits to geographic deployment
  • No formal user or developer communities

Consider Habu When

Habu’s differentiation is the company’s focus on providing a flexible tool for a variety of use cases and custom queries available across a broad array of platforms. Consider Habu when you and your data clean room collaborators have data residing on many different clouds and plan to utilize multiple data science, data analyst, and business user roles.

Methodology

IDC MarketScape Vendor Inclusion Criteria

To be considered a data clean room technology in IDC’s study, the technology needs to facilitate the combining of multiple parties’ private data and may include the option to add third-party external data. The solution needs to be a technology solution rather than services provided by an agency or other third party.

Vendors that qualify for inclusion in this IDC MarketScape must meet the following criteria:

  • Has data clean room technology available to the public as of 4Q23 (not private preview)
  • Allows data collaboration for two or more parties while preserving aspects of privacy of the data and/or algorithms contributed by the parties
  • Does not require users to purchase specific hardware for privacy functions (may offer this as an option)
  • Does not require users to encrypt data prior to making it accessible to the data clean room technology (may offer this as an option)
  • Has a standalone data clean room — in cases where vendors offer a customer data platform (CDP), customer relationship management (CRM) solution, or a similar solution (It must be possible to buy or license the data clean room without buying or licensing a particular CDP or CRM system.)
  • Is not a data clean room space, where one entity is offering data clean room function but only with its private data

Reading an IDC MarketScape Graph

For the purposes of this analysis, IDC divided potential key measures for success into two primary categories: capabilities and strategies.

Positioning on the y-axis reflects the vendor’s current capabilities and menu of services and how well aligned the vendor is to customer needs. The capabilities category focuses on the capabilities of the company and product today, here and now. Under this category, IDC analysts will look at how well a vendor is building/delivering capabilities that enable it to execute its chosen strategy in the market.

Positioning on the x-axis, or strategies axis, indicates how well the vendor’s future strategy aligns with what customers will require in three to five years. The strategies category focuses on high-level decisions and underlying assumptions about offerings, customer segments, and business and go-to-market plans for the next three to five years.

The size of the individual vendor markers in the IDC MarketScape represents the market share of each individual vendor within the specific market segment being assessed.

IDC MarketScape Methodology

IDC MarketScape criteria selection, weightings, and vendor scores represent well-researched IDC judgment about the market and specific vendors. IDC analysts tailor the range of standard characteristics by which vendors are measured through structured discussions, surveys, and interviews with market leaders, participants, and end users. Market weightings are based on user interviews, buyer surveys, and the input of IDC experts in each market. IDC analysts base individual vendor scores, and ultimately vendor positions on the IDC MarketScape, on detailed surveys and interviews with the vendors, publicly available information, and end-user experiences in an effort to provide an accurate and consistent assessment of each vendor’s characteristics, behavior, and capability.

Market Definition

Enterprises want to engage in data sharing but need special technologies to protect privacy and trade secrets and ensure trust between parties. Data clean rooms allow collaboration and matching of data while preserving privacy and ownership. They can de-risk the practice of data collaboration and exposure of customer information or trade secrets and permit insights not previously possible.

To be considered a data clean room technology in IDC’s study, the technology needs to facilitate the combining of multiple parties’ private data and may include the option to add third-party external data.

Related Research

  • IDC FutureScape: Worldwide Future of Enterprise Intelligence 2024 Predictions (IDC #US51293423, October 2023)
  • Market Analysis Perspective: Worldwide CX Services, 2023 (IDC #US49772123, September 2023)
  • Shift Toward External Data: Collaboration Is the Name of the Game (IDC #US5058322, April 2023)
  • Going Beyond 1:1 — The Case for Sharing Data in Industry Ecosystems (IDC #US50504323, March 2023)
  • IDC TechBrief: Data Clean Rooms for Shared Data and Insight (IDC #US49486822, October 2022)
  • Data Clean Rooms: All Talk or Some Action? (IDC #US49673722, September 2022)

IDC MarketScape: Worldwide Data Clean Room Technology
for Advertising and Marketing Use Cases 2023–2024
Vendor Assessment