Utilizing data to drive smart business outcomes — Matt Kilmartin & Matthew Karasick // Habu

Matt Kilmartin and Matthew Karasick, CEO and CPO at Habu, explore data-driven AI solutions for business efficiency. Using data to drive smart business outcomes within the framework of data clean rooms involves collaborating with partners' data without sharing the actual data itself. For instance, companies can analyze consumer behavior, optimize marketing strategies, and measure the impact of advertising campaigns using combined datasets, all while safeguarding data privacy and security. Today, Matt and Matthew discuss utilizing data to drive smart business outcomes.
About the speaker

Matt Kilmartin & Matthew Karasick

Habu

- Habu

Matt is CEO and Founder at Habu

Show Notes

  • 01:53
    Using data to drive smart business outcomes
    Examples of this include enhancing consumer engagement, delivering personalized advertising, and optimizing marketing investments through data utilization. Habu's data clean room software grants access to protected datasets, empowering marketers to achieve these outcomes.
  • 02:53
    Leveraging clean rooms for smarter marketing outcomes
    Pepsi, a Habu customer, utilizes clean rooms to gain visibility into diverse consumer touchpoints and run advanced propensity models on partner datasets. Theyre even leveraging Habu to gain access to datasets to improve supply chain operations.
  • 04:58
    Unlocking propensity to buy models and data collaboration in clean rooms
    Pepsi collaborates with retail partners and data providers in clean rooms to develop propensity-to-buy models. These models allow dynamic training, the creation of propensity scores, and targeted marketing while ensuring privacy and measurement of marketing efficacy.
  • 07:27
    Building multi party models and data connections in clean rooms
    Data clean rooms enable collaborations involving multiple parties. In Pepsis case, they can integrate marketing data, first-party data, POS data, and potentially identity data from multiple parties to build comprehensive models within the privacy-safe environment of clean rooms.
  • 08:19
    Habu's templated approach to efficient scalability in data collaborations
    Customers can establish data-sharing setups once and easily onboard new partners with predefined templates, rules, and constraints. This scalable solution allows for seamless collaborations, reducing the need for a repetitive setup and direct access to the source data.
  • 10:05
    The analyst experience within Habu
    Analysts establish data connections, create analytical templates or use pre-made ones, and invite partners to do the same. They then run implemented use cases, obtain privacy-safe output, and analyze it within Habu's BI layer or export it to their preferred environment for further analysis and reporting.
  • 12:56
    A data collaboration story between Indeed and Disney
    Indeed and Disney used Habu to collaboratively segment audiences and measure the impact of Indeed's advertising on Disney's platform. By analyzing user behaviors and exposure without sharing sensitive data, they accurately determined the lift and the campaign's effectiveness.

Quotes

  • "Being able to leverage data to drive smarter consumer engagement, to deliver more relevant, personalized advertising, and to make the best use of marketing investment dollars, those are all smarter business outcomes." - Matt Kilmartin

  • "The marketing industry has long known that user and event-level data is the right way to achieve the best results. However, for too long, the industry did it all on data transfer. And that's going away, as it should." - Matthew Karasick

  • "Very often, these clean rooms are not just two parties, it can be n parties." - Matthew Karasick

  • "This whole data collaboration thing was new to two and a half years ago. But at this point, we now have customers doing this in the 100s or 1000s of scale." - Matthew Karasick

About the speaker

Matt Kilmartin & Matthew Karasick

Habu

- Habu

Matt is CEO and Founder at Habu

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