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CDP FAQ: Why Less Data is Not More

There is a reason why topics around data enrichment, the death of the cookie, and big data are so important right now: more data means finer outcomes. With myriad ways to approach this, however, it is understandable that in many organisations there is a desire to 'simplify' data, which carries the clear risk of losing data fidelity in the process. In this Coffee Break FAQ Session, we tackle:

- Reasons why less data is not 'more'
- Identifying and leveraging value in big data
- Simplifying outcomes, not data
- Improving Customer Experience with CDP
Recorded Sep 9 2021 25 mins
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Presented by
Neill Brookman, Director of Solution Consulting, EMEA and India
Presentation preview: CDP FAQ: Why Less Data is Not More

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    - Reasons why less data is not 'more'
    - Identifying and leveraging value in big data
    - Simplifying outcomes, not data
    - Improving Customer Experience with CDP
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    So advertisers are optimistic about these changes, but the big question remains: are they ready?

    For Executives to better understand how advertisers are approaching these changes and pivoting their practices, Advertiser Perceptions has put together an expert panel to discuss the current state of identity, advertisers’ state of readiness for changes, what’s being done to address these changes, new targeting and measurement tactics advertisers are planning to use, why first-party data is so important and what’s being done to collect it, store it and activate it.

    TOPICS COVERED IN THE WEBINAR
    • The Current State of Identity
    • Advertisers’ State of Readiness
    • How Are Changes Being Addressed
    • New Targeting and Measurement Tactics
    • The Importance of First-Party Data

    PANELISTS
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    • Jeffrey Ralls, Senior Strategy Manager Adtech | Martech, Treasure Data
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    David Raab, Founder at CDP Institute
    Customer Data Platforms and Data Management Platforms both manage customer data, but they are still very different. This session explores the different goals that each is designed for, the different technical approach that each uses to meet those goals effectively, and the implications of those technical differences. We’ll then explore specific use cases including retargeting, prospecting, personalized recommendations, CRM integration, and inventory notifications, and illustrate why each is appropriate for one type of system or the other.

    You will learn:
    · The primary purpose of CDP and DMP systems
    · How each system is optimized to support its primary purpose
    · The types of data stored in each system
    · Which system works with known individuals and which with anonymous profiles
    · The systems that a CDP and DMP typically connect with
    · How CDP and DMP can work with each other
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    Dilyan Kovachev, Manager, Machine Learning Engineering at Treasure Data
    In an era where consumers are bombarded with many different messages, offers, and content, how do you know which touchpoints worked to close a sale or build enduring customer loyalty? There are many different “ multi-touch attribution models ” that provide insights into what works. But which models are best for your business, and when and how should you apply them?

    These questions have only become harder to answer with the growing complexity of consumer journeys across many digital and physical touchpoints, from brand websites, online ads and social media to brick-and-mortar stores.

    To tackle this challenge, Treasure Data has developed a multi-touch attribution (MTA) model that combines a Long Short-Term Memory (LSTM) deep learning ML-model with Shapley values, a concept developed by Nobel Prize-winning economist Lloyd Shapley.

    With multi-touch attribution models, marketers are able to:

    · Use real-world customer behavior data and ML to calculate and update attribution values
    · Unveil correlations between touchpoints during the customer journey
    · Provides granular channel attribution % at each step of the customer journey to conversion
    · Allows for a data-driven budget allocation across channels and funnel stages
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    -Unifying first-party data assets
    -Sharing first-party data across the organisation
    -Providing enrichment through second- and third-party data
    -Integrating with partners to contextually target customers
    -Creating a probabilistic model for marketing attribution
Empowers enterprises to deliver relevant, real-time CX
Treasure Data is the only enterprise Customer Data Platform (CDP) that harmonizes an organization’s data, insights, and engagement technology stacks to drive relevant, real-time customer experiences throughout the entire customer journey. Treasure Data helps brands give millions of customers and prospects the feeling that each is the one and only. With its ability to create true, unified views of each individual, Treasure Data CDP is central for enterprises who want to know who is ready to buy, plus when and how to drive them to convert. Flexible, tech-agnostic, and infinitely scalable, Treasure Data provides fast time to value even in the most complex environments. To learn more, visit www.treasuredata.com.

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  • Presented by: Neill Brookman, Director of Solution Consulting, EMEA and India
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