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    CDP

    What is CDP and it’s checklist?

    Pankaj KumarBy Pankaj KumarMarch 4, 2023Updated:April 9, 2023No Comments7 Mins Read

    Customer Data Platforms have quickly gained the attention of marketers and others who need a unified,
    accessible view of their customer data. But the popularity of the concept has led to confusion as many
    vendors with related systems seek to take advantage of buyer interest. The purpose of this paper is to
    reduce that confusion by providing buyers with a simple checklist of items that are required for a system
    to be considered a CDP. This is called RealCDP.

    The term Customer Data Platform was introduced in 2013 to describe what was then a new phenomenon:
    packaged software that build a unified customer database in addition to providing applications such as
    predictive modeling, campaign management, or advertising audience creation. Previously, marketing
    applications had largely connected to custom-built systems such as data warehouses or held only limited
    information, such as CRM, marketing automation, and Data Management Platforms (DMPs). In
    subsequent years, marketers became increasingly aware that previous solutions were not adequate for
    assembling and sharing a comprehensive profile for each customer – often known as a Single Customer
    View. By 2016, interest in CDPs as a new option began to rise sharply

    RealCDP Checklist


    The RealCDP checklist consists of six items that cover key features needed to provide a unified, accessible
    customer database that meets buyer expectations for such a system. A complete set of core CDP features
    would be much larger, so only meeting the five checklist items does not ensure a CDP will meet your own
    business needs. Even the six checklist items themselves can be met in different ways, some of which will
    be more or less appropriate for a specific situation. The purpose of RealCDP is to set a minimum standard
    for calling a system a CDP: a product that does not meet the RealCDP criteria is definitely not a CDP
    according to the CDP Institute definition. Such products may still be suitable for your situation, but you
    should consider carefully whether you really need any RealCDP feature they are missing.

    Ingest all sources.

    The CDP promise to assemble all customer data requires that the CDP be able to
    ingest that data as a start. This includes structured data, such as purchase transactions and customer
    address details; semi-structured data, such as Web interaction logs; and unstructured data, such as chat
    transcripts or social media comments. Ingestion may be via API connectors that push events into the CDP,
    via queries from the CDP that pull data from source systems, via streaming connectors that load a constant stream of data, and via file imports.

    It may happen in period batch processes or continuously in “real time”; when looking at real time ingestion, it’s important to understand how long it takes before the new data is available for use by applications. Ingestion processes may also include checks related to privacy permissions, data quality and governance. Users will also want to understand the effort needed to add a new source: in particular, whether data must be mapped in advance to a specific schema or can simply be ingested and stored as it arrives, with structures applied later.

    Capture full detail

    The CDP promises to build a profile containing all customer data. This means it
    must retain the full details of all ingested data, rather than summaries or selected attributes. For
    regulatory reasons, the system may not be allowed to retain some items and may be required to capture
    customer consent or constraints on how it can be used.

    The CDP may either retain the data in its original format, which then requires subsequent processing to extract useful attributes, or perform initial processing that adds some structure to simplify later access and analysis. Often the initial processing converts the data into “key-value pairs” that include an identifier (the “key”) and the data being stored (the “value”). Some systems may apply more elaborate structures, similar to a conventional multi-table relational database model.

    This requires the most preparation and initial processing but requires the least
    subsequent work when data is accessed. In practice, few companies will truly store all details from all
    sources, but the CDP should have this capability so that system limits do not prevent users from storing
    what they determine they need.

    Persist data indefinitely

    The CDP needs to store the data it ingests. This is a key difference from
    integration platforms and tag managers, which gather data but then pass it to other systems without
    retaining a copy. It also differs from many approaches that query the original source system in real time.
    Both of these approaches support many useful applications but they cannot create a complete customer
    view because the source systems often don’t retain old data for as long as a CDP user might want it. In
    other cases, retrieving data from source systems would take too long because significant processing is
    required to find the right records or perform complex calculations, or the source system may simply not
    allow direct real time access.

    Specific uses for stored data include identity management time-series,
    trends, aggregates, and change detection. Like initial data capture, data storage must comply with privacy
    regulations. Similarly, few companies will store all data forever; rather, they will set limits on data types
    and retention period based on business needs and costs. In practice, most companies will rely on a mix
    of stored data and real-time queries against source systems.

    Unified profiles

    The unified customer profile is the fundamental purpose of the CDP. It needs to
    associate all available data with an identified individual. The ability to work with identified individuals in
    particular is an important contrast to systems like DMPs that are limited to anonymous profiles. It
    requires the system to manage personal identifiers (PII), to link identifiers that belong the same individual
    (identity management), and to process the raw data in ways that make it usable.

    Such processing may include extracting specific information from unstructured or semi-structured data sources; standardizing information from different sources; and, creating derived values such as aggregates, segment assignments, and predictive model scores. Again, profiles need to comply with privacy regulations.

    Open access

    The CDP needs to make its data available to all external systems. This is an important
    goal for many users, who want to avoid being locked into a particular set of tools. It also reduces the cost
    of maintaining separate databases for individual systems, ensures that all systems work with the same
    data, and makes it easier to orchestrate customer experience across systems. Open access is usually
    achieved through a published API that lets any system query the CDP. In practice, many CDPs have
    developed prebuilt connectors for specific systems.

    Access may also be achieved by exporting CDP data into other formats, such as analytical data sets, flat files, or relational databases. Such exports are usually designed with a segmentation tool built into the CDP. Users often need to specify in advance which CDP data will be available for use. Some preparation may be needed to make data available use. A CDP should offer similar access capabilities to all target systems, rather than favoring access by its own applications.

    Real-time response

    The CDP needs to respond immediately to certain events. The acceptable
    response time varies but is usually under one second. Typical real-time use cases include immediate
    reaction to events such as a dropped shopping cart or new customer sign-up, and immediate response to
    a profile request from a personalization system or call center. Real-time reaction to events is often
    achieved by parsing new data as it enters the CDP system, either in a continuous stream or through receipt of batch files.

    Post Views: 1,500
    Pankaj Kumar
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    Pankaj Kumar is a senior professional holding 10+ years of experience in CRM, Email Deliverability & Marketing Analytics, Deliverability Onboarding, Implementation, Deliverability Automations He has worked with a broad range of clients to provide strategic, data-driven guidance to increase email delivery, subscriber engagement and revenue. He also helps marketers through this blogs in preparing strategies, data analytics, deliverability, and CRM with a passion for helping email marketers exceed subscriber expectations. You may connect with him on LinkedIn at https://www.linkedin.com/in/kumarpankaj793/

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