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What Does Resolution Of Data Really Means

resolution of data
Resolution of data is defined as the process of connecting unique ‘identifiers’ to create a single, unified, real-time, persistent customer identity.

What Does Resolution Of Data Really Means

In this article, we talk about what resolution of data is, its components and process, who needs it, and why – with examples and use cases for marketers.

What Is Resolution of Data?

Resolution of data is the process of connecting unique ‘identifiers’ to create a single, unified, real-time, persistent customer identity. Identifiers include device identity, browser behavior, transactions and other contextual data that help connect the same individual across devices, platforms, and channels. The outcome is an accurate, complete and 360-degree view of each customer that can then be communicated to, in the most engaging and relevant way possible.

The goal of resolution of data is to get a holistic view of the customer’s interactions with the brand in an omnichannel environment, which is key to turning data complexity into an opportunity for exceptional customer experience.

Marketers are only too aware that their prospects and customers live in a device-dominated, multi-channel world. Marketers need to deliver a consistent brand experience irrespective of what device, platform or channel the customer chooses to engage – whether online or offline. That is where resolution of data helps.

In this feature, we will try and set out a detailed primer for enterprise marketers interested in understanding the concept of resolution of data, why they may need it, how to go about it and the types of resolution of data possible, even as they go about finding ways to incorporate the approach into their customer data management strategy.

Who needs a resolution of data, Why, and When?

Challenges, Use Cases, and Examples

Progressive marketers have always been focused on understanding the customers journey and addressing the most relevant messages to them, but it has been a long evolution from the time when the technology simply was not sophisticated enough for the kind of segmentation we can do today.

In fact, modern resolution of data and customer data management platform technology can help deliver the holy grail of ‘segment of one’ where each individual customer gets a personalized and unique brand experience based on their own characteristics, behavioral triggers and journey map.

The goal of resolution of data is to get a holistic view of the customer’s interactions with the brand in an omnichannel environment, which is key to turning data complexity into an opportunity for exceptional customer experience.

Between the rising inadequacy of cookies as a way to track customers and the increasing complexity of the device, platform and channel landscape, customer-centric marketers, who are focused on marketing efficiency, effectiveness and delivering a seamless, friction-free and optimal customer experience (CX) to their prospects and customers will prioritize resolution of data to better engage and retain customers.

Also read: Top 9 Proper Guidelines on How to Make Data Transfer Agreement Template

While the early adopters of resolution of data technology to enhance customer data management outcomes are in industries such as retail, travel & hospitality, ecommerce etc., it is a useful technology for any consumer-focused and customer-centric industry that wants to prepare for a world where customers increasingly expect to be recognized and treated to personalized and contextual journeys in an ever more complex environment. The primary use-cases for resolution of data applications for customer acquisition, engagement, retention and loyalty.

5 Core Components & Functionalities of an Resolution of Data System

Modern resolution of data and customer data management platform technology can help deliver the holy grail of ‘segment of one’ where each individual customer gets a personalized and unique brand experience.
  1. Data onboarding: the process of bringing all the available online and online customer data into a single system. Speed, accuracy and security are key to successful data on-boarding.
  2. Real-time and persistent matching and resolution at scale: once all the data is in one place, typically on the vendors resolution of data system or on the customer data platform (CDP), the process of deduplication, (probabilistic and deterministic) matching; hashing or anonymizing; and suppression begins*. The final outcome is the creation of one unique individual profile of each customer, which is persistent (changes with any change in customer’s use of device, channel, platform or address) and real-time.
  3. Identity Graph: proprietary identity graph models differ across vendors, but the basic idea of an identity graph is to further enrich the PII (personally identifiable information) collected in the customer profile with additional external channel, device or behavioral data that can act as digital identifiers. This could include third-party data from marketing partners or data vendors; municipal data in the public domain such as house or car ownership, or voter data; online surveys, event attendance, cookie and IP data, device data, mobile advertising IDs etc. The outcome is a complete customer identity – digital and online – created from both – owned and external data sources – that can inform the design of campaigns and customer experience.
  4. Integration & Activation: making these complete and addressable customer profiles available to other systems that can then further activate the data by running campaigns and delivering experiences.
  5. Compliance: adhering to prevailing regulations that define what ‘personal information’ means in a particular geography, industry or time frame. Usually, this means anything that can be associated or linked with an individual or household is subject to privacy and data security compliance. resolution of data solutions must cater to all that are applicable in the context of your brand.

Measures to facilitate resolution of data

Where appropriate, the Commission may, take any or all of the following
measures when seeking to facilitate the resolution of a complaint.

  1. Encouraging self-resolution: The Commission encourages individuals who have a concern with an organisation’s conduct with respect to their personal data to first approach the organisation, clarify the reasons for the organisation’s conduct and seek an appropriate resolution of the matter. This is especially important in cases where an individual may be unclear as to an organisation’s data protection policies or specific aspects of the organisation’s collection, use or disclosure of his personal data.
  2. Referring a complaint to an organisation: The Commission also encourages organisations to deal directly with a complainant’s concerns in an appropriate manner. Hence, another basic step that the Commission may take is to refer a complaint to the organisation (for example, through its data protection officer).
  3. Facilitating resolution: Where the Commission has referred a complaint to an organisation, the Commission will generally monitor the progress of discussions between the complainant and the organisation. If necessary, the Commission may facilitate the resolution of the complaint.
  4. Referring a complaint to mediation: If a complainant and an organisation are unable to resolve the matter directly and require additional assistance, the Commission may refer the matter for mediation by a qualified mediator. The Commission will only do so if both the complainant and the organisation agree that the matter be referred to mediation.
  5. Directing the parties to attempt to resolve the complaint: In certain situations, the Commission may, pursuant to section 27(2) of the PDPA, direct the complainant, the organisation, or both, to attempt to resolve the complainant’s complaint in the manner directed by the Commission. Before making such a direction, the Commission may consider the manner in which the complaint may be more appropriately or more expeditiously resolved.

Also read: 7 Phases Of Data Life Cycle Every Business Must Be Informed



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