Nielsen Marketing Cloud Features

Reports interface for standard and self-service reports is intuitive and easy to use.

Requires a minimal number of steps/clicks to answer business question.

Offers a variety of attractive graph and chart formats.

Score cards visually track KPI's.

Provides business users an interface to easily design, refine and collaborate on their dashboards

Using formulas based on existing data elements, users can create and calculate new field values.

Business users have the ability to filter data in a report based on predefined or automodeled parameters.

Users can drill down and explore data to discover new insights.

Ability to search global data set to find and discover data.

Ability for users to share data and reports they have built within the BI tool and outside the tool through other collaboration platforms.

Tool automatically suggests data types, schemas and hierarchies.

Analyze current and historical trends to make predictions about future events.

Communicate complex information clearly and effectively through advanced graphical techniques.

Ability to handle large, complex, and/or siloed data sets.

Converts data formats of source data into the format required for the reporting system without mistakes.

Ability to (re)structure data in a manner that allows extracting insights fast and accurate.

Provides business users an interface to easily design and refine their dashboards and reports. (What You See Is What You Get)

Application Programming Interface - Specification for how the application communicates with other software. API's typically enable integration of data, logic, objects, etc with other software applications.

Integration with ad servers, DSPs, and SSPs, and other data sources for in- and out-bound data transfer.

Allows user to combine first party data collected with additional first party data of strategic partners.

Breadth of standard integrations to third-party data providers.

Able to easily integrate data from offline sources.

Able to easily integrate mobile data within the DMP platform.

Able to extract data from the DMP in bulk through a structured file.

Ease of segmenting user profiles into groups.

Analyzes data to find and recommend the highest value customer segmentations.

Provides pre-built dashboards to aggregate and display data.

Allows users to easily build customized reports and dashboards.

Able to set data permissions for strategic partners.

Grant access to select data, features, objects, etc. based on the users, user role, groups, etc.

Software is consistently available (uptime) and allows users to complete tasks quickly because they are not waiting for the software to respond.

Provides features to allow scaling for large organizations.

Enables users to use the DMP in multiple languages.

Helps marketers measure return on investment (ROI) by analyzing campaign effectiveness against costs 10 reviewers of Nielsen Marketing Cloud have provided feedback on this feature.

As reported in 13 Nielsen Marketing Cloud reviews. Gathers data about the effectiveness, impact, and reach of marketing campaigns

Based on 10 Nielsen Marketing Cloud reviews. Collects and reports on data relating to customer journeys, preferences, and history

Allows multiple users access to a unified, transparent overview of analytics, dashboards, and campaign results This feature was mentioned in 11 Nielsen Marketing Cloud reviews.

Includes features for budgeting, forecasting, and managing marketing investments

Offers a white labeling service for agencies or resellers to customize platform branding

Based on 13 Nielsen Marketing Cloud reviews. Analyzes historical and current marketing campaigns to inform future strategy

Creates reports and dashboards to analyze results of campaigns 13 reviewers of Nielsen Marketing Cloud have provided feedback on this feature.

As reported in 12 Nielsen Marketing Cloud reviews. Identifies which marketing campaigns resolved in open or closed opportunities

Collects marketing campaign performance data across multiple channels This feature was mentioned in 10 Nielsen Marketing Cloud reviews.

Provides opportunities for brands and businesses to fix or modify existing or future campaigns via feedback

Uses artificial intelligence (AI) to predict campaign outcomes and suggest actions for optimization

Uses an attribution model that assigns credit to one touchpoint in the customer’s journey.

Uses an attribution model that assigns credit to all touchpoints in the customer’s journey.

Uses machine learning to create an attribution model.

Tracks customer interactions across mobile and desktop.

Allows users to track touchpoints through offline channels, such as events.

Allows the user to create a custom attribution model.

Provides features for B2B marketers.

Provides features for B2C marketers.

Enables marketers to track multiple marketing channels.

Integrates with other sales, marketing, and advertising software.

Provides customizable dashboards that allow users to view and manage data.

Displays attribution data through easy-to-interpret charts and graphs.

Allows users to build custom reports.

Ability to connect the analytics platform with a wide range of connector options for common data sources, including popular enterprise applications.

Connects to enterprise data governance software, or provides integrated data governance features to avoid misuse of data

Using formulas based on existing data elements, users can create and calculate new field values

Business users have the ability to filter data in a report based on predefined or automodeled parameters.

Allows the user to combine data from multiple sources into a functioning dataset.

Allows users to generate text based on a text prompt.

Condenses long documents or text into a brief summary.

Capability to perform complex tasks without constant human input

Works across multiple software systems or databases

Anticipates needs and offers suggestions without prompting

Capability to perform complex tasks without constant human input

Works across multiple software systems or databases

Engages in human-like conversation for task delegation

Anticipates needs and offers suggestions without prompting

Capability to perform complex tasks without constant human input

Ability to break down and plan multi-step processes

Works across multiple software systems or databases

Improves performance based on feedback and experience

Engages in human-like conversation for task delegation

Anticipates needs and offers suggestions without prompting

Makes informed choices based on available data and objectives

Capability to perform complex tasks without constant human input

Ability to break down and plan multi-step processes

Works across multiple software systems or databases

Improves performance based on feedback and experience

Anticipates needs and offers suggestions without prompting

Makes informed choices based on available data and objectives

Enables non-technical users to build dashboards through intuitive, drag-and-drop interfaces

Enables automated report generation and scheduled delivery to stakeholders

Allows dashboards and analytics to be embedded into external apps with branding flexibility

Supports integration with major data sources like cloud data warehouses, SQL/NoSQL databases, and SaaS applications

Efficiently processes large datasets with minimal lag and ensures high performance under load

Maintains performance and uptime during high traffic from multiple users or teams

Supports semantic data layers, role-based access controls, and metadata governance

Integrates with Jupyter, Python, or R for custom analytics and modeling

Provides native tools for statistical analysis, forecasting, and trend prediction

Uses AI to generate textual summaries, key takeaways, and data stories from dashboards

Allows users to query data and build reports using conversational or plain language

Detects and notifies users about KPI anomalies or significant metric changes in real time

Recommends next questions, analyses, or exploration paths using autonomous AI agents

Learns from historical user interactions to improve and personalize query results over time

Tailors dashboard views and suggestions based on user roles, access levels, and past behavior

Supports AI-driven exploration via prompts or multi-turn conversations for iterative querying