Neustar Inc., a TransUnion company, today announced a partnership with Permutive to enable trusted connections between advertisers and publishers by bridging the gap between consumer identity data and a privacy-first web.
The partnership brings together the Neustar Fabrick™ data connectivity platform within the Permutive Audience Platform for advertisers and publishers to collaborate securely without the use of third-party cookies or device IDs. The partnership safeguards advertiser and publisher first-party identity data to bring addressability, transparency and privacy to digital advertising.
Permutive’s Audience Platform powers the leading Publisher Cohort Infrastructure on the open web. Extending Neustar Fabrick into cohorts allows publishers to meet advertisers’ demand for their audiences in a secure environment. This partnership is the first integration of this kind at Permutive and paves the way for a more responsible web.
With this partnership, advertisers and publishers can work together to build and activate their desired audiences at scale via Publisher Cohorts across high-quality, premium publisher inventory. Publisher Cohorts are a privacy-preserving approach to activation that groups like-minded users based on similar characteristics and behaviors – without identifying individuals.
Announcing Google Cloud Contact Center AI Platform, which offers an out-of-box, end-to-end solution for the contact center. It brings together the advantages of AI, cloud scalability, multi-experience capabilities, and tight integration with customer relationship management (CRM) platforms to unify sales, marketing, and support teams around data across the customer journey.
Contact Center AI Platform is purpose-built for customer relationship management, extending ability to offer personalized customer experiences that are consistent across the brand, whether delivered through a virtual agent, a human agent, or a combination of both. It eliminates many long-running pain points, from managing data fragmentation to replacing rigid customer experience flows with more engaging, personalized, and flexible support. With this addition, Contact Center AI now lets you:
Orchestrate the customer journey by creating modern experiences that can be embedded in their chosen channels with mobile/web software developer kits (SDKs), compatible with iOS and Android.
Leverage CRM as a single source of insight into the customer experience, to unify content, increase personalization, and automate processing with CRM data unification.
Manage multiple channels without pivoting across voice, SMS, and chat support.
Predict customer needs and route calls appropriately with AI-driven routing, based on both historical CRM data and real-time interactions.
Automate scheduling, schedule adherence monitoring, and manage employee scheduling preferences with Workforce Optimization (WFO) integration.
Provide customers with self-service via web or mobile interfaces using Visual Interactive Voice Response (IVR).
“Elections don’t just choose government, but also opposition” says Prashant Kishor the Indian Political Strategist. Founder Indian Political Action Committee (I-PAC), India’s first and largest cross-party political advocacy group.
Data analytics has established itself as an essential aspect of political campaigns. In I-PAC, the Data Analytics team works on electoral analysis, survey analysis, behavioural analysis, and sentiment analysis to identify they key focus areas and improve the campaign efficiencies with data backed insights.
Derive insights from electoral and demographic data using statistical techniques. Apply ML and AI modeling to gain actionable insights and boost campaign productivity. Design algorithms to analyse public sentiment using information from digital platforms. Design algorithms to improve the accuracy of surveys and provide insights. Analyse unstructured data sets including reviewing data for completeness and consistency and make recommendations.
“Artificial Intelligence and Machine Learning” by Vijay Gadepally
This lecture provides an overview of 5 to 6 Decades of Development in the Artificial Intelligence space, Key Ingredients in building AIML Workflows, and examples/details related to Supervised, Unsupervised, and Reinforcement Learning.
Jeremi Gorman became Snap’s Chief Business Officer back in the fall of 2018. The key to Gorman’s success is her ability to build relationships and trust, based on consultative touch instead of a hard-sell
She’s known to ask a lot of questions. It is a relationship-building tactic that helped Gorman find her niche between brand and performance marketing.
The mobile-first platform (primarily targeting Gen Z audience) had launched what it claimed as the world’s first camera advertising at scale with its AR Lenses and filters between 2015 and 2016. And a self-service Advertising Platform, called Ads Manager ( allows to create Ads, launch campaigns, monitor performance, and optimize goals)in 2017
Previously, they served their Clients based on the region instead of Industry, which Gorman felt was disjointed and counterproductive. Put another way: Snap was struggling to get in front of marketers; even when it did, the pitch didn’t always stack up.
Snap transitioned from a regionalized to verticalized sales structure and streamlined the sales process. Instead of sorting clients by region, clients are sorted by industry, improving partnerships between clients and the Snap sales team.
Gorman’s efforts have made a difference for media buyers. Snap’s AR lens was a bit of a one-trick pony, but thanks to Gorman’s revised strategy, R/GA has made Snap part of its core strategy, crediting the company with flexibility in media buying, creative, data-informed responses, and partnership transparency.
R/GA has utilized Snap’s dynamic retargeting capabilities, dynamic ads for broad audiences, and other hyper-focused direct response tactics within Snap’s ad product. Here is the TECHCRUNCH Article detailing about Snap’s Dynamic Ads Gorman’s training at Amazon (from 2012-2018) on ROI and data has helped her maintain a focus in those areas and effectively bring them to the marketplace
Know your customers like never before with a real-time customer data platform. Discover the new, powerful engagement insights from Microsoft that delivers the most comprehensive view of your customers.
Holistic view of Customers : To understand Customers or Prospects by Unifying and Enriching data in complete, centrally accessible profiles that deliver more personalized experiences. Create comprehensive view of each customer across channels—including campaign responses, in-store and online visits and purchases, loyalty redemptions, customer service encounters, social interactions, or IoT signals.
Data from Multiple Sources equals Comprehensive Insights : Access demographic, transactional, or behavioral data in real time from a variety of sources. This data helps ensure customer profiles are up to date and can generate relevant insights. Simplify the process of pulling in data with pre-built connectors available for myriad first- and third-party data sources, and organize customer data to derive powerful insights.
Unify Data for More Actionable Insights: The Data Unification Process aims to bring together data that is locked in disparate systems and applications to create a master customer data set for a more complete view of your customers.
The data unification process entails three steps: Map, Match, and Merge.
In the first stage, entities are mapped to a Common Data Model (CDM) schema.In Customer Insights, entities are data sets.
Many of the product processes—including data unification, relationships and segmentation, and measures and activities—are organized around the entities you choose.
Once the entities have been identified, select the attributes that you want to combine and reconcile in the Match and Merge phases.
The Match phase allows you to specify how to combine your data sets into a unified customer profile using deterministic and probabilistic matching. One can learn to evaluate the quality of match pairs and define rules to improve.
The Merge phase is the last step in the data unification process.
Conflicting data, such as customer names or phone numbers, might appear in different formats in data sets for the same record. The primary purpose of this step is to reconcile conflicting data
Enrich Data to Extend Solutions: Microsoft Graph provides proprietary audience intelligence such as demographics and interests, market trends, and product and service usage data. Bring in third-party sources to further enrich customer profiles and find new audiences and segments.
Generate Insights for an Improved Customer Experience: AI proactively recommends segments and generates predictive insights that drive optimized customer experiences and processes.
Discover new audience segments with AI-driven recommendations or define custom segments. Segments group your customers into Cohorts based on Demographic, Transactional, or Behavioral Attributes. Define sophisticated filters around the customer profile entity and its graph of related entities. Each segment outputs customer records that you can export and act on. Measures represent key performance indicators (KPIs) that reflect the performance and health of specific business areas. Create an intuitive experience for building different types of measures by using a query builder that doesn’t require you to code or validate measures manually. Export segments to sales and marketing applications to generate more targeted actions, such as promotional campaigns, sales activities, or customer support.
Activate Insights to Drive Better Solutions : Now that we have seen the power of data configuration and segmentation, let’s look at how this comes to life in day-to-day business operations. The Export destinations page shows you all the locations you’ve set up to export data to. You can add new destinations to personalize marketing strategies and safely connect with brands across social, digital, and TV ecosystems.
Leverage Timeline Control and Demographic Control to unlock rich insights on selected customers, including their location, age, and latest activities.
Connect Customer data with Microsoft Power BI to customize dashboards and reports.
Trigger workflows in response to customer signals by using Power Automate.
Build Custom Apps with Customer Insights embedded with Microsoft Power Apps.
With mobile apps that provide a 360-degree view of their customers, this empowers sales representatives to provide more personalized service.
Advanced Analytics for Deeper Insights : Leverage Azure Machine Learning (AML) to customize and train models for predictive insights that can be directly imported into the customer record. The predictive web service can be scheduled at predetermined intervals to automatically refresh and update the prediction scores.
Derive deeper insights with Azure Synapse Analytics, which combines customer data and enterprise data to improve data completeness, run high-speed analytical processing, and build custom machine-learning models.
Data Security, & Compliance to help one stay Current : Built on a secure and hyper-scalable Azure platform, advanced features help ensure that your organization is secure and compliant.
You can support data privacy and General Data Protection Regulation (GDPR) compliance with corporation-ready security and built-in governance tools, all while retaining full ownership of your data.
Customer Insights is available for government and public customers with higher compliance needs, allowing them to better understand and interact with citizens, empower employees, and transform cities at scale.
Industry-First Solution that Analyzes the Breadth and Depth of the Customer Journey. Powered by Machine Learning, “Journeys” can automatically evaluate the thousands of possible customer events and home in on the moments that matter most to the business
By evaluating the thousands of possible events along a customer path, Journeys automatically focuses teams on the few exact moments that have the greatest business impact, such as drop-off or paths which yield the highest conversion.
Product teams then leverage this real-time, predictive intelligence to identify the exact friction or conversion point by user, and group customers into cohorts for targeted messages and offers to accelerate conversion
Holistic View and True Understanding of the Customer, from the lens of the product itself. With Amplitude Journeys, the customer is now the center of any digital product experience, transforming yesterday’s product and data problems into today’s business growth opportunities
Understanding workflows, like sign-up to activation, and key milestones. Being able to flush this out in one click is incredibly powerful and Journeys enables us to increase the understanding and velocity.
As the economy is getting battered due to Covid 19, OTT consumption is scaling up; Mobile has become the Home for Premium video consumption.
This emerging landscape has provided a great opportunity for Marketers and Agencies to work towards creating the much-needed rich creative environment that can aid impactful Creative Storytelling powered by Data-led In-app Programmatic Targeting. Buoyed by the surge in demand for Online Video, Media planners are increasing their programmatic budgetary allocations for OTT services.
As Marketers we need to explore the emerging contours of this exciting digital marketing opportunity and delve deeper into how to make the most of this data-led programmatic and mobile goldmine.
And understand how the growth of the OTT provides marketers a great opportunity to be seen and heard in the right environment, by the right audience and at the right time. Some Key Questions to ponder
What is the DNA of the post-pandemic consumer who has gotten used to staying at home more than ever in their life and how best to serve them?
What does it mean to the ecosystem of brands, advertisers, and media planners?
How in-app programmatic video can bridge creative and data for brands and publishers?
What kind of skill sets are needed to tackle the needs of this ‘new’ consumer set and target them with the right creative?
How to strategize the increasing relevance and importance of data safety in the emerging landscape.
Can the premium nature of programmatic video be the answer to many of the challenges being faced currently?
What needs to be done to unlock this opportunity to the optimum?