Rivvit Inc., a data management firm for investment managers, unveiled a new artificial intelligence tool on Tuesday designed to let financial professionals “talk” to their portfolios.

The launch of the AI-powered virtual analyst marks a strategic pivot for the company, moving it beyond backend data reporting and into the competitive arena of conversational interface. The new tool allows users to query complex datasets and documents using natural language, effectively bypassing the need for SQL queries or static dashboards.

The ‘Fuel’ for AI

In an industry where a decimal point error can cost millions, financial institutions have been hesitant to embrace generative AI due to fears of “hallucinations fully”—confident but incorrect answers.

Rivvit is pitching its existing infrastructure—the unglamorous plumbing of data unification and governance—as the essential safety rail that makes this new technology viable for Wall Street.

“Data is the fuel for AI,” Matt Biver, the chief executive of Rivvit, said in a statement. “But AI only works when the data beneath it is clean, organized, and reliable.”

Biver argued that because Rivvit already governs the investment data across a firm’s systems, its virtual analyst can deliver “trustworthy, explainable answers that users can act on with confidence.”

Also Read: GenAI Search Is Rewriting the Shopper’s Playbook

A New Interface for Wall Street

The tool is designed to democratize access to data across the front, middle, and back offices.

• Portfolio Managers can ask for immediate asset allocation insights.
• Accountants can verbally request explanations for changes in Assets Under Management (AUM).
• Risk Managers can investigate performance trends without waiting for a specialized report.

“Rivvit now gives everyone the ability to talk to their data,” Biver added.

Also Read: AI and the New Rules of Business Adaptation

From Governance to Intelligence

The release represents the culmination of a broader evolution for Rivvit. The company has spent years building a “data foundation”—establishing centralized, clean data streams and enforcing strict governance protocols to track data lineage and health.

According to the company, the virtual analyst is not a standalone product but the “reward” for that foundational work. By layering a conversational AI on top of a rigorously governed database, Rivvit aims to solve the “last mile” problem in data analytics: delivering the correct answer to the user instantly.

“AI isn’t the end of the data journey,” Biver concluded. “It’s the reward for doing data right.”

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Marketers view Customer Data Platforms (CDPs) as essential because these tools can extract information from numerous sources and unify it in one location for easy reference. The integration of artificial intelligence (AI) has ushered in the era of AI-powered CDPs, fundamentally expanding the opportunities for marketing professionals to anticipate needs and deliver personalized customer journeys at scale.

What Defines an AI-Powered CDP?

Although the specific features vary by vendor, AI-powered CDPs typically use machine learning algorithms to analyze vast quantities of data in real-time. These advanced tools move beyond traditional audience segmentation, allowing users to create in-depth profiles, anticipate needs, and distribute tailored communications. These capabilities make marketing teams far more responsive to changing market trends and individual preferences. To understand how AI is changing consumer engagement, read about real-time data and personalization.

The Impact: Key Benefits for Marketing Professionals

A 2025 study of CDP users found that 81% felt highly satisfied with their products’ ability to support AI initiatives. The advantages of combining AI with a CDP are clear and measurable:

These advantages help marketers maximize customer experiences, making people more likely to show brand loyalty, recommend products to their friends, and share positive experiences on social media. Analyzing a wealth of data about individuals also allows marketing professionals to examine how well specific campaigns resonated and which favorable actions they caused—a core pillar of customer experience excellence.

More benefits should become apparent as additional companies integrate AI into workflows. A separate report found that 91% of executives are actively increasing AI applications, ensuring that AI-enabled CDPs become the new next-generation standard.

Embracing the New CDP Era: How to Adopt

AI is poised to upend how marketing professionals use their CDPs, providing new functionalities and valuable insights. Professionals interested in taking the next steps in their technological journeys should begin by assessing the shortcomings of their current CDPs or identifying their most desired features. AI-powered tools may fill those gaps and increase willingness to adopt as marketers anticipate solving workflow pain points.

Marketers can also contact the vendors of their current tools to ask about plans to introduce AI-powered CDP features. Statistics suggest that worldwide AI marketing revenue will exceed $107 billion by 2028. That robust growth encourages more product developers to find feasible ways to incorporate the technology into CDPs to help users accomplish more.

Remaining aware of associated industry developments is also critical. In one example, a CDP provider and a customer-experience engineering leader announced a strategic partnership to build enterprise-targeted products that help marketers facilitate personalized interactions with target groups or individuals. The results will let marketers make comprehensive customer profiles and use a proprietary recommendation engine to reach more confident decisions about maximizing engagement.

Overcoming the AI Challenges

Professionals rolling out AI-powered CDP platforms should select relevant metrics to track before, during, and after their tech implementations. That data can help them verify which parts of their process run smoothly versus the ones they should aim to improve with the new tools.

It is important to maintain realistic perspectives rather than viewing AI as the solution to all organizational problems. AI can streamline workflows, unlock insights, and elevate customer experiences, but it does not solve systemic process breakdowns. If a company has large quantities of duplicated or unreliable data, even the most advanced platforms cannot extract trustworthy insights. Establishing a data quality procedure for handling incoming information can optimize results by addressing issues that could degrade the AI’s conclusions.

In one study examining how marketers use AI, 63% mentioned data quality as an area for improvement. Some also cited the need for skill-building, with 72% viewing internal expertise as critical for scaling their initiatives. These takeaways emphasize how marketing departments may need to set and work toward relevant goals to achieve the necessary results.

Innovation and the Future of CDPs

AI-enabled CDPs have emerged as powerful marketing tools because they let users analyze information, monitor trends, and engage with customers more effectively. Marketers who want to adopt them should allow plenty of time to learn the basic features and investigate how the products fit into their workflows. That strategic approach should reveal productivity-enhancing advantages that drive measurable results.

The post The AI-Powered CDP: A New Era for Customer Data Management appeared first on MartechView.

Customers have become used to being hyperconnected, “always on,” in the digital world. They receive marketing messages on every platform, at every interaction, from pop-up ads to social media sponsored posts to reviews from their favorite influencers.

There’s a lot of competition for their attention, making it more challenging for brands to develop genuine relationships – no matter how much data is available. Personalization without authenticity falls flat, but understanding the behavioral data, what makes the customer tick, can be the key to building the relationship you want.

What Is Behavioral Data?

Behavioral data is the information that reflects how customers interact with a brand, product, or service. This can include website visits and clicks, purchase history, cart abandonment, email open and click-through rates, time spent on pages, and app usage patterns. You can also glean valuable insights from social media interactions like comments and shares or customer service communications.

Unlike demographic or psychographic data, which merely tells you who a customer is or what they value, behavioral data tells you what they do. These insights are more dynamic and can provide an authentic, real-time picture of customer intent and preference, which you can then use to deliver more personalized, timely, and relevant experiences.

How Does Behavioral Data Affect Authenticity?

Customers are increasingly skeptical of traditional marketing tactics. A report from Edelman Trust Barometer found that 71% of consumers say that if they perceive a brand as putting profit over people, they lose trust in the brand.

It’s clear—customers want authenticity. They prefer communications that feel personal, relevant, and rooted in a genuine understanding of their needs. Behavioral data can help you respond to actual customer behavior instead of your own assumptions for more accurate ways to highlight their preferences, anticipate their needs, and engage with them on a human level.

Strategies to Use Behavioral Data to Build Authentic Relationships

Contextual Personalization

Personalization isn’t just about including a first name in an email greeting. Behavioral data is a valuable tool for tailoring content recommendations and messaging based on the customer’s interactions and journey.

For example, a customer may visit a restaurant’s website and check out the brunch menu, but doesn’t book a reservation. This is a restaurant marketing opportunity to use behavioral data to trigger a geo-targeted ad offering a limited-time weekend brunch special or send a personalized SMS reminding them to finish booking. It’s timely, relevant, and based on real behavior, not guesswork.

Timing Is Everything

Behavioral signals can inform not only what you say but also when you say it. For example, triggering a discount offer after a cart abandonment or delivering onboarding content after a customer signs up for a subscription are timely, behavior-driven communications demonstrating attentiveness and respect for the customer’s journey. They reduce friction, support the customer’s goals, and make them feel understood.

Enabling Predictive Engagement

Tools like AI can forecast what customers are likely to do next based on their past behaviors. For example, data demonstrates that customers who engage with a brand’s blog for two months convert into paid subscribers after reading a case study. This information can be used to proactively suggest case studies to engage these users further and speed up the conversion.

Keep in mind that there’s no manipulation or pressure here. Instead, this approach offers value that is aligned with the customer’s current behavior and their likely needs. It gives your brand credibility while gently guiding the customer through the buying journey.

Driving Two-Way Conversations

Behavioral data doesn’t just help brands speak to customers. It helps them listen, too. For example, if customers frequently search for a feature that doesn’t exist or leave feedback in chat interactions, this may indicate they have needs that aren’t met.

You have an opportunity to acknowledge and respond to these insights. You could add a requested feature, improve support workflows, or reach out for more details to better serve the customer. This shows that you’re actively listening and care, which is the foundation of an authentic and valuable business relationship.

Some brands leverage behavioral data to adapt tone and channel preference. Some customers won’t check your marketing emails, but they’re happy to listen when you use SMS or social media messages. That signals that they need you to meet them where they are.

Segmenting with Purpose, Not Stereotypes

Traditional marketing segmentation often groups customers into static categories like “High-Income Professional” or “Gen X Mom.” Leaving people in broad categories can miss the important nuances of each customer, and your messaging could fall flat.

Behavioral data offers more fluid, accurate segmentation. You can group customers by shared behaviors, such as “customers who use social media purchase buttons” or “customers who download content often.” That’s inspiration to design experiences around those actions and deliver more meaningful interactions to these segments.

Improving the Experience Instead of Selling

A key aspect of an authentic relationship is to provide value without always asking for something in return. Behavioral data can help identify friction points in the customer journey, or places where the customer may get stuck, confused, overwhelmed, or frustrated.

If it’s bad enough, the customer may drop off completely. For example, if you see a lot of customers abandoning ships before the final step of a form, it may indicate that there’s a design flaw or that the pages are lagging. You can proactively fix the issue without discussing it with the customer – or waiting for a complaint – and show that you are attentive to the customer’s needs.

Ethical Use of Behavioral Data

Authenticity also relies on transparency and respect. Customers should know how their data is being used and can opt out of data collection or targeting. Personalization can quickly become ” creepy, ” but committing to ethical data practices and privacy can help you avoid these scenarios and maintain trust.

Let Customer Behavior Guide the Experience

Behavioral data helps you cut through the noise with meaningful, personalized experiences. You can respond to real customer actions, not your own assumptions, to build trust, loyalty, and authentic, long-term relationships. 

The post Using Behavioral Data to Drive Authentic Customer Relationships in a Digital World appeared first on MartechView.

Bottle Rocket, a leader in digital transformation, announced the successful launch of Zippy’s Restaurants’ enhanced digital ordering platform. This collaboration propels Hawaii’s iconic eatery, which recently expanded to Las Vegas, into a new era of seamless, intuitive, and robust digital engagement, bringing the flavors of Hawaii comfort food closer to its loyal customers and dedicated Zipsters, the name for the most loyal Zippy’s fans.

“This digital transformation is a game-changer for Zippy’s,” said Kevin Yim, Vice President of Marketing & Communications at Zippy’s. “Our partnership with Bottle Rocket has not only delivered a superior ordering experience but has also laid a flexible, future-proof foundation for our digital growth. This transformation will significantly enhance customer satisfaction, streamline operations, and ultimately drive our business forward by making it easier and more enjoyable for everyone to connect with Zippy’s, whether they’re ordering a Zip Pac or our famous chili.”

The upgrade represents a pivotal step in Zippy’s commitment to advancing restaurant technology and improving the overall customer journey. Recognizing the growing dominance of online orders, Zippy’s partnered with Bottle Rocket for end-to-end expertise in user experience (UX), visual design, and platform development. The goal: to streamline ordering while authentically integrating Zippy’s iconic brand and its deep connection to the Hawaii community.

“Our approach centered on understanding Zippy’s unique brand, operational needs, and, critically, their customers’ expectations,” said Matt Smith, EVP, Client Engagement & Growth at Bottle Rocket. “By focusing on intuitive UX, engaging design, and a flexible MACH-based architecture, we’ve crafted a digital ordering platform that extends the Zippy’s experience directly into customers’ hands. We anticipate increased order values as customers discover the expanded ease and breadth of options available online, a trend Zippy’s is already observing.”

The new platform empowers customers to order their favorite local comfort foods faster and more conveniently online, via their phones, or in-store. Key enhancements include:

• Faster Checkout: Streamlined process with fewer steps.
• Flexible Ordering: Order breakfast items for the next day, anytime.
• Enhanced Visuals: More food images for easier selection.
• Live Order Tracking: Real-time updates and wait times.
• Integrated Loyalty: Support for loyalty programs and exclusive digital deals.
• Fresh Interface: Redesigned for intuitive navigation and a modern feel.

This collaboration underscores Bottle Rocket’s dedication to empowering beloved brands with transformative digital solutions that boost customer engagement and operational excellence. The new Zippy’s online ordering experience is live now on their app and at.zippys.com.

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Work and personal life used to exist on separate tracks. Today, they’re running on the same rails. Whether someone is joining a webinar in the morning, ordering groceries at lunch, or catching up on work emails in the evening, there’s no clear line between professional and personal identity anymore.

This shift is backed by more than anecdotal evidence. Many companies now support some form of hybrid work, and workers routinely toggle between personal and professional tasks throughout the day. These blurred roles aren’t just a feature of daily life. They are now a fundamental part of how people engage with brands, platforms, and content.

This has significant implications for marketers. When someone shops online, watches a demo video, downloads a whitepaper, and signs up for a rewards program, are those four different people in your system, or one? If your data model doesn’t have an answer, it’s likely not working hard enough.

What’s Missing in Most Marketing Data

For years, customer data has been trapped in separate systems: CRM records, web analytics, media buys, and offline files that rarely line up. Marketing teams have tried to patch things together, often relying on third-party cookies or device IDs to connect the dots.

That’s getting harder by the day. Regulatory changes have pushed marketers toward first-party data strategies, but those alone don’t provide the whole picture. Cookies are going away. Device-level targeting is inconsistent. And even the most robust in-house data still tends to separate people into “consumer” or “professional” categories, as if those are two different humans.

Marketers need a unified identity framework to meet today’s targeting and engagement demands. This means:

• Connecting business and personal attributes at the individual level  
• Recognizing people across devices and channels  
• Enabling consistent, permission-based outreach at scale  

The companies that can do this will operate with far greater confidence in their data, deliver more relevant experiences, and reduce wasted spend.

Ideal Person Profiles: A Better Kind of Profile

One solution gaining traction is the Ideal Person Profile, or IPP. It’s not a new database or a new targeting tool. It’s a more complete approach to understanding people, and it is quickly becoming the only viable path forward for understanding people in a more complete and connected way.

An IPP combines multiple data sources, linking first-party information with verified business and consumer insights. The goal is to build a clear view of someone’s interests, roles, responsibilities, preferences, and behaviors across both their professional and personal life.

With this kind of profile, marketers can:

• Identify who is behind a set of interactions—often through multiple channels  
• Find new audiences that share key traits with existing high-value customers  
• Tailor campaigns that match someone’s context, no matter the touchpoint  

For example, someone might interact with a brand during work hours as a B2B buyer and later on as a consumer. An IPP makes it possible to understand and connect with that person appropriately in both moments, based on a shared profile grounded in real data, not guesses.

What Makes This Work

Profiles like these don’t build themselves. They rely on a few key elements:  

• A reliable method for linking business and consumer data  
• Persistent key at the person level, which enables tracking and retention of identities across offline and digital signals and attributes, such as hashed emails, mobile advertising IDs, and postal address data
• A structured, privacy-compliant framework that respects consent and regulation  

Most marketing teams can’t source or maintain this kind of system internally. Even with a strong first-party dataset, it’s difficult to make connections that go beyond your own properties. That’s why external data partners are so critical in this space.

Where It Comes Together

To address this challenge, marketers need solutions that can connect personal and professional data under a unified structure, so that they can create more complete profiles, improve targeting, and deliver consistent messaging across email, social, mobile, CTV, and more.

The solutions they use should support the creation of IPPs by linking first-party data with verified business and consumer signals, all within a privacy-first framework. When this is accomplished, the result is better identity resolution, more efficient outreach, and a stronger foundation for personalized engagement.

As marketers adjust their strategies for a more fluid, cross-channel world, a better understanding of individual identity isn’t optional—it’s the only way forward.

The post Blurring Boundaries: Why Marketers Need Unified Profiles appeared first on MartechView.

Fleet Farm, a leading Midwest retailer, announced that it has selected Amperity’s Customer Data Cloud to modernize its customer data infrastructure and enhance its loyalty program capabilities. The platform’s advanced AI-driven identity resolution and out-of-the-box ML models will enable Fleet Farm to unify customer data across retail stores, home shipping, and loyalty programs, while dramatically improving their speed to market with personalized experiences.

“Partnering with Amperity represents a foundational investment in Fleet Farm’s future,” said Jessica Gillett, senior director of marketing & ecommerce at Fleet Farm. “By establishing a clean, unified customer data foundation, we can now move at the speed our business demands. This technology will enable us to better understand and serve our customers through timely, relevant personalization, while setting us up for long-term growth and innovation in how we engage with our shoppers.”

Fleet Farm will initially focus on the following strategic initiatives:

• Creating a unified view of customers by combining in-store, online, and loyalty program data
• Accelerating access to customer insights to enable segmentation and targeting
• Delivering more personalized offers and promotions across all channels
• Developing sophisticated audience strategies for improved customer engagement
• Building a modern data foundation to scale their loyalty program for future growth

Fleet Farm’s investment will support a dual loyalty strategy: deepening relationships with dedicated members while attracting younger demographics through enhanced digital experiences. These capabilities will also deliver broader business benefits, including improved customer retention, enhanced personalization, and optimized marketing spend.

Also Read: AI’s Rise: Fueled by Advertising Dollars

“Fleet Farm’s vision for customer-centric retail aligns perfectly with our mission at Amperity,” said Jason Perocho, SVP, head of marketing at Amperity. “Our customer data cloud provides the foundation for advanced segmentation and personalization capabilities that will power Fleet Farm’s next generation of shopping experiences. We’re excited to see how this partnership will help them drive loyalty and growth, while further demonstrating our momentum in helping leading retailers transform their customer data strategies.”

Interested in learning how to deliver AI-powered personalization, and optimize customer data amid evolving privacy regulations? Register for our upcoming fireside chat, “The New Customer Data Imperative: Turning Foundations into Value,” featuring Forrester.

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Red Maple, a leading innovator in enterprise payment solutions, is excited to announce the release of its new Subscription Payments for Microsoft Dynamics, built to seamlessly integrate with Microsoft Dynamics 365 Finance & Operations and Business Central. Leveraging Microsoft’s subscription feature introduced in 2024, Red Maple’s latest offering provides businesses with a flexible and automated way to manage recurring payments, billing, and customer subscriptions.

As businesses increasingly shift to subscription-based models, the need for streamlined subscription and payment management has never been greater. Red Maple’s new software eliminates manual processes, enhances customer experience, and ensures timely payments through automation, customization, and seamless integrations.

Key Features and Benefits

Subscription & Plan Management

• Easily create and manage multiple subscription plans, including monthly, annual, and custom billing cycles.
• Attach payments directly to contracts for better tracking and compliance.
• Configure primary payment methods and collect payments before invoicing, reducing revenue leakage.

Billing & Payments

• Automate recurring billing for effortless revenue collection.
• Flexibility to choose a preferred payment processor.
• Support for both one-time and recurring charges.
• Customizable communication tools for invoices, payment confirmations, and rejections.
• Automated payment retries to reduce failed transactions.
• Multi-currency support for global business operations.
• Customers can leverage Clever Division to set preferred payment methods and manage their payments efficiently.

Customer Management

• Self-service portal for customers to manage subscriptions and payment methods.
• Full account history and transaction tracking for complete transparency.
• Support for multiple subscriptions per customer, catering to diverse business needs.
• Integrated communication tools, including notifications, emails, and reminders, to keep customers informed.

Also Read: How Companies Can “Own the Moment” with Real-Time Customer Data

“With Microsoft’s new subscription feature in Dynamics 365, we saw an opportunity to develop a best-in-class payment management solution that aligns with modern business needs,” said Patrick Hodo, CTO at Red Maple. “This new software empowers businesses to streamline their subscription models, reduce administrative burdens, and enhance the customer experience.”

Red Maple’s Subscription Payments for Microsoft Dynamics is available now for businesses looking to optimize their subscription billing processes and leverage the full power of Microsoft Dynamics 365.

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Deep Sync, a leading provider of omnichannel identity and data solutions, has launched new integrations with Shopify and HubSpot on the Deep Sync One platform. Now, users can seamlessly activate their customer data from Shopify and HubSpot into Deep Sync One with the touch of a button.

Shopify powers over 2 million e-commerce businesses in the U.S. and HubSpot’s Customer Relationship Management (CRM) tool has roughly 95,000 U.S. business users. Deep Sync developed integrations for these platforms based on their extensive user bases.

Also Read: Oracle’s Adtech Exit: A Ripple Effect on the Industry

Deep Sync One’s new integrations simplify three audience targeting challenges for advertising on the open web: customer onboarding, the gleaning of actionable customer insights, and lookalike audience creation. This seamless process empowers Shopify retailers and HubSpot users to drive more impactful campaigns and reach more consumers likely to engage with their brands.

“Our new Shopify and HubSpot integrations make it easier than ever for businesses to unlock the full potential of their customer data. These direct data integrations enable seamless access to our powerful Lookalike Audience, Enhanced Onboarding, and Customer Insights tools, so businesses can expand their reach and improve campaign impact.” — Pieter De Temmerman, CEO, Deep Sync

Once a user’s Shopify or HubSpot data is in Deep Sync One, users can reach up to 25% more of their customers with their social and programmatic campaigns through Enhanced Onboarding; learn more about their customers’ demographic and psychographic makeup with a Customer Insights report; and build lookalike audiences that closely resemble their current customers for more effective campaigns.

Also Read: Salesforce in Advanced Talks to Buy Informatica

The data services available in Deep Sync One are powered by the company’s offline-to-online identity graph, built on a definitive view of the nation’s deterministic truth set, covering 97% of U.S. consumers. This fully deterministic identity graph enables brands to reach, understand, and engage their customers across channels for omnichannel marketing.

To get started, make a free Deep Sync One account. Navigate to File Uploader, select your Data Source (Shopify or HubSpot), and follow the directions to log in and select your data. When done, your data file will be uploaded to your Deep Sync One account.

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GrowthLoop, the leading SaaS platform empowering marketers to unlock the full potential of their organization’s customer data, today unveiled The Loop. This groundbreaking solution and methodology allows marketers – for the first time  – to understand how specific marketing channels and audiences directly impact business outcomes so they can strategize, pivot, and iterate for maximum return on investment (ROI). The Loop does this by securely applying AI to the data cloud – including data from marketing channel results, customer interactions, and sales performance – to reveal campaign insights and future recommendations based on the specific tactics that drove sales.

“The Loop is an absolute game-changer for marketers,” said Rebecca Corliss, VP of Marketing at GrowthLoop. “For the first time, marketers can see the sales they produce for each audience across any channel or campaign and make improvements based on what made money, not just clicks.”

Solving a Major Pain Point for Marketers

Historically, marketing teams have used manual, disparate tools that only offer partial insights – like newsletter click-through rates or social media likes – that don’t connect to actual business outcomes. 

Meanwhile, many marketing SaaS platforms are racing to provide AI- and data-powered tools that can bridge reporting gaps and assist overburdened marketing teams. But these tools can only support some aspects of marketing,  limiting the depth of analysis or types of outcomes AI can drive for enterprise businesses. With The Loop, GrowthLoop is the first company to offer an end-to-end solution that helps marketing teams effectively leverage AI to accelerate their ability to learn, execute, and improve marketing value. 

Unlike traditional customer data platforms (CDPs) such as Adobe, Segment, and Lytics, which often create data silos that leave marketers guessing, The Loop offers a unique advantage by applying AI to the data cloud and providing a holistic view across all campaign performance data, audience data, and sales results. From there, marketers can work side-by-side with generative AI to iterate on highly tailored campaign cycles faster than ever.  

“The Loop is revolutionizing the marketing function. Previously, marketing teams contended with a myriad of fragmented systems and data, akin to navigating a complex trail with a blurred map. With our new approach, it’s as if an experienced guide has joined the expedition, providing seasoned insights that enable smarter, more informed decisions,” said Chris O’Neill, CEO of GrowthLoop. “This transformation fuels immediate enhancements and paves the way for marketers to craft robust, long-term strategies with greater confidence and precision. GrowthLoop has set a new benchmark in innovation, reshaping expectations and redefining standards for data and AI solutions in the enterprise sector.”

Also Read: Salesforce in Advanced Talks to Buy Informatica

Key Features and Benefits

• AI applied to the data cloud: The Loop sits atop major data clouds – including Google BigQuery, Snowflake, and Amazon Redshift – which act as a single source of truth for company data and ensure full data security within these environments. The more The Loop’s AI learns, the more it understands each company’s unique business goals and the strategies to achieve them. Because it evolves, it continuously provides high-value recommendations for marketers. 
• Intelligent recommendations beyond human observation: The Loop’s application of generative AI across comprehensive data sets is unparalleled. Because it can evaluate data so quickly and effectively, a human can’t replicate its recommendations. The insights this technology provides arms marketers with the knowledge they need to drive strategic decision-making and campaign optimization. 

Built for enterprise ROI: Unlike tactical tools focused solely on automated A/B testing or automated decisioning, The Loop supports strategic marketers by advising marketers at a strategic level to help them meet essential, company-wide objectives such as increasing lifetime value, revenue, and retention.

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Vericast announced its NXTDRIVE customer data marketing platform (CDMP), which is now available for retail marketers nationwide. NXTDRIVE is the only CDMP that combines first-party data management and marketing activation from a single partner and solution for precise targeting and media delivery across print and digital channels. NXTDRIVE harnesses the power of machine learning (ML) and Vericast proprietary data and technologies to unify, clean, and enrich a client’s first-party data.

“NXTDRIVE empowers marketers by taking the guesswork and complexity out of managing and acting on first-party customer data to drive more performance-based marketing,” said Marc Mathies, SVP, NXTDRIVE at Vericast. “NXTDRIVE propels conversion, acquisition and customer loyalty while respecting consumer privacy and adapting to industry challenges.”

NXTDRIVE leverages Vericast’s Consumer Graph data to enrich a client’s first-party data with curated demographics, in-market interest, psychographic signals, and more. The Consumer Graph is Vericast’s identity resolution technology that uses billions of online and offline intent and location signals from more than 130 million households to uncover new opportunities. The enriched customer profile dataset forms the bedrock of reliable and on-time predictive insights like projected customer lifetime value, propensity of next purchase, and more.

NXTDRIVE instills confidence in campaign performance and helps marketers activate data on intelligence. Machine learning enables both predictive (what might happen) and prescriptive insights (how to influence outcomes) using advanced algorithms. The platform presents dynamic segmentation of the client’s customer base to help marketers gain deeper insights into various customer cohorts based on their past purchases, geo-demographics, RFM (recency, frequency, and monetization value), lifestyle, interests, preferences, conversion propensity, next best product, and other insightful signals. This helps marketers formulate precise physical and digital audiences for retention and acquisition campaigns.

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