When a team of insurance brokers receives more than 500 emails per day from clients, it quickly becomes difficult to keep things organized and make sense of it all. That’s where Libero comes in: a solution that summarizes and classifies all incoming emails. Beyond that, Libero also categorizes them properly within the client database (CRM). All of this, which brokers and their assistants used to do manually, is now fully automated, freeing up a tremendous amount of time every day. Through this presentation, we want to bring you into the heart of Libero’s design and the key decisions made during its development: its architecture, the challenges, the specific requirements of the insurance industry, the solution’s evolution, and more. And most importantly, we want to open up a discussion with you, the community, around this question: - How do we build and deploy AI solutions that can actually be maintained and evolve over time? This question is more important now than ever, with the rapid evolution of AI solutions, products and services that hit the market each week. The rhythm of innovation (and sometime fluff…) is astonishing! How do we continue building solutions that stay relevant and keep delivering business value? As a service provider, iuvo-ai is constantly balancing innovation with pragmatism. Every client has a different level of technical maturity, infrastructure, and internal talent. In that reality, the real challenge isn’t just getting a solution to work; it’s making sure it can live on. How do we design architectures that are flexible enough to evolve as the ecosystem changes, but simple enough for our clients to own and maintain? How do we make decisions that reduce friction when the next API version drops or when the internal IT team needs to take over? Those are the questions we wrestle with every day when bringing AI into production, and we’d love to exchange ideas and lessons learned with you 🙂

As organizations modernize customer engagement, migrating from legacy CRM to Agentic CRM is a critical shift. Join Microsoft experts and community leaders for a candid, technical discussion on migration strategies, architecture decisions, and lessons from early adopters. Whether you're planning or implementing, this session offers a collaborative space to share insights, ask questions, and connect with peers.

Connection Pods accommodate up to 15 people. Please RSVP and arrive at least 5 minutes before the start time, at which point remaining spaces are open to standby attendees.

Explore how Dynamics 365 and Microsoft 365 Copilot deliver agentic CX, helping organizations drive revenue and improve CSAT. We’ll delve into real-world impacts, lessons learned, and what’s next for those embracing this shift. Finally, learn about CRM and CCaaS innovations and hear Microsoft’s AI vision to transform revenue-generating functions.

Drive faster lead-to-deal conversion with AI agents. Microsoft 365 Copilot and prebuilt agents in Dynamics 365 are freeing sellers to focus on building quality relationships by transforming critical sales processes. Lead qualification, deal acceleration, closing, and cross-selling are automized using real-time customer signals. Learn about new agents, seller use cases, and adoption strategies to drive revenue.

Learn what’s new in agentic service and how organizations are evolving toward frontier service models with Dynamics 365. See how collapsing legacy systems and unifying platforms enables more autonomous operations—improving CSAT, lowering costs, and strengthening security and compliance. Explore new opportunities and use cases that span customer service and IT help desk, powered by AI, extensibility, and secure, integrated data.

Ready to leave legacy CRM behind? Discover how global companies are moving to Dynamics 365 to drive growth. Learn proven strategies for rapid time-to-value, smooth data migration, and quick adoption of Copilot and agents. Get tools, templates, and real-world stories to guide a secure, confident transformation - at your pace.

Explore how Dynamics 365 and Microsoft 365 Copilot deliver agentic customer experiences (CX), helping organizations drive higher revenue and improved customer satisfaction (CSAT). Visa shares their journey and vision for agentic CX transformation. Discover real-world impacts, lessons learned, and what’s next for organizations embracing this shift. Learn about the latest CRM and CCaaS innovations and Microsoft’s AI vision to transform revenue-generating functions.

Does size matter? When it comes to datasets, the conventional wisdom seems to be a resounding, "Yes!" But what about small datasets? Small- and mid-sized businesses and nonprofits, especially, often have limited web traffic, small email lists, CRM systems that can comfortably operate under the free tier, and lead and order counts that don't lend themselves to "big data" descriptors. Even large enterprises have scenarios where some datasets easily fit into Google Sheets with limited scrolling required. Should this data be dismissed out of hand, or should it be treated as what it is: potentially useful? Joe Domaleski from Country Fried Creative works with a lot of businesses that are operating in the small data world, and he was so intrigued by the potential of putting data to use on behalf of his clients that he's mid-way through getting a Master's degree in Analytics from Georgia Tech! He wrote a really useful article about the ins and outs of small data, so we brought him on for a discussion on the topic! This episode's Measurement Bite from show sponsor Recast is an explanation of synthetic controls and how they can be used as counterfactuals from Michael Kaminsky! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

Depuis plus de 4 ans, NEXT, le laboratoire d'innovation d'Epsilon France, travaille à la conception d’outils basés sur l’IA pour faciliter la collaboration avec les équipes Sales, Marketing & les équipes IT. Il y a un an, nous sortions Amplify, une interface en langage naturel qui permet de créer, activer et piloter des audiences CRM & Média. Lors de cette session, nous reviendrons sur les bénéfices d'Amplify et comment cette solution peut véritablement transformer la manière dont les DSI soutiennent les objectifs marketing grâce à l'IA. 

Nous présenterons aussi Campaign Companion, notre nouvelle solution pour simplifier la gestion des campagnes CRM.

• Identifier, prioriser et activer les professionnels de santé (HCPs) au plus fort potentiel, qui desservent votre population de patients cible, est essentiel pour aider les patients à accéder à nos traitements.
• En tirant parti de l’apprentissage automatique, nous identifions dynamiquement les profils les plus prometteurs en fonction de leur influence et de leur potentiel, et nous combinons cette approche avec différentes solution afin d’améliorer la prise de décision et d’ajuster nos plans d’actions.
• Cette approche a permis d’augmenter considérablement le nombre de nouveaux patients traités sur plusieurs aires thérapeutiques.

Le processus d’allocation des coûts dans Alteryx s’appuie sur des workflows automatisés pour répartir avec précision les coûts des ETP entre les centres d’activités, selon des critères prédéfinis tels que les effectifs ou les volumes, en respectant des règles spécifiques d’allocation des coûts et de calcul des KPI.

1. Ingestion et préparation des données

Alteryx se connecte à plusieurs sources (par exemple, ERP, CRM, stockage cloud) pour extraire les données liées aux ETP, aux coûts et aux volumes. Le processus agrège, prépare et aligne ces ensembles de données disparates afin de créer une base de coûts unifiée.

2.Amélioration de la qualité des données

Des règles de transformation dynamiques sont appliquées pour garantir la cohérence, supprimer les doublons, gérer les valeurs manquantes et standardiser les types de données. Des outils de profilage des données offrent une visibilité sur les anomalies et valeurs aberrantes susceptibles d’impacter la logique d’allocation.

3. Logique d’allocation des coûts

Cela permet de définir des règles d’allocation flexibles et des étapes de validation — allant de ratios simples à des règles dynamiques dictées par les besoins métiers — en fonction des moteurs de coûts, ETP et volumes, pour garantir l’exactitude des calculs de KPI.

4. Intégration de l’IA générative

Les fonctions d’IA générative (par exemple via OpenAI ou les outils Gen AI d’Alteryx) renforcent le workflow en permettant :

La génération automatique de schémas de données adaptés à un format cible.

L’assistance via un outil Copilot pour créer des transformations à partir d’instructions en langage naturel.

La création de règles d’allocation dynamiques.

5. Sortie et visualisation

Les allocations finales peuvent être exportées vers des outils de reporting, des tableaux de bord ou des data lakes. Les utilisateurs peuvent consulter des synthèses d’allocation, des écarts et des vues détaillées pour appuyer la prise de décision via des applications analytiques personnalisées.

Selecting a suitable and high performing target group for CRM initiatives—such as newsletters and coupons—often involves time-consuming, manual coordination across multiple teams. In this session, we will demonstrate how we leveraged the combined strengths of Snowpark, Streamlit, and dbt to build a self-service application that allows CRM managers to define target groups independently—without relying on analytics resources. 

Our solution delivers real-time feedback based on user input, dramatically reducing turnaround times and simplifying the targeting workflow. We will explore how Snowpark acts as a seamless bridge between Streamlit and Snowflake, enabling efficient, in-database processing. Meanwhile, dbt ensures data consistency and reusability through standardized data products. 

Join us to discover how this integrated approach accelerates decision-making, ensures data governance, and unlocks scalable, self-service capabilities for your CRM teams.

Ready to unlock the full potential of your operations? By integrating CRM with ERP and powering it with AI and business process automation, you create a seamless, intelligent system that connects every part of your business—from customer touchpoints to backend processes.

The line between human work and AI capabilities is blurring in today's business environment. AI agents are now handling autonomous tasks across customer support, data management, and sales prospecting with increasing sophistication. But how do you effectively integrate these agents into your existing workflows? What's the right approach to training and evaluating AI team members? With data quality being the foundation of successful AI implementation, how can you ensure your systems have the unified context they need while maintaining proper governance and privacy controls? Karen Ng is the Head of Product at HubSpot, where she leads product strategy, design, and partnerships with the mission of helping millions of organizations grow better. Since joining in 2022, she has driven innovation across Smart CRM, Operations Hub, Breeze Intelligence, and the developer ecosystem, with a focus on unifying structured and unstructured data to make AI truly useful for businesses. Known for leading with clarity and “AI speed,” she pushes HubSpot to stay ahead of disruption and empower customers to thrive. Previously, Karen held senior product leadership roles at Common Room, Google, and Microsoft. At Common Room, she built the product and data science teams from the ground up, while at Google she directed Android’s product frameworks like Jetpack and Jetpack Compose. During more than a decade at Microsoft, she helped shape the company’s .NET strategy and launched the Roslyn compiler platform. Recognized as a Product 50 Winner and recipient of the PM Award for Technical Strategist, she also advises and invests in high-growth technology companies. In the episode, Richie and Karen explore the evolving role of AI agents in sales, marketing, and support, the distinction between chatbots, co-pilots, and autonomous agents, the importance of data quality and context, the concept of hybrid teams, the future of AI-driven business processes, and much more. Links Mentioned in the Show: Hubspot Breeze AgentsConnect with KarenWebinar: Pricing & Monetizing Your AI Products with Sam Lee, VP of Pricing Strategy & Product Operations at HubSpotRelated Episode: Enterprise AI Agents with Jun Qian, VP of Generative AI Services at OracleRewatch RADAR AI  New to DataCamp? Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

Atelier sur le ciblage précis de prospects et l’alignement ABM.

Optimisation de l’expérience client tout au long du parcours.

The Databricks Data Intelligence Platform and Lakeflow Connect have transformed how Porsche manages and uses its customer data. By opting to use Lakeflow Connect instead of building a custom solution, the company has reaped the benefits of both operational efficiency and cost management. Internally, teams at Porsche now spend less time managing data integration processes. “Lakeflow Connect has enabled our dedicated CRM and Data Science teams to be more productive as they can now focus on their core work to help innovate, instead of spending valuable time on the data ingestion integration with Salesforce,” says Gruber. This shift in focus is aligned with broader industry trends, where automotive companies are redirecting significant portions of their IT budgets toward customer experience innovations and digital transformation initiatives. This story was also shared as part of a Databricks Success Story — Elise Georis, Giselle Goicochea.

With 75M+ Treats Rewards members, PetSmart knows how to build loyalty with pet parents. But recently, traditional email testing and personalization strategies weren’t delivering the engagement and growth they wanted—especially in the Salon business. This year, they replaced their email calendar and A/B testing with AI Decisioning, achieving a +22% incremental lift in bookings. Join Bradley Breuer, VP of Marketing – Loyalty, Personalization, CRM, and Customer Analytics, to learn how his team reimagined CRM using AI to personalize campaigns and dynamically optimize creative, offers, and timing for every unique pet parent. Learn: How PetSmart blends human insight and creativity with AI to deliver campaigns that engage and convert. How they moved beyond batch-and-blast calendars with AI Decisioning Agents to optimize sends—while keeping control over brand, messaging, and frequency. How using Databricks as their source of truth led to surprising learnings and better outcomes.

Nasdaq’s rapid growth through acquisitions led to fragmented client data across multiple Salesforce instances, limiting cross-sell potential and sales insights. To solve this, Nasdaq partnered with Slalom to build a unified Client Data Hub on the Databricks Lakehouse Platform. This cloud-based solution merges CRM, product usage, and financial data into a consistent, 360° client view accessible across all Salesforce orgs with bi-directional integration. It enables personalized engagement, targeted campaigns, and stronger cross-sell opportunities across all business units. By delivering this 360 view directly in Salesforce, Nasdaq is improving sales visibility, client satisfaction, and revenue growth. The platform also enables advanced analytics like segmentation, churn prediction, and revenue optimization. With centralized data in Databricks, Nasdaq is now positioned to deploy next-gen Agentic AI and chatbots to drive efficiency and enhance sales and marketing experiences.

Try Julius.ai 👉 https://bit.ly/4jn4cFF Coupon code: AVERY25 AI is transforming how we work, how we make decisions, and how we understand the world through data. In this episode, I explore how Julius AI can simplify your data tasks, automate repetitive work, and offer valuable insights in MINUTES. Dive into the future of data analysis and get ready to 10x your productivity! Get my weekly newsletters (free): https://www.datacareerjumpstart.com/newsletter

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How This Delivery Driver Became a FAANG Data Analyst (Jen Hawkins) https://youtu.be/f-BWp_IJZ-I?si=2_tKqHEng_EYNRCB

💌 Join 10k+ aspiring data analysts & get my tips in your inbox weekly 👉 https://www.datacareerjumpstart.com/newsletter 🆘 Feeling stuck in your data journey? Come to my next free "How to Land Your First Data Job" training 👉 https://www.datacareerjumpstart.com/training 👩‍💻 Want to land a data job in less than 90 days? 👉 https://www.datacareerjumpstart.com/daa 👔 Ace The Interview with Confidence 👉 https://www.datacareerjumpstart.com/interviewsimulator

⌚ TIMESTAMPS 00:00 - Introduction 01:55 - My CRM Data Analysis 02:23 Exploring and Cleaning Data with Julius AI 06:15 Email Analysis and Insights 13:39 Sales Cycle Length Analysis 15:27 The Power of AI in Data Analysis

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If your goal is to land a data job in 2026, this is your chance to get ahead of the competition and start strong.

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