talk-data.com talk-data.com

Topic

CRM

Customer Relationship Management (CRM)

sales marketing customer_service

10

tagged

Activity Trend

12 peak/qtr
2020-Q1 2026-Q1

Activities

10 activities · Newest first

Accelerate revenue and seller productivity with agentic CRM

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.

Resolve cases faster in service with agentic CRM

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.

Migrate from legacy systems to agentic CRM

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.

Drive agentic CX with what’s new in Dynamics 365 for sales and service

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.

Unifying Customer Data to Drive a New Automotive Experience With Lakeflow Connect

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.

Sponsored by: Hightouch | Unleashing AI at PetSmart: Using AI Decisioning Agents to Drive Revenue

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.

Sponsored by: Slalom | Nasdaq's Journey from Fragmented Customer Data to AI-Ready Insights

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.

Next-Gen Sales Forecasting: AI-Powered Pipeline Management | The Data Apps Conference

Sales pipeline forecasting is essential for revenue planning, but traditional approaches rely on either unstructured spreadsheets or rigid SaaS applications like Clari—creating data silos, limiting customization, and forcing teams to switch between multiple tools for complete pipeline visibility.

In this session, Oscar Bashaw (Solution Architect) will demonstrate how to:

Create a unified sales forecasting app with role-specific views for both reps and managers Implement structured data capture with input tables for consistent deal-level forecasting Consolidate multiple data sources (CRM, call recordings, product usage) into a single tool Leverage AI models from your data warehouse to provide intelligent deal insights without leaving the workflow Build dynamic visualizations with real-time pipeline coverage and attainment tracking Use AI to surface risk signals by analyzing call sentiment, deal history, and activity trends from connected data sources With Sigma, sales teams can move beyond disconnected spreadsheets and inflexible SaaS tools to create a dynamic, AI-powered forecasting solution that scales with your business. Join this session for a complete walkthrough of the app's architecture and learn how to build similar capabilities for your organization—reducing costs while improving forecast accuracy and sales team productivity.

➡️ Learn more about Data Apps: https://www.sigmacomputing.com/product/data-applications?utm_source=youtube&utm_medium=organic&utm_campaign=data_apps_conference&utm_content=pp_data_apps


➡️ Sign up for your free trial: https://www.sigmacomputing.com/go/free-trial?utm_source=youtube&utm_medium=video&utm_campaign=free_trial&utm_content=free_trial

sigma #sigmacomputing #dataanalytics #dataanalysis #businessintelligence #cloudcomputing #clouddata #datacloud #datastructures #datadriven #datadrivendecisionmaking #datadriveninsights #businessdecisions #datadrivendecisions #embeddedanalytics #cloudcomputing #SigmaAI #AI #AIdataanalytics #AIdataanalysis #GPT #dataprivacy #python #dataintelligence #moderndataarchitecture

Building Apps on the Lakehouse with Databricks SQL

BI applications are undoubtedly one of the major consumers of a data warehouse. Nevertheless, the prospect of accessing data using standard SQL is appealing to many more stakeholders than just the data analysts. We’ve heard from customers that they experience an increasing demand to provide access to data in their lakehouse platforms from external applications beyond BI, such as e-commerce platforms, CRM systems, SaaS applications, or custom data applications developed in-house. These applications require an “always on” experience, which makes Databricks SQL Serverless a great fit.

In this session, we give an overview of the approaches available to application developers to connect to Databricks SQL and create modern data applications tailored to needs of users across an entire organization. We discuss when to choose one of the Databricks native client libraries for languages such as Python, Go, or node.js and when to use the SQL Statement Execution API, the newest addition to the toolset. We also explain when ODBC and JDBC might not be the best for the task and when they are your best friends. Live demos are included.

Talk by: Adriana Ispas and Chris Stevens

Connect with us: Website: https://databricks.com Twitter: https://twitter.com/databricks LinkedIn: https://www.linkedin.com/company/databricks Instagram: https://www.instagram.com/databricksinc Facebook: https://www.facebook.com/databricksinc

Why you should not do lead scoring in your marketing automation tools

As your business and number of product lines grow, the out-of-the-box lead scoring in CRM tools starts becoming difficult to work with and lead scoring becomes that more important for sales teams. Join Ben Lewinsky as he shows how Culture Amp approaches multi-product lead scoring in their data warehouse using dbt.

Check the slides here: https://docs.google.com/presentation/d/1NOyZLs1QUf6HQqF6jusx32OjUb-Gi-PTnmiDQ8EFKM8/edit?usp=sharing

Coalesce 2023 is coming! Register for free at https://coalesce.getdbt.com/.