Cloud-Enabled Customer Relationship Management

I confess that I’ve grown weary of products being prefixed with 'AI'. So when the concept of an AI-native CRM emerged, I met it with skepticism. Yet the category, though still nascent, is gaining momentum among teams who want a CRM tailored to their business without having to assemble a complex GTM stack. Early traction could be felt in the August funding rounds of Attio ($52M Series B) and Aurasell AI ($30M Seed). Other emerging players include Aero, Breakcold, Day AI, Lightfield, Reevo, SalesDesk (UnifiedCRM), Skarbe, toflow AI, and Zipteams. So, what should you expect from an AI-native CRM? 1) A flexible data model that breaks the rigidity of the legacy lead/contact/opportunity framework, enabling custom objects and adaptable workflows without complex customization. 2) A unified data infrastructure with a graph combining structured data (people, accounts) and unstructured data (conversations, intent, documents). 3) Built-in dataset enrichment. 4) Automated activity capture (emails, calls, meetings, chats, documents, etc.), all summarized and semantically indexed. 5) A modern UX that allows users to interact through natural-language and conversational commands, with in-context coaching and next-best-action guidance. 6) Built-in pipeline management, sales engagement, and forecasting. Of course, incumbent CRM players aren’t standing still and are racing to infuse these capabilities across their platforms. Salesforce has woven Data Cloud across its portfolio to unify structured and unstructured data, with Customer 360 acting as the connective tissue between its clouds and MuleSoft managing third-party integrations. A broad set of AI features is available as add-on modules, with Agentforce agents simplifying access to them. On paper, it checks every box, but in practice, realizing the vision still demands stitching together multiple modules and complex integrations. HubSpot has taken a different route, evolving its CRM into the newly minted Smart CRM, a unified repository for structured and unstructured data. It is gradually expanding customization, notably through custom objects and a more flexible schema design, while Data Hub now provides rich connectivity to third-party systems. The integration of Clearbit into the platform simplifies data enrichment and signal acquisition. Over time, HubSpot has embedded numerous AI features across the suite, which feel native to the user experience. The AI-native CRM category is still in its early days, but alongside the moves of incumbents, it is already setting a new yardstick for modern GTM infrastructure. I’m curious to hear your perspective and whether other innovative providers deserve a spot on your radar. #salestech #crm #ai

Rodobens — one of Brazil’s largest diversified financial-services providers spanning insurance, credit, banking, and automotive retail — was operating across five business units tied to more than 20 legacy systems. In such a fragmented environment, their vision of “customer-at-the-center” personalization was more aspiration than reality. Data inconsistencies and limited integration meant marketing and #CRM campaigns were handicapped — and the company lacked a single, reliable view of its customers. Recognizing that their legacy data infrastructure was a barrier, Rodobens spent months evaluating solutions. They needed a cloud-native, scalable platform that could integrate across #Azure, #AWS, #SAP, #Salesforce ecosystems. Ultimately, Informatica IDMC won out offering powerful data governance, unification, validation, enrichment, and a path to support predictive and generative AI. Once implemented, IDMC became the backbone of Rodobens’ data architecture: a “single source of truth” unifying customer data across all business units and legacy applications. The transformation paid off — fast. In the first six months of the new CRM-driven campaigns, Rodobens hit 182% of their Gross Merchandise Value(GMV) target, delivering an estimated $40M additional annual GMV — a dramatic win. On the operations side, they cut 50% of monthly IT hours previously spent on data maintenance and troubleshooting. As data quality improved (contact info completeness, validation, enrichment), marketing effectiveness soared: email compliance jumped from 43% to 62%, and phone contact compliance rose from 65% to 73%. With reliable, clean, unified customer data, Rodobens unlocked cross-sell and upsell opportunities, identifying familial and corporate linkages, mapping economic groups, and personalizing outreach with real clarity. Freed from firefighting data issues, IT and marketing teams could focus on higher-value initiatives: segmentation, predictive analytics, and setting the stage for #AI-driven engagement. Rodobens didn’t just solve a technical problem, they turned #data chaos into a growth engine. The partnership with Informatica transformed their “customer at the center” ambition into tangible business results. With a robust, governed data foundation in place, they’re now ready to harness predictive and generative AI to deliver personalized, intelligent #customerexperiences at scale. Image created using ChatGPT.

17% CAGR. $2.3 trillion by 2032. 89% of companies using multi-cloud. Cloud computing has given CRM a massive upgrade. In a digital-first world, customers expect more. Businesses are under pressure to keep up. Companies leading the pack are using multi-cloud, AI, edge computing, and serverless architecture. And it’s making all the difference. Traditional systems? Too rigid, too slow, and often outdated. Here’s how cloud computing is addressing these pain points: 𝟭. 𝗦𝗰𝗮𝗹𝗮𝗯𝗶𝗹𝗶𝘁𝘆 𝗮𝗻𝗱 𝗙𝗹𝗲𝘅𝗶𝗯𝗶𝗹𝗶𝘁𝘆 Cloud CRMs make it easy to scale as business needs change. This saves on infrastructure costs and avoids being locked into outdated systems. Example: 𝗥𝗲𝘁𝗮𝗶𝗹𝗲𝗿𝘀 can use cloud CRMs to manage seasonal spikes (like Black Friday) without overwhelming your system. 𝟮. 𝗥𝗲𝗮𝗹-𝗧𝗶𝗺𝗲 𝗗𝗮𝘁𝗮 𝗔𝗰𝗰𝗲𝘀𝘀 With cloud computing, teams gain real-time data access, allowing faster decisions and more relevant customer interactions. Example: For 𝗛𝗲𝗮𝗹𝘁𝗵𝗰𝗮𝗿𝗲 𝗣𝗿𝗼𝘃𝗶𝗱𝗲𝗿𝘀, cloud CRMs allow instant access to patient information, enabling faster, personalized care. 𝟯. 𝗔𝗜 𝗮𝗻𝗱 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻 AI-powered cloud CRMs improve predictive analytics, lead scoring, and customer service response times. Example: 𝗙𝗶𝗻𝗮𝗻𝗰𝗶𝗮𝗹 𝗦𝗲𝗿𝘃𝗶𝗰𝗲𝘀 use AI in CRMs to anticipate customer needs and automate support, providing a proactive approach that improves customer relationships. 𝟰. 𝗗𝗮𝘁𝗮 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆 𝗮𝗻𝗱 𝗖𝗼𝗺𝗽𝗹𝗶𝗮𝗻𝗰𝗲 Cloud CRMs handle data securely, meeting regulations like GDPR and CCPA without requiring in-house infrastructure. Example: 𝗟𝗲𝗴𝗮𝗹 𝗙𝗶𝗿𝗺𝘀 leverage cloud CRMs with built-in compliance to protect sensitive data, building client trust. 𝟱. 𝗖𝗼𝘀𝘁 𝗘𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝗰𝘆 Cloud solutions reduce infrastructure costs and allow smaller teams to access enterprise-grade CRM functionalities. Example: 𝗦𝘁𝗮𝗿𝘁𝘂𝗽𝘀 using cloud CRMs avoids high upfront costs, providing access to scalable tools that allow you to compete with larger companies. 𝟲. 𝗠𝗼𝗯𝗶𝗹𝗲 𝗔𝗰𝗰𝗲𝘀𝘀 Mobile-friendly CRMs allow teams to access information on the go, essential for real-time client interactions. Example: For 𝗥𝗲𝗮𝗹 𝗘𝘀𝘁𝗮𝘁𝗲 𝗔𝗴𝗲𝗻𝘁𝘀, mobile-first CRMs keep agents connected, allowing them to manage property information and client needs from anywhere. If you're in CRM or service delivery, don’t wait to explore cloud solutions. Focus on flexibility and security, and find ways to use AI and automation to improve customer interactions. The investment today will keep you agile and ready for what’s next. #CloudComputing #CRM #ServiceDelivery #CustomerExperience #DigitalTransformation #AI

Financial Services Innovators Are Data-Driven, Cloud-Focused, and Customer-Centric Across Their Value Chains 💡 Banking and insurance cloud innovators are: 👨💻 Data-driven: 🔹 FS cloud Innovators actively use data to support their sales and marketing functions by recommending relevant products to their customers through targeted marketing campaigns. During customer onboarding, innovators use AI to process structured and unstructured data they obtain from their customers and maintain it in a database for future reference, enabling a seamless onboarding process. 🔹 On the banking side, innovators actively use data to identify and prevent fraudulent transactions, calculate customer credit scores to evaluate potential risks, streamline the process of loan approvals, and estimate the probability of loan defaults. 🔹 On the insurance side, innovators integrate traditional and third-party data for the underwriting process to help price policies better. Insurance innovators also actively leverage data during claims process to automate claims triage, identify fraudulent claims, and estimate damage value. ☁️ Cloud-focused: 🔹 They actively leverage APIs to facilitate collaboration between different teams during product development to identifyand integrate best practices. 🔹 Innovators actively use intelligent cloud-based CRM systems to manage customer data and effectively support their various business functions. They also use cloud-based systems to automate the customer onboarding process. 🔹 FS cloud innovators drive contact center modernization with the help of the cloud to enable faster resolution of issues and enhance upsell and cross-sell opportunities. 🙋♂️ Customer-centric: 🔹 Furthermore, cloud innovators have optimized KYC processes for onboarding to ensure that their customers have a seamless experience. 🔹 These innovators provide their customers with an omnichannel experience, ensuring they have straightforward and instantaneous access to their services. They offer their customers comprehensive, personalized financial advisory services in addition to their standard products and services. 🔹 Finally, these organizations leverage intelligent chatbots to assist their customers with the challenges they face during their financial journey. Gen AI helps innovators manage data, re-engineer processes, make realtime automated decisions, and drive simulations to delight customers. Some critical uses of generative AI across the value chain include market forecasting, tailored content marketing, personalized credit analysis in banking and premium calculations in insurance, fraud prevention and management, and intelligent chatbots and virtual assistants. Source: Capgemini - https://t.ly/A5cZC #Innovation #Fintech #Banking #OpenBanking #API #FinancialServices #Payments #Loans #Compliance #AI #Data #Cloud #GenAI