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Salesforce Einstein Features

Salesforce Einstein Features

Salesforce Einstein Discover the power of the #1 AI for CRM with Einstein. Built into the Salesforce Platform, Einstein uses powerful machine learning and large language models to personalize customer interactions and make employees more productive. With Einstein powering the Customer 360, teams can accelerate time to value, predict outcomes, and automatically generate content within the flow of work. Einstein is for everyone, empowering business users, Salesforce Admins and Developers to embed AI into every experience with low code. Salesforce Einstein Features. Einstein Copilot Sales Actions: Sell faster with an AI assistant in the flow of work.Call Exploration: Ask Einstein to synthesize important call information in seconds. Ask Einstein to identify important takeaways and customer sentiment, so you have the context you need to move deals forward.

 Sales Summaries: Summarize records to identify likelihood the deal will close, the competitors involved, key activities, and more. Forecast Guidance: Ask Einstein to inform your forecast and help you identify which deals need your attention. Close Plan: Generate a customized action plan personalized to your customer and sales process. Increase conversion rates with step-by-step guidance and milestones grounded in CRM data. Salesforce Einstein Features Sales Generative AI features: ° Knowledge Creation: ° Search Answers for Agents and Customers: Einstein Copilot Service Actions: Streamline service operations by drafting Knowledge articles and surfacing answers, grounded in knowledge, to the most commonly asked questions. Summarize support interactions to save agent time and formalize institutional knowledge. Surface generated answers to agents’ & customers’ questions that are grounded in your trusted Knowledge base directly into your search page. Search Answers for Agents is included in the Einstein for Service Add-on SKU and Search Answers for Customers is included in the Einstein 1 Service Edition.
Empower agents to deliver more personalized service and reach resolutions faster with an AI assistant built into the flow of work. You can leverage out-of-the-box actions like summarize conversations or answer questions with Knowledge or you can build custom actions to fit your unique business needs. Service Salesforce Einstein Features This Release Einstein CopilotSell faster with an AI assistant. No data requirements
Included in Einstein 1 Sales Edition.hEinstein Copilot: Sales ActionsSell faster with an AI assistant.No data requirements. 
 Call explorer and meeting follow-up requires Einstein Conversation Insights.
Included in Einstein 1 Sales Edition. Generative AIBoost productivity by automating time-consuming tasks.No data requirements. 
 Call summaries and call explorer requires Einstein Conversation Insights.
Included in Einstein 1 Sales Edition. Einstein will use a global model until enough data is available for a local model. For a local model: ≥1,000 lead records created and ≥120 of those converted in the last 6 monthsEinstein Automated Contacts Automatically add new
contacts & events to your CRM≥ 30 business accounts. If you use Person Accounts, >= 50 percent of accounts must be business accounts Einstein Recommended ConnectionsGet insights about your teams network to see who knows your customers and can help out ona deal ≥ 2 users to be connected to Einstein Activity Capture
and Inbox (5 preferred) Einstein Forecasting Easily predict sales forecasts inside
of Salesforce Collaborative Forecasting enabled; use a standard fiscal year; measure forecasts by opportunity revenue; forecast hierarchy must include at least one forecasting enabled user who reports to a forecast manager; opportunities must be in Salesforce ≥ 24 months;Einstein Email Insights Prioritize your inbox with actionable intelligence Einstein Activity Capture enabledEinstein Activity Metiics (Activity 360) Get insight into the activities you enter
manually and automatically from Einstein
Activity Capture Einstein Activity Capture enabled Sales Analytics Get insights into the most common sales KPIs No data requirements. User specific requirements like browser and device apply Einstein Conveisation Insights Gain actionable insights from your sales calls with conversational intelligenceCall or video recordings from Lightning Dialer, Service Cloud Voice, Zoom and other supported CTI audio and video partners.Buyer Assistant Replace web-to-lead forms with real-time conversations. No data requirements – Sales Cloud UE or Sales Engagement. Einstein Opportunity ScoringEinstein Activity CaptuiePrioritize the opportunities most likely to convertAutomatically capture data & add to your CRMEinstein will use a global model until enough data is available for a local model. For a local model: ≥ 200 closed won and ≥ 200 closed lost opportunities in the last 2 years, each with a lifespan of at least 2 days≥ 30 accounts, contacts, or leads; Requires Gmail, Microsoft Exchange 2019, 2016, or 2013 Einstein Relationship Insights Speed prospecting with AI that researches for you. No data requirements. Einstein Next Best Action Deliver optimal recommendations at the point of maximumimpactNo data requirements. User specific requirements like browser and device apply Sales AIGenerate emails, prioritize leads & opportunities most likely to convert, uncover pipeline trends, predict sales forecasts, automate data capture, and more with Einstein for Sales. Generative AIPrompt BuilderEinstein Lead ScoringEinstein Opportunity ScoringEinstein Activity CaptureEinstein Automated ContactsEinstein Recommended ConnectionsEinstein ForecastingEinstein Email InsightsEinstein Activity Metrics (Activity 360)Sales AnalyticsEinstein Conversation InsightsBuyer Assistant Sales AIGenerative AI: 
Feature Why is it so Great? What do I need? Automate common questions and business processes to solve customer requests fasterBoost productivity by auto-generating service replies, summarizing conversations during escalations andtransfers or closed interactions, drafting knowledge articles, and surfacing relevant answers grounded inknowledge for agents’ and customers’ commonly asked questions. Deliver optimal recommendations at the point of maximum impactEliminate the guesswork with AI-powered recommendations for everyoneDecrease time spent on manual data entry for incoming cases and improve case field accuracy and completionAutomate case triage and solve customer requests fasterDecrease time spent selecting field values needed to close a case with chat conversations and improved field accuracySurface the best articles in real time to solve any customer’s questionEliminate time spent typing responses to the most common customer questionsGet insights into contact center operations, understand customers, and deliver enhanced customerexperiencesChat or Messaging channels, minimum of 20 examples for most languagesNo data requirements. User specific requirements like browser and device apply Make sure that your dataset has the minimum records to build a successful recommendation. Recipient Records need a minimum of 100 records,Recommended Item Records need a minimum of 10 records, andPositive Interaction Examples need a minimum of 400 records

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Data Cloud and Snowflake Bidrectional Data Sharing

Data Cloud and Snowflake Bidrectional Data Sharing

Salesforce Data Cloud and Snowflake are excited to announce that bidirectional data sharing between Snowflake, the Data Cloud company, and Salesforce Data Cloud is now generally available. In September, we introduced the ability for organizations to leverage Salesforce data directly in Snowflake via zero-ETL data sharing, enabling unified customer and business data, accelerating decision-making, and streamlining business processes. Today, we’re thrilled to share that customers can now also share Snowflake data into the Salesforce Data Cloud, using the same zero-ETL innovation to reduce friction and quickly surface powerful insights across sales, service, marketing, and commerce applications. Data Cloud and Snowflake Bidrectional Data Sharing. Data Cloud and Snowflake Bidrectional Data Sharing Enterprises generate valuable customer data within Salesforce applications, while increasingly relying on Snowflake as their preferred data platform for storing, modeling, and analyzing their full data estate. This integration between Salesforce and Snowflake minimizes friction, data latency, scale limitations, and data engineering costs associated with using these two leading platforms. The Snowflake Marketplace also offers customers the opportunity to acquire new data sets to enhance or fill gaps in their existing business data, driving innovation. By combining enterprise data and third-party data from Snowflake Marketplace with valuable customer data from Salesforce applications, organizations can unify their data and build powerful AI solutions to surface rich insights, driving superior and differentiated customer experiences. “Zero-ETL data sharing between Salesforce Data Cloud and Snowflake is game-changing. It has opened up new frontiers of data collaboration. We’re excited to see how customers are powering their customer data analytics and developing innovative AI solutions with near real-time data from Salesforce and Snowflake, generating incredible business value. Now that this integration is generally available, this kind of innovation will be broadly accessible,” says Christian Kleinerman, SVP of Product, Snowflake. Power Personalized Experiences with Salesforce and Snowflake Data sharing between Salesforce Data Cloud and Snowflake brings together holistic insights, empowering multiple customer-facing departments within any organization to create a truly robust customer 360. As Snowflake’s Chief Marketing Officer, Denise Persson, often states, a true, enterprise-wide customer 360 is the beating heart of a modern, customer-facing organization. The applicability of this integration spans various industries and unlocks new growth opportunities. For example: The bidirectional integration enables data sharing across business systems, Salesforce clouds, and operational systems, facilitating data set analysis and future action planning. This brings actionable insights and drives actions, unleashing a new level of customer experience and business productivity. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Salesforce and Snowflake

Is Snowflake a Data Cloud?

Is Snowflake recognized as a data cloud? Certainly, Snowflake stands as an encompassing platform integral to the Data Cloud. Uniquely designed for global connectivity, it empowers businesses to navigate diverse data types and scales, accommodating various workloads and fostering seamless data collaboration. Globally, over 400 million SaaS data sets often remain isolated in cloud storage and on-premise data centers, creating data silos. The Data Cloud, driven by Snowflake, eradicates these silos, facilitating the effortless consolidation, analysis, sharing, and monetization of data. Is Snowflake categorized as a database or cloud? Snowflake exclusively operates on cloud infrastructure. With all components residing in public cloud infrastructures (excluding optional command line clients, drivers, and connectors), Snowflake utilizes virtual compute instances for computing needs and a storage service for persistent data storage. What characterizes a data cloud? A data cloud serves as a unified platform for structured, unstructured, or semi-structured data, simplifying data discovery and reducing complexity. It should be capable of collecting, ingesting, and processing data from various on-premises or cloud-based source systems, consolidating it into a single accessible location. Snowflake’s Data Cloud facilitates organizations in effortlessly unifying and connecting to a single copy of all their data. This results in an ecosystem where businesses connect not only to their individual data but also to each other, seamlessly sharing and consuming data and data services. How does Snowflake’s Data Cloud handle different workloads? Snowflake’s Data Cloud efficiently powers diverse data workloads, including Data Warehousing, Data Lake, Data Engineering, AI and ML, Applications, and Cybersecurity. It operates seamlessly across multiple cloud providers and regions, catering to organizational needs from any location within the organization. What storage type does Snowflake employ? Snowflake utilizes scalable Cloud blob storage for its storage layer, accommodating data, tables, and query results. This storage is designed to scale independently from compute resources, allowing customers to adjust storage and analytics requirements independently. Is Snowflake considered a data warehouse or ETL? Snowflake’s capabilities in data loading, transformation, and storage eliminate the need for additional ETL tools, providing an end-to-end solution. Renowned worldwide, many organizations have adopted Snowflake as their primary Data Warehousing solution due to its distinctive features, scalability, and security. Where is Snowflake’s data stored? Snowflake’s database storage layer resides in a scalable cloud storage service, such as Amazon S3, ensuring data replication, scaling, and availability without requiring customer management. The data is optimized and stored in a columnar format within the storage layer, following user-specified database organization. How does Snowflake’s architecture benefit organizations? Snowflake’s architecture offers near-unlimited storage and real-time computing to an extensive number of concurrent users within the Data Cloud. It enables organizations to execute critical workloads on a fully managed platform, leveraging the cloud’s near-infinite resources. What are the advantages of Snowflake’s single platform? Snowflake’s single platform delivers optimal workload performance, full automation, secure global collaboration, Snowflake capabilities for non-SQL code processing, and optimized storage. It encompasses features such as Elastic Multi-Cluster Compute, Cloud Services, and Snowgrid, providing businesses with a comprehensive and fully managed solution. Why opt for Snowflake over competitors? Snowflake’s main advantage lies in its multi-cloud capability, available on major platforms like Azure, AWS, and GCP. This flexibility benefits companies operating in multi-cloud environments, enabling them to query Snowflake data directly from any of these platforms. About Snowflake Inc. Snowflake Inc., an American cloud computing-based data cloud company located in Bozeman, Montana, was founded in July 2012 and publicly launched in October 2014. Operating as a data-as-a-service provider, Snowflake offers cloud-based data storage and analytics services. Like Related Posts CRM Cloud Salesforce What is a CRM Cloud Salesforce? Salesforce Service Cloud is a customer relationship management (CRM) platform for Salesforce clients to Read more How Travel Companies Are Using Big Data and Analytics In today’s hyper-competitive business world, travel and hospitality consumers have more choices than ever before. With hundreds of hotel chains Read more Capture Initial Traffic Source With Google Analytics To ensure the proper sequencing of Tags, modify the Tag sequencing in the Google Analytics preview Tag settings. The custom Read more Snowflake and Salesforce with Embed Snowflake has deepened its partnership with investor Salesforce by introducing two tools that seamlessly connect their cloud-native systems. Snowflake and Read more

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Salesforce Data Cloud

Salesforce Data Cloud vs Snowflake

A Comprehensive Comparison In the today’s data-driven world, businesses increasingly turn to cloud-based data platforms for managing, analyzing, and deriving insights from their customer data. Among the prominent options available, Salesforce Data Cloud and Snowflake stand out from the crowd. While both platforms offer robust capabilities, they exhibit distinct strengths and weaknesses. This insight looks into the comparison of Salesforce Data Cloud vs Snowflake. Salesforce Data Cloud: Salesforce Data Cloud is a hyperscale customer data platform (CDP) designed to help businesses consolidate all their customer data, including engagement data sourced externally. It establishes a unified view of the customer, empowering businesses to personalize experiences, enhance decision-making, and foster growth. Snowflake: Snowflake is a cloud-based data warehousing platform that facilitates the storage, analysis, and sharing of data for businesses. It encompasses a wide array of features, including an awesome SQL engine, elastic scalability, and compatibility with various data sources. Salesforce Data Cloud vs Snowflake Feature Salesforce Data Cloud Snowflake Focus Customer data General data Strengths Data enrichment, personalization, real-time updates Scalability, analytics, SQL support Weaknesses Less flexible than Snowflake, limited analytics capabilities Not as user-friendly as Salesforce Data Cloud Pricing Based on data volume Based on usage The ideal platform for you will be contingent on your specific needs and requirements. If your primary focus is on managing customer data and enhancing customer engagement, Salesforce Data Cloud proves to be a suitable option. On the other hand, if you require a more versatile data platform capable of handling a broad range of data types and workloads, Snowflake emerges as a better choice. Additional considerations include: Ultimately, the most effective way to determine the right platform for you is to experiment with both and assess which one aligns better with your preferences. Contact Tectonic today to explore Data Cloud and Snowflake for your data needs. Like2 Related Posts Top Ten Reasons Why Tectonic Loves the Cloud The Cloud is Good for Everyone – Why Tectonic loves the cloud You don’t need to worry about tracking licenses. Read more 50 Advantages of Salesforce Sales Cloud According to the Salesforce 2017 State of Service report, 85% of executives with service oversight identify customer service as a Read more CRM Cloud Salesforce What is a CRM Cloud Salesforce? Salesforce Service Cloud is a customer relationship management (CRM) platform for Salesforce clients to Read more How Travel Companies Are Using Big Data and Analytics In today’s hyper-competitive business world, travel and hospitality consumers have more choices than ever before. With hundreds of hotel chains Read more

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Marketing Cloud Cloudpages

Salesforce Marketing Cloud for a Healthcare Provider

Personalized Care & Communication: Salesforce Marketing Cloud for a Healthcare Provider As the elderly become more tech-savvy, they expect modern, efficient ways to communicate with healthcare providers. A regional Medicare provider in the Northeastern United States faced challenges with their outdated communication systems. Relying solely on paper mail, postcards, and phone calls, the organization struggled to connect with members, lacked visibility into the success of their campaigns, and experienced early turnover due to minimal engagement. These inefficiencies strained the customer experience and made it clear that modernization was overdue. To address these challenges, we implemented Salesforce Marketing Cloud to engage customers through email and SMS. Goals for the Project: Tectonic’s Role in the Transformation Tectonic designed and implemented a Salesforce Marketing Cloud solution that transformed how the provider communicated with its members. The solution enabled multi-channel, multi-language communications integrated with Salesforce Health Cloud via the Marketing Cloud Connector and additional systems like MuleSoft and Snowflake. To enhance SMS capabilities, the organization also integrated with Five9. Early collaboration with the provider’s Salesforce Health Cloud team enabled Tectonic to address outdated customer data issues, create safeguards for inaccurate information, and plan future strategies for seamless customer data collection. A custom preference center was also developed and translated into multiple languages. Overcoming Data Challenges Accurate customer data was a significant obstacle—only 60% of records included valid email or mobile phone numbers, with an even smaller percentage having both. Tectonic conducted multiple working sessions to develop strategic efficiencies and establish a foundational process for gathering and cleansing member contact information. Customized journeys were created to ensure messaging aligned with available communication channels. For example: Key Outcomes Tectonic’s efforts allowed the healthcare provider to modernize their communications, better analyze engagement data, and improve member interactions. The results exceeded expectations: Impact Across Departments This project not only improved member communication but also empowered internal departments—including Marketing, Customer Experience, Sales, and Retention—with easy-to-understand metrics. It laid the foundation for future campaigns, enhanced data accuracy, and fostered stronger member relationships. By leveraging Salesforce Marketing Cloud and Tectonic’s expertise, the healthcare provider transformed its operations to deliver personalized, timely communication and ensure lifelong member satisfaction. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Data Cloud Credits

Data Cloud Credits

Credits are the currency of usage in Salesforce Data Cloud, where every action performed consumes credits. The consumption rate varies based on the complexity and compute cost of the action, reflecting different platform features. Data Cloud Pricing Model The pricing model for Data Cloud consists of three primary components: Data Service Credits Each platform action incurs a specific compute cost. For instance, processes like connecting, ingesting, transforming, and harmonizing data all consume ‘data service credits’. These credits are further divided into categories such as connect, harmonize, and activate, each encompassing multiple services with differing consumption rates. Segment and Activation Credits Apart from data service credits, ‘segment and activation credits’ are consumed based on the number of rows processed when publishing and activating segments. Monitoring Consumption Currently, Data Cloud users must request a consumption report from their Salesforce Account Executive to review credit and storage usage. However, the new Digital Wallet feature in the Summer ’24 Release will provide users with real-time monitoring capabilities. This includes tracking credit and storage consumption trends by usage type directly within the platform. Considerations and Best Practices To optimize credit consumption and ensure efficient use of resources, consider the following best practices: Final Thoughts Credits are integral to Data Cloud’s pricing structure, reflecting usage across various platform activities. Proactive monitoring through the Digital Wallet feature enables users to manage credits effectively, ensuring optimal resource allocation and cost efficiency. Content updated June 2024. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Crucial Role of Data and Integration in AI at Dreamforce

The Crucial Role of Data and Integration in AI at Dreamforce

Understanding The Crucial Role of Data and Integration in AI at Dreamforce At this year’s Dreamforce, AI is the star of the show, but two essential supporting actors are data and integration. Enterprises are increasingly recognizing the importance of unifying their diverse data sources for effective analysis and swift action, and the race to harness AI makes this integration even more critical. Integration is key not only for merging data but also for automating end-to-end processes, enabling organizations to move faster and deliver better outcomes to customers. Crucial Role of Data and Integration in AI at Dreamforce. It’s no surprise that MuleSoft, acquired by Salesforce five years ago, is now a major contributor to Salesforce’s growth. Brian Millham, President and COO at Salesforce, highlighted this during the company’s recent Q2 earnings call: “In Q2, nearly half of our greater than $1 million deals included MuleSoft. As customers integrate data from all sources to drive efficiency, growth, and insights, MuleSoft has become mission-critical and was included in half of our top 10 deals.” Breaking Down Silos Param Kahlon, EVP and General Manager for Automation and Integration at Salesforce, recently discussed the investments customers are making in data and integration. He emphasized the importance of breaking down operational silos: “We are in the business of breaking silos across systems to ensure that data can travel seamlessly through multiple systems and people for processes like order-to-cash or procure-to-pay. Our technology connects these dots.” The surge in AI interest has increased the urgency to act, as Kahlon explained: “Creating data repositories for AI algorithms requires real-time data across silos, driving significant demand for our integration solutions.” Consolidating Data Enterprises have long struggled with data consolidation due to monolithic application stacks with separate data stores. This has been a challenge even within Salesforce’s own products. Last year, Salesforce introduced a Customer Data Platform (CDP) called Data Cloud, which includes a real-time data layer named Genie. Kahlon elaborated on its significance: “Data Cloud’s strength lies in its understanding and storage of Salesforce metadata. This native integration allows for real-time actions within Salesforce, enhancing the ability to aggregate, reason over, and act on data.” For example, when a customer contacts a bank, Data Cloud can compile their ATM usage, website interactions, and recent support cases, providing the agent with a comprehensive view to better assist the customer. Leveraging Metadata for AI Salesforce’s metadata layer, which has been fine-tuned over two decades, gives it a distinct advantage. Kahlon noted: “This metadata-based architecture allows us to create meaningful AI algorithms that are natively consumed within Salesforce, enabling visualization and action based on real-time data.” This is crucial for training the underlying Large Language Model (LLM) accurately, ensuring generated content is contextually grounded and trustworthy. Kahlon emphasized: “The trust layer is essential. We need to ensure no hallucination or toxicity in the LLM’s responses, and that communications align with our company’s values.” Real-Time Data and API Management Data Cloud’s ability to connect to other data sources like Snowflake without duplicating data is a significant benefit. Kahlon commented: “Duplicating data is not desirable. Customers need real-time access to the actual source of truth.” On the integration front, APIs have simplified connecting applications and data sources. However, managing API sprawl is crucial. Kahlon explained: “Standardizing API use and publishing them in a centralized portal is essential for reusability and consistency. Low-code platforms and connectors are becoming increasingly relevant, enabling business users to access data without relying on IT.” Automation and AI The demand for automation is growing, and low-code tools are vital. Instead of integration experts being overwhelmed, organizations should establish Centers for Excellence to focus on creating reusable connectors and automations. Kahlon added: “Companies need low-code tools to involve more business users in the transformation journey without slowing down due to legacy applications.” In the future, AI may further ease the workload on integration specialists. MuleSoft recently introduced an API Experience Hub to make APIs discoverable, and AI might eventually help monitor execution logs and manage APIs more effectively. Kahlon concluded: “AI could help developers find and use APIs efficiently, enhancing security and governance while simplifying access to data across the organization.” Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Scale Data and Analytics in the Cloud

Scale Data and Analytics in the Cloud

Winning in the Data Economy In the rapidly growing data economy, enterprises are eager to gain a competitive edge. This data economy, which revolves around the global supply and demand for data and data-driven applications, continues to expand as more organizations seek critical insights to drive their success. Scale Data and Analytics in the Cloud. The value of data isn’t a new concept. Companies acquired other companies for the sole purpose of obtaining their data – customers, prospects, etc. The value of actionable data is a bit newer. Whereas we once marketed to prospects based primarily on historical data, data-driven applications let us market at the right time on the right channel with the right message. To understand what it takes to excel in the new data economy, Tableau partner Snowflake surveyed business and technology leaders. Their research highlighted the characteristics of the leaders and laggards, emphasizing the importance of a strong data strategy for achieving successful outcomes. Industries like financial services, health and life sciences, and retail are still struggling to fully benefit from the data economy, often finding it challenging to unlock the full value of their data. Here are four key actions that can help organizations win in today’s data economy and achieve tangible results: 1. Create a Strong Data Culture A robust data culture is foundational for realizing the value of data. Organizations that prioritize becoming data-driven see significant benefits: Jennifer Belissent, Principal Data Strategist at Snowflake, emphasizes how a cloud-enabled data culture accelerates time-to-value by breaking down organizational silos. Tableau offers a playbook to help organizations build, expand, and mature their data capabilities. 2. Adopt an AI-Driven, Enterprise-Ready Analytics Platform Data leaders utilize AI-driven enterprise analytics platforms like Tableau, which provide trusted predictions and insights to scale decision-making. Traditional solutions often fall short in delivering speed to insight and self-service capabilities. Tableau, particularly with Tableau Cloud, offers an easy-to-scale solution that manages and analyzes data across various sources, supporting meaningful impact and agility. Tableau Cloud’s Advanced Management capabilities enhance security, usability, and scalability. Additionally, Tableau Accelerators—over 100 ready-to-use, in-product dashboard starters—support various industries, enabling comprehensive analysis and problem-solving. 3. Migrate to the Cloud Cloud adoption is accelerating as organizations pursue data-driven digital transformations. The cloud offers flexibility, agility, scalability, reduced IT overhead, and increased resilience and performance. Key considerations for cloud migration include: Whether opting for on-premise, hybrid, or full cloud migration, Tableau connects to data wherever it resides, fueling insights across the business. Tableau’s own journey to the cloud involved evaluating criteria, enhancing collaboration, and applying new data management processes, resulting in a unified source of truth. 4. Choose the Right Partners to Scale Cloud-Native Analytics Selecting partners that facilitate cloud-native analytics is crucial. Ideal partners should offer: Snowflake and Tableau exemplify these qualities, addressing data and organizational demands. Snowflake provides extensive data storage and processing, while Tableau offers intuitive, self-service analytics. This partnership has helped enterprises like Cart.com achieve significant revenue growth by embedding Tableau analytics in Snowflake’s platform. Embrace the Data Economy with Cloud-Native Analytics Regardless of where your organization stands in the data economy, taking steps to leverage cloud-native analytics can unlock numerous opportunities. Tableau continues to invest in its platform to help organizations thrive with data in the cloud, offering expert advice, solutions, and valuable partnerships. By adopting these strategies, your organization can become a leader in the data economy and achieve remarkable results. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Salesforce and Snowflake

What Makes Snowflake So Popular?

Why opt for Snowflake over its competitors? What Makes Snowflake So Popular? One of Snowflake’s standout features is its multi-cloud capability, being accessible on major cloud platforms like Azure, AWS, and GCP. This is particularly advantageous for companies operating in multi-cloud environments, as they can seamlessly query Snowflake data from any of these platforms. Snowflake distinguishes itself as a true self-managed service, eliminating the need for users to handle hardware selection, installation, configuration, or management. Moreover, there is minimal software involvement, with ongoing maintenance, management, upgrades, and tuning efficiently managed by Snowflake. If your scaling requirements are primarily related to data warehousing, Snowflake’s data-centric scalability makes it a preferred choice. On the other hand, AWS might be more suitable for general infrastructure scalability across diverse cloud infrastructure components. Organizations opt for Snowflake’s cloud-built data warehouse to achieve significant benefits. These include reducing query times from hours to seconds, providing universal access to all business users, handling structured and semi-structured data swiftly, and doing so more cost-effectively compared to other data analytics platforms. Snowflake’s storage and compute separation enables seamless sharing of live data across business units, eliminating the need for data marts or maintaining multiple data copies. The flexibility to scale virtual warehouses based on specific needs, without concerns about underlying hardware, sets Snowflake apart. Additionally, its pricing model and central data repository contribute to enhanced flexibility, scalability, and cost-effectiveness. Furthermore, Snowflake allows users to share data with partners and customers, irrespective of region or cloud, fostering collaboration on a global scale. If you would like learn more about Snowflake cloud-build data warehouse, contact Tectonic today. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Salesforce Data Cloud Explained

Salesforce Data Cloud Explained

Salesforce Data Cloud, previously recognized as Salesforce CDP/Genie, made its debut at Dreamforce 2022, hailed by Salesforce as one of the most significant innovations in the company’s history. A hyperscale data platform built into Salesforce. Activate all your customer data across Salesforce applications with Data Cloud. Data Cloud facilitates the intake and storage of real-time data streams on a massive scale, empowering automated tasks that result in highly personalized experiences. Data can be sourced from diverse Salesforce data outlets, including Mulesoft, Marketing Cloud, and others, along with customers’ proprietary applications and data sources. Subsequently, it can dynamically respond to this real-time data by automating actions across Salesforce CRM, Marketing Cloud, Commerce, and more, inclusive of automating actions through Salesforce Flow. What is the Salesforce data cloud? Data Cloud is the fastest growing organically built product in Salesforce’s history (i.e. Salesforce built it themselves, not via acquisitions). Data Cloud could be described as the ‘Holy Grail of CRM’, meaning that the data problem that’s existed since the infancy of CRM is now finally solvable. Data Cloud is the foundation that speeds up the connectivity between different ‘clouds’ across the platform. However, Data Cloud is also a product that can be purchased. While not all Salesforce customers have licensed Data Cloud, being at the foundation means they are still taking advantage of Data Cloud to a degree – but this all becomes even stronger with Data Cloud as a personalization and data unification platform. What is the history of Data Cloud? Salesforce has gone through several iterations with naming its CDP product: Customer 360 Audiences → Salesforce CDP → Marketing Cloud Customer Data Platform → Salesforce Genie → Salesforce Data Cloud. In some instances, changes were made because the name just didn’t stick – but what’s more important to note, is that some of the name changes were to indicate the significant developments that happened to the product. Salesforce Data Cloud Differentiators Data Cloud, in itself, is impressive. While many organizations would consider it expensive, if you were to flip the argument on its head, by buying your own data warehouse, building the star schema, and paying for ongoing compute storage, you’d be looking to spend 5 to 10 times more than what Salesforce is charging for Data Cloud. Plus, data harmonization works best when your CRM data is front and center. There are other key differentiators that helps Data Cloud to stand out from the crowd: Is data cloud a data lakehouse? That means that Data Cloud is now not just a really good CDP, it’s now a data lake which will be used in sales and service use cases. But it also means that we can start to fundamentally move some of our higher-scale consumer products like Marketing and Commerce onto the platform. Is Snowflake a data Lakehouse? Snowflake offers customers the ability to ingest data to a managed repository, in what’s commonly referred to as a data warehouse architecture, but also gives customers the ability to read and write data in cloud object storage, functioning as a data lake query engine. What is the benefit of Salesforce data cloud? Data Cloud empowers Salesforce Sales Cloud with AI capabilities and automation that quickly closes deals and boosts productivity across every channel. It drives customer data from all the touchpoints and unifies it separately in individual customer profiles. Salesforce Data Cloud is a powerful data warehouse solution that allows companies to effectively manage and analyze their data. What is the difference between Salesforce CDP and data lake? Talking abut Salesforce CDP is a little bit like a history lesson. While a CDP provides a unified, structured view of customer data, a data lake, on the other hand, is more of a raw, unstructured storage repository that holds a vast amount of data (more than just customer data) in its native format until it’s needed. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Salesforce Loyalty Management

Salesforce Loyalty Program Explained

Loyalty Management enables you to customize programs that precisely align with the unique needs of your business and customer base. Salesforce, equipped with a flexible platform, aids businesses in reimagining their loyalty strategies. The Salesforce Loyalty Cloud empowers businesses across various industries to effortlessly build intelligent loyalty programs without the need for coding. These programs incentivize customers to engage more with the brand, fostering repeat business. Salesforce Loyalty Program Explained. Unleash the full potential of your Customer Loyalty platform through impactful features: The centralized program management feature allows you to configure loyalty programs tailored to your needs, activate segments across channels quickly, and iterate based on results. Improved customer engagement uses behavior analysis to optimize experiences across web and mobile, tailoring them to individual users. Cross-industry partnerships provide customers with more options, and fast time-to-market for referral promotions is facilitated through a guided setup wizard. Identifying brand advocates and implementing AI-powered referral programs with predictive dashboards enhance program impact. Personalizing promotions based on member data and utilizing predictive performance insights maximize engagement and ROI. A single customer view connects loyalty across the customer experience, triggering marketing journeys and providing insights for enhanced interactions. Elevate your loyalty initiatives, engage customers effectively, and drive business growth with the robust capabilities of the Customer Loyalty platform and the expert guidance from Tectonic. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Snowflake Database

Snowflake Database

What is Snowflake Database? Snowflake Database serves as the repository for an organization’s structured and semi-structured data sets, facilitating processing and analysis. It offers automated management of various aspects of data storage, including organization, structure, metadata, file size, compression, and statistics. Snowflake: The Global Data Cloud Platform Snowflake stands as a unified global platform powering the Data Cloud, connecting businesses worldwide across diverse data types, scales, and workloads, fostering seamless data collaboration. Understanding Snowflake Database Snowflake, a relational database hosted in the cloud, serves as a data warehousing solution. Leveraging infrastructure from Google Cloud Platform, Azure, and AWS, it combines traditional database features with innovative functionalities. Snowflake: More Than Just a Data Warehouse Snowflake’s Data Cloud encompasses a pure cloud-based SQL data warehouse, uniquely engineered to handle all data and analytics aspects. It offers high performance, concurrency, simplicity, and affordability unmatched by other data warehousing solutions. Snowflake Database’s Role in ETL Processes Snowflake streamlines data loading, transformation, and storage, eliminating the need for additional ETL tools. Its unique features, scalability, and security have led many organizations worldwide to adopt it as their primary Data Warehousing solution. Snowflake’s Integration with SQL and Python Built on a new SQL database engine, Snowflake’s data warehouse architecture is tailored for the cloud. Moreover, Snowflake provides first-class Python APIs for managing core resources, enabling seamless integration without SQL queries. Challenges and Advantages of Snowflake Despite its advantages such as scalability, performance tuning, and data security, Snowflake faces challenges like higher costs and limited support for unstructured data. Snowflake’s Position in Comparison to Other Databases Snowflake offers faster, easier-to-use, and more flexible data storage and analytic solutions compared to traditional offerings. It is not built on existing database technology or big data software platforms like Hadoop. Ownership and Integration Snowflake operates on major public clouds like AWS, Azure, and GCP, offering pre-warmed virtual machines to support rapid compute. Salesforce had a stake in Snowflake but sold its holdings, making Snowflake an independent entity. Snowflake vs. Salesforce: Choosing the Right Solution Snowflake is preferable for businesses requiring a versatile data platform, whereas Salesforce Data Cloud suits organizations already using Salesforce products due to its seamless integration. Some companies utilize both platforms for diverse needs. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Salesforce Genie Announced

Salesforce Genie Announced

Salesforce Genie announced this year is an innovative data platform recently unveiled at Dreamforce 2022, heralding the world’s first real-time CRM. Genie is the driving force behind Salesforce’s entire Customer 360 platform, delivering hyper-scale, real-time data capabilities. With Genie, any business can harness the power of data to create magical customer experiences, offering seamless, personalized interactions across sales, service, marketing, and commerce. It adapts effortlessly to evolving customer needs. Consider scenarios we encounter daily: the frustration of lengthy customer support calls navigating purchase history, or the challenge of locating specific items on cluttered e-commerce websites. These situations underscore the demand for real-time updates in every customer interaction, a demand that Genie aims to fulfill. In the last 12 hours alone, the volume of stored customer data worldwide has doubled, explaining the delays in customer support. However, with Salesforce Genie, businesses can make sense of their data regardless of source, system, or channel. This unified data drives unprecedented levels of personalization, akin to magic. Salesforce Genie’s Key Features: Genie is pivotal for various industries leveraging Salesforce, like banks managing vast customer records and administrative tasks. Salesforce aims to enhance data utilization without altering existing approaches. Comparison with Salesforce CDP: Genie transcends traditional Customer Data Platforms (CDPs) by: How Genie Works: Genie ingests and stores real-time data streams at scale, integrating them seamlessly with Salesforce data. It consolidates data from diverse channels, legacy systems via MuleSoft, and proprietary data lakes through connectors. Core Pillars of Salesforce Genie: Salesforce Genie’s Extensibility: Genie partners with leading data providers such as Snowflake and Amazon SageMaker, enabling seamless integration and real-time data sharing without data movement. Unified Customer 360 Use Cases: Genie unifies data across Salesforce’s Customer 360 products for various departments: In essence, Salesforce Genie revolutionizes data integration and utilization, enabling businesses to deliver unparalleled customer experiences across all touchpoints. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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