Salesforce Data Archives - gettectonic.com - Page 9

Measures for Granular Calculated Insights

Add More Measures to Calculated Insights Now you can add more measures to your calculated insights to achieve an improved result. The max number of measures per calculated insight has increased from 5 to 20. View Calculated Insights in Builder Now it’s easier to review the objects, filters, relationships, and logic that you selected for a Calculated Insight. When you use the Insight Builder to create a Calculated Insight, you can view insight logic in the builder and in SQL. Where: This change applies to Lightning Experience in all editions. How: From Customer Data Platform, click Calculated Insights, and then click Show In Builder. Install or Update Data Kits That Power Standard Data Bundles Salesforce CRM data bundles are now powered by data kits to enable more scalable delivery and faster innovation for Salesforce CRM data bundles. As a Customer Data Platform Admin, you can install or update data kits that power Salesforce CRM data bundles. Where: This change applies to Lightning Experience in all editions. Exploring the Power of Calculated Insights (CI) Calculated Insights (CIs) in Salesforce Data Cloud enable you to define and compute complex, multidimensional metrics, offering a deeper understanding of your data. These insights help analyze performance across different dimensions—like channel-level activity or customer engagement metrics—empowering your organization to make data-driven decisions. For example, CIs can rank customers by engagement or spending, evaluate product performance, and uncover trends in purchasing or browsing behavior. Let’s walk through how to use CIs effectively, with examples and reporting guidance. Example 1: Simplifying Metrics with a Single Measure Consider a CI with one aggregatable metric, such as Lifetime Value (LTV). To report on this CI: When the report opens, all CI dimensions appear as groupings, while measures display as columns in a summary format. What Happens with CIs Containing More Than Three Dimensions? Currently, reports support up to three groupings. For CIs with more than three dimensions, the first three are automatically included, though you can replace one dimension with another. Salesforce plans to expand this limit in the future. For example, a CI with the dimensions brand, customer ID, and product category will default to these three groupings in a summary report. Example 2: Handling Complex Metrics Now, imagine a CI that includes: A measure is non-aggregatable when summing it wouldn’t provide meaningful results. For instance, summing rank values for 10 customers doesn’t make sense; instead, metrics like min or max can be applied. Reporting for Complex CIs: By default, reports group CI dimensions and display measures as columns in summary format. However, non-aggregatable measures depend on all dimensions being present. For example, Rank values rely on dimensions like Lead Source and Stage—if one dimension is removed, the related non-aggregatable measures will also be excluded to maintain data integrity. Using Calculated Insights in Real-World Scenarios Use Case 1: Optimizing Marketing Efforts Create a report on a CI that ranks web traffic sources and breaks them down by product category. Use Case 2: Enhancing Patient Engagement Develop a report on a unified patient profile CI, grouping patients by age group and health score. Use Case 3: Identifying High-Performing Channels Generate a CI report grouped by marketing channels and regions in your Customer Lifetime Value metric. Visualizing CIs in Reports You can add charts to your CI reports, adhering to the same restrictions as in Lightning Reports. This visualization capability enables you to uncover trends and share insights effectively. Calculated Insights unlock a powerful layer of reporting in Salesforce, offering flexibility, precision, and actionable intelligence. Whether optimizing marketing efforts, improving patient engagement, or refining customer segmentation, CIs empower teams to make data-driven decisions that drive success. 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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January 7, 2024in Data, Salesforce, Salesforce Data Cloud
Data Cloud Credits
12Dec

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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December 12, 2023in Salesforce Data Cloud, Snowflake
Salesforce Tableau Pulse
02Dec

Tableau Pulse

Tableau Pulse, fueled by Tableau Artificial Intelligence and exclusive to Tableau Cloud, revolutionizes the data ingestion experience. The ability to empower business users with intelligent, personalized insights seamlessly integrated into their workflows. Whereas once upon a time AI for the lay user was about as friendly as asking Siri a question which she Googles for an answer and reads back to you. It saves a few clicks and a little typing, but it isn’t exactly thinking outside of the box – or phone. In the current data analytics demanding world, characterized by generative AI, the Internet of Things (IoT), and automation, the landscape is evolving. Data is at the core of these transformative technologies, and our interaction with said data is changing rapidly. As businesses worldwide confront an inflection point, embracing data-driven decision-making becomes crucial for staying competitive and building robust customer relationships. Tableau Pulse is a reimagined data experience, democratizing data accessibility for all users, irrespective of their familiarity with data visualization tools. Exclusively available to Tableau Cloud users, Tableau Pulse harnesses Tableau AI’s power to deliver more personalized, contextual, and intelligent data experiences in an easy-to-understand format. Key Features of Tableau Pulse: Upcoming Tableau Pulse Features in 2024: Tableau Pulse aims to breathe new life into analytics for everyone, capitalizing on the potential of generative AI, automation, and sensors to redefine how businesses interact with data. In a landscape where success hinges on data utilization, Tableau Pulse is poised to empower every employee with personalized, contextual, and intelligent insights directly within their workflow, fostering a truly data-driven organizational culture. Imaging the industry specific use cases for travel and tourism, manufacturing, health and life sciences, and the public sector? If you have data you aren’t able to utilize, reach out to Tectonic today to discover how Tableau Pulse could solve your challenges. 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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December 2, 2023in Life Sciences Cloud, Salesforce Health and Life Sciences Solutions, Salesforce Hospitality Travel and Transportation, Salesforce Manufacturing Automotive Energy, Salesforce Tableau
Salesforce Shield Data Monitoring and Encryption
29Nov

Salesforce Shield Encryption

Salesforce Uses a symmetric encryption key to encrypt the customer data that it stores. (The symmetric encryption used isAES with 256-bit keys using CBC mode, PKCS5 padding, and random initialization vector (IV).) Salesforce Shield Encryption works in this way. 1) There are three channels to enter data into Salesforce.com. One: user via desktop using a browser, two: users via mobile device or three: a system making an API call directly into Salesforce. 2) The Application servers in the salesforce data centers serve as a gateway to intercepting requests coming in determining which data elements should be encrypted or decrypted and then applying the appropriate encryption credentials. The Data Encryption Key (which is also the decryption key) is never transmitted or even written to disk (persisted). 3) It is created/derived in the Salesforce Platform and never leaves. It is created in a component of the platform called the Key Derivation Server. The Encryption key is derived/created from a combination of a Salesforce component and customer/tenant specific component. These are called secrets. Sometimes they are also referred to as key fragments. 4) The Encryption key in Salesforce Shield Encryption is generated from the master secret (Salesforce component) and the tenant secret (customer component) using PBKDF2 (Password-Based Key Derivation Function 2). 5) The Derived data encryption key is then securely passed to the encryption service and held in the cache of an application server. – Salesforce Retrieve The Data Encryption Key from the cache and performs the encryption. – To decrypt the data Salesforce Reads the encrypted data from the database and if the encryption (decryption) key is not in the cache then it needs to derive it again using the associated tenant secret, and then it decrypts using the key and the associated iv. 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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November 29, 2023in Data, Salesforce, Salesforce Managed Services, Salesforce Shield
How Good is Our Data
28Oct

How Data Cloud and Salesforce Success Depend on Data Quality

Optimizing AI’s Impact on Your Business: The Crucial Role of Data Quality in Salesforce In the ever-evolving digital landscape, the convergence of data quality and artificial intelligence (AI) is a linchpin for organizational success. Success depends on data quality within the Salesforce ecosystem. The synergy between Einstein, an advanced AI system, and Data Cloud underscores the pivotal role of high-quality, comprehensive, and real-time data. Thereby unleashing the full potential of AI-driven insights and interactions with customers and prospects. Let’s explore how data quality profoundly influences these two emerging features. This insight will be shedding light on the repercussions of poor data quality and how Einstein and Data Cloud can elevate your organization to greater levels of sales success. Understanding Data Value Depends on Data Quality: Quality data extends beyond merely addressing duplicate records or inaccurate phone numbers It isn’t just about ensuring the area code field doesn’t contain zip codes. It is more than aligning contacts to accounts. It encompasses factors such as completeness, accuracy, and timeliness in your CRM: Consequences of Bad Data: Poor-quality data leads to inefficiencies and wasted time. Oftentimes causing flawed decision-making and strains on organizational resources. More critically, these poor business decisions often lead to tangible financial losses. Transforming bad data into quality data is imperative. Quality is key for relying on it to enhance company performance, requiring ongoing strategies rather than a one-stop solution. The Financial Impact of Accurate Data: Accurate data holds immense value. With data volumes projected to exceed 180 zettabytes by 2025, organizations must harness the power of their data. Proactive handling of data quality not only ensures higher data quality but also mitigates the financial impact of poor data quality. The sooner a plan is implemented to enhance and sustain data quality, the fewer negative repercussions organizations face in leveraging their data for growth. Your next decision is based on your last data. Is it going to help you or hurt you? Salesforce Einstein and the GIGO Principle: Salesforce Einstein, positioned as Artificial Intelligence for everyone, underscores trust as a core value. The system’s ability to create relevant and timely content and interactions is contingent on the quality of the data it operates on. Similar to the historical concept of “Garbage In, Garbage Out” (GIGO), AI results are only as reliable and valuable as the completeness and accuracy of the input data. No surprise, right? Introduction to Salesforce Data Cloud: Enter Salesforce Data Cloud, a platform allowing the organization and segmentation of customer data from any source. This open, extensible platform enables data enrichment from various sources, creating an optimal customer record. This enriched record empowers Sales, Service, and Marketing teams to perform intelligently and swiftly, ultimately driving enhanced results for the company. The WIIFM Factor: Amidst discussions about AI and Data Cloud, addressing the “What’s in it for me?” (WIIFM) question is crucial for organization adoption. Individual organizations must evaluate the reliability and accuracy of their data and determine forward-looking strategies for maintaining quality data, regardless of the source. The common theme remains: for data to yield valuable insights, it must be complete, timely, relevant, and accurate. Ultimately, success depends on data quality. Like3 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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October 28, 2023in Artificial Intelligence, Data, Salesforce, Salesforce Data Cloud, Salesforce Einstein, Salesforce Financial Cloud, Salesforce Managed Services, Salesforce Sales Cloud
Retrieval Augmented Generation in Artificial Intelligence
26Oct

RAG – Retrieval Augmented Generation in Artificial Intelligence

Salesforce has introduced advanced capabilities for unstructured data in Data Cloud and Einstein Copilot Search. By leveraging semantic search and prompts in Einstein Copilot, Large Language Models (LLMs) now generate more accurate, up-to-date, and transparent responses, ensuring the security of company data through the Einstein Trust Layer. Retrieval Augmented Generation in Artificial Intelligence has taken Salesforce’s Einstein and Data Cloud to new heights. These features are supported by the AI framework called Retrieval Augmented Generation (RAG), allowing companies to enhance trust and relevance in generative AI using both structured and unstructured proprietary data. RAG Defined: RAG assists companies in retrieving and utilizing their data, regardless of its location, to achieve superior AI outcomes. The RAG pattern coordinates queries and responses between a search engine and an LLM, specifically working on unstructured data such as emails, call transcripts, and knowledge articles. How RAG Works: Salesforce’s Implementation of RAG: RAG begins with Salesforce Data Cloud, expanding to support storage of unstructured data like PDFs and emails. A new unstructured data pipeline enables teams to select and utilize unstructured data across the Einstein 1 Platform. The Data Cloud Vector Database combines structured and unstructured data, facilitating efficient processing. RAG in Action with Einstein Copilot Search: RAG for Enterprise Use: RAG aids in processing internal documents securely. Its four-step process involves ingestion, natural language query, augmentation, and response generation. RAG prevents arbitrary answers, known as “hallucinations,” and ensures relevant, accurate responses. Applications of RAG: RAG offers a pragmatic and effective approach to using LLMs in the enterprise, combining internal or external knowledge bases to create a range of assistants that enhance employee and customer interactions. Retrieval-augmented generation (RAG) is an AI technique for improving the quality of LLM-generated responses by including trusted sources of knowledge, outside of the original training set, to improve the accuracy of the LLM’s output. Implementing RAG in an LLM-based question answering system has benefits: 1) assurance that an LLM has access to the most current, reliable facts, 2) reduce hallucinations rates, and 3) provide source attribution to increase user trust in the output. Retrieval Augmented Generation in Artificial Intelligence Content updated July 2024. Like2 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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October 26, 2023in Einstein 1 Platform, Generative AI, Salesforce, Salesforce Data Cloud
Hubspot vs Salesforce
21Oct

Hubspot vs Salesforce

HubSpot began as a marketing automation solution tailored for small businesses, but it has since grown into a comprehensive Enterprise CRM, integrating marketing, sales, CMS, and service functionalities. While Salesforce continues to be a popular choice for CRM, more teams are increasingly turning to HubSpot for its marketing automation capabilities. HubSpot is a leading platform in CRM, marketing, sales, and customer service software, with a clear mission: to empower companies to optimize their sales processes and drive growth. HubSpot offers a range of resources centered around its five main products or “Hubs,” with the Marketing Hub and Sales Hub being the most prominent. HubSpot vs. Salesforce: Key Differences Salesforce is known for its robust reporting and extensive customization options. In contrast, HubSpot offers a smoother learning curve, a more intuitive interface, and a comprehensive suite of marketing and sales tools, all available at an accessible price point, including a free tier. Integrating HubSpot with Salesforce Integrating HubSpot with Salesforce allows you to streamline operations, creating a seamless and efficient connection between the two platforms without the need for complex technical setup. Key Benefits of HubSpot-Salesforce Integration: Enhanced Data Management The HubSpot-Salesforce integration simplifies and accelerates data management by eliminating manual data transfers and reducing the risk of errors. Syncing all relevant business data to HubSpot in just a few clicks provides deep insights into customer interactions and preferences, enabling you to deliver personalized experiences that boost engagement and foster customer loyalty. Empowering Sales Teams The integration enables seamless bi-directional synchronization, giving your sales team critical lead intelligence. By customizing record syncing and providing lead scores from HubSpot to Salesforce, sales teams can prioritize their outreach efforts more effectively, ultimately leading to increased deal closures. Bridging the Gap Between Marketing and Sales Close the gap between marketing and sales by using Salesforce data to personalize emails, segment databases, and send emails on behalf of sales representatives. The integration eliminates the need for manual exporting and importing of lists and campaign responses, while also allowing you to track revenue from closed-won deals in HubSpot, attributing campaigns directly to the revenue they generate. 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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October 21, 2023in Marketing Automation
Salesforce CPQ
10Oct

Choosing a New Salesforce for Outlook Solution

6 Tips for Choosing a New Salesforce for Outlook Solution as an Email Tool: As you gear up for the transition, consider the following insights when selecting a replacement for Salesforce for Outlook: As you evaluate New Salesforce for Outlook Solutions, reach out to Tectonic for assistance in selecting the right solution for your 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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October 10, 2023in Salesforce, Salesforce Implementation Services, Salesforce Managed Services
Einstein 1 is Coming
09Oct

Einstein 1 is Coming

What Does the New Einstein 1 Data Cloud Mean for Your Organization? Einstein 1 is Coming One of the major announcements at Dreamforce was the exciting intro that Einstein 1 is Coming. The Einstein 1 Data Cloud is now natively integrated with the Einstein 1 Platform. This integration allows users to connect any data, create unified customer profiles, and enhance every customer experience with AI, automation, and analytics. This is a giant step for Salesforce-kind. It can revolutionize the ways businesses engage with their customers. While this announcement is exciting, what does it mean for organizations at different stages of their Salesforce journey? In this insight, we explore the announcement details, considerations for using the Einstein 1 Data Cloud in your company, and how Tectonic can assist in navigating this new offering. What’s New with the Platform? The integration of Salesforce Data Cloud and Einstein AI into the Einstein 1 Platform marks a significant enhancement. The platform integration enables companies to securely connect any data, build AI-powered apps with low code, and deliver superior CRM experiences. It unifies data across the enterprise by mapping it to Salesforce’s underlying metadata framework, regardless of how the data is structured in disparate systems. Regardless of how complex it is. What is Einstein 1 Data Cloud? The Key to Unified Data Salesforce Einstein 1 Data Cloud unifies customer data, enterprise content, telemetry data, Slack conversations, and other structured and unstructured data to create a single view of the customer. This integration unlocks otherwise siloed data and scales operations in new ways: Salesforce has announced that Enterprise Edition and above customers can use Data Cloud at no additional cost. However, organizations should consider their position on the Salesforce maturity curve before implementation. Data Cloud’s capabilities, while extensive, might not fully optimize data for organizations further along in their Salesforce journey without a thorough trial. What is the Einstein Conversational Assistant? An AI-Powered Shift Einstein now includes a generative AI-powered conversational assistant featuring Einstein Copilot and Einstein Copilot Studio. These tools operate within the Einstein Trust Layer, a secure AI architecture native to the Einstein 1 Platform that ensures data privacy and security. Why Should Organizations Consider Einstein 1? Customer data is often fragmented and siloed across disparate systems, preventing a unified view necessary for informed business decision-making. Data unification is essential for data-driven decision making and fully getting the full ROI of AI. AI is a major trend in technology, but effective AI requires comprehensive, aligned data. Without a unified data foundation, AI’s potential is limited. Einstein 1 with Data Cloud provides the solution by consolidating data, enabling the training of AI models to make optimal decisions and recommendations. How Can Tectonic Help You Transition? Tectonic brings extensive Salesforce expertise and industry-specific experience in sectors heavily reliant on data, such as healthcare, financial services, and travel and tourism. These industries face strict data regulations and often have siloed data in legacy systems. Einstein 1 helps organizations achieve a 360-degree view of their customers by unifying data. Tectonic can assist in maximizing AI on the Salesforce platform by building a robust data foundation and providing a roadmap for future scalability. While both Einstein 1 and AI Cloud are Salesforce terms that promise AI-driven capabilities, there are differences to consider. Einstein 1 Platform is a comprehensive suite that includes Data Cloud, AI tools, and automation capabilities. In contrast, AI Cloud is more of an overarching term that might encompass Einstein 1 as part of its suite, focusing on the broader application of AI across Salesforce’s entire range of products and services. Understanding these distinctions is critical in identifying which solution aligns with your organizational 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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October 9, 2023in Einstein 1 Platform, Mulesoft, Salesforce, Salesforce Data Cloud, Salesforce Einstein
Best Practices for Data Management
04Oct

Best Practices for Data Management

Mastering Data Management in Salesforce Effective data management is crucial for maximizing success with Salesforce. Ensuring you have high-quality, useful data empowers your team to achieve business goals and identify growth opportunities. Below are learning resources, expert articles, and video guides designed by Salesforce professionals to help you take control of your data. Build a Data Management Strategy A solid data management strategy ensures that your team is aligned on how data is collected, analyzed, and used to drive success. These resources will guide you through creating a strategy and avoiding common pitfalls: Improve Data Quality Clean data is essential for tracking, reporting, and ensuring the success of your Salesforce implementation. Explore the following resources to improve your data quality: Import Data Seamlessly bring existing data into Salesforce to ensure you have a full record for reporting and tracking. These resources will guide you through importing data: Maintain and Clean Up Data To keep your data clean and reliable over time, follow these best practices for long-term data management: Go Further with Data Management Take your data management expertise to the next level with these additional resources: These curated resources empower you to master data management within Salesforce, ensuring your organization makes the most of its CRM data to drive growth and success. Content updated September 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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October 4, 2023in Data, Salesforce
Einstein 1 Unveiled
03Oct

Einstein 1 Unveiled

Salesforce Unveils Einstein 1: Enhancing Productivity and Fostering Customer Trust through Data, AI, and CRM-Einstein 1 Unveiled In September, Salesforce introduced the Einstein 1 Platform, a groundbreaking advancement that merges the capabilities of Salesforce Data Cloud with Einstein AI. This innovative platform harnesses a trusted metadata framework, enabling companies to effortlessly connect data and build AI-driven applications with minimal coding, thereby revolutionizing CRM experiences. Why it Matters: With customer data scattered across an average of 1,061 applications and limited integration, Salesforce addresses the challenge of fragmented customer data stacks. The metadata framework bridges this gap by offering a unified view of enterprise data, allowing organizations to customize user experiences across low-code platform services like Einstein for AI predictions, Flow for automation, and Lightning for user interfaces. Data Cloud Integration: The Einstein 1 Platform now seamlessly integrates with Data Cloud, a real-time hyperscale data engine processing 30 trillion transactions per month and harmonizing various data sources to create unified customer profiles. This integration unlocks siloed data, facilitating rich customer profiles and enabling new CRM experiences. Scalability and Automation: The platform supports thousands of metadata-enabled objects per customer and can handle up to 20,000 events per second. It enables the integration of massive data volumes from various sources, triggering flows and interactions with enterprise systems, including legacy ones. Analytics Offerings: Salesforce provides a suite of analytics solutions, including Reports and Dashboards, Tableau, CRM Analytics, and Marketing Cloud Reports. The common metadata schema and access model of the Einstein 1 Platform allow these solutions to operate on the same data, delivering comprehensive insights. Free Access to Data Cloud: Customers with Enterprise Edition or above can now access Data Cloud at no cost, empowering them to ingest, harmonize, and explore their data, thereby accelerating their AI journey. Einstein’s Conversational AI Assistant: The next generation of Einstein introduces Einstein Copilot, an out-of-the-box conversational AI assistant embedded in every Salesforce application. Copilot enhances productivity by responding to natural language queries with secure, proprietary company data from Data Cloud. It also proactively suggests actions and options to users. Einstein Copilot Studio: Companies can develop custom AI-powered apps with Einstein Copilot Studio, which facilitates the creation of AI models for various business tasks, making it adaptable for consumer-facing channels and messaging platforms. Einstein Copilot and Einstein Copilot Studio operate within the secure Einstein Trust Layer, ensuring data privacy and security. Salesforce’s Einstein 1 Platform represents a significant milestone in AI-powered CRM, providing companies with a seamless way to leverage AI, streamline processes, and deliver exceptional customer experiences. By Tectonic Salesforce Marketing Architect, Shannan Hearne 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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October 3, 2023in Einstein 1 Platform, Einstein Insights, Salesforce
Shield
21Sep

Salesforce Shield Explained

Salesforce Shield Explained: It is tailored for companies with heightened security and compliance considerations. Comprising four products that layer onto existing Salesforce products, it provides additional protection. These components include: Salesforce Shield is best explained is a encryption and event monitoring and field audit trail tool for your business. Block Unauthorized or Unlawful ActivityCreate real-time security rules in an org to prevent undesired events with Event Monitoring.Find and Classify Sensitive Data QuicklyDiscover and classify sensitive data in just a few clicks with Data Detect.Add Additional Security to Sensitive DataEncrypt sensitive data at rest and manage keys with Platform Encryption.Meet Compliance and Industry RegulationsView data as far back as a decade with Field Audit Trail. Protect critical information at scale. Identify, categorize and encrypt data to mitigate threats and avoid costs associated with data loss. Three Reasons to Use Data Detect1 Integrates Seamlessly With native Salesforce software for ease of implementation and cost savings.2 Identifies Sensitive Data regardless of what field it is in, so you can take the necessary steps to obfuscate or protect it3 Classifies Sensitive Fields Use convenient UI to update data classifications as you discover fields with sensitive data Like2 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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September 21, 2023in Data, Salesforce, Salesforce Shield
Data Cloud Free Licenses
15Sep

Data Cloud Free Licenses

Salesforce Announces Data Cloud Free Licenses at Dreamforce 2023 At Dreamforce 2023, Salesforce announced that free Data Cloud licenses are now included for all Enterprise Edition or above customers to help them familiarize themselves with new capabilities and develop use case ideas. Starting September 19th, 2023, Enterprise Edition and above customers can get started with Data Cloud Provisioning at no cost by signing up under Your Account. Data Cloud Provisioning includes: Unlimited Plus Edition customers will get access to 2,500,000 Data Service credits. Two Tableau Creator licenses are a separate line item and can be quoted by your Salesforce Account Executive. Salesforce has been focusing on large data and AI tools for several years, acquiring Tableau, accelerating their Einstein AI tools, and significantly extending the Data Cloud product. Data Cloud allows you to easily harmonize data, analyze it in Tableau, and make it actionable across marketing, sales, and service. What Can I Do with Data Cloud? Data Cloud enables customers to start with one of three use cases: Across these use cases, customers can ingest data from multiple sources, unify data with identity resolution, calculate insights, visualize data in Tableau (with the provisioning of the Tableau Cloud – Creator for Data Cloud SKU), and view consolidated data on the contact record. Differences Between Data Cloud and Data Cloud Provisioning Functionality: Data Cloud Provisioning includes all the features of the existing Data Cloud offerings, except Segmentation and Activation. Credits for Segmentation and Activation can be purchased as add-ons through Marketing Cloud account teams. Capacity: Both include 1 TB of data storage, 1 Data Cloud admin, 100 internal Data Cloud identity users, 1,000 Data Cloud PSL, and 5 integration users. Entitlement: Data Cloud Provisioning entitlement is the same for all Enterprise Edition and above customers. Additional Information Sandbox Availability: Data Cloud is not available in Sandbox orgs; it can only be provisioned to an existing production org. Professional Edition Access: Data Cloud Provisioning is not available to Professional Edition customers. Existing Data Cloud or CDP Customers: Those with an existing Data Cloud or CDP tenant cannot sign up for Data Cloud Provisioning. Unlimited Edition Plus Bundle Customers: Data Cloud Provisioning is not available, as the bundle includes a Data Cloud tenant. Edition Information: Check your Salesforce org’s edition in Setup > Company Information > Organization Edition. Government Cloud: Data Cloud Provisioning is not available. Non-Profit Customers: Data Cloud Provisioning is available. Industry Cloud Customers: Industry Cloud customers with Enterprise Edition and above are eligible. ISV Partners: Data Cloud Provisioning is not accessible via Your Account in ISV Enterprise Edition orgs. ISV Partners need to create a support case with the Partner Ops team to request provisioning. Existing Tableau Customers: Tableau Cloud – Creator for Data Cloud is intended to provision a new Tableau tenant (aka site). Multiple Instances: Only one Data Cloud Provisioning instance is allowed per account/tenant. Access to Tableau Cloud – Creator for Data Cloud: To get access, you must have or include on the same quote any of the following: 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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September 15, 2023in Salesforce Data Cloud
Sales Cloud Einstein
11Sep

How Einstein Lead Scoring Works on Your Prospect Data

How Einstein Lead Scoring Works on Your Prospect Data By Shannan Hearne, Tectonic Marketing Consultant The love hate relationship between sales and marketing is based on lead quality.  Each party is tempted to blame the other for deals that fail to close.  Either marketing thinks the sales team dropped the ball following up with the prospect. Or the sales team thinks marketing failed to properly qualify the lead.  With Einstein Lead Scoring, the relationship between sales and marketing can improve. Not every lead holds the same significance, and relying on arbitrary details for accurate scoring is ineffective. Clicks, opens, and form fills vary in value for each lead, and visiting the Careers page does not necessarily diminish a lead’s potential.  Humans from both sales and marketing have to work together to craft scoring criteria that reflects behavior that great customers took before becoming customers.  The development of the scoring model is key to making Einstein Lead Scoring Works on Your Prospect Data. Einstein Lead Scoring, integrated with Sales Cloud Einstein, leverages artificial intelligence to enhance sales conversion efficiency. By automatically analyzing historical sales data and identifying key factors influencing lead conversion, sales reps can effectively segment and prioritize leads. With data supplied by Einstein running lead scoring in the background.  While the human factor is important, the speed of artificial intelligence to analyze data cannot be beaten. Tailored to individual business needs, Einstein Lead Scoring models analyze both standard and custom fields associated with the Lead object. By using predictive models like Logistic Regression, Random Forests, and Naive Bayes (definitions below). The system autonomously selects the best model based on a sample dataset, eliminating the need for statistical or mathematical expertise.  No more pouring through hours of spreadsheets sorting and creating pivot tables. Model Updates Regular model updates ensure accuracy. With leads being scored every hour using the latest model. This allows quick response to changes, ensuring that the prioritization of leads remains effective. The scoring factors are prominently displayed on the lead record page. Thus enabling sales reps to prepare for calls or emails efficiently with accurate engagement data. The true strength of Einstein Lead Scoring lies in its machine learning capabilities. Einstein is continuously refining predictions based on the latest Salesforce data. If new patterns emerge, such as VP titles in a specific industry showing interest in demos, Einstein automatically rescores leads meeting this criteria. Key benefits of Einstein Lead Scoring include increased connection and conversion rates, accelerated engagement with top leads, and a clear understanding of lead scoring factors. Important features encompass zero setup requirements, custom lead score-driven workflows for task assignments, and smart lead lists that prioritize the best leads for reps. Einstein Lead Scoring Works on Your Prospect Data For businesses utilizing or considering Salesforce Sales Cloud, consulting with Tectonic about integrating Einstein Lead Scoring can lead to faster implementation and deal closures. As your Salesforce implementation partner, Tectonic ensures a tailored Salesforce solution. Remaining aligned with your business needs, incorporating the powerful capabilities of Einstein tools within your Salesforce ecosystem.  Contact Tectonic today. Logistic regression estimates the probability of an event occurring, such as voted or didn’t vote, based on a given dataset of independent variables. Random forest is a commonly-used machine learning algorithm trademarked by Leo Breiman and Adele Cutler. It combines the output of multiple decision trees to reach a single result. Its ease of use and flexibility have fueled its adoption, as it handles both classification and regression problems. The Naïve Bayes classifier is a supervised machine learning algorithm, which is used for classification tasks, like text classification. It is also part of a family of generative learning algorithms, meaning that it seeks to model the distribution of inputs of a given class or category. 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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September 11, 2023in Einstein Insights, Salesforce Sales Cloud

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