Salesforce Data Cloud

01Apr

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 Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

April 1, 2024in Salesforce Data Cloud, Salesforce Marketing Cloud, Snowflake

31Mar

WhatsApp Integration Brings Service and Marketing Together

Salesforce has announced the general availability of Unified Conversations for WhatsApp, transforming one-way marketing promotions and service requests into dynamic, two-way conversations from a single WhatsApp number. WhatsApp Integration Brings Service and Marketing Together. Now, instead of managing separate threads for promotions and support, customers can receive personalized opt-in marketing promotions and individual support all within a single WhatsApp chat. This unified approach allows companies like Agibank to leverage Salesforce data from over 900 hubs within WhatsApp to deliver personalized loan proposals, resolve issues faster, and better support customers in a single conversation. Why It Matters A significant 79% of customers expect consistent interactions across departments, and 75% prefer to communicate with brands through messaging. However, businesses often fail to meet these expectations, with disconnected experiences being a top customer frustration. Salesforce Perspective “With over two billion people using WhatsApp, Salesforce’s Unified Conversations for WhatsApp enables brands to connect with customers in a unified, trusted manner,” said Steve Hammond, EVP and GM of Salesforce Marketing Cloud. “This helps brands break down internal barriers and build stronger relationships throughout the customer journey, ensuring personalized engagement at the right time and context.” Go Deeper Unified Conversations for WhatsApp is powered by Salesforce Data Cloud, allowing companies to consolidate data into Salesforce and create a unified customer profile. This shared profile provides marketers and service agents with the relevant context to deliver trusted experiences in a single chat thread. Innovation in Action Unified Conversations for WhatsApp combines marketing and service conversations, enabling: Customer Perspective Matheus Girardi, Chief Marketing and Customer Officer at Agibank, shared, “Our customers rely on WhatsApp to engage with us. Unifying our data in Salesforce for WhatsApp has improved our user experience by personalizing loan proposals, resolving concerns, and supporting customers. Salesforce’s previous integration with WhatsApp tripled our digital sales, and we are excited to do more.” Roberto Maia, Chief Information Officer at YDUQS, added, “WhatsApp is the preferred messaging app for our students across Brazil. We look forward to utilizing Unified Conversations to better engage and serve them and convert leads faster.” Availability Unified Conversations for WhatsApp is now generally available. More Information 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 Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

March 31, 2024in Salesforce Data Cloud, Salesforce Implementation Services, Salesforce Marketing Cloud, Salesforce Optimization, Salesforce Service Cloud

26Mar

Salesforce Data Cloud Free Edition

Let Tectonic clarify a misconception circulating in the Salesforce community regarding the Salesforce Data Cloud Free Edition. As you may recall, Salesforce unveiled at Dreamforce 2023 that a Data Cloud edition would be accessible at no charge to clients using Sales and Service Cloud Enterprise Edition. This announcement was also reiterated in Salesforce’s February 2024 press release focusing on Marketing Cloud Growth Edition. (Queue the voice in the commercial “some restrictions may apply”.) To dispel any confusion, it’s essential to emphasize there is potential benefit from this offer, but you still require Sales or Service Enterprise Edition. Merely having Marketing Cloud or Account Engagement does not make you eligible. Salesforce Data Cloud Free Edition Considerations For Sales and Service Enterprise Edition Customers wondering about the no-cost Data Cloud offer, the next steps require careful consideration. While the prospect of getting an account provisioned might be exciting, preparation is key. Data Cloud holds the potential to revolutionize your organization, making a well-crafted plan, strategy, and vision imperative. These elements form the basis and foundation of effective change management. Without a comprehensive plan, vision, consensus, and understanding, embarking on Data Cloud implementation could lead to various challenges: Drawing from our experience, diving into Data Cloud without a clear plan often results in these issues. However, before formulating a plan, it’s vital to assess your organization’s readiness based on several key criteria. These factors impact the feasibility of implementing Data Cloud: Data Cloud Readiness Criteria: Respectfully, while the prospect of a no-cost Data Cloud offer is exciting, careful preparation, assessment, and strategic planning are crucial for ensuring a successful and transformative implementation within your organization. Otherwise, it becomes just another unused tool in your martech stack. Like Related Posts 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 Integration of Salesforce Sales Cloud to Google Analytics 360 Announced In November 2017, Google unveiled a groundbreaking partnership with Salesforce, outlining their commitment to develop innovative integrations between Google Analytics Read more

March 26, 2024in Salesforce Data Cloud, Salesforce Sales Cloud

14Mar

Marketing Cloud Growth Edition

Salesforce has unveiled the Marketing Cloud Growth Edition, (Marketing Cloud Engagement) offering a glimpse into the future of marketing applications aligned with the core Salesforce platform. This edition marks the first iteration of Marketing Cloud on the ‘core’ Salesforce platform, known as Einstein 1 Platform. Built on Data Cloud, it introduces new builders powered by Salesforce CMS, a data model tapping into Salesforce objects, and a suite of data management capabilities through Data Cloud and Einstein’s generative AI tools. It’s crucial to understand that while this edition brings new functionality, Salesforce remains committed to innovating existing Marketing Cloud products as well. Marketing Cloud Growth Edition targets B2B SMB organizations, offering lead capture, cross-channel journeys, engagement scoring, and reporting capabilities. Built on Einstein 1 Built on Einstein 1, Marketing Cloud Growth Edition leverages Data Cloud’s technology to enhance marketing products with AI-powered features. This move signifies Salesforce’s focus on integrating powerful new technologies into the Marketing Cloud tech stack. Two years ago, Salesforce made the decision to rename a number of their Marketing Cloud offerings. Marketing Cloud’s most popular modules for messaging and journeys go by Marketing Cloud Engagement. Has it really been two years? The architecture of Marketing Cloud Growth Edition represents a significant shift, with key components like the email and form builders built on Salesforce CMS. These builders offer guided setup processes and seamless integration with Flow, Salesforce’s automation engine. Marketers will benefit from simplified workflows and advanced personalization options. Marketing Cloud Account Engagement (formerly Pardot), caters to more B2B use cases. So which product is Marketing Cloud Growth Edition really: Marketing Cloud Engagement or Marketing Cloud Account Engagement? Being targeted at B2B, SMB (small-medium) organizations, you may be asking if this is the beginning of the end for Account Engagement. In short, this is not only a new edition, it’s a whole new world…Marketing Cloud ‘On Core’ (Einstein 1). Marketing Cloud Growth Edition and Einstein AI Einstein AI plays a pivotal role in Marketing Cloud Growth Edition, providing features like Send Time Optimization and Co-Create for campaign brief and message generation. Additionally, robust analytics capabilities built on Data Cloud offer insights into marketing performance. Announced at Dreamforce ‘23 as a better re-engineered core platform with the inherent ability to handle generative AI with speed and agility. Support of Salesforce Data Cloud for their marketing platforms has been a focus and now it is a reality. Pricing for Marketing Cloud Growth Edition starts at $18,000 per org per year, with additional options for email sends, unified profiles, segmentation credits, and SMS sends. With Marketing Cloud Growth Edition, you will gain the following: 180k email sends /org/year (add on email sends at an additional cost). 10k unified profiles, unified via Data Cloud. 10k activation and segmentation credits, to use with Data Cloud. The rollout of Marketing Cloud Growth Edition begins in North America, with plans for availability in Europe/Middle East (EMEA) in the second half of 2024. Learning resources and guided setup will be available to help customers get started with the new edition. While Marketing Cloud Growth Edition represents a significant step forward, it’s important to note that it’s not the end of Marketing Cloud or Account Engagement products. Salesforce continues to invest in innovation and development, with future plans to migrate more Marketing Cloud functionality onto the core platform. Great Changes with Marketing Cloud Growth Edition This includes lead capture, sending leads on journeys with email and SMS, automating notifications to sales and service teams, engagement scoring, and reporting for engagement on assets (such as emails, SMS, landing pages and forms). A new type of scoring that combines what we have known as scoring (behavioral) and grading (demographic). With the advent of advanced personalization, sending a large volume of customers through personalized cross-channel journeys, and reporting on these results. The email builder is built on top of Salesforce CMS, a shared service across other parts of the platform, so you have a single repository for assets. Let the tools do what they each excel at. CMS do what it does best, and allow Flow to do what it does best. Tectonic suspects Account Engagement (formerly Pardot) customers will start to see some of this reimagined building experience in the first half of 2024. Salesforce platform users have long known Flow to be Salesforce’s automation engine, bringing incredible power to non-coder that they historically didn’t have. Flow will power the automation behind Marketing Cloud Growth Edition too – including email sending. On The Core Platform As a result of being on the Einstein 1 (‘core’) platform, any AI-powered features marketers choose to use will be accessible and more powerful. Einstein Send Time Optimization is included, which will advise the most optimal time to send an email, based on the best performing emails for that audience in the past. Also, you’ll find Einstein Co-Create for campaign brief and message generation, and likely more that we’ve yet to encounter. When it comes to reporting on marketing on the Salesforce platform, you have many options. B2B Marketing Analytics (B2BMA) is an add-on to Account Engagement, where customers gain access to a pre-built CRM Analytics app that contains dashboards for use cases such as pipeline, engagement, account-based marketing, and other. Will there be access to something similar? For Marketing Cloud Growth Edition, at the time of launch there will instead be a set of reports and dashboards, built on Data Cloud. Details are currently yet to be released by Salesforce. Tectonic will alert you as soon as we hear. Easy Guided Set-ups You may have already gone through the new-style guided setup with other Salesforce modules. You will know that Salesforce has cut down the number of clicks required. Everyone on the Salesforce side involved with the project has been through the setup multiple times, which can be launched in minutes. Overall, Marketing Cloud Growth Edition promises to empower marketers with advanced capabilities and insights, setting the stage for continued evolution and growth in the marketing automation landscape. Marketers like us

March 14, 2024in Salesforce Marketing Cloud

05Feb

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

February 5, 2024in Salesforce Data Cloud, Salesforce Optimization, Snowflake

24Jan

Salesforce for Energy and Utilities

The Energy & Utilities Cloud (E&U Cloud) integrates and extends the comprehensive capabilities of Salesforce Sales and Service Cloud. Integrated with the Salesforce Platform to provide an industry-specific solution tailored for utilities, retail energy, and modern energy services companies. Align your business with the future of energy through personalized service, unified customer and asset data, and enhanced business agility. Key Features: By Tectonic’s Salesforce Marketing Consultant, Shannan Hearne 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 Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

January 24, 2024in Salesforce, Salesforce Manufacturing Automotive Energy, Salesforce Sales Cloud, Salesforce Service Cloud

21Jan

Salesforce Data Cloud License Offer

At Dreamforce 2023, Salesforce announced that Data Cloud free licenses are now included for all Enterprise Edition or above customers so they can become familiar with the new capabilities and develop use case ideas for Salesforce Data Cloud. Salesforce Data Cloud License Offer! Are you taking advantage of Salesforce Data Cloud’s customer 360 capabilities when it comes to intuitive, fast, efficient customer service? Today is the day! With the Salesforce Data Cloud Offer you can take advantage now! Data Cloud is the fastest growing organically built product in Salesforce’s history (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 earliest days of CRM is now finally solved. This is truly a 360 degree customer view. Why is Data Cloud important? A data cloud gives you an infrastructure for efficient data management across multiple systems at any scale. You can ensure data is available to anyone who needs it without compromising data integrity or security. There’s never been a better time to partner with Tectonic to explore Salesforce Data Cloud for your data and your business. Take advantage of the Data Cloud License Offer today. Like1 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 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 Advantages of a Cloud Managed Service Provider Considering outsourcing your IT management to a cloud managed service provider? Here are several benefits of opting for a cloud Read more

January 21, 2024in Salesforce Data Cloud, Salesforce Managed Services

20Jan

Spring ’24 Enhancements to Salesforce Analytics, Data Cloud, Einstein, and Net Zero Cloud

Discover the Spring ’24 Enhancements to Analytics Data Cloud Einstein and Net Zero Cloud Enhancements to Salesforce Analytics, Data Cloud, Einstein, and Net Zero Cloud in Spring’24. Reports and Dashboards for Data Cloud Enhancements Analytics Create custom report types, more core semantics, calculated insights, and date and time formulas. Analytics Collection Components Analytics Curate related analytics assets for better organization and easier consumption. Embed a specific collection directly into Lightning pages to easily access the insights you need right in your workflow. Enhanced Dashboard Customization Analytics Easily create and remember custom colors for widgets. Save hours in development time by applying layouts and colors to all widgets in a dashboard with just a few clicks. Revenue Intelligence Enhancements Analytics A new streamlined setup helps you get started even faster, and a library of KPI components lets you further customize Forecast Insights. To better understand conversation rates, use the new Win Rate Funnel view. Data Graphs Data Cloud Combine multiple data model objects and calculated insights into a unified view. New Profile API improves query performance to power near real-time use cases across Customer 360. Bring Your Own Lake with Snowflake Data Cloud Share data between Data Cloud and Snowflake with zero-ETL. With Data Federation, you can now share your data bidirectionally and access Snowflake datasets in Salesforce to enrich your unified customer profiles and unlock new insights. Bring Your Own Lake with Google BigQuery Data Cloud Share data between Data Cloud and Google BigQuery with zero-ETL. With seamless data access, you can enrich your unified customer profiles with BigQuery datasets, helping you unlock new insights and better power your Google Analytics and AI models. Streaming Data Ingest for Salesforce CRM Connector Data Cloud Ingest changes to Salesforce standard and custom objects in near real-time with streaming data ingest for the Salesforce CRM Connector. Now, existing batch ingestion checks for more frequent updates to your Salesforce objects. Einstein Copilot Einstein Embed Einstein Copilot—a conversational AI assistant—across all Salesforce applications to help teams be more productive. Automate steps or tasks with out-of-the-box actions, or create custom actions that call flows, Apex, or MuleSoft APIs. Prompt Builder Einstein Create, test, and refine prompt templates easily without code. Ground prompts with dynamic CRM data, including merge fields and flows. Invoke prompted workflows across the Einstein 1 Platform through Flow, Lightning Web Components, and Apex. ESG (Environmental, Social, and Governance) Disclosure Authoring with Generative AI Net Zero Cloud Use Einstein to generate more efficient Corporate Sustainability Reporting Directive (CSRD), Global Reporting Initiative (GRI), and Carbon Disclosure Project (CDP) reports. Einstein can access and use the internal information you’ve uploaded to Net Zero Cloud to write and answer specific questions required for these reporting standards. Disclosure and Compliance Hub Plugin for Microsoft Word Net Zero Cloud Net Zero Cloud now provides sustainability managers more flexibility to support multiple authoring formats using Microsoft Word Office 365. Multiuser collaboration, easy navigation, and rich text support create a cleaner and easier experience. Marginal Abatement Cost Visualizations Net Zero Cloud With marginal abatement cost visualizations, customers can gain insights into required investments for various programs and forecast future emissions based on the cost to offset carbon. Sustainability Program Visualizations Net Zero Cloud Visualize the combined effects of multiple environmental, social, and corporate governance (ESG) initiatives and gain a deeper understanding into different ESG projects and specific metrics within these projects. Improved Emissions Factors Management Net Zero Cloud Automatically integrate emissions factors from Net Zero Marketplace into Net Zero Cloud to easily manage and apply the data, for improved transparency and visibility in one location. Stay tuned to Tectonic’s Insights for more details and news from Salesforce. Enhancements to Salesforce Analytics, Data Cloud, Einstein, and Net Zero Cloud. 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 Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

January 20, 2024in Google Analytics, Salesforce Data Cloud, Salesforce Einstein, Salesforce Marketing Automation, Salesforce Net Zero Cloud

30Dec

January ’24 Einstein Data Cloud Updates

Utilize Generative AI to Target Audiences Effectively Harness the power of generative AI with Einstein Segment Creation in Data Cloud to create precise audience segments. Describe your target audience, and Einstein Segment Creation swiftly produces a segment using trusted customer data available in Data Cloud. This segment can be easily edited and fine-tuned as necessary. Jan ’24 Einstein Data Cloud Updates. Where: This enhancement is applicable to Data Cloud in Developer, Enterprise, Performance, and Unlimited editions. Einstein generative AI is accessible in Lightning Experience. When: This functionality is rolling out gradually, starting in Spring ’24. How: In Data Cloud, create a new segment and choose Einstein Segment Creation. In the Einstein panel, input a description of your segment using simple text, review the draft, and make adjustments as needed. Gain Insights into Segment Performance with Segment Intelligence Analyze segment data efficiently with Segment Intelligence, an in-platform intelligence tool for Data Cloud for Marketing. Offering a straightforward setup process, out-of-the-box data connectors, and pre-built visualizations, Segment Intelligence aids in optimizing segments and activations across various channels, including Marketing Cloud Engagement, Google Ads, Meta Ads, and Commerce Cloud. Where: This update applies to Data Cloud in Developer, Enterprise, Performance, and Unlimited editions. Utilizing Segment Intelligence requires a Data Cloud Starter license. When: For details regarding timing and eligibility, contact your Salesforce account executive. How: To configure Segment Intelligence, navigate to Salesforce Setup. To view Segment Intelligence dashboards, go to Data Cloud and select the Segment Intelligence tab. Activate Audiences on Google DV360 and LinkedIn Effortlessly activate audiences on Google DV360 and LinkedIn as native activation destinations in Data Cloud. Directly use segments for targeted advertising campaigns and insights reporting. Where: This change is applicable to Data Cloud in Developer, Enterprise, Performance, and Unlimited editions. Requires an Ad Audiences license. When: This functionality is available starting in March 2024. Enhance Identity Resolution with More Frequent Ruleset Processing Experience more timely ruleset processing as rulesets now run automatically whenever your data changes. This improvement eliminates the need to wait for a daily ruleset run, ensuring efficient and cost-effective processing. Where: This update applies to Data Cloud in Developer, Enterprise, Performance, and Unlimited editions. Refine Identity Resolution Match Rules with Fuzzy Matching Extend the use of fuzzy matching to more fields, allowing fuzzy matching on any text field in your identity resolution match rules. Up to two fuzzy match fields, other than first name, can be used in a match rule, with a total of six fuzzy match fields in any ruleset. Enhance match rules by updating to the “Fuzzy Precision – High” method for fields like last name, city, and account. Where: This enhancement applies to Data Cloud in Developer, Enterprise, Performance, and Unlimited editions. Salesforce Einstein’s AI Capabilities Salesforce Einstein stands out as a comprehensive AI solution for CRM. Notable features include being data-ready, eliminating the need for data preparation or model management. Simply input data into Salesforce, and Einstein seamlessly operates. Additionally, Salesforce introduces the Data Cloud, formerly known as Genie, as a significant AI-powered product. This platform, combining Data Cloud and AI in Einstein 1, empowers users to manage unstructured data efficiently. The introduction of the Data Cloud Vector Database allows for the storage and retrieval of unstructured data, enabling Einstein Copilot to search and interpret vast amounts of information. Salesforce also unveils Einstein Copilot Search, currently in closed beta, enhancing AI search capabilities to respond to complex queries from users. Jan ’24 Einstein Data Cloud Updates This groundbreaking offering addresses the challenge of managing unstructured data, a substantial portion of business data, and complements it with the capability to use familiar automation tools such as Flow and Apex to monitor and trigger workflows based on changes in this data. Overall, Salesforce aims to revolutionize how organizations handle unstructured data with these innovative additions to the Data Cloud. Like2 Related Posts Salesforce Artificial Intelligence Is artificial intelligence integrated into Salesforce? Salesforce Einstein stands as an intelligent layer embedded within the Lightning Platform, bringing robust 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 Salesforce’s Quest for AI for the Masses The software engine, Optimus Prime (not to be confused with the Autobot leader), originated in a basement beneath a West 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

December 30, 2023in Einstein 1 Platform, Einstein Insights, Salesforce Data Cloud, Salesforce Einstein

27Dec

How Do You Personalize the Customer Journey?

Delight your customers with personalized moments at every touchpoint of their journey. Personalize the Customer Journey whether B2B or B2C, whether product or service, whether lead warming or customer loyalty, every journey is better with personalization. Enhance customer satisfaction by delivering personalized experiences at every touchpoint of the customer journey, whatever the context, with products or services, focusing on lead nurturing or customer loyalty. Orchestrate sophisticated customer journeys at scale, executing meaningful personalization campaigns across any channel, or all channels. Personalize the Customer Journey Across Lifecycle Manage the entire customer lifecycle, from awareness to advocacy, by engaging customers with personalized messages tailored to their buying stage and preferred communication channel. Achieve real-time customer engagement by adapting messaging and campaigns based on ongoing customer experiences, ensuring every customer feels valued and prioritized. Utilize AI to transform every customer interaction into a unique and tailored experience, predicting user behavior and automating journey creation based on predictive audience insights. While we’ll use retail as a case study, these principles are applicable across all industries. Utilizing Salesforce tools empowers you to harness explicit customer data for tailoring content to specific visitor groups, delivering more relevant and personalized experiences. To effectively prioritize customer segments and initiate personalized efforts with your most valuable visitors, adopt the PVE criteria—Potential, Value, and Ease: Start by focusing on segments with high potential and value, then gradually extend personalization efforts to other segments with promising potential. Mapping Customer Journeys: Understand each stage of the customer journey to ensure optimal engagement: Create a table summarizing each segment’s journey stage, description, engagement touchpoints, and customer actions. Building Digital Relevancy Maps (DRM): DRMs serve as a planning framework, aligning content and functionality with major segments across their journey stages. Evaluate and Optimize Content: Assess existing content against DRM-defined journey stages and visitor intentions. Data-driven Personalization: Leverage data—demographics, behavior, and purchase history—to craft personalized journeys. Automate for Efficiency: Use automation to adjust marketing campaigns in real-time based on customer behavior. Personalized Email Campaigns: Craft tailored email content reflecting customer preferences and behaviors. Social Media Integration: Tailor social media campaigns based on individual preferences and feedback. Harness AI for Real-time Insights: Artificial Intelligence algorithms predict customer behavior and offer personalized recommendations. Individualized Homepage Experiences: Enhance your website or mobile app by providing customers with personalized homepage experiences. Tailor product displays and content to align with their preferences, recent purchases, or browsing habits. A dynamically personalized homepage captivates attention and encourages deeper engagement. Integration for Personalized Customer Journeys Crafting personalized customer journeys requires a comprehensive strategy that integrates data-driven marketing, automation, and a deep understanding of customer behavior. By breaking down organizational barriers, connecting multiple channels, and utilizing AI-driven algorithms, businesses can enhance customer experiences, foster loyalty, and boost conversion rates. Stay Ahead with Adaptive Strategies Anticipate customer expectations by continually refining and adapting personalized strategies based on real-time data and feedback. This ensures your brand remains a trusted partner throughout your customers’ journeys. Leverage Salesforce’s Digital Experience Platform to Personalize the Customer Journey Gain insights into your priority segments, their journey stages, intentions, appropriate calls to action, and relevant content. Utilize Salesforce’s digital experience platform to deliver highly personalized and impactful experiences to prospects and customers, with measurable performance and business outcomes. 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 Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

December 27, 2023in Salesforce, Salesforce Data Cloud, Salesforce Einstein

18Dec

Introducing Salesforce Einstein Copilot

Einstein Copilot introduces a cutting-edge generative A. Powered by a conversational assistant seamlessly embedded within every Salesforce application. Its strategically enhancing workflow and yielding substantial gains in productivity. Announced at Dreamforce 2023, in case you missed it, read on. The newly integrated Einstein 1 Data Cloud, part of the Einstein 1 Platform, allows customers to establish a unified customer profile. By connecting any data source. This integration infuses AI, automation, and analytics into every customer experience, fostering a comprehensive approach. Salesforce Einstein Copilot Studio Einstein Copilot Studio provides organizations with the flexibility to tailor Einstein Copilot. A Salesforce tool used according to specific business requirements. It incorporates the Einstein Trust Layer, ensuring the protection of sensitive data while leveraging trusted information to enhance generative AI responses. Unlike other generative AI copilot solutions, Einstein Copilot is natively integrated into the world’s leading AI CRM – Salesforce. Seamlessly tapping into data from various Salesforce applications. This integration ensures more accurate AI-powered recommendations and content generation. Data Cloud The Data Cloud serves as the foundation for Einstein Copilot. Data Cloud offers real-time, consolidated views of customers or entities. With Data Cloud, creating a data graph is simplified, enabling the generation of AI-powered apps with a single click, eliminating the need for manual data queries or joins. Einstein Trust Layer The Einstein Trust Layer, an integral part of the Einstein 1 Platform, ensures the secure retrieval of relevant data from Data Cloud. Before sending it to the Language Model (LLM), proprietary, sensitive, or confidential information is masked, maintaining a high level of data security and compliance. Copilot for Sales aligns with existing CRM access controls and user permissions. Salesforce requires ensuring administrators and users have the necessary permissions for customization and data management within Copilot for Sales. Salesforce Copilot service functions similarly to other generative AI tools in the customer experience landscape, responding to customer queries automatically with personalized answers grounded in company data. Einstein Copilot & Search, anticipated for availability from February 2024, is set to leverage Data Cloud unstructured support. It will be ushering in a new era where Generative AI-based apps redefine the user interface. Thereby allowing seamless interactions and conversations with applications. This transformative shift signifies a significant milestone in Enterprise Software, with Salesforce actively participating in this evolving landscape. Copilot for Sales How is Copilot for Sales different from Copilot for Microsoft 365? Microsoft Copilot for Sales is an AI assistant designed for sellers that brings together the capabilities of Copilot for Microsoft 365 with seller-specific insights and workflows. What Salesforce just did is drop the GPT name and go with Copilot, By endorsing the Microsoft branding it announced earlier this year with Microsoft Copilot for Microsoft 365 and CoPilot for Dynamics 365. Like Related Posts Salesforce Artificial Intelligence Is artificial intelligence integrated into Salesforce? Salesforce Einstein stands as an intelligent layer embedded within the Lightning Platform, bringing robust 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 Salesforce’s Quest for AI for the Masses The software engine, Optimus Prime (not to be confused with the Autobot leader), originated in a basement beneath a West 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

December 18, 2023in Einstein 1 Platform, Salesforce Data Cloud

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 Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

December 12, 2023in Salesforce Data Cloud, Snowflake

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 Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

October 26, 2023in Einstein 1 Platform, Generative AI, Salesforce, Salesforce Data Cloud

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 Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

October 9, 2023in Einstein 1 Platform, Mulesoft, Salesforce, Salesforce Data Cloud, Salesforce Einstein

15Sep

Bring Your Own Lake With Google BigQuery

Can BigQuery Function as a Data Lake? Why you should Bring Your Own Lake With Google BigQuery. Google BigQuery serves as a fully-managed, petabyte-scale data warehouse, utilizing Google’s infrastructure’s processing power. The combination of Google Cloud Storage and BigQuery transforms Google Cloud Platform into a scalable data lake capable of storing both structured and unstructured data. Why Embrace BigQuery’s Serverless Model? In a serverless model, processing is automatically distributed across numerous machines operating in parallel. BigQuery’s serverless model allows data engineers and database administrators to concentrate less on infrastructure and more on server provisioning and deriving insights from data. Advantages of Using BigQuery as a Data Warehouse: BigQuery is a completely serverless and cost-effective cloud data warehouse designed to work across clouds, scaling seamlessly with your data. With integrated business intelligence, machine learning, and AI features, BigQuery provides a unified data platform for storing, analyzing, and sharing insights effortlessly. The Relevance of Data Lakes: Data Lakes and Data Warehouses are complementary components of data processing and reporting infrastructure, each serving distinct purposes rather than being alternatives. Data Lakes in the Evolving Landscape: Data lakes, once immensely popular, are gradually being supplanted by more advanced storage solutions like data warehouses. Data Lake Content Formats: A data lake encompasses structured data from relational databases (rows and columns), semi-structured data (CSV, logs, XML, JSON), unstructured data (emails, documents, PDFs), and binary data (images, audio, video). Building a Data Lake on GCP: Constructing a Data Lake: Introduction to Google Big Lake: BigLake serves as a storage engine, offering a unified interface for analytics and AI engines to query multiformat, multicloud, and multimodal data securely, efficiently, and in a governed manner. It aspires to create a single-copy AI lakehouse, minimizing the need for custom data infrastructure management. Data Extraction from a Data Lake: Distinguishing BigQuery as a Data Warehouse: BigQuery stands out as a serverless and cost-effective enterprise data warehouse, functioning across clouds and seamlessly scaling with data. It incorporates built-in ML/AI and BI for scalable insights. Data Lake Implementation Time: Building a fully productive data lake involves several steps, including workflow creation, security mapping, and tool and service configuration. As a result, a comprehensive data lake implementation can take several months. Acquiring a Data Lake: One option is to buy a Data Lake through a decentralized exchange (DEX) supporting the blockchain where the Data Lake resides. Connecting a crypto wallet to a DEX and utilizing a Binance account to purchase the base currency is outlined in a guide for this purpose. Like Related Posts Guide to Creating a Working Sales Plan Creating a sales plan is a pivotal step in reaching your revenue objectives. To ensure its longevity and adaptability to 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 Web Pages That Helped With My Google Data Engineer Exam Google Data Engineer Exam It seems like every day more resources appear to help you study for the Google Data Read more What is Advanced Reporting in Salesforce? Cross Filters, Summary Formulas, and More: Advanced Reporting in Salesforce Salesforce comes with report types out-of-the-box for all standard objects Read more

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