Salesforce Einstein Archives - gettectonic.com - Page 14
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
Salesforce Life Sciences Cloud
24Oct

Salesforce Life Sciences Cloud

Salesforce has unveiled Life Sciences Cloud, a secure and trusted platform tailored for pharmaceutical (pharma) and medical technology (medtech) organizations. This innovative solution aims to expedite drug and device development, streamline patient enlistment and retention throughout the clinical trial journey, and harness AI capabilities to deliver personalized customer experiences. The significance of this announcement lies in the life sciences industry’s urgent need for accurate and accessible data to advance research and development efforts and enhance clinical trials. Despite this need, the industry has been slow to adopt digital tools, with a staggering 88% of healthcare and life sciences organizations yet to achieve their digital transformation objectives. Amit Khanna, SVP & GM of Health and Life Sciences at Salesforce, emphasized the necessity for integrated, compliant, and data-driven solutions in the life sciences industry. He highlighted Salesforce’s commitment to enhancing stakeholder engagement across the R&D and commercialization spectrum by leveraging data, AI, and CRM capabilities. The Salesforce solution encompasses: Commercial Operations, available now, provides insights into the commercial lifecycle, including contract compliance, pricing, and inventory management. AI-powered bots offer timely alerts to field representatives and forecasting insights to optimize sales strategies. Clinical Operations offers tools to set up and execute efficient trials, including Data Cloud for Health, Chain of Custody Management, and Participant Management features, aiming to enhance patient recruitment, safety, and engagement. Pharma CRM facilitates personalized engagement with stakeholders, managing interactions and digital content while ensuring compliance with regulations. Features like Healthcare Professional (HCP) Engagement and Einstein for Life Sciences enhance engagement and automate tasks for streamlined operations. Customer testimonials, such as from SI-BONE, highlight the tangible benefits of digitizing processes and improving efficiency with Salesforce solutions. Availability details for various features are provided, with some features already generally available and others set to roll out in the coming months and years. To learn more about Salesforce’s offerings for healthcare and life sciences, access industry insights, and explore the potential of CRM and AI in this sector, interested parties are encouraged to dig into the available resources or contact Tectonic today. Additionally, it’s noted that sales automation functionality for pharma/biotech customers will be available from mid-2025 onward. Learn about Salesforce for healthcare and life sciences  Learn more about Salesforce Life Sciences Cloud 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 24, 2023in Life Sciences Cloud, Salesforce Einstein, Salesforce Health and Life Sciences Solutions, Salesforce Implementation Services
Einstein Email Insights Explained
18Oct

Einstein Email Insights Explained

In 2016, Salesforce ventured into the realm of artificial intelligence (AI) with the introduction of Salesforce Einstein. Far from a standalone product, Salesforce Einstein represents a technological layer seamlessly integrated into the Salesforce Lightning platform and various other Salesforce cloud products. Insights for Sales Specifically designed for sales professionals, Einstein Email Insights proves to be a valuable tool. It provides crucial information within the email interface, empowering salespeople to respond to customers more effectively and at the opportune moment. Einstein Email Insights offers sales representatives essential context related to sales alongside pertinent inbound emails. By specifying criteria for email content analysis, users can extract the most relevant insights. Einstein ensures that contextual sales information is surfaced while composing emails, facilitating the delivery of optimal responses at the right time. This feature is available with Sales Cloud Einstein, Inbox, High Velocity Sales, or Revenue Intelligence, albeit with an additional cost. It is accessible for Salesforce Enterprise, Performance, and Unlimited editions, subject to an extra charge. The Einstein Family If you are using Einstein Activity Capture with a Sales Cloud Einstein or Inbox license, Email Insights is automatically activated upon enabling Einstein Activity Capture. However, users without these licenses must read and agree to the Email Insights terms of service before utilizing the feature. The insights derived from Einstein Conversation Insights go beyond mere data points; they offer actionable intelligence. Businesses can leverage these insights to refine products, optimize customer service processes, and make informed decisions that positively impact the overall customer experience. Salesforce Einstein Insights ensures that every action taken by your sales representatives is calculated and meaningful, aiming to convert prospects into customers. Statistics show that Salesforce Einstein Insights can boost conversion rates by 43%. This AI-powered platform compiles data from accounts, opportunities, call histories, and even news sources to predict business outcomes, empowering your team to strategize with confidence at every stage of customer engagement. Salesforce has recently introduced new email features in its Marketing Cloud to enhance the efficiency of email capabilities. The new Einstein Email capabilities enable modern marketers to increase productivity, send more personalized emails, and drive greater customer engagement. Additionally, Salesforce’s acquisition of Rebel, an interactive email provider, brings forth the ability to create interactive emails, allowing recipients to take action directly within the email. This functionality, akin to AMP for Gmail, enables users to browse image carousels, fill out forms, register for events, and more, directly from their inbox. Salesforce plans to launch this pilot early in 2020, integrating it with Email Studio and Journey Builder. Like2 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 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 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

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October 18, 2023in Einstein Insights, Salesforce Einstein
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
Generative AI Glossary
27Sep

The Salesforce Generative AI Glossary

Salesforce has built and maintains a fairly definitive glossary of generative Artificial Intelligence terminology, Tectonic thought was good enough to share in our insights. Salesforce Generative AI Glossary. Help everyone in your company understand key generative AI terms, and what they mean for your customer relationships. Fun fact: This article was (partially) written using generative AI. Bookmark this! This generative AI glossary will be updated regularly. Does it seem like everyone around you is casually tossing around terms like “generative AI,” “large language models,” or “deep learning”? Salesforce has created a primer on everything you need to know to understand the newest, most impactful technology that’s come along in decades. Let’s dive into the world of generative AI. Salesforce has built a list of the most essential terms that will help everyone in your company — no matter their technical background – understand the power of generative AI. Each term is defined based on how it impacts both your customers and your team. And to highlight the real-world applications of generative AI, we put it to work for this article. Salesforce experts weighed in on the key terms, and then let a generative AI tool lay the groundwork for this glossary. Each definition needed a human touch to get it ready for publication, but it saved loads of time. Anthropomorphism The tendency for people to attribute human motivation, emotions, characteristics or behavior to AI systems. For example, you may think the model or output is ‘mean’ based on its answers, even though it is not capable of having emotions, or you potentially believe that AI is sentient because it is very good at mimicking human language. While it might resemble something familiar, it’s essential to remember that AI, however advanced, doesn’t possess feelings or consciousness. It’s a brilliant tool, not a human being. Artificial intelligence (AI) AI is the broad concept of having machines think and act like humans. Generative AI is a specific type of AI (more on that below). Artificial neural network (ANN) An Artificial Neural Network (ANN) is a computer program that mimics the way human brains process information. Our brains have billions of neurons connected together, and an ANN (also referred to as a “neural network”) has lots of tiny processing units working together. Think of it like a team all working to solve the same problem. Every team member does their part, then passes their results on. In the end, you get the answer you need. Augmented intelligence Think of augmented intelligence as a melding of people and computers to get the best of both worlds. Computers are great at handling lots of data and doing complex calculations quickly. Humans are great at understanding context, finding connections between things even with incomplete data, and making decisions on instinct. Augmented intelligence combines these two skill sets. It’s not about computers replacing people or doing all the work for us. It’s more like hiring a really smart, well-organized assistant.  Customer Relationship Management (CRM) with Generative AI CRM is a technology that keeps customer records in one place to serve as the single source of truth for every department, which helps companies manage current and potential customer relationships. Generative AI can make CRM even more powerful — think personalized emails pre-written for sales teams, e-commerce product descriptions written based on the product name, contextual customer service ticket replies, and more. Deep learning Deep learning is an advanced form of AI that helps computers become really good at recognizing complex patterns in data. It mimics the way our brain works by using what’s called layered neural networks, where each layer is a pattern (like features of an animal) that then lets you make predictions based on the patterns you’ve learned before (ex: identifying new animals based on recognized features). It’s really useful for things like image recognition, speech processing, and natural-language understanding. Discriminator (in a GAN) In a Generative Adversarial Network (GAN), the discriminator is like a detective. When it’s shown pictures (or other data), it has to guess which are real and which are fake. The “real” pictures are from a dataset, while the “fake” ones are created by the other part of the GAN, called the generator (see generator below). The discriminator’s job is to get better at telling real from fake, while the generator tries to get better at creating fakes. This is the software version of continuously building a better mousetrap. Ethical AI maturity model An Ethical AI maturity model is a framework that helps organizations assess and enhance their ethical practices in using AI technologies. It maps out the ways organizations can evaluate their current ethical AI practices, then progress toward more responsible and trustworthy AI usage. It covers issues related to transparency, fairness, data privacy, accountability, and bias in predictions.  Explainable AI (XAI) Remember being asked to show your work in math class? That’s what we’re asking AI to do. Explainable AI (XAI) should provide insight into what influenced the AI’s results, which will help users to interpret (and trust!) its outputs. This kind of transparency is always important, but particularly so when dealing with sensitive systems like healthcare or finance, where explanations are required to ensure fairness, accountability, and in some cases, regulatory compliance. Generative AI Generative AI is the field of artificial intelligence that focuses on creating new content based on existing data. For a CRM system, generative AI can be used to create a range of helpful outputs, from writing personalized marketing content, to generating synthetic data to test new features or strategies. Generative adversarial network (GAN) One of two deep learning models, GANs are made up of two neural networks: a generator and a discriminator. The two networks compete with each other, with the generator creating an output based on some input, and the discriminator trying to determine if the output is real or fake. The generator then fine-tunes its output based on the discriminator’s feedback, and the cycle continues until it stumps the discriminator. Generative pre-trained transformer

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September 27, 2023in Generative AI, Salesforce Einstein
salesforce einstein analytics and hospitality
16Sep

Trust in AI Data

As companies rapidly embrace Artificial Intelligence and realize its benefits, trust must be their top priority. And to instill trust in AI, they must first instill trust in the data that powers it. Think about data as a well-balanced diet for AI — you’re healthiest when you avoid junk food and consume all the proper nutrients. Simply put, organizations can only harness the full power of AI when it is fueled by accurate, comprehensive data.  The Future is Here AI is no longer a futuristic concept; it has become a reality in our living rooms, cars, and frequently, in our pockets. As this technology continues to play an ever-expanding role in our daily lives, a crucial question arises: To what extent can, and should, we place our trust in these AI systems? Trust in AI data comes more naturally for some than others. As the prevalence of AI increases, so does the concern about ensuring that it aligns with human values. A frequently cited example illustrating this challenge involves the moral decision an autonomous car may face when confronted with a collision scenario. Consider a situation where a driver must swerve to avoid being hit and seriously injured by an oncoming bus. However, the dilemma arises as the car faces the prospect of hitting a baby if it swerves left or an elderly person if it swerves right—posing a complex ethical question for the autonomous car. Arvind Krishna, Senior Vice President of Hybrid Cloud and Director of IBM Research, emphasizes the importance of careful programming in AI systems to prevent biases introduced by programmers from influencing outcomes. Recognizing the complexity of such issues, he discusses the need to develop frameworks for addressing these ethical challenges, a task IBM is tackling through its participation in the Partnership on AI alongside other technology organizations. Trust in AI data vs bias: Instances of machines demonstrating bias have already garnered attention, eroding trust in AI systems. AI technicians are actively working to identify and mitigate the origins of bias, acknowledging that machines can become biased due to inadequate representation in their training data. Guru Banavar, IBM Chief Science Officer for Cognitive Computing, notes that unintentional bias may arise from a lack of care in selecting the right training dataset, while intentional bias can result from a malicious attacker manipulating the dataset. James Hendler, Director of the Institute for Data Exploration and Applications at Rensselaer Polytechnic Institute, reminds us that while AI can be a force for social good, it also holds the potential for diverse social impacts, where actions deemed good by one may be perceived as harmful by another. Hence, an awareness of these complexities is essential in navigating the ethical landscape of AI applications. Artificial Intelligence (AI) is revolutionizing work processes and service delivery, empowering organizations to harness its formidable capabilities for data-driven predictions, product and service optimization, innovation augmentation, increased productivity, and cost reduction. While the benefits of AI adoption are immense, it also introduces risks and challenges, prompting concerns about the current level of trustworthiness in AI applications. Public Trust in AI data Unlocking the full potential and return on investment from AI necessitates a sustained commitment to building and upholding public trust. For widespread adoption, people must have confidence that AI development and utilization adhere to responsible and trustworthy practices. In a pioneering initiative, KPMG Australia, in collaboration with the University of Queensland, conducted a world-first in-depth exploration of trust and global attitudes toward AI across 17 countries. The resulting report, “Trust in Artificial Intelligence: A Global Study 2023,” delivers comprehensive insights into the factors influencing trust, the perceived risks and benefits of AI utilization, community expectations regarding AI governance, and the entities considered trustworthy in AI development, usage, and regulation. This report, titled “Trust in Artificial Intelligence: 2023 Global Study on the Shifting Public Perceptions of AI,” presents key findings from the global study and offers individual country snapshots, serving as a valuable resource for those leading, creating, or governing AI systems. Importantly, it outlines four critical pathways for policymakers, standards setters, governments, businesses, and non-governmental organizations (NGOs) to navigate the challenges associated with trust in the development and deployment of AI. 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 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 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 Salesforce Data Studio Data Studio Overview Salesforce Data Studio is Salesforce’s premier solution for audience discovery, data acquisition, and data provisioning, offering access Read more

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September 16, 2023in Salesforce Einstein, Salesforce Public Sector Solutions
Google 360 Analytics Dashboard in Marketing Cloud
13Sep

Salesforce Audience Insights

Salesforce Audience Insights By Tectonic’s Marketing Consultant, Shannan Hearne Salesforce Marketing Cloud is so much more than just an email sending platform. This insight explores how it can power your advertising.; Marketing Cloud offers robust audience segmentation capabilities, empowering marketers to effectively segment their customer base. The integration of AI through Audience Insights enhances this power. Formerly known as Advertising Studio, the platform is now recognized as Marketing Cloud Advertising. Audience Insights provides a deeper understanding of customers by unveiling unique characteristics, interests, and behaviors of user groups interacting with your ads and converting. By connecting Marketing Cloud Advertising to paid media channels, you can optimize your audience strategy, gaining a unified, cross-channel view and assessing the effectiveness of first-party audiences through a dedicated dashboard. Key features of Audience Insights include: To leverage Audience Insights, your Marketing Cloud Intelligence admin needs to configure it before connecting Advertising to paid media channels. This integration allows you to analyze the effectiveness of first-party audiences with a single, cross-channel perspective. As a Marketing Cloud Advertising customer with a Marketing Cloud Intelligence license, you gain access to comprehensive audience and campaign analytics through Audience Insights for Marketing Cloud Advertising. This application is conveniently available in the Marketing Cloud Intelligence Marketplace. Utilize the Audience Insights for Advertising Studio dashboard to refine campaigns using first-party audiences. Additionally, the Marketing Insights for Sales Cloud solution facilitates a deeper understanding of how marketing efforts and spend translate into revenue, offering insights into the sales funnel and guiding strategic decisions. Salesforce Audience Insights The Marketing Insights for Sales Cloud solution utilizes objects such as Leads, Opportunities, Accounts, Contacts, Campaigns, and Campaign Members to provide a holistic view of marketing and sales alignment. Setting up your digital advertising strategy within Salesforce, particularly through Advertising Studio, yields significant benefits. Integration with Google Analytics 360 expands your digital marketing and analytics possibilities. Advertising Studio seamlessly connects with advertising platforms like Google Display Ads, Facebook Ads, Instagram, Pinterest, Twitter, LinkedIn, AdWords, Gmail, and YouTube. Are you ready to employ the full power of Salesforce Marketing Cloud and Advertising Studio? Contact Tectonic today. Like3 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 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 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 Salesforce Data Studio Data Studio Overview Salesforce Data Studio is Salesforce’s premier solution for audience discovery, data acquisition, and data provisioning, offering access Read more

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September 13, 2023in Marketing Automation, Salesforce Einstein, Salesforce Marketing Cloud, Salesforce Marketing Cloud Advertising, Salesforce Sales Cloud
Crucial Role of Data and Integration in AI at Dreamforce
13Sep

The Crucial Role of Data and Integration in AI at Dreamforce

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

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September 13, 2023in Mulesoft, Salesforce, Salesforce Einstein, Snowflake
Salesforce Data Cloud
08Sep

Salesforce Data Cloud Evolution

Data Cloud stands as the fastest-growing organically built product in Salesforce’s history, signifying a significant milestone in solving the enduring data problem within Customer Relationship Management (CRM). Salesforce Data Cloud Evolution since its beginnings is an interesting story. With an average of 928 systems per company, identity resolution becomes challenging, especially when managing more than one system. Salesforce’s expansion into AI-powered CRM emphasizes the synergy between AI and data, recognizing that AI’s optimal functionality requires robust data support. Data Cloud acts as the foundation accelerating connectivity across different ‘clouds’ within the Salesforce platform. While it’s available for purchase, even Salesforce customers without licensed Data Cloud still benefit from its foundational advantages, with increased strength when utilized as a personalization and data unification platform. The history of Data Cloud reflects its evolution through various iterations, from Customer 360 Audiences to Salesforce Genie, ultimately settling as Data Cloud in 2023. This journey marked significant developments, expanding from a marketer’s tool to catering for sales, service, and diverse use cases across the Salesforce platform. Data harmonization with Data Cloud simplifies the complex process, requiring fewer efforts compared to traditional methods. It comes pre-wired to Salesforce objects, reducing the need for extensive data modeling and integration steps. The technical capability map showcases a comprehensive integration of various technologies, making Data Cloud versatile and adaptable. Data Cloud’s differentiators include being pre-wired to Salesforce objects, industry-specific data models, prompt engineering capabilities, and the inclusion of the Einstein Trust Layer, addressing concerns related to generative AI adoption. Looking ahead, Data Cloud continues to evolve with constant innovation and features in Salesforce’s major releases. The introduction of Data Cloud for Industries, starting with Health Cloud, signifies ongoing enhancements to cater to industry-specific needs. Closing the skills gap is crucial for effective Data Cloud implementation, requiring a blend of developer skills, data management expertise, business analyst skills, and proficiency in prompt engineering. Salesforce envisions Data Cloud, combined with CRM and AI, as the next generation of customer relationship management, emphasizing the importance of sound data and skillful implementation. Data Cloud represents the ‘Holy Grail of CRM,’ offering a solution to the long-standing data challenges in CRM. However, its success as an investment depends on the organization’s readiness to demonstrate return on investment (ROI) through solid use cases, ensuring unified customer profiles and reaping the rewards of this transformative technology. FAQ When did Salesforce introduce data cloud? Customer 360 Audiences: Salesforce’s initial CDP offering, launched in 2020. Salesforce CDP: The name changed in 2021 to align with how the blooming CDP market was referring to this technology. Does Salesforce data cloud compete with Snowflake? They offer distinct capabilities and cater to diverse business needs. Salesforce Data Cloud specializes in data enrichment, personalization, and real-time updates, while Snowflake boasts scalable data warehousing and powerful analytics capabilities. What is the data cloud in Salesforce? Deeply integrated into the Einstein 1 Platform, Data Cloud makes all your data natively available across all Salesforce applications — Sales Cloud, Service Cloud, Marketing Cloud, Commerce Cloud, Tableau, and MuleSoft — to power automation and business processes and inform AI. Is Salesforce Genie now data cloud? Announced at Dreamforce ’22, Salesforce Genie was declared the greatest Salesforce innovation in the company’s history. Now known as Data Cloud, it ingests and stores real-time data streams at massive scale, and combines it with Salesforce data. This paves the way for highly personalized customer experiences Like1 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 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

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September 8, 2023in Salesforce Data Cloud, Salesforce Einstein
Cloud Based Business Solutions
07Sep

AI Fundamental Role in the Future of Business

AI is not a novel concept, but its pivotal role in shaping the future of business is rapidly emerging. Particularly, generative AI stands out as a transformative advancement with far-reaching implications for our lives and enterprises. However, merely investing in the technical capabilities of AI is insufficient. For AI Fundamental Role in the Future of Business to come to fruition, skills have to be learned. Road maps must be developed. Organizations need to prioritize building a comprehensive and reliable data foundation to guide decision-making and strategy development.  Training or employing new talent to work in this field is already competitive. Generative AI and large language models (LLMs) are poised to redefine how we live, work, and conduct business. Experts from Snowflake share insights into navigating the opportunities and uncertainties associated with these technologies, including their impact on various aspects: Engaging Partners: Transforming the Enterprise: AI Impact on Various Aspects: AI Fundamental Role in the Future of Business Furthermore, the report emphasizes the crucial role of a robust data strategy, the importance of cybersecurity in the generative AI era, and the potential for AI to significantly impact global GDP. Goldman Sachs Research predicts that breakthroughs in generative AI could boost global GDP by 7% and increase productivity growth by 1.5 percentage points over a decade. Investors are advised to focus on industries such as semiconductor manufacturing, digitalization, and healthcare, given the growing influence of AI. However, discernment is crucial, and the report highlights the need for efficient implementation, identifying specific use cases for AI, and leveraging new AI techniques for informed investment decisions. AI, with its capacity to process vast amounts of information quickly and accurately, is anticipated to play a pivotal role in supporting investors in making more informed decisions and extracting valuable insights from data. Like Related Posts 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 Alphabet Soup of Cloud Terminology As with any technology, the cloud brings its own alphabet soup of terms. This insight will hopefully help you navigate Read more We Are All Cloud Users My old company and several others are concerned about security, and feel more secure with being able to walk down Read more 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

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September 7, 2023in Salesforce Einstein
Einstein in Salesforce
26Aug

Einstein in Salesforce

Salesforce AI and CRM Evolution Salesforce has long been a leader in customer relationship management (CRM) by pioneering cloud technologies. Recently, the platform has significantly advanced with the integration of generative artificial intelligence (AI) and AI-powered features, thanks to its Einstein technology. Einstein in Salesforce is like a super smart computer overseeing and analyzing the data in your CRM. This guide explores Salesforce’s AI strategy, exploring its specific products and features to help business teams understand and benefit from this technology. Exploring Salesforce’s Advanced AI Features Einstein, Salesforce’s AI technology, powers various advanced features within the platform. This guide will cover these capabilities, provide real-life adoption examples, and discuss their benefits. Additionally, it offers best practices, solutions, and services to facilitate your Einstein implementation. Salesforce’s Comprehensive CRM Solution Salesforce remains a number one in the CRM software world, offering robust solutions for managing relationships across various departments. Specific clouds within Salesforce enable teams to handle marketing, sales, customer service, e-commerce, and more. The platform focuses on customer experience and provides robust data analytics to support decision-making. Enhancements Through Generative AI Salesforce’s generative AI has rapidly enhanced the platform’s automation, workflow management, data analytics, and assistive capabilities for customer management. A prime example is Salesforce Copilot, which aids internal users with outreach and analysis tasks while improving the external user experience. What is Salesforce Einstein? Salesforce Einstein is the first comprehensive AI for CRM, integrating AI technologies to enhance the Customer Success Platform and bring AI to users everywhere. It is seamlessly integrated into many Salesforce products, offering generative AI built specifically for CRM. Key Features of Salesforce Einstein Comprehensive AI Capabilities of Salesforce Einstein Einstein extends its capabilities across the Salesforce CRM platform under the Customer 360 umbrella, enhancing intelligence and providing personalized customer experiences. Key Benefits of Salesforce Einstein Salesforce Einstein helps close deals faster, personalize customer service, understand customer behaviors, target audience segments better, and create personalized shopping experiences. It ensures data protection and privacy through the Einstein Trust Layer, maintaining strong data governance controls. Responsible AI Principles Salesforce is committed to responsible AI principles, ensuring Einstein is trustworthy and safe for every organization. Organizations can select from various principles to ensure ethical AI use in their operations. Implementation of Salesforce Einstein Salesforce Einstein is a powerful AI solution transforming how businesses interact with customers. By leveraging machine learning and data analysis, it personalizes experiences, predicts customer behavior, and automates tasks, boosting sales, enhancing service, and driving growth. As AI evolves, its impact on CRM will continue to grow, making it an indispensable tool for businesses aiming to stay competitive in today’s data-driven landscape. Top 4 Benefits of Salesforce Einstein in an Organization Einstein Essentials Salesforce Einstein and GPT (Generative Pretrained Transformer) technologies represent significant advancements in AI, particularly in CRM and natural language processing. Here’s a brief overview of their relevance and potential intersection: Data Handling and Ethics in Salesforce Salesforce manages a vast amount of customer data, and the ethical handling of this data is crucial. Key considerations include data privacy, secure storage, access controls, compliance with regulations like GDPR and CCPA, and the ethical use of AI and machine learning. It’s important to maintain transparency, avoid biases, and ensure AI models are making ethical decisions. Newest Einstein Features for 2024 In the rapidly evolving ecosystem of Salesforce, AI offers a suite of tools to spark innovation, streamline operations, and provide richer business insights. Explore these potentials and let Einstein AI reshape your work in 2024. Content updated June 2024. 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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August 26, 2023in Einstein 1 Platform, Generative AI, Salesforce Data Cloud, Salesforce Einstein
AI Drives Demand for Trusted Data
25Aug

AI Drives Demand for Trusted Data

The demand for reliable data has long been emphasized due to the ongoing need for real-time personalization and increased business efficiencies. Generative AI is amplifying these requirements, prompting analytics and IT leaders to strengthen their data foundations. AI Drives Demand for Trusted Data and we are on the frontlines. A significant majority (86%) of analytics and IT leaders acknowledge that the effectiveness of AI outputs is contingent on the quality of data inputs. On a positive note, technical leaders express optimism about their current standing. More than one-third of analytics and IT leaders categorize their data maturity as best-in-class, considering factors such as data capabilities, processes, sponsorship, investment, and vision. However, only a small fraction (6%) describe their data maturity as below industry standard or nonexistent. This might indicate the challenge of benchmarking maturity against peers or, at worst, an overestimation of confidence in data strategy and capabilities. Despite generally favorable self-assessments by IT and analytics leaders, a significant majority of business leaders (94%) believe there is untapped potential in deriving more value from their data, signaling the need for improvement. To address this, analytics and IT leaders are prioritizing fundamental aspects such as data quality, enhanced security, and readiness for AI adoption. However, the path to achieving these goals is perceived as challenging. Generative AI represents a substantial leap beyond established technologies like predictive AI, and business leaders are enthusiastic about its potential. A vast majority (91%) consider generative AI to offer significant advantages, with compelling use-cases ranging from content creation to software development. Despite its relative novelty, generative AI is advancing rapidly, and more than three-quarters of business leaders express concerns about missing out on its benefits. In particular, marketing leaders are apprehensive that their companies are falling behind in fully harnessing generative AI in workflows, with 88% sharing this concern. 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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August 25, 2023in Generative AI, Salesforce Einstein
Data Quality A Challenge and A Priority
15Aug

Data Quality A Challenge and A Priority

Data accuracy — and confidence in data accuracy — is a key component of trusted data. This makes Data Quality A Challenge and A Priority. Departments closest to the data, like data and analytics teams, have the highest confidence in their data accuracy. Confidence among line-of-business leaders is lower, revealing an opportunity to instill data confidence across marketing, sales, and service teams. 57% of data and analytics leaders have complete confidence in their data’s accuracy. Overall, there is room for improvement. Increased tracking of critical metrics, such as data quality, data utilization, data management and costs, data services delivery, and the ROI of data initiatives, could be one giant leap forward in making such an improvement. Surging Data Overwhelms Users — And Poses an Opportunity Business leaders’ second biggest data challenge, dealing with overwhelming volumes of data, shows no signs of abating. Over two-thirds of analytics and IT leaders expect data volumes to increase 22% on average over the next year. They expect similar growth rates across a variety of sources including third-party data and device data. For data leaders, increasing and diverse data sources require more effort to standardize data. This is likely to worsen a major challenge for analytics and IT leaders: lack of data harmonization (i.e., standardizing data from different sources). Overcoming this challenge presents an opportunity for differentiation. Almost two-thirds (65%) of customers say they expect companies to adapt experiences to match their changing needs, yet 80% of business leaders say personalization is difficult to scale. For companies looking to serve more tailored experiences, mature data management capabilities are a key competitive advantage. 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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August 15, 2023in Salesforce Data Cloud, Salesforce Einstein
Benefits of Salesforce Experience Cloud
11Aug

Benefits of Salesforce Experience Cloud

Salesforce Experience Cloud: Transforming Digital Customer Engagement To understand the Benefits of Salesforce Experience Cloud we must understand what a customer or partner portal is intended to do. Salesforce Experience Cloud, previously known as Community Cloud, is a powerful digital experience platform (DXP) designed to help organizations create and deliver exceptional, customer-centric experiences across multiple channels. This platform goes beyond community management, offering tools for building and managing websites, portals, mobile apps, and integrating social media. Benefits of Salesforce Experience Cloud explored. Built on Salesforce Customer 360, Experience Cloud gives businesses a comprehensive view of their customers by connecting data from various sources. With these insights, businesses can create personalized experiences tailored to each customer’s preferences and needs. Organizations can use Experience Cloud to design portals, websites, and communities, providing seamless access to relevant information, collaboration tools, and resources. The platform’s flexibility allows businesses to enhance customer satisfaction, improve partner collaboration, and boost employee productivity. Key Benefits of Salesforce Experience Cloud Salesforce Experience Cloud offers numerous benefits that help businesses deliver seamless experiences across the customer journey. Here are some of its key advantages: 1. Seamless Integration Experience Cloud integrates effortlessly with other Salesforce products like Sales Cloud and Service Cloud, providing a unified platform for comprehensive customer management. 2. Scalability and Customization The platform is highly scalable, allowing businesses to expand their communities as they grow. With extensive customization options, businesses can tailor the platform to meet their specific needs and branding requirements. 3. Security and Trust Salesforce is known for its robust security features, ensuring customer data is protected at all times. Businesses can confidently manage sensitive customer information within Experience Cloud. 4. Extensive AppExchange Ecosystem Salesforce’s AppExchange marketplace provides access to a wide range of pre-built integrations and apps that enhance the functionality of Experience Cloud, allowing businesses to customize and extend their platform capabilities. Real-World Uses of Salesforce Experience Cloud Salesforce Experience Cloud is used by businesses across various industries to improve customer engagement, enhance collaboration, and boost productivity. Some key use cases include: 1. Partner Portals Experience Cloud enables businesses to create dedicated partner portals where partners can collaborate with internal teams, access resources, and share leads. This accelerates partner engagement and streamlines business processes. 2. Self-Service Portals Businesses can offer 24/7 self-service portals, allowing customers to access product information, troubleshoot common issues, and track their interactions. These portals help reduce the workload on support teams and enhance customer satisfaction. 3. Customer Communities Experience Cloud allows businesses to create customer communities where users can find personalized content, engage with other users, and access self-service resources. This promotes collaboration and reduces the strain on customer support teams. 4. Employee Communities Internal employee communities serve as hubs for company-wide communication, training, and collaboration. Employees can access resources, share knowledge, and seek support, ultimately boosting engagement and productivity. 5. Branded Mobile Apps Businesses can use Experience Cloud to develop branded mobile apps that give customers, partners, and employees convenient access to services, resources, and information on the go. 6. Social Media Integration Experience Cloud integrates with popular social media platforms, allowing businesses to engage with customers directly, share content, and respond to inquiries. Top Features of Salesforce Experience Cloud Salesforce Experience Cloud is packed with features that enhance customer engagement, streamline operations, and improve overall efficiency: Companies Using Salesforce Experience Cloud Nike and PUMA leverage Experience Cloud for personalization. Nike’s loyalty program and Puma’s mobile shopping experience are enhanced by the platform’s built-in mobile UX design and technical architecture, resulting in better customer engagement and increased sales. Bank of America and Wells Fargo use Experience Cloud to offer customer support through self-service portals and community forums, improving customer satisfaction and gathering valuable feedback. IBM uses the platform to create collaborative communities for employees and customers alike. With integrated tools like Salesforce Einstein and IBM Watson, the company has enhanced internal collaboration and customer service. Hulu uses Salesforce to power its Help Center, where customers can find answers, engage with other viewers, and leave feedback that shapes Hulu’s content. OpenTable relies on Experience Cloud for its Diner Help portal, a one-stop shop for dining-related queries, enhancing the user experience and operational efficiency. Choosing the Right Salesforce Experience Cloud Partner for Implementation When implementing Salesforce Experience Cloud, choosing the right partner is crucial to ensure success. Look for a partner with: With the right partner, like Tectonic, businesses can fully grasp the power of Salesforce Experience Cloud to deliver exceptional digital experiences that foster customer loyalty, drive business growth, and improve operational efficiency. Content updated October 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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August 11, 2023in Data, Salesforce, Salesforce Development Services, Salesforce Einstein, Salesforce Experience Cloud

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