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salesforce einstein analytics and hospitality
03Jan

Important Information for Spring ’24 Release

Your Salesforce org gets upgraded to Spring ’24 Release in about 1 Month. The time and date for your organization’s five-minute upgrade window is listed on status.salesforce.com. During the upgrade window, your users receive a message stating that the service is momentarily unavailable. When the service becomes available, your Salesforce org is on the Spring ’24. This reminder only applies to the upgrade of your production instance. For information on sandbox upgrades, see status.salesforce.com. Bookmark status.salesforce.com for easy reference to this information. Spring ’24 Release notes. Are you ready, Awesome Admins? It’s almost time for the Spring ’24 Salesforce Release! An essential part of every admin’s job is staying on top of the latest Salesforce Releases. Three times a year, Salesforce releases new features and updates to our technology, enabling users everywhere to take advantage of the latest and greatest that our platform has to offer! As an Awesome Admin, getting the benefits from these releases is made even easier by knowing the basics and best practices. December 20: Review the Release Notes Search the products you use for release updates in the Release Notes section of Salesforce Help. The notes will go live December 20and we will share the link here. Get help from the community! With each release, there are a number of blogs by community members who break it down. Check out the Release Readiness Trailblazer Community Group where you can continue to get updates, share your favorite features, and ask questions about the upcoming release. January 4 before 5 p.m. PT: Be sure to refresh your Sandbox Once you’ve explored the pre-release org and reviewed the Release Notes for features that are important to you, it’s time to try out features related to your customizations in your sandbox. This is a great time to evaluate how specific features may be useful or impact the way your organization uses Salesforce. During each release, there is a group of sandboxes slated to remain on the non-preview instance (i.e. the current release) while there is another group of sandboxes that will upgrade to the preview instance. Use the Salesforce Sandbox Preview Guide to determine the plan for your sandbox instance(s). Below are screenshots of the tool where you can search by sandbox instance and then specify what you want to do with your sandbox — stay on the non-preview or move to preview. It will then instruct you to refresh your sandbox to get to the desired instance or that there is no action needed because your sandbox is slated for the desired instance. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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January 3, 2024in Salesforce
Salesforce data success
03Jan

The Long and Winding Data Success Road

Long and Winding Data Success Road Fostering a Data-Driven Culture for Informed Decision-Making Enhancing trust in data goes beyond technical solutions; it hinges on cultivating a culture that instills confidence and fosters widespread adoption. Data culture, defined as the collective behaviors and beliefs of individuals who value, practice, and promote data usage for improved decision-making, empowers all members of an organization with insights to address complex business challenges. Key Insights: Redefining Data Governance for Trustworthiness Data governance extends beyond a mere set of rules and restrictions; strategically employed, it becomes a vital tool for reinforcing data trustworthiness. An impressive 85% of analytics and IT leaders use data governance to ensure and certify baseline data quality. It entails establishing rules or policies governing the collection, management, storage, measurement, and communication of information, setting parameters for data access, accuracy, privacy, security, and retention. Governance in Action: A Multi-Pronged Approach Defying Data Gravity Data gravity, the notion that accumulating large data volumes in a specific location or system attracts additional applications and services, poses challenges for data relocation. Leaders in analytics and IT adopt a multi-pronged approach, employing an average of 3.2 different strategies to counteract data gravity. Strategies to Mitigate Data Gravity: Like1 Related Posts CRM Cloud Salesforce What is a CRM Cloud Salesforce? Salesforce Service Cloud is a customer relationship management (CRM) platform for Salesforce clients to Read more How Travel Companies Are Using Big Data and Analytics In today’s hyper-competitive business world, travel and hospitality consumers have more choices than ever before. With hundreds of hotel chains Read more Capture Initial Traffic Source With Google Analytics To ensure the proper sequencing of Tags, modify the Tag sequencing in the Google Analytics preview Tag settings. The custom Read more Snowflake and Salesforce with Embed Snowflake has deepened its partnership with investor Salesforce by introducing two tools that seamlessly connect their cloud-native systems. Snowflake and Read more

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January 3, 2024in Salesforce Data Cloud, Salesforce Tableau
Cloud Based Business Solutions
02Jan

What Can’t Generative AI Do?

There is a tremendous amount of discussion about all the capabilities of generative AI, but once in a while it doesn’t hurt to look at the other side of the AI coin. The USC Library published a piece in October of 2023 that did just that. In addition to the identified limitations discussed below, generative AI may be susceptible to issues that have yet to be uncovered or fully grasped. Clearly we learn new things about it every day. What Can’t Generative AI do? Large language models (LLMs) are susceptible to “hallucinations,” producing fictional information presented as factual or accurate. This includes citations, publications, biographical details, and other data commonly used in research and academic papers. Furthermore, answers generated by LLMs may be incorrect, often presented as correct or authoritative. ChatGPT has been known to “make things up” when it’s last data load didn’t cover the time frame asked to generate content about. The fundamental structure of generative AI models, coupled with frequent updates, makes content reproduction challenging. This poses a significant challenge in research and academia, where reproducibility is crucial for establishing credibility. Generative AI models don’t function as databases of knowledge. Instead, they attempt to synthesize and replicate the information they were trained on. This complexity makes it exceptionally difficult to validate and properly attribute the sources of their content. Generative AI models have no reason to believe any information it has is inaccurate. When asked to tell me how the sky was purple, ChatGPT explained both why the daytime sky is normally blue and reasons from volcanic ash to pollution that it might “appear” purple. But when asked who owns Twitter, ChatGPT refers to it as a publicly traded entity as it’s last data load was prior to Elon Musk purchasing and renaming Twitter to X. Is the Data Up to Date? Many common generative AI tools lack internet connectivity and cannot update or verify the content they generate. Additionally, the nature of generative AI models, especially when provided with simple prompts, can lead to content that is overly simplistic, of low quality, or overly generic. When asked for the weather forecast, Chat GPT replied, “I’m sorry, but I don’t have the capability to provide real-time information, including current weather forecasts. Weather conditions can change rapidly, and it’s important to get the most up-to-date information from a reliable source.” Several generative AI models, including ChatGPT, are trained on data with cutoff dates. Thus resulting in outdated information or an inability to provide answers about current events. In some instances, the data cutoff date may not be explicitly communicated to the user. The capabilities of generative AI are obviously limited by outdated data. Data Privacy Precautions: Exercise extra caution when dealing with private, sensitive, or identifiable information, whether directly or indirectly, regardless of using a generative AI service or hosting your own model. While some generative AI tools permit users to set their data retention policies, many collect user prompts and data, presumably for training purposes. USC researchers, staff, and faculty should particularly avoid sharing student information (a potential FERPA violation), proprietary data, or other controlled/regulated information. Salesforce recognizes this. According to their news and insights page, companies are actively embracing generative AI to power business growth. Building trustworthy generative AI requires a firm foundation at the inception of AI development. Salesforce published an overview of their five guidelines for the ethical development of generative AI that builds on their Trusted AI Principles and AI Acceptable Use Policy. The guidelines focus on accuracy, safety, transparency, empowerment, and sustainability – helping Salesforce AI engineers create ethical generative AI from the start. Additional Considerations: Apart from providing direct access to generative AI tools, many companies are integrating generative AI functionality into existing products and application. Tools such as Google Workspace, Microsoft Office, Notion, and Adobe Photoshop to name a few. Extra care should be taken when using these tools for research and academic work. Be careful especially to avoid the use of auto-completion for sentences or generating text without explicit permission. When working with images or videos, clearly communicate and attribute the use of generative AI assistance. Detecting Generative AI: In an effort to counter undisclosed and inappropriate uses of generative AI content, many organizations are developing generative AI detectors. These tools use AI to flag content created by generative AI. However, these tools can be unreliable and have erroneously flagged student content as AI-generated when it was created by a human. Relying solely on these tools to identify the origin of an assignment or work is not advisable. I played with one such tool using content solely written by generative AI. Amazingly it received a 99% human generated score. I rewrote the content in my own words and the score dropped by 20%. In April 2023, Turnitin introduced a preview of their AI detection tool, available to USC instructors via the Turnitin Feedback Studio. When in doubt, professors should engage with their students to better understand if and how generative AI tools were used. This interaction provides an essential opportunity for both parties to discuss the nuances of the technology. Thereby they can address any questions or concerns. Determining how and when the capabilities of generative AI is useful for you, is not ever going to be a cut and dry process. By Shannan Hearne, Tectonic Salesforce Marketing Consultant 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 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

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January 2, 2024in Salesforce Einstein
Ready for GPT5
01Jan

Ready for GPT5

Anticipating GPT-5: OpenAI’s Next Leap in Language Modeling Ready for GPT5-OpenAI’s recent advancements have sparked widespread speculation about the potential launch of GPT-5, the next iteration of their groundbreaking language model. This insight aims to explore the available information, analyze tweets from OpenAI officials, discuss potential features of GPT-5, and predict its release timeline. Additionally, it explores advancements in reasoning abilities, hardware considerations, and the evolving landscape of language models. Clues from OpenAI Officials Speculation around GPT-5 gained momentum with tweets from OpenAI’s President and Co-founder, Greg Brockman, and top researcher Jason Way. Brockman hinted at a full-scale training run, emphasizing the utilization of computing resources to maximize the model’s capabilities. Way’s tweet about the adrenaline rush of launching massive GPU training further fueled anticipation. Training Process and Red Teaming OpenAI typically follows a process of training smaller models before a full training run to gather insights. The red teaming network, responsible for safety testing, indicates that OpenAI is progressing towards evaluating GPT-5’s capabilities. The possibility of releasing checkpoints before the full model adds an interesting layer to the anticipation. Enhancements in Reasoning Abilities – Ready for GPT5 A key focus for GPT-5 is the incorporation of advanced reasoning capabilities. OpenAI aims to enable the model to lay out reasoning steps before solving a challenge, with internal or external checks on each step’s accuracy. This represents a significant shift towards enhancing the model’s reliability and reasoning prowess. Multimodal Capabilities GPT-5 is expected to further expand its multimodal capabilities, integrating text, images, audio, and potentially video. The goal is to create an operating system-like experience, where users interact with computers through a chat-based interface. OpenAI’s emphasis on gathering diverse data sources and reasoning data signifies their commitment to a holistic approach. Predictions on Model Size and Release Timeline Hardware CEO Gavin Uberti suggests that GPT-5 could have around 10 times the parameter count of GPT-4. Considering leaks indicating GPT-4’s parameter count of 1.5 to 1.8 trillion, GPT-5’s size is expected to be monumental. The article speculates on a potential release date, factoring in training time, safety testing, and potential checkpoints. Language Capabilities and Multilingual Data – Ready for GPT5 GPT-4’s surprising ability to understand unnatural scrambled text hints at the model’s language flexibility. The article discusses the likelihood of GPT-5 having improved multilingual capabilities, considering OpenAI’s data partnerships and emphasis on language diversity. Closing Thoughts Predictions about GPT-5’s exact capabilities remain speculative until the model is trained and unveiled. OpenAI’s commitment to pushing the boundaries of AI, surprises in AI development, and potential industry-defining products contribute to the excitement surrounding GPT-5. 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 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 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

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January 1, 2024in Generative AI
Generative AI Trends for 2024
31Dec

Generative AI Trends for 2024

It’s hard to believe that ChatGPT is only a year old. The number of exciting new product launches over the past 12 months has been astonishing — and there’s no sign of slowing down. In fact, quite the opposite. Earlier in November, OpenAI hosted DevDay, where the company announced extensive offerings across B2C and B2B markets. Cohere has doubled down on its knowledge search capabilities and private deployments. Amazon Web Services launched PartyRock, its no-code gen AI app-building playground. Generative AI Trends for 2024 you can expect to see. We believe that last month’s activity sets the stage for 2024 in the gen AI space. Here are six major trends happening across the space: While the technology’s possibilities continue to grow, we believe there are four principles for CEOs to consider as they drive their gen AI agendas. These principles draw from our experiences building gen AI applications with our clients throughout the year, as well as decades of delivering digital and analytics transformations. Be Intentional: Set Gen AI Strategy Top-Down Gen AI is a gold rush. Everyone from shareholders to employees to boards is scrambling to deploy the latest and most powerful gen AI tools, and many large organizations have over 150 gen AI use cases on backlog. While we share their excitement and admire their ambition, allowing dozens of gen AI projects to spawn across an organization puts at-scale value creation at risk. Generative AI Trends for 2024 With recent developments in the gen AI space, the proliferation of use cases and opportunities will continue to split the already divided attention of leadership teams. C-suites must bring focus with a top-down gen AI strategy, constantly asking how the technology can create enduring strategic distance between the organization and its competitors. Here are some examples from first movers: Smart organizations are taking a 2×2 approach: identifying two fast use cases to register quick wins and excite the organization while working on two slower, more transformational use cases that will change day-to-day business operations. Reimagine Entire Domains Rather Than Isolated Use Cases During 2023, most organizations began experimenting with gen AI, building one-off prototypes and buying off-the-shelf solutions. Yet, as these solutions are rolled out to end users, organizations are struggling to capture value. For example, some organizations that invested in GitHub Copilot have yet to figure out how the value capture is passed back to the business. Organizations need to reframe from isolated use cases to the full software delivery lifecycle. Scrum teams need to commit to shipping more product features, or sales need to offer more competitive pricing to win more business. Stopping at just buying a new shiny tool means the productivity gains will not translate to bottom-line gains. This often means reimagining entire workflows and domains. This serves two purposes: 1) it creates a more seamless end-user experience by avoiding point solutions; and 2) organizations can more easily track value against clear business outcomes. For example, an insurer we worked with is reimagining its end-to-end claims process — from first notice of loss to payment. For each step along the way, the insurer has identified gen AI, digital, and analytics opportunities, while never losing sight of the claims adjuster’s experience. Ultimately, this comprehensive approach made a step-change impact on end-to-end handling time. Buy Selectively, Build Strategically Matching the pace of innovation, many new startups and software offerings are entering the market, leaving enterprises with a familiar question: “Buy or build?” On the “buy” side, organizations are wary about investing in capabilities that will eventually be available for a fraction of the cost. These organizations are also skeptical of off-the-shelf solutions, unsure if the software will perform at scale without significant customization. As these solutions mature and prove their value, “buy” strategies will continue to play a central role in any gen AI strategy. Meanwhile, some organizations find compelling business cases to “build.” These players start by identifying use cases that create strategic competitive advantages against their peers by compounding existing strengths in their domain expertise, workflow integration, or regulatory know-how. For example, deploying gen AI to accelerate drug discovery has become standard in the pharmaceutical industry. Additionally, organizations are investing in data and IT infrastructure to enable their portfolio of gen AI use cases. For many organizations, there has been little to no investment in unstructured data governance. Now is the time. Build Products, Not Proofs of Concept (POCs) With the new tooling available, a talented engineer can build a proof-of-concept over a weekend. In some cases, this might be sufficient to serve an enterprise need (e.g., a summarization chatbot). However, for most use cases in a large enterprise context, proofs-of-concept are not sufficient. They do not scale well into production and their performance degrades without the appropriate engineering and experimentation. At OpenAI’s Dev Day, engineers demonstrated how hard it is to turn a POC into a production-grade product. Initially, a demo POC only achieved 45% accuracy for a retrieval task. After a few months and numerous experiments (e.g., fine-tuning, re-ranking, metadata tagging, data labeling, model self-assessment, risk guardrails), the engineers achieved 98% accuracy. Implications of Generative AI Trends for 2024 This has two implications. First, organizations cannot seek near-perfection on every use case. They need to be selective about when it is worthwhile to invest scarce engineering talent to develop high-performance gen AI applications. For some situations, 45% accuracy may be sufficient to deliver business benefits. Second, organizations need to scale their gen AI capabilities to meet their ambitions. Most organizations have identified hundreds of gen AI use cases. Therefore, organizations are turning to reusable code components to accelerate development. Dedicated engineers, often in a Center of Excellence (COE), codify best practices into these code components, allowing subsequent gen AI efforts to build off the lessons learned from pioneering projects. We have seen these components accelerate delivery by 25% to 50%. Throughout the past year, there has been an endless stream of gen AI news and hype. The coming year will likely be similar

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December 31, 2023in Generative AI
Jan '24 Einstein Data Cloud Updates
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 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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December 30, 2023in Einstein 1 Platform, Einstein Insights, Salesforce Data Cloud, Salesforce Einstein
Salesforce Release Notes
29Dec

What’s New With Salesforce’s Release Notes?

Explore the latest updates in the Salesforce Release Notes! Discover new features designed to enhance your usage of the release notes. Effectively treating this page as your go-to source for updates. Visit regularly with each seasonal release to stay informed about the latest enhancements. Know that Salesforce values your feedback. The Salesforce release notes are meant to be a source of information AND a place to ask questions. Effortlessly Access Salesforce Release Information Based on user feedback on how customers navigate and utilize this valuable content, Salesforce has strategically positioned the Release Updates section near the top of the Release Notes. By the table of contents. Easily locate it right after the Salesforce Overall section for swift access. Unified Einstein Features for Seamless Discovery They’ve streamlined the Einstein and Einstein Generative AI sections of the release notes into a consolidated Einstein section. This simplifies the process of finding the most intelligent features and platform improvements. In true Salesforce fashion all powered by predictive AI, generative AI, or a combination of both. Expect Einstein features and platform changes to be rolled out as frequently as monthly. Prudently check back often. Stay Updated with Salesforce Customer Success on X As part of Salesforce’s evolution, they are retiring the @salesforcedocs X handle and joining forces with Salesforce Customer Success at @asksalesforce. Follow them there for curated documentation updates and highlights to stay in the loop. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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December 29, 2023in Salesforce
Salesforce Einstein Copilot
28Dec

What’s Included in Einstein Copilot Studio?

Christmas came early this year with Salesforce’s announcement of Einstein Copilot Studio. Einstein Copilot Studio will encompass the following features: By Tectonic’s Salesforce Marketing Consultant, Shannan Hearne Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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December 28, 2023in Einstein 1 Platform, Salesforce Einstein
Salesforce Flow
24Dec

Einstein Flow and Generative AI

By Shannan Hearne, Tectonic Marketing Consultant Based on Nov 2023 Salesforce post from Cesar Castro As part of the ongoing evolution of Salesforce’s Einstein AI, Salesforce provided an update on how Einstein is impacting one of your favorite tools in your Salesforce admin toolkit: Salesforce Flow. Flow, with its numerous powerful capabilities, has been instrumental in helping Salesforce Admins streamline and automate their work, delivering value to all end users in their organizations.  Often without the need for any additional Salesforce development assistance! Einstein Flow and Generative AI are powering a whole new brand of Salesforce actions. Salesforce Flow is a blanket term for everything in the Salesforce ecosystem that allows you to create, manage, and run automation with clicks not code.  Those of you who are using Flow on the regular?  You are known as Flownatics! Working With Einstein Flow and Generative AI In preparation for Einstein for Flow, content was collaborated on with Ajaay Ravi, Einstein for Flow Product Manager, Cesar Castro, Product Manager for Einstein Flow, and Vera Vetter, Director of Product Management, AI Research. Together, as product managers, they are actively working on enhancing Einstein for Flow. As Tectonic’s Salesforce Marketing Consultant I am very excited to share the news with you! Generative AI Einstein for Flow is a generative artificial intelligence (AI) tool that utilizes large language models (LLMs). To drive process automation across multiple Salesforce products. Whether you are a new Flow user or an experienced admin, Einstein for Flow aims to assist in learning and adopting this capability. By aiding in the creation of more complex flows and time saving automations.  Many of Salesforce Flow’s capabilities allow you to do what used to require Apex developers. The powerhouse behind Einstein for Flow is CodeGen, Salesforce’s in-house LLM released by Salesforce AI Research in 2022 to transform software development. CodeGen is the driving force behind the tailored AI solution for the needs of Salesforce users. So, how does Einstein for Flow operate? It’s as straightforward as describing your flow requirement in plain language through a natural language prompt. Einstein then invokes code to interpret and generate the natural flow data. To handle intricate flows, a concept called a “chain of thought” is introduced. By breaking down the flow into manageable steps, sequentially creating each part, and merging them to produce the final flow. In tis way Einstein is ensuring accuracy in meeting your business automation needs. Looking ahead, Salesforce’s roadmap for Einstein for Flow includes exciting features. One notable feature is the ability to use Einstein to edit an existing flow. This is irrespective of whether Einstein created it. Salesforce’s goal is to make flow building more accessible by enabling editing of both new and existing flows. In upcoming releases, an Einstein assistive interface will be integrated. Thereby allowing you to open and edit flows by conversing with Einstein in natural language. For all you Star Trek fans out there, the age of the Enterprise doing your verbal bidding is upon us! Einstein Suggestions Einstein will suggest changes and present a list of interconnected updates resulting from the proposed modifications. Designed to be user-friendly yet advanced, you can inspect recommended changes. Then review step by step, and view individual modifications. Additionally, a history of all changes suggested and made by Einstein will be available for those interested in maintaining an audit trail of AI-driven alterations. This is just the beginning for Einstein for Flow. As Salesforce launched a pilot program with diverse customers, they plan to go general availability (GA) in Spring ’24, with capabilities to generate flows for both standard and custom objects. Customer feedback will play a crucial role in shaping their future roadmap as they continue to explore more use cases and capabilities for Einstein for Flow. Flows are such a powerful tool, they are like visual coding created with clicks. Unlike code requiring only an understanding of programming concepts and logic. Examples of Flow Automation Use Cases: Stay tuned for updates as we ride the Einstein for Flow wave. It’s a game-changer! Tectonic will be watching and implementing with Einstein Flow and look forward to helping you do the same. 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 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 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

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December 24, 2023in Salesforce Einstein, Salesforce Implementation Services, Salesforce Managed Services
2024 AI and Machine Learning Trends
23Dec

2024 AI and Machine Learning Trends

In 2023, the AI landscape experienced transformative changes following the debut of ChatGPT in November 2022, a landmark event for artificial intelligence. 2024 AI and Machine Learning Trends ahead, AI is set to dramatically alter global business practices and drive significant advancements across various sectors. Organizations are shifting their focus from experimental initiatives to real-time applications, reflecting a more mature understanding of AI’s capabilities while still being intrigued by generative AI technologies. Key AI and Machine Learning Trends for 2024 Here are the top trends shaping the AI and machine learning landscape for 2024: 1. Agentic AIAgentic AI is evolving from reactive to proactive systems. Unlike traditional AI that primarily responds to user inputs, these advanced AI agents demonstrate autonomy, proactivity, and the ability to independently set and pursue goals. 2. Open-Source AIOpen-source AI is democratizing access to sophisticated AI models and tools by offering free, publicly accessible alternatives to proprietary solutions. This trend has seen significant growth, with notable competitors like Mistral AI’s Mixtral models and Meta’s Llama 2 making strides in 2023. 3. Multimodal AIMultimodal AI integrates various types of inputs—such as text, images, and audio—mimicking human sensory capabilities. Models like GPT-4 from OpenAI showcase this ability, enhancing applications in fields like healthcare by improving diagnostic precision. 4. Customized Enterprise Generative AI ModelsThere is a rising interest in bespoke generative AI models tailored to specific business needs. While broad tools like ChatGPT remain widely used, niche-specific models are increasingly popular for their efficiency in addressing specialized requirements. 5. Retrieval-Augmented Generation (RAG)RAG combines text generation with information retrieval to boost the accuracy and relevance of AI-generated content. By reducing model size and leveraging external data sources, RAG is well-suited for business applications that require up-to-date factual information. 6. Shadow AIShadow AI, which refers to user-friendly AI tools used without formal IT approval, is gaining traction among employees seeking quick solutions or exploring new technologies. While it fosters innovation, it also raises concerns about data privacy and security. Looking Ahead to 2024 These trends highlight AI and machine learning’s expanding role across industries in 2024. Organizations must adapt to these advancements to remain competitive, balancing innovation with strong governance frameworks to ensure security and compliance. Staying informed about these developments will be crucial for leveraging AI’s transformative potential in the coming year. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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December 23, 2023in Generative AI
nCino and Salesforce
21Dec

nCino and Salesforce

Leaders in cloud innovation reinforce alliance to provide best-in-class solutions to the financial services industry by extending successful partnership to 2031. Updated commercial terms are expected to improve nCino’s subscription gross margins. Wilmington, N.C. – December 21, 2023 – nCino, Inc. (NASDAQ: NCNO), a pioneer in cloud banking for the global financial services industry, today announced an expanded partnership with Salesforce to accelerate the delivery of best-in-class cloud solutions to the financial services industry. This builds on nCino and Salesforce’s long-standing collaboration, established in 2011, to empower financial institutions with digital innovations that increase efficiency, transparency, and reduce risks while driving customer growth and loyalty. “Our strategic partnership with Salesforce has enabled nCino to transform the financial services industry by providing industry-specific solutions that drive efficiencies, deliver intelligence, and help institutions modernize for a more agile future,” said Pierre Naudé, Chairman and CEO of nCino. “We’re glad to again be expanding our work with Salesforce and are committed to utilizing each other’s strengths to further benefit financial institutions of all sizes around the globe.” “nCino’s success is a testament to the enormous opportunity in front of ISVs building on Salesforce,” said Brian Landsman, Executive Vice President, Global Technology Partners, at Salesforce. “Salesforce is the world’s #1 AI CRM, trusted by thousands of partners to power purpose-built solutions for highly specialized industries. The expansion of our work with nCino will only accelerate how our customers are reimagining the future of personalized financial services.” As part of the agreement, nCino will deepen its connectivity to Salesforce platform tools including CRM, powered by AI and automation, and Financial Services Cloud. These innovations will empower financial institutions utilizing nCino and Salesforce to further modernize customer experiences like onboarding, loan origination, deposit account opening, and portfolio management. The expanded agreement also includes updated commercial terms which are expected to improve nCino’s subscription gross margins, minimum payment commitments from nCino during the first four fiscal years of the term of the extension, and an extension of the term of the agreement to 2031. About nCinonCino (NASDAQ: NCNO) is the worldwide leader in cloud banking. Through its single software-as-a-service (SaaS) platform, nCino helps financial institutions serving corporate and commercial, small business, consumer, and mortgage customers modernize and more effectively onboard clients, make loans, manage the loan lifecycle, and open accounts. Transforming how financial institutions operate through innovation, reputation and speed, nCino is partnered with more than 1,850 financial services providers globally. For more information, visit www.ncino.com. Salesforce, Financial Services Cloud and others are among the trademarks of Salesforce, Inc. nCino Media ContactsNatalia [email protected] Safe Harbor StatementThis press release contains forward-looking statements within the safe harbor provisions of the Private Securities Litigation Reform Act of 1995. Forward-looking statements generally include actions, events, results, strategies and expectations and are often identifiable by use of the words “believes,” “expects,” “intends,” “anticipates,” “plans,” “seeks,” “estimates,” “projects,” “may,” “will,” “could,” “might,” or “continues” or similar expressions. Any forward-looking statements contained in this press release are based upon nCino’s historical performance and its current plans, estimates, and expectations, and are not a representation that such plans, estimates, or expectations will be achieved. These forward-looking statements represent nCino’s expectations as of the date of this press release. Subsequent events may cause these expectations to change and, except as may be required by law, nCino does not undertake any obligation to update or revise these forward-looking statements. These forward-looking statements are subject to known and unknown risks and uncertainties that may cause actual results to differ materially including, among others, risks and uncertainties relating to the market adoption of our solution and privacy and data security matters. Additional risks and uncertainties that could affect nCino’s business and financial results are included in reports filed by nCino with the U.S. Securities and Exchange Commission (available on our web site at www.ncino.com or the SEC’s web site at www.sec.gov). Further information on potential risks that could affect actual results will be included in other filings nCino makes with the SEC from time to time. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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December 21, 2023in Salesforce Financial Services Solutions, Salesforce Implementation Services
Copilot Capabilities
20Dec

Copilot Capabilities

Einstein Copilot stands out from other AI assistants and copilots by leveraging Salesforce customers’ proprietary and trusted data to generate valuable responses. Unlike alternatives that lack access to relevant company data or require costly AI model training, Einstein Copilot capabilities provide answers, content summaries, task automation, and complex conversation interpretation—all while maintaining strict data governance. This innovation is achieved through a combination of conversational user interface, a robust large language model, and trusted company data integrated directly into Salesforce’s leading AI CRM applications. Einstein Copilot revolutionizes how users interact with Salesforce applications, offering seamless integration into their workflow to drive significant productivity improvements. With Einstein Copilot Studio, organizations can tailor their assistant to meet specific business requirements, further enhancing its effectiveness. Additionally, Einstein Copilot and Einstein Copilot Studio feature the Einstein Trust Layer, safeguarding sensitive data while leveraging trusted information to enhance generative AI responses. Copilot Capabilities The significance of these advancements is underscored by the increasing investment in AI, with 45% of executives boosting their AI initiatives. Early adopters are already experiencing benefits such as freeing up over 30% of employee time to focus on revenue growth, cost reduction, and delivering superior customer experiences. Einstein Copilot delivers accurate recommendations and content for various tasks, from building digital storefronts to drafting custom code and providing sales guidance. It securely integrates customer data from Salesforce Data Cloud, including enterprise content, Slack conversations, telemetry data, and structured/unstructured data, ensuring informed and precise decision-making. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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December 20, 2023in Einstein 1 Platform, Generative AI, Salesforce, Salesforce Slack
Marketing Cloud Cloudpages
20Dec

Salesforce Marketing Cloud for a Healthcare Provider

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

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December 20, 2023in Data, Mulesoft, Salesforce, Salesforce Health Cloud, Salesforce Marketing Cloud, Snowflake

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