Salesforce Einstein - gettectonic.com - Page 15
Salesforce Data Cloud
15May

Salesforce Data Cloud Explained

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

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May 15, 2023in Mulesoft, Salesforce Data Cloud, Salesforce Einstein, Salesforce Implementation Services
Revolutionizing Public Sector Efficiency
12May

Revolutionizing Public Sector Efficiency

Salesforce: Transforming and Revolutionizing Public Sector Efficiency Salesforce, known worldwide as the premier CRM solution, continues to innovate with its adaptable features tailored to diverse audiences. It excels in delivering cutting-edge solutions, addressing unique needs across various industries and sectors. Particularly, the public sector stands to gain substantial benefits from Salesforce’s capabilities, offering a suite of solutions poised to optimize operations within any public office setting. Understanding the Role of Salesforce in the Public Sector The public sector encompasses the administrative segment responsible for managing essential citizen concerns at state, local, federal, and governmental agency levels. While carrying out critical tasks, these entities can significantly enhance efficiency with the right tools. Salesforce is dedicated to optimizing and streamlining processes within the public sector, recognizing its vital importance. Government offices face similar expectations to private enterprises, with citizens anticipating service quality on par with commercial experiences. Therefore, public entities must deliver efficiency, agility, and direct engagement to demonstrate proximity to the populace. In response to these expectations, Salesforce has developed a range of solutions tailored to the specific demands of the public sector. Revolutionizing Public Sector Efficiency Salesforce’s offerings for the public sector include meticulously crafted applications designed to meet its unique requirements. These flexible and secure e-government tools aim to revolutionize the sector’s experience, providing a comprehensive view of citizens and enhancing the efficacy of public employees. By simplifying processes and fostering innovation, these solutions drive efficiency at both organizational and individual levels, facilitating smoother operations. Integrated into Public Sector Solutions, these offerings leverage Salesforce’s standard functionalities and Service Cloud capabilities. Additionally, they enable the creation of an Experience Cloud site, allowing citizens seamless access to government services. Known as a Citizen Portal. Some of the available solutions cater to general tasks managed by public sector agencies, including: Thanks to these solutions, citizens can effortlessly navigate various processes, such as applying for licenses or permits. Through an online portal accessible at all times, individuals can interact seamlessly with public service agencies. Intelligent forms dynamically adjust based on user input, simplifying the submission process. From an employee standpoint, work processes are streamlined, with all citizen requests conveniently consolidated in one location. The system offers recommendations to guide employees, simplifies task delegation, and ensures seamless collaboration across departments. Key Advantages of Salesforce Solutions for the Public Sector Salesforce solutions offer numerous advantages to the public sector, aligning with citizens’ and employees’ current demands. These include: Salesforce emerges as an invaluable ally in the public sector’s modernization journey, transforming processes to be more agile and efficient. For organizations seeking to implement Salesforce solutions tailored for the public sector, the Tectonic team stands ready to assist. In the ever-evolving landscape of public administration and government services, the need for advanced, secure, and user-friendly technology solutions has never been more crucial. Enter Salesforce Public Sector Cloud—a dynamic platform designed to transform how government agencies engage with citizens, deliver services, and drive efficiency in their operations. Overview of Salesforce Public Sector Cloud: Salesforce Public Sector Cloud is a specialized offering tailored to meet the unique needs of government entities at all levels. Whether it’s federal, state, or local government agencies, the platform is engineered to enhance collaboration, streamline processes, and ultimately improve the delivery of public services. Key Features and Capabilities: Real-World Impact: Several government agencies have already embraced Salesforce Public Sector Cloud, realizing tangible benefits in their day-to-day operations. From improved citizen satisfaction to streamlined internal processes, the impact of this cloud solution is evident across various use cases. Challenges and Considerations: While Salesforce Public Sector Cloud offers numerous advantages, it’s essential to consider potential challenges. These may include customization complexities, data migration issues, and the need for comprehensive training for government personnel. A thoughtful and well-executed implementation strategy is crucial to overcoming these challenges. Salesforce Introduces Public Sector Einstein 1 for Service: Salesforce today announced Public Sector Einstein 1 for Service, including CRM, trusted AI, and data capabilities. What’s new in compliance: Salesforce also now offers several Federal Risk and Authorization Management Program (FedRAMP) compliant tools to help government agencies drive efficiency and productivity while meeting regulatory requirements. These tools include:  Content updated April 2024. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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May 12, 2023in Einstein 1 Platform, Public Sector Solutions, Salesforce, Salesforce Einstein, Salesforce Experience Cloud, Salesforce Government Cloud, Salesforce Public Sector Solutions, Salesforce Slack
Salesforce Flow
05May

Einstein GPT Integration with Flow and Data Cloud Now Available

Salesforce has recently unveiled exciting new capabilities for Flow, Einstein GPT Integration with Flow and Data Cloud. Introducing Einstein GPT and Data Cloud features to its growing family of automation tools. This development empowers everyday administrators, eliminating the need for extensive engineering teams to harness large datasets for automation purposes. The groundbreaking aspect lies in the ability to achieve this in real-time, using a user-friendly interface without the need for coding. Introduction to Einstein GPT: Einstein GPT builds upon ChatGPT technology, combining public and private AI models with CRM data within Salesforce. This allows users to pose natural-language prompts directly within Salesforce CRM, receiving AI-generated content that adapts continuously to changing customer information and needs. The learning capability of Einstein GPT ensures ongoing improvement based on user input, aligning with best practices. Einstein GPT for Flow: When integrated with Salesforce Flow, Einstein GPT enables users to create and modify automations through a conversational interface, simplifying the flow creation process significantly. This fusion lowers barriers for non-technical users, enhancing the overall experience with Flow Builder and ensuring adherence to best practices. Key benefits of Einstein GPT for Flow include: Pricing details for Einstein GPT products are pending confirmation, and Salesforce will soon announce pilot program dates to broaden accessibility. Data Cloud for Flow: Introduced at Dreamforce 2022, Salesforce Data Cloud, formerly Genie, facilitates highly personalized customer experiences in real-time. Serving as a command center for customer data, Data Cloud integrates real-time data streams with Salesforce data, powering Flow with actionable insights. By combining Data Cloud with Flow, users can automate complex workflows and trigger actions based on real-time changes without the need for extensive IT involvement. This approach streamlines the process of designing, building, and testing custom integrations, reducing the burden on IT teams. Key advantages of Data Cloud for Flow include: These announcements bring forth transformative capabilities, making data utilization more accessible and streamlining the automation process within Salesforce. The combination of Einstein GPT and Data Cloud for Flow opens up possibilities for creating personalized and interconnected customer experiences across different sectors. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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May 5, 2023in Salesforce Data Cloud, Salesforce Einstein
Salesforce Nonprofit Cloud
03May

Trustworthy Data in AI

Behind transformative breakthroughs powered by generative AI, advanced analytics, and real-time personalization, is the quiet reliance on trusted data. Trustworthy Data in AI powers much of what we do. Nearly all analytics and IT decision makers surveyed (92%) say trustworthy data is needed more than than ever before. How can business, IT, and analytics leaders harness data to fuel these opportunities and overcome roadblocks that are derailing data-driven strategies? Let’s uncover the obstacles leaders are facing and the tactics they’re focusing on to maximize their data’s volume. Characteristics of trustworthy AI systems include: valid and reliable, safe, secure and resilient, accountable and transparent, explainable and interpretable, privacy-enhanced, and fair with harmful bias managed. What is trustworthy use of artificial intelligence? Together, governance and compliance are the means by which an organization and its stakeholders ensure AI deployments are ethical and can be trusted. User privacy is respected, and data is not used or stored beyond its intended and stated use and duration; users are able to opt-in / out of sharing their data. Requirements of Trustworthy AI Like Related Posts Salesforce Artificial Intelligence Is artificial intelligence integrated into Salesforce? Salesforce Einstein stands as an intelligent layer embedded within the Lightning Platform, bringing robust Read more 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 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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May 3, 2023in Salesforce Einstein
Sales Cloud Innovation Driven by UX Design Principles
26Apr

Use Cases for AI in Marketing

Navigating The Challenges as AI Empowers Marketers Use Cases for AI in Marketing. What is AI in marketing? AI marketing is when marketers use artificial intelligence to gather insights into their customers and produce better content. Marketing assets guided by AI are personalized and optimized for the customer journey. This can look like chatbots, targeted advertising, and content generation. Marketers encounter diverse challenges shaped by industry, organizational size, and customer dynamics. Despite these variations, they converge on four crucial pillars essential for success: understanding customers, personalizing interactions, engaging across the entire customer journey, and swiftly and accurately analyzing results. Establishing a cohesive customer profile across all touchpoints requires the identification of customers across diverse devices and channels. AI proves invaluable by employing probability models to match actions with identities. AI goes beyond by unveiling previously undiscovered audience insights and segments. When dealing with expansive audience datasets, traditional business intelligence tools may falter, but AI excels at clustering data for analysis and pinpointing overlaps in audiences or segments. As marketers accumulate new data points from interactions, content, and conversations, the sheer volume and speed can overwhelm conventional analysis methods. Here, AI steps in to augment data and attributes through capabilities like natural language processing and image recognition. Additionally, manual lead scoring and rule-based approaches can introduce biases. AI intervenes with predictive lead scoring, offering insights into customer journeys and enhancing accuracy. Generative AI could help SMEs create more personalized and effective marketing strategies through utilizing capabilities like SD, DL, and IoT. For example, SMEs might use Generative AI to generate personalized product or service suggestions for certain customers. As a result, customer engagement and retention can rise. Marketers are using gen AI to analyze competitor moves, assess consumer sentiment, and test new product opportunities. Rapid generation of response-ready product concepts can improve the efficiency of successful products, increase testing accuracy, and accelerate time to market. AI-driven content marketing tools can analyze vast amounts of data to identify trending topics, customer pain points, and content preferences. This allows manufacturers to create more relevant and engaging content that resonates with their target audience, driving better lead generation and brand awareness. Leveraging AI in these capacities empowers marketers to delve deeper into customer understanding, facilitating the delivery of enhanced experiences and an overall boost in marketing effectiveness. 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 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 Guide to Creating a Working Sales Plan Creating a sales plan is a pivotal step in reaching your revenue objectives. To ensure its longevity and adaptability to Read more 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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April 26, 2023in Salesforce Einstein
Shifting KPIs With Real-Time Intelligence
25Apr

Shifting KPIs With Real-Time Intelligence

Marketing without metrics is akin to driving blindfolded. To gauge the effectiveness of their efforts, marketers are investing in analytics capabilities to gain a precise understanding of how their messages, campaigns, and marketing expenditures impact their objectives. The ability to swiftly unlock these insights empowers marketers to promptly address customer needs and make well-informed decisions to propel business growth. This is bringing about Shifting KPIs With Real-Time Intelligence In contrast to 61% of underperforming marketers, a significant 72% of high-performing marketers can analyze marketing performance in real time. This real-time analysis provides them with a distinct advantage in responding to and optimizing campaign performance. However, a notable 33% of marketers still rely on manual processes for marketing attribution, a figure that has seen marginal improvement from 34% in 2020. In 2022, 68% of marketers claim they can analyze marketing performance in real time. For organizations aiming to enhance efficiency and maximize value, identifying the right metrics to track is imperative. As marketing budgets face rigorous scrutiny, analytics offer leaders the insights needed to optimize spending and reduce acquisition costs, reinforcing the value of marketing efforts. Shifting KPIs With Real-Time Intelligence The landscape of analytics has expanded, with marketers now monitoring a comprehensive set of metrics, including year-over-year revenue and customer satisfaction. Personalization and customer touchpoints have gained prominence, leading to increased tracking of web/mobile analytics, content engagement, and customer lifetime value. Marketers are now monitoring an extensive array of key performance indicators (KPIs), encompassing revenue, customer satisfaction metrics (CSAT), web and mobile analytics, customer acquisition costs, B2B sales funnel statistics, content engagement, customer retention rates, customer referral rates, and customer lifetime value. Despite the growing sophistication in tracking various metrics, marketers highlight measuring marketing ROI/attribution as their second most significant challenge. This indicates a continued need for streamlining the reporting process to enhance efficiency and effectiveness. 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 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 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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April 25, 2023in Salesforce Einstein
Cloud First
19Apr

Advances in Generative AI

What is generative AI?  Generative AI focuses on creating new and original content, chat responses, designs, synthetic data or even deepfakes.  While predictive AI worked on predefined, human supplied rules, generative AI functions somewhat autonomously. Advances in Generative AI have been groundbreaking. Advances in generative AI represent a significant advancement beyond established technologies like predictive AI, and business leaders are eagerly embracing its potential. A remarkable 91% recognize generative AI as a major advantage, driven by its diverse applications, from content creation to software development. Despite its novelty, generative AI is rapidly progressing, causing over three-quarters of business leaders to express concerns about potentially missing out on its benefits. In particular, marketing leaders are apprehensive about not fully leveraging generative AI in their workflows, with 88% worried that their companies are lagging behind. Insight Generation and Decision-Making: Going beyond traditional data analysis, generative AI excels by not only analyzing existing data but also generating potential scenarios. This predictive modeling empowers businesses to anticipate market shifts, understand consumer preferences, and identify potential risks, fostering proactive strategies over reactive ones. Generative AI’s Global Impact: Generative AI has captivated global attention, with ChatGPT becoming the fastest-growing software program in history, reaching a hundred million users within two months of its public debut. This surge has sparked an arms race among tech giants like Microsoft and Google, and AI chip maker Nvidia has witnessed increased business. Unlike previous AI programs that provided numeric scores, generative AI, including programs like Stability AI’s Stable Diffusion and OpenAI’s DALL-E, reproduces elements of the real world. Amazon announced in 2023 that its voice assistant Alexa now comes with generative AI capabilities. Apple is developing a large array of features that use generative AI, including a new version of Siri expected to launch in 2024. Mixed Modality in AI: The concept of mixed modality or “multi-modality” is taking center stage, enabling programs to fuse text, images, physical space representations, sounds, video, and entire computer functions as smart applications. This approach enhances program capabilities and contributes to continuous learning, potentially advancing the goal of “embodied AI” and robotics. Evolution of Generative AI: Generative AI will continue evolving, contributing to advancements in translation, drug discovery, anomaly detection, and the generation of new content, spanning text, video, fashion design, and music. A generative AI chatbot, for example, is a type of conversational AI system that uses deep learning and natural language processing techniques to generate human-like text responses in real-time. These chatbots can hold text-based conversations with users, understand user input, and generate contextually relevant responses. Transformative Trends in Marketing and Sales Operations: Generative AI is reshaping marketing and sales operations with key trends, including hyper-quick sales and marketing content creation, automation of repetitive tasks (e.g., keyword research, administrative work, content formatting, and data analysis), and the facilitation of sales enablement and custom materials. What is the Main Goal of Generative AI? The answer likely would vary depending on who you ask, but commonly we expect generative AI tools to change the calculus of knowledge work automation. Generative AI isn’t going to eliminate the need for human workers, but it will assist them with the ability to produce human-like writing, images, audio, or video in response to plain-English text prompts. The potential to collaborate with human partners to generate contact that represents practical work is exciting. Curious how generative AI could help your business? Contact Tectonic today to learn more. Like1 Related Posts Salesforce Artificial Intelligence Is artificial intelligence integrated into Salesforce? Salesforce Einstein stands as an intelligent layer embedded within the Lightning Platform, bringing robust Read more 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 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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April 19, 2023in Salesforce Einstein
Sales Cloud Einstein
17Apr

Salesforce Einstein Explained

Einstein serves as Salesforce’s integrated AI layer, intricately woven into nearly every Salesforce Cloud. Salesforce Einstein Explained. While certain features, like Opportunity Scoring in Salesforce, are now offered at no cost, many Einstein functionalities are premium add-ons for essential Salesforce products like Sales, Service, Commerce, and Marketing Cloud. A notable development came in March 2023 when Salesforce introduced Einstein GPT, an extension of the Einstein product. This groundbreaking application leverages the ChatGPT platform from OpenAI, renowned for its widespread popularity, and is anticipated to be released later this year. Thereby incorporating generative AI into many Salesforce cloud features. Salesforce AI delivers trusted, extensible AI grounded in the fabric of our Platform. Utilize our AI in your customer data to create customizable, predictive, and generative AI experiences to fit all your business needs safely. Bring conversational AI to any workflow, user, department, and industry with Einstein. Salesforce Einstein is the only comprehensive Artificial Intelligence for CRM. It is data ready to work in your Salesforce org and clouds. Einstein is an integrated set of AI technologies that make the Customer Success Platform smarter. Einstein is the only comprehensive AI for CRM. It is: Einstein enables you to become an AI-first company so you can get smarter and more predictive about your customers. What can you do with Einstein? Drive productivity and personalization with predictive and generative AI across the Customer 360 with Salesforce Einstein. Create and deploy assistive AI experiences natively in Salesforce, allowing your customers and employees to converse directly with Einstein to solve issues faster and work smarter. Empower sellers, agents, marketers, and more with AI tools safely grounded in your customer data to make every customer experience more impactful. Build and customize a conversational AI assistant for CRM. Einstein Copilot is a trusted, generative-AI powered assistant built into the user experience of every Salesforce application. Whether employee-facing or customer-facing, Einstein Copilot can automatically reason through tasks based on pre-built skills. Use prompts, APIs, apex, and more to customize your own AI assistant. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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April 17, 2023in Einstein Insights, Salesforce Einstein
hospitality
07Apr

Salesforce Einstein and Your Data

Einstein Lead Scoring is a robust tool, equipping sales teams to accelerate deal closures. Integrated into Salesforce’s Sales Cloud Einstein platform, this tool harnesses the power of artificial intelligence (AI) to analyze historical sales data, identifying leads with the highest likelihood of conversion. Salesforce Einstein and Your Data. Utilize AI to score leads based on their alignment with your company’s historical successful conversion patterns. Empower your sales team to prioritize leads according to their lead scores, and understand which fields most influence each lead score. Einstein Lead Scoring employs data science and machine learning to show patterns in your business’s lead conversion. Predicting which current leads to prioritize based on your business’s conversion patterns, Einstein offers a more straightforward, faster, and accurate solution compared to traditional rules-based lead scoring approaches. The tool examines past leads to identify commonalities with previously converted leads, scoring leads using various lead fields. Admins can exclude fields that don’t impact lead quality. Einstein also categorizes certain lead text fields, such as job titles or industries, creating associations for better pattern recognition. Einstein creates a predictive model for your organization, reanalyzing lead data every 10 days to ensure it captures emerging trends. Whether using a global model or a personalized one based on your data, Einstein Lead Scoring adds a Lead Score field to leads, allowing sales reps to prioritize work effectively. Sales representatives benefit from Einstein Lead Scoring’s ability to effortlessly identify and prioritize promising leads. The system, utilizing machine learning algorithms, scrutinizes data linked to lead records, recognizing patterns indicative of a heightened probability of conversion. Salesforce Einstein and Your Data Crafting a lead scoring model becomes a streamlined process with Einstein’s automated approach. The tool examines standard and custom fields associated with the Lead object, employing diverse predictive models like Logistic Regression, Random Forests, and Naive Bayes. Monthly model updates ensure ongoing accuracy and relevance, while leads receive scores hourly for the latest predictions. Einstein Lead Scoring facilitates lead segmentation and prioritization, offering insights into factors influencing conversion probabilities. These factors are prominently displayed on each lead record, enabling sales reps to prepare swiftly for every call, essentially providing each representative with a personal data scientist, elevating connection and conversion rates. Learn more about the lead prioritization process facilitated by Einstein Lead Scoring. Einstein Lead Scoring utilizes data science and machine learning to unveil patterns in your business’s lead conversion history, predicting which current leads to prioritize. This approach, leveraging machine learning, provides a simpler, faster, and more accurate solution compared to traditional rules-based lead scoring. The Scoring Model: Einstein analyzes past converted leads, including custom fields and activity data, to determine conversion patterns. Identifying current leads with commonalities to prior converted leads, Einstein builds one or more scoring models for your organization. During setup, Salesforce admins can choose to score all leads together or group them into segments based on field criteria. A separate scoring model is built for each lead segment, allowing admins to omit certain lead fields if necessary. The global model, utilizing anonymous data from multiple Salesforce customers, is employed when there isn’t enough lead data initially. As your organization accumulates sufficient lead data, Einstein shifts to a personalized model for better results. Einstein models are refreshed every 10 days or whenever admins update Lead Scoring configurations. Lead scores are updated at least every six hours for real-time predictions. Factors That Contribute to Scores: Einstein displays the lead’s field values with the most significant positive and negative effects on its score. These fields, known as top positives and top negatives, offer insights into why leads are likely to convert or not. However, in some cases, a lead’s score may be influenced by multiple fields with slight effects, and in such instances, top positives or top negatives may not be displayed. When Scores Don’t Appear: Several reasons may lead to a score not appearing on a particular lead: When Scores Don’t Change: Scores may not change on some leads for reasons such as: In medium to large enterprises, Sales agents manage numerous leads from various channels, and sorting through them can be overwhelming. Lead Scoring, assigning a score to a lead based on its ranking among prospects, provides a valuable indicator for Sales teams looking to focus on promising leads. Lead Scoring Definition: Lead Scoring is a score assigned to a lead, ranking it in relation to others, indicating the likelihood of conversion. In the vast sea of leads, a higher lead score serves as a handy indicator, helping Sales teams prioritize their attention effectively. While Lead Scoring has been a longstanding practice, the challenge lies in creating a consistent and effective lead scoring model. Without a reliable framework, ranking leads becomes arbitrary, leading to issues such as unknown or undocumented conversion patterns, models based on incorrect assumptions, or reliance on stale or non-relevant data. Sales Cloud Einstein addresses these challenges with Einstein Lead Scoring, utilizing machine learning and data science to discover patterns in lead conversion history. The tool autonomously selects the best predictive model for each customer, eliminating the need for statistical or mathematical expertise. Monthly model updates ensure ongoing accuracy, and leads receive scores hourly, providing businesses with the latest and most precise predictions. Einstein Lead Scoring, a key capability of Sales Cloud Einstein, revolutionizes lead conversion for sales reps. It automates the analysis of historical sales data, identifying top factors determining lead conversion likelihood. Sales reps can segment and prioritize leads, gaining insights into the factors influencing conversion probabilities, displayed prominently on each lead record. Einstein Lead Scoring acts as a personal data scientist for each sales representative, enhancing connection and conversion rates. Tectonic, as your Salesforce implementation success partner, can tailor Salesforce solutions aligned with your business needs, leveraging the power of tools like Einstein Lead Scoring. Based in Colorado, Tectonic is a Salesforce Consulting Partner, boasting a skilled team of certified Consultants, Developers, Analysts, and Project Managers. Contact us today to explore innovative Salesforce solutions for your business. Like1 Related Posts Salesforce OEM

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April 7, 2023in Einstein Insights, Salesforce Einstein
Einstein GPT and AI-Powered CRM
06Apr

Einstein GPT and AI-Powered CRM

As many of you are already aware, ChatGPT has become a prominent term in AI chatbot systems. It leverages predictive computing to respond to user questions and queries, spanning from recipes for favorite dishes to new song lyrics or even code writing assistance. It’s quite thrilling, isn’t it? Einstein GPT and AI-Powered CRM bring forth the world’s first generative AI tool for customer relationship management. In this insight, we’ll introduce you to Einstein GPT, a fusion of proprietary Einstein AI models with ChatGPT or other leading large language models. We’ll dig into its applications across sales, service, marketing, and development. Firstly, GPT stands for Generative Pre-Trained Transformer, an AI framework that generates text from datasets and offers human-like responses to user queries. Einstein GPT and AI-Powered CRM. Einstein GPT marks the world’s inaugural implementation of generative AI CRM technology, delivering AI-generated content across sales, service, marketing, commerce, and IT interactions, at scale. Although currently in a closed pilot phase, it’s set to transition to the BETA phase soon. Now, let’s explore how Einstein GPT can assist sales representatives in composing emails. How Einstein GPT Can Enhance Sales?Imagine you’re an Account Executive (AE) charged with engaging the prospect account, Escape LTD. You can kickstart by asking Einstein Assistant to provide an overview of the account, including recent news. It furnishes details instantly, eliminating the need for manual research (Time saver#1). Based on the information provided, it appears they are expanding operations to the US. You can delve deeper by exploring top contacts for the US expansion initiative. Mara Williams, the VP of sales, emerges as a key contact. Einstein has already identified the corresponding contact record for you (Time saver#2) and conveniently offers a “Compose Email” button to draft a personalized email to Mara instantly. Clicking on it generates a tailored email for you, ready to be copied into the email composer (Time saver#3). If you prefer a less formal tone, you can request Einstein to adjust accordingly (Time saver#4). You can also instruct Einstein to create a private Slack channel for real-time communication with Mara. Notably, it not only generates the link but also includes it in the email (Time saver#5). Once satisfied with the email, simply hit “Send,” and it’s on its way. We’ve added “Time saver#” just for fun, but truthfully, these are genuine time savers that you’ll appreciate when using Einstein GPT. As we know, an AE’s time is better spent interacting with customers than on email composition, meeting scheduling, or CRM data entry. As demonstrated above, composing emails is a breeze, showcasing how Einstein GPT streamlines sales processes. There’s much more Einstein GPT can do for Sales: Retrieve information on top contacts.Integrate sign-up forms.Extract insights about new accounts.Generate leads, and much more. As mentioned earlier, Einstein GPT extends its benefits to Service, Marketing, and Developers too: Einstein GPT for Service: Generate knowledge articles from past case notes, and auto-generate personalized agent chat replies for enhanced customer satisfaction. Einstein GPT for Marketing: Dynamically generate personalized content to engage customers across various channels. Einstein GPT for Developers: Boost developer productivity by generating code and addressing queries in languages like Apex. Pretty cool, right? We’re equally excited at Tectonic to witness Einstein GPT’s general availability. If you’re eager to learn more or need additional information about Einstein GPT, feel free to reach out— Tectonic is here to assist. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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April 6, 2023in Generative AI, Salesforce Einstein
Salesforce Big Data and Travel and Hospitality
03Apr

Utilizing Generative AI

Taking advantage of generative AI requires complete, unified, and accurate data, according to over half of IT leaders. Yet roadblocks remain. A recent survey found most IT leaders don’t have a unified data strategy and can’t integrate generative AI into their current tech stack. Technical requirements aside, generative AI also surfaces serious ethical considerations. Utilizing Generative AI. Nearly three-quarters of IT leaders are wary of biased or inaccurate results, yet fewer than a third consider ethical use guidelines critical. As an IT practitioner, it’s your job to understand the tech landscape and educate your organization about the power and risks of certain technology solutions, regardless of their application. Generative AI is no different. At this stage, you should be thinking about generative AI from a board-level perspective, looking beyond the near term and well into the future. What are all the risks and rewards? What are the ways your organization might win or lose? How will your people react or respond? How might generative AI make your organization more competitive and effective? Don’t assume anyone within your organization is thinking strategically about how or where generative AI should be applied. Developing a proprietary generative AI solution will take months to deliver (if not longer), but if done correctly, the resulting model would be highly secure and likely very impactful for your specific organization. Most organizations will lean toward buying or leasing a base model and fine-tuning as needed. This approach would still consume time and resources but be optimized for use cases and maintain a level of security. Generative AI focuses on creating new and original content, chat responses, designs, synthetic data or even images. It’s particularly valuable in creative fields and for novel problem-solving, as it can autonomously generate many types of new outputs. How can we use generative AI? Generative AI models can create graphs that show new chemical compounds and molecules that aid in drug discovery, create realistic images for virtual or augmented reality, produce 3D models for video games, design logos, enhance or edit existing images, and more. Which tasks uses generative AI? Generative AI or generative artificial intelligence refers to the use of AI to create new content, like text, images, music, audio, and videos. Generative AI is powered by foundation models (large AI models) that can multi-task and perform out-of-the-box tasks, including summarization, Q&A, classification, and more. Like1 Related Posts Guide to Creating a Working Sales Plan Creating a sales plan is a pivotal step in reaching your revenue objectives. To ensure its longevity and adaptability to Read more 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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April 3, 2023in Salesforce Einstein
Salesforce Document Generation
14Mar

Generative AI

Artificial Intelligence in Focus Generative Artificial Intelligence is a type of artificial intelligence technology that can produce various types of content, including text, imagery, audio and synthetic data. What is the difference between generative AI and general AI? Traditional AI focuses on analyzing historical data and making future numeric predictions, while generative AI allows computers to produce brand-new outputs that are often indistinguishable from human-generated content. Recently, there has been a surge in discussions about artificial intelligence (AI), and the spotlight on this technology seems more intense than ever. Despite AI not being a novel concept, as many businesses and institutions have incorporated it in various capacities over the years, the heightened interest can be attributed to a specific AI-powered chatbot called ChatGPT. ChatGPT stands out by being able to respond to plain-language questions or requests in a manner that closely resembles human-written responses. Its public release allowed people to engage in conversations with a computer, creating a surprising, eerie, and evocative experience that captured widespread attention. This ability of an AI to engage in natural, human-like conversations represents a notable departure from previous AI capabilities. The Artificial Intelligence Fundamentals badge on the Salesforce Trailhead delves into the various specific tasks that AI models are trained to execute, highlighting the remarkable potential of generative AI, particularly in its ability to create diverse forms of text, images, and sounds, leading to transformative impacts both in and outside the workplace. Let’s explore the tasks that generative AI models are trained to perform, the underlying technology, and how businesses are specializing within the generative AI ecosystem. It also delves into concerns that businesses may harbor regarding generative Artificial Intelligence. Exploring the Capabilities of Language Models While generative AI may appear as a recent phenomenon, researchers have been developing and training generative AI models for decades. Some notable instances made headlines, such as Nvidia unveiling an AI model in 2018 capable of generating photorealistic images of human faces. These instances marked the gradual entry of generative AI into public awareness. While some researchers focused on AI’s capabilities generating specific types of images, others concentrated on language-related AI. This involved training AI models to perform various tasks related to interpreting text, a field known as natural language processing (NLP). Large language models (LLMs), trained on extensive datasets of real-world text, emerged as a key component of NLP, capturing intricate language rules that humans take years to learn. Summarization, translation, error correction, question answering, guided image generation, and text-to-speech are among the impressive tasks accomplished by LLMs. They provide a tool that significantly enhances language-related tasks in real-world scenarios. Predictive Nature of Generative AI Despite the remarkable predictions generated by generative AI in the form of text, images, and sounds, it’s crucial to clarify that these outputs represent a form of prediction rather than a manifestation of “thinking” by the computer. Generative Artificial Intelligence doesn’t possess opinions, intentions, or desires; it excels at predicting sequences of words based on patterns learned during training. Understanding this predictive nature is key. The AI’s ability to predict responses aligns with expectations rather than reflecting any inherent understanding or preference. Recognizing the predictive character of generative AI underscores its role as a powerful tool, bridging gaps in language-related tasks for both professional and recreational purposes. Like Related Posts Salesforce Artificial Intelligence Is artificial intelligence integrated into Salesforce? Salesforce Einstein stands as an intelligent layer embedded within the Lightning Platform, bringing robust Read more 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 Sales Cloud Einstein Forecasting Salesforce, the global leader in CRM, recently unveiled the next generation of Sales Cloud Einstein, Sales Cloud Einstein Forecasting, incorporating Read more

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March 14, 2023in Salesforce Einstein
Salesforce Einstein
12Mar

Salesforce ChatGPT

ChatGPT, an AI chatbot and Large Language Model developed by OpenAI with support from Microsoft, employs Natural Language Processing (NLP) to engage with users and provide responses by mining a vast database compiled from millions of websites. Its interactions are designed to be natural and conversational, but the accuracy may vary depending on the specificity of the user’s inquiry. In the context of the Salesforce ecosystem, the impact of ChatGPT can lead to both positive and negative outcomes. For example, it excels in generating code such as validation rules, formulas, and Apex classes. However, caution is advised when relying on it for declarative results or comprehensive answers. Junior developers may face challenges, as ChatGPT, drawing insights from extensive code samples, has the potential to outperform them in code writing. It is worth acknowledging that Salesforce has been integrating artificial intelligence since 2017. When it comes to output, ChatGPT is a little bit like canned cheese and string cheese. They are both “cheese” but neither one is cheese. For business analysts and consultants, ChatGPT can be a valuable resource for crafting generic proposals or suggesting process steps. Nevertheless, a measured reliance on its outputs is recommended. Architects, in contrast, may find limited value in ChatGPT, lacking the necessary experience and context for their role. Additionally, ChatGPT can be utilized to generate initial drafts of documents like training materials or business cases, but users must specify the rationale behind suggested changes, as ChatGPT lacks intrinsic understanding. It is crucial to clarify that ChatGPT functions as a content development tool and should not be confused with Salesforce Service Cloud Voice and conventional chatbots. Awareness of Salesforce’s My Domain changes is essential for those currently using chatbots, as these changes can impact their functionality. For marketers and content writers, it is essential to recognize that Large Language Models like ChatGPT may accentuate social biases and produce potentially inaccurate results. This stems from the questionable data found in some of the millions of websites that contribute to its training. In summary, while ChatGPT can be a beneficial tool, it is imperative to validate and verify its results before relying on them. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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March 12, 2023in Salesforce, Salesforce Einstein
Salesforce Service Cloud Einstein
09Mar

Salesforce Service Cloud Einstein

Einstein for Service is a robust suite of time-saving Artificial Intelligence features designed to empower agents in delivering exceptional customer service experiences. Salesforce Service Cloud Einstein-learn more. Customer service has evolved from being a cost center to a growth driver, and leading companies are prioritizing customer service to increase brand loyalty. In Service Cloud Einstein, various AI technologies, such as Machine Learning (ML), deep learning, predictive analytics, Natural Language Processing (NLP), and smart data discovery, work collaboratively to enhance customer support, providing faster and better service. Salesforce Einstein, recognized as the world’s first “generative AI” built for CRM, seamlessly integrates into multiple Salesforce products, including Marketing Cloud, Sales Cloud, and Service Cloud. Sales Cloud incorporates Einstein in the form of eight essential tools: Salesforce Einstein, since its inception in 2016, has been at the forefront of CRM AI technology, delivering personalized and predictive experiences for enhanced professionalism. Salesforce Service Cloud is a CRM platform focused on providing service and support to business customers. It is an extension of the Sales Cloud product tailored for sales professionals. Service Cloud Einstein is utilized by notable companies like Thomson Reuters, Southern Glazer’s Wine and Spirits, Cisco, and Skillsoft. Service Cloud Einstein benefits businesses by providing efficient customer service, with Einstein GPT responding promptly to inquiries, offering precise responses, enhancing customer satisfaction, and reducing resolution time. Studies show that in the same time 3 customers could be serviced before Service Cloud Einstein, now ten can be taken care of. The difference between Einstein GPT and ChatGPT lies in their design, with Einstein GPT specifically tailored for Salesforce users and clouds, while ChatGPT is a more versatile model for general use. Einstein is available for free with Salesforce’s Developer Edition, providing access to most platform features for building and testing custom applications and integrations using Einstein. Salesforce Sales Cloud and Service Cloud differ in their focus, with Sales Cloud concentrating on sales processes, while Service Cloud centers around customer service and support. Einstein remains the overarching AI brand for Salesforce, present across the portfolio, including within Tableau. Einstein Discovery is available as part of Tableau CRM Plus or through Einstein Predictions. Are you ready to explore the power of Einstein in your Salesforce Service Cloud implementation?  Contact Tectonic today. Tectonic is please to announce Salesforce Service Cloud Implementation Solutions. Content updated January 2024. Like1 Related Posts 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 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

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March 9, 2023in Marketing Automation, Salesforce Einstein, Salesforce Service Cloud

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