Analytics

13Apr

Salesforce Einstein Features

Salesforce Einstein Discover the power of the #1 AI for CRM with Einstein. Built into the Salesforce Platform, Einstein uses powerful machine learning and large language models to personalize customer interactions and make employees more productive. With Einstein powering the Customer 360, teams can accelerate time to value, predict outcomes, and automatically generate content within the flow of work. Einstein is for everyone, empowering business users, Salesforce Admins and Developers to embed AI into every experience with low code. Salesforce Einstein Features. Einstein Copilot Sales Actions: Sell faster with an AI assistant in the flow of work.Call Exploration: Ask Einstein to synthesize important call information in seconds. Ask Einstein to identify important takeaways and customer sentiment, so you have the context you need to move deals forward.   Sales Summaries: Summarize records to identify likelihood the deal will close, the competitors involved, key activities, and more. Forecast Guidance: Ask Einstein to inform your forecast and help you identify which deals need your attention. Close Plan: Generate a customized action plan personalized to your customer and sales process. Increase conversion rates with step-by-step guidance and milestones grounded in CRM data. Salesforce Einstein Features Sales Generative AI features: ° Knowledge Creation: ° Search Answers for Agents and Customers: Einstein Copilot Service Actions: Streamline service operations by drafting Knowledge articles and surfacing answers, grounded in knowledge, to the most commonly asked questions. Summarize support interactions to save agent time and formalize institutional knowledge. Surface generated answers to agents’ & customers’ questions that are grounded in your trusted Knowledge base directly into your search page. Search Answers for Agents is included in the Einstein for Service Add-on SKU and Search Answers for Customers is included in the Einstein 1 Service Edition. Empower agents to deliver more personalized service and reach resolutions faster with an AI assistant built into the flow of work. You can leverage out-of-the-box actions like summarize conversations or answer questions with Knowledge or you can build custom actions to fit your unique business needs. Service Salesforce Einstein Features This Release Einstein CopilotSell faster with an AI assistant. No data requirements Included in Einstein 1 Sales Edition.hEinstein Copilot: Sales ActionsSell faster with an AI assistant.No data requirements.   Call explorer and meeting follow-up requires Einstein Conversation Insights. Included in Einstein 1 Sales Edition. Generative AIBoost productivity by automating time-consuming tasks.No data requirements.   Call summaries and call explorer requires Einstein Conversation Insights. Included in Einstein 1 Sales Edition. Einstein will use a global model until enough data is available for a local model. For a local model: ≥1,000 lead records created and ≥120 of those converted in the last 6 monthsEinstein Automated Contacts Automatically add new contacts & events to your CRM≥ 30 business accounts. If you use Person Accounts, >= 50 percent of accounts must be business accounts Einstein Recommended ConnectionsGet insights about your teams network to see who knows your customers and can help out ona deal ≥ 2 users to be connected to Einstein Activity Capture and Inbox (5 preferred) Einstein Forecasting Easily predict sales forecasts inside of Salesforce Collaborative Forecasting enabled; use a standard fiscal year; measure forecasts by opportunity revenue; forecast hierarchy must include at least one forecasting enabled user who reports to a forecast manager; opportunities must be in Salesforce ≥ 24 months;Einstein Email Insights Prioritize your inbox with actionable intelligence Einstein Activity Capture enabledEinstein Activity Metiics (Activity 360) Get insight into the activities you enter manually and automatically from Einstein Activity Capture Einstein Activity Capture enabled Sales Analytics Get insights into the most common sales KPIs No data requirements. User specific requirements like browser and device apply Einstein Conveisation Insights Gain actionable insights from your sales calls with conversational intelligenceCall or video recordings from Lightning Dialer, Service Cloud Voice, Zoom and other supported CTI audio and video partners.Buyer Assistant Replace web-to-lead forms with real-time conversations. No data requirements – Sales Cloud UE or Sales Engagement. Einstein Opportunity ScoringEinstein Activity CaptuiePrioritize the opportunities most likely to convertAutomatically capture data & add to your CRMEinstein will use a global model until enough data is available for a local model. For a local model: ≥ 200 closed won and ≥ 200 closed lost opportunities in the last 2 years, each with a lifespan of at least 2 days≥ 30 accounts, contacts, or leads; Requires Gmail, Microsoft Exchange 2019, 2016, or 2013 Einstein Relationship Insights Speed prospecting with AI that researches for you. No data requirements. Einstein Next Best Action Deliver optimal recommendations at the point of maximumimpactNo data requirements. User specific requirements like browser and device apply Sales AIGenerate emails, prioritize leads & opportunities most likely to convert, uncover pipeline trends, predict sales forecasts, automate data capture, and more with Einstein for Sales. Generative AIPrompt BuilderEinstein Lead ScoringEinstein Opportunity ScoringEinstein Activity CaptureEinstein Automated ContactsEinstein Recommended ConnectionsEinstein ForecastingEinstein Email InsightsEinstein Activity Metrics (Activity 360)Sales AnalyticsEinstein Conversation InsightsBuyer Assistant Sales AIGenerative AI:  Feature Why is it so Great? What do I need? Automate common questions and business processes to solve customer requests fasterBoost productivity by auto-generating service replies, summarizing conversations during escalations andtransfers or closed interactions, drafting knowledge articles, and surfacing relevant answers grounded inknowledge for agents’ and customers’ commonly asked questions. Deliver optimal recommendations at the point of maximum impactEliminate the guesswork with AI-powered recommendations for everyoneDecrease time spent on manual data entry for incoming cases and improve case field accuracy and completionAutomate case triage and solve customer requests fasterDecrease time spent selecting field values needed to close a case with chat conversations and improved field accuracySurface the best articles in real time to solve any customer’s questionEliminate time spent typing responses to the most common customer questionsGet insights into contact center operations, understand customers, and deliver enhanced customerexperiencesChat or Messaging channels, minimum of 20 examples for most languagesNo data requirements. User specific requirements like browser and device apply Make sure that your dataset has the minimum records to build a successful recommendation. Recipient Records need a minimum of 100 records,Recommended Item Records need a minimum of 10 records, andPositive Interaction Examples need a minimum of 400 records

April 13, 2024in Generative AI, Salesforce Einstein, Snowflake

12Apr

Harnessing Sales Data

Harnessing Sales Data for Better Insights and Rapid Deal Closure Sales data is a critical asset for gaining insights and closing deals swiftly. With the ever-expanding data footprint, including customer response rates, leads in the pipeline, and quota attainment, tracking these metrics is essential. Ignoring them can be detrimental, as nearly all sales professionals recognize the importance of real-time data in meeting customer expectations, according to the Trends in Data and Analytics for Sales Report. However, concerns about data setup for generative AI and data accuracy persist. Sixty-three percent of sales professionals report that their company’s data isn’t optimized for AI, and only 42% are confident in their data’s accuracy. The demand for sales data has become a focal point for sales leaders and representatives, who increasingly rely on data to enhance customer engagement and productivity through trusted sources and AI integration. What is Sales Data? Sales data encompasses two main categories: external data, which includes information about prospects such as demographics, interests, behavior, and engagement; and internal sales data, including deal attributes and sales performance metrics. This data helps inform deal actions, assess progress toward sales targets or key performance indicators (KPIs), and supports tools like AI to enhance efficiency. Why is Sales Data Important? Sales data provides a measurable framework for all sales activities, enabling the setting of performance benchmarks and targets. It helps identify risks in the pipeline and highlights opportunities for upselling or fostering competition among sales reps. The data is also crucial for leveraging generative AI, which can automate tasks such as email drafting and sales pitch creation, provided the data is accurate and well-organized. Types of Sales Data Collecting and Utilizing Sales Data To effectively collect and utilize sales data, invest in a CRM system that serves as a centralized data repository with analytics capabilities. Automate data collection within the CRM, integrate data from other tools, and prioritize the security of sensitive information. Visualizing data through dashboards can help track progress toward business goals and make informed decisions. Real-Life Application: A Case Study A global consulting firm used sales data to enhance win rates and accelerate deal velocity. By integrating CRM analytics with data from various sources, the firm identified key deal attributes impacting success and adjusted strategies accordingly. The use of AI-driven “opportunity scores” further enabled the firm to monitor deal health and optimize resource allocation. Essential Tools for Harnessing Sales Data Turning Sales Data into Actionable Insights Regularly reviewing CRM-generated insights and adjusting strategies based on these insights is crucial for closing more deals and delivering consistent value to customers. By focusing on data-driven decision-making, sales teams can stay competitive and meet evolving customer needs. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

April 12, 2024in Generative AI

06Apr

Einstein Copilot for Tableau in Public Beta

Salesforce Introduces Einstein Copilot for Tableau in Public Beta In early April, Salesforce unveiled the public beta availability of Einstein Copilot for Tableau, an innovative AI-powered assistant aimed at assisting users across various roles and functions in exploring and interacting with data within Tableau. This groundbreaking tool enables deep dives into data by leveraging Tableau’s analytical engine through natural language queries, accessing data from spreadsheets, cloud and on-premises data warehouses, and Salesforce Data Cloud. The public release of Copilot for Tableau is anticipated to be widely available to customers by summer 2024. Key Features of Einstein Copilot for Tableau Einstein Copilot for Tableau offers several features tailored to enhance user experience and streamline data exploration: Recommended Questions: The assistant automatically analyzes data and suggests relevant questions, allowing users to interact with data effortlessly without the need for specialized data analysis skills. Conversational Data Exploration: Users can iterate and refine their data exploration process seamlessly while maintaining context, enabling them to ask follow-up questions and delve deeper into insights as if they were engaging in a conversation with their data. Guided Calculation Creation: Copilot guides users through the process of creating calculations and parsing information, simplifying complex tasks such as extracting specific data elements from text fields. Enhancing Accuracy and Trust To ensure accuracy and contextual relevance, Einstein Copilot for Tableau leverages trusted company data from Data Cloud, fostering trust among users by delivering precise and relevant outputs based on internal data sources. Future Outlook Salesforce’s approach to introducing generative AI assistants for specific product types and use cases underscores the importance of function-specific training to meet users’ specific needs. As the technology matures, vendors may transition from premium license fees to consumption-based models, reflecting the evolving landscape of AI assistant technology adoption. The rollout of Einstein Copilot for Tableau represents a significant step forward in making data analysis accessible to a broader audience, reinforcing Salesforce’s commitment to innovation and customer-centric solutions in the realm of AI-powered analytics. 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

April 6, 2024in Einstein 1 Platform, Salesforce, Salesforce Data Cloud, Salesforce Tableau

01Apr

Data Cloud and Snowflake Bidrectional Data Sharing

Salesforce Data Cloud and Snowflake are excited to announce that bidirectional data sharing between Snowflake, the Data Cloud company, and Salesforce Data Cloud is now generally available. In September, we introduced the ability for organizations to leverage Salesforce data directly in Snowflake via zero-ETL data sharing, enabling unified customer and business data, accelerating decision-making, and streamlining business processes. Today, we’re thrilled to share that customers can now also share Snowflake data into the Salesforce Data Cloud, using the same zero-ETL innovation to reduce friction and quickly surface powerful insights across sales, service, marketing, and commerce applications. Data Cloud and Snowflake Bidrectional Data Sharing. Data Cloud and Snowflake Bidrectional Data Sharing Enterprises generate valuable customer data within Salesforce applications, while increasingly relying on Snowflake as their preferred data platform for storing, modeling, and analyzing their full data estate. This integration between Salesforce and Snowflake minimizes friction, data latency, scale limitations, and data engineering costs associated with using these two leading platforms. The Snowflake Marketplace also offers customers the opportunity to acquire new data sets to enhance or fill gaps in their existing business data, driving innovation. By combining enterprise data and third-party data from Snowflake Marketplace with valuable customer data from Salesforce applications, organizations can unify their data and build powerful AI solutions to surface rich insights, driving superior and differentiated customer experiences. “Zero-ETL data sharing between Salesforce Data Cloud and Snowflake is game-changing. It has opened up new frontiers of data collaboration. We’re excited to see how customers are powering their customer data analytics and developing innovative AI solutions with near real-time data from Salesforce and Snowflake, generating incredible business value. Now that this integration is generally available, this kind of innovation will be broadly accessible,” says Christian Kleinerman, SVP of Product, Snowflake. Power Personalized Experiences with Salesforce and Snowflake Data sharing between Salesforce Data Cloud and Snowflake brings together holistic insights, empowering multiple customer-facing departments within any organization to create a truly robust customer 360. As Snowflake’s Chief Marketing Officer, Denise Persson, often states, a true, enterprise-wide customer 360 is the beating heart of a modern, customer-facing organization. The applicability of this integration spans various industries and unlocks new growth opportunities. For example: The bidirectional integration enables data sharing across business systems, Salesforce clouds, and operational systems, facilitating data set analysis and future action planning. This brings actionable insights and drives actions, unleashing a new level of customer experience and business productivity. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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

24Mar

Salesforce Education Cloud for Educational Challenges

Educational institutions today confront a multitude of complex challenges, ranging from disjointed information systems to the need for agility in meeting evolving educational demands. Salesforce Education Cloud presents a unified solution aimed at overcoming these obstacles by enhancing operational efficiencies, boosting student engagement, and ensuring compliance with ever-changing educational standards. Below is an in-depth examination of the prevalent challenges faced by educational institutions and the tailored solutions provided by Salesforce Education Cloud. Key Challenges in the Education Sector Salesforce Education Cloud: Tailored Solutions for Education Salesforce Education Cloud addresses these challenges through a suite of customized features and tools designed to streamline operations, enhance student services, and promote effective communication. Real-World Impact of Salesforce Education Cloud Implementation of Salesforce Education Cloud yields transformative benefits across educational institutions: Conclusion Salesforce Education Cloud offers a comprehensive solution to the diverse challenges faced by educational institutions. By integrating this robust platform, schools, colleges, and universities can enhance operational efficiency, improve student outcomes, and cultivate a collaborative educational environment. Institutions seeking to explore the benefits of Education Cloud or enhance their existing systems are encouraged to consult with a Salesforce Education Cloud Consultant for tailored guidance and implementation strategies. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

March 24, 2024in Salesforce, Salesforce Education Cloud, Salesforce Education Solutions, Salesforce Einstein

24Mar

Account Engagement Marketing Attribution

Marketing Attribution has been a contentious topic among marketers. Account Engagement Marketing Attribution is just one platform where it is discussed. The two distinct viewpoints: One perspective suggests caution in interpreting current attribution data, emphasizing its limitation to the information available at the point of conversion. Conversely, another viewpoint advocates for utilizing available data rather than disregarding it entirely. While acknowledging the validity of both stances, a neutral position is maintained here. Acknowledging the importance of capturing attribution data, its practical application hinges on individual attribution tracking processes. For those interested in exploring the foundational elements of effective marketing attribution, this insight looks into leveraging the Attribution Engine to capture attribution data, harnessing Marketing Cloud Account Engagement (MCAE), and optimizing Salesforce campaigns to construct robust attribution models. Capturing Attribution Data Essential to identifying the channels driving website traffic is leveraging the Attribution data. This can include UTM values, capturing details like referral URLs and discovery timestamps. Campaign drivers, asset consumption, web page visits, and more. Subsequent visits update conversion-specific values, facilitating precise attribution. Integrating with Marketing Cloud Account Engagement (MCAE) Configure MCAE forms to capture attribution data. Aligning fields with Lead and Contact objects in Salesforce ensures seamless data transfer for enhanced insights. Configuring Salesforce Campaigns Effective prospect engagement tracking through Salesforce campaigns necessitates a structured campaign hierarchy. Utilizing the Campaign Member object to log UTM-based attribution data obviates the need for creating multiple campaigns per channel. Establishing distinct record types for marketing campaigns safeguards data integrity amidst multifaceted campaign operations. Customizable Campaign Influence Customizable Campaign Influence in Account Engagement facilitates revenue attribution configuration across diverse attribution models. This feature scans active campaigns, associating revenue influence with members holding contact roles on open opportunities. Defining auto-association criteria optimizes influence attribution accuracy and relevance. Capturing Attribution Data in Campaign Member Records Automating last-touch point data retention in Campaign Member records enhances campaign efficacy tracking. Salesforce Flows streamline data extraction from Lead or Contact records, appending it to Campaign Member entries upon assignment. This setup ensures comprehensive visibility into campaign impact on pipeline development. Leveraging B2BMA Analytics Dashboards Driving campaign performance analysis and pipeline impact requires robust reporting frameworks. Leveraging Analytics Studio empowers comprehensive data aggregation from Campaign Influence, Opportunity, and Campaign objects. This capability supports in-depth performance evaluation and channel-specific insights. Analytics Studio provides the foundational tool for building CRM Analytics assets—the lenses and dashboards that make up Analytics apps. Use Analytics Studio to explore your data and build lenses and dashboards with data visualizations that give you the insights to help you run your business. Store everything in apps— the containers of assets that tell a story about an aspect of your business through data visualizations. Analytics Studio lets you do most of your work declaratively through its intuitive graphical user interface. You can also access the JSON, XMD, SaQL, and other files that control how Analytics consumes and displays data in dashboards and apps. Open those files with your editor of choice to make fine-grained changes to Analytics business user functionality. To open Analytics Studio, navigate to the Salesforce app picker , and select Analytics Studio. Sometimes you must scroll or click View All to find it. From there, click Create, and start building. The Analytics Learning Map provides pointers to help get you going and master Analytics visualizations. Conclusion While integrating these functionalities presents challenges, existing familiarity with Marketing Cloud Account Engagement simplifies implementation. Collaboration with Business Intelligence for Analytics Studio dashboard configuration and Salesforce Admin for Flow automation supports seamless adoption. Once established, these elements collectively fortify an agile and effective attribution model. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

March 24, 2024in Salesforce Implementation Services, Salesforce Marketing Cloud Account Engagement (Pardot), Salesforce Optimization

19Mar

Top AI Tools Shaping Business Success

Top AI Tools Shaping Business Success in 2024 In the dynamic world of business, staying ahead means embracing the latest technologies. Artificial Intelligence (AI) is no longer just a buzzword—it’s a transformative force that helps businesses operate more efficiently, make smarter decisions, and enhance customer experiences. As we move through 2024, the AI tool ecosystem is rapidly expanding, offering innovative solutions to automate tasks, gain deep insights, and improve customer engagement. Below, we explore the top AI tools that are shaping the future of business. StoryChief is a comprehensive content marketing platform that simplifies the creation and distribution of content through AI. From ideation to optimization, it leverages machine learning to help businesses generate high-quality, engaging content at scale. Key Features: Pricing: Plans start with a free tier, with paid options ranging from $40 to $500 per month. Developed by OpenAI, ChatGPT is a versatile language model capable of generating human-like text. It excels in content creation, customer support, and data analysis. Key Use Cases: Pricing: API access with usage-based pricing. Perplexity AI is an advanced search engine that provides accurate, summarized answers to complex queries using natural language processing (NLP). Key Features: Pricing: Free version available, with Pro version at $20/month offering enhanced features. Zapier connects over 5,000 apps, enabling automation of repetitive tasks across your tech stack with AI-powered tools that simplify complex automations. Key Features: Pricing: Free plan available for up to 100 tasks per month; paid plans start at $19.99/month. Grammarly is an AI-driven writing assistant that enhances the quality of written communication, ensuring clarity, conciseness, and error-free content. Key Features: Pricing: Free version available; Premium plans start at $12/month for individuals and $25/user/month for businesses. Typeframes simplifies video creation with AI, turning scripts or images into professional-quality videos with animations, transitions, and voiceovers. Key Features: Pricing: Plans start at $29/month, with higher-tier options available. Chatbase enables businesses to build intelligent chatbots and virtual assistants that handle a wide range of customer service inquiries. Key Features: Pricing: Free plan available with limited message credits; paid plans start at $19/month. Secta is an AI-powered headshot generator that creates professional-quality headshots from user-submitted photos, ideal for businesses needing polished profile pictures. Key Features: Pricing: Pay-as-you-go at $49 per headshot session. Voicenotes is an AI-driven transcription tool that converts voice memos into concise summaries and action items, perfect for capturing important information efficiently. Key Features: Pricing: Free plan available; paid plans start at $10/month, with lifetime payment options. Notion AI enhances the popular Notion productivity platform with AI-powered writing assistance, content summarization, and database management. Key Features: Pricing: Available as an add-on at $10 per user per month, with discounts for annual plans. Choosing the Right AI Tools for Your Business Selecting the right AI tools involves considering several factors: By evaluating these aspects, you can effectively leverage AI to enhance efficiency, drive growth, and maintain a competitive edge in 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

March 19, 2024in Salesforce

16Mar

LLMs Beyond Generative AI

Beyond Text Generation: The Versatile Capabilities of Large Language Models While large language models (LLMs) and generative AI have dominated the conversation over the past year, the spotlight has largely been on their text generation capabilities. There’s no denying the value of LLMs in generating answers to questions. However, focusing solely on this use case overlooks other valuable applications. This insight will explore several primary uses of LLMs, ensuring you recognize their broader potential beyond just generative purposes. Creation and Generation This is the most publicized use case for LLMs today. Applications like ChatGPT can answer questions with detailed responses, and tools like DALL-E generate images based on user prompts. Similar generators exist for code, video, and 3D virtual worlds. Interestingly, these generators share fundamental algorithmic approaches despite producing different content types—text, images, videos. Since they all process prompts, they require training to understand and decompose these prompts to guide the generation process, necessitating the use of LLMs. However, generating new content is just one aspect of what LLMs can achieve. Summarization LLMs excel at summarizing information. For instance, if you have a list of papers on your to-read list, an LLM can summarize their key themes, common points, and differences. This provides a clear baseline, helping you focus on essential aspects as you read. Summarizing content with AI tends to have a lower error risk compared to generating new content because the LLM works within the boundaries of the provided information. While it might occasionally miss a pattern or emphasize the wrong details, it’s unlikely to produce completely incorrect summaries. Translation Often underrated, translation might be one of the most impactful uses of LLMs. For example, LLMs can translate old code from obsolete languages into modern ones. An LLM generates a draft translation, which, although imperfect, can be refined by a programmer who understands the goal of the code even with limited knowledge of the original language. Human language translation also stands to benefit significantly. Soon, we’ll be able to communicate in our preferred languages, with LLMs instantly translating our words into the listener’s language. This will eliminate the need for a common language and help preserve uncommon languages by removing the communication barriers associated with them. Interpretation and Extraction LLMs are also adept at interpreting statements and triggering subsequent actions. Image generators use this approach, as do tools that handle analytical queries. For instance, asking “Please summarize this year’s sales by region and subtotal by product” allows an LLM to interpret the request, extract key parameters, and pass them to a query generator for the answer. Companies like Quaeris, which I advise, focus on this capability. Additionally, LLMs can handle tasks like sentiment analysis and customer service inquiries. They can ingest inquiries and extract relevant details, such as the product in question, the issue raised, and the requested action, to route the inquiry to the appropriate person more effectively. LLMs Beyond Generative AI The examples discussed are not exhaustive but represent some common and powerful uses of LLMs. They highlight that LLMs offer far more than just text generation. Exploring these other applications can provide significant benefits for you and your organization. Originally posted in the Analytics Matters newsletter on LinkedIn. 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

March 16, 2024in Generative AI, Salesforce Einstein

14Mar

What is Einstein Used for in Salesforce?

Salesforce Einstein is an AI-powered platform that can be used in various ways to enhance customer experiences and streamline business operations: SalesSalesforce Einstein can help sales teams better understand customers, improve conversion rates, and close deals more quickly. For instance, it can generate sales call summaries, draft emails using customer data, and provide real-time predictions. Customer ServiceEinstein helps customer service agents resolve cases faster and provide customers with relevant information during interactions. MarketingSalesforce Einstein enables marketers to create personalized experiences and send the right content to the right customer at the right time. ITSalesforce empowers IT teams to embed intelligence across the business and create smarter apps for customers and employees. CommerceSalesforce assists retailers by recommending the best products to each customer. Salesforce also includes features to protect data privacy and security, such as the Tectonic GPT Trust Layer, which provides AI bias detection, data security, and regulatory compliance. Salesforce Einstein is the first all-inclusive AI for CRM. It’s an integrated set of AI technologies that makes the Customer Success Platform smarter and brings AI to Salesforce users everywhere. Salesforce is the only comprehensive AI for CRM. It is: Tectonic and Salesforce allow businesses to become AI-first, providing the ability to anticipate customer needs, improve service efficiency, and enable smarter, data-driven decision-making. Sales teams can anticipate next opportunities and exceed customer needs,Service teams can proactively resolve issues before they occur,Marketing teams can create predictive journeys and personalize experiences like never before,IT teams can embed intelligence everywhere and create smarter apps. AI that works for your business.Drive business productivity and personalization with predictive AI, generative AI, and agents across the Customer 360 platform. Create and deploy assistive AI experiences natively in Salesforce, allowing your customers and employees to converse directly with Agentforce to solve issues faster and work smarter. Empower service reps, agents, marketers, and others with AI tools safely grounded in your customer data to make every customer experience more impactful. What is Salesforce Einstein?As of 2024, this groundbreaking AI-based product remains a leader in the CRM industry since its release in 2016. It combines a range of AI technologies, including advanced machine learning, natural language processing (NLP), predictive analytics, and image recognition, enabling businesses to improve productivity and sustain growth. Salesforce AI BenefitsThe most significant benefits of AI are the time and efficiency gains it offers to business processes. By automating tasks, employees can focus on more strategic work. Additionally, automating repetitive tasks reduces errors and enhances operational efficiency. Saleesforce provides robust reporting features that generate valuable insights to support decision-making, helping businesses understand customer needs and identify opportunities. From a customer perspective, Salesforce ensures more meaningful and personalized experiences through advanced NLP capabilities and machine learning to better understand customer behavior. Salesforce AI FeaturesSalesforce is a feature-rich platform that leverages AI’s capabilities in Natural Language Processing, Machine Learning, and image processing. Some of the key features include: Salesforce PricingCosts depend on the required features and the size of the business. Pricing starts at $50 per user per month, with potential increases based on the specific capabilities needed. Salesforce Tectonic ChallengesAlthough Salesforce Tectonic offers numerous benefits, companies may face challenges during integration, such as aligning it with existing systems and ensuring proper training for employees to maximize its use. How to Prepare for Salesforce Tectonic IntegrationUsing an implementation partner like Tectonic can help ensure seamless integration. A partner will assess your current Salesforce setup, recommend the right features, and guide you through the integration process. ConclusionSalesforce is a cutting-edge platform that empowers businesses to transform operations with comprehensive AI capabilities. It provides tailored solutions for sales, service, marketing, and commerce teams, enabling better customer interactions, data-driven decision-making, and increased productivity. With the right implementation partner like Tectonic, businesses can seamlessly integrate and leverage Tectonic to stay ahead in a competitive landscape. Content updated November 2024. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

March 14, 2024in AI Tools, Data, Generative AI, Salesforce, Salesforce Einstein

Leverage AI and Machine Learning in Your Data Warehouse

08Mar

Exploring Machine Learning with Salesforce

Machine Learning (ML) falls into three main categories: Supervised Learning, Unsupervised Learning, and Reinforcement Learning. Let’s dive into some issues and considerations that might leave you wondering if it’s even worth starting! Not embracing what Professor Stuart Russell called “the biggest event in human history” may be short-sighted. Don’t worry, Salesforce can help. Salesforce and Machine Learning Salesforce has a 20-year history of making complex technologies business-friendly. This extends to Machine Learning, integrating ML capabilities throughout the Salesforce Customer 360 suite, which includes solutions for Marketing, Commerce, Sales, Service, and Analytics, among others. Machine Learning in Action with Salesforce Marketing Imagine you’re in a marketing role. You want to predict the likelihood that a customer will engage with your campaigns to maximize effectiveness. Supervised Learning can help here by predicting subscriber engagement (opens, click-throughs, conversions) using historical data (90 days of engagement metrics). For example, using predictive Engagement Scoring, a Salesforce customer in the travel industry achieved a 66% drop in unsubscribe rates and a 13% revenue increase. You also want to ensure prospective customers can quickly find relevant products. Unsupervised Learning can personalize product assortments throughout the shopper journey by analyzing buying patterns, site browsing tendencies, and relationships between search terms and products. Using AI-powered Predictive Sort, businesses have seen a 9.1% increase in revenue per visitor and a 3.8% increase in conversion rates. Sales For sales teams handling many opportunities, predicting the quality of each Opportunity can help prioritize efforts. Supervised Learning, using historical data of at least 200 Closed/Won and 200 Closed/Lost Opportunities, can provide a prioritized list of Opportunities to maximize revenue potential. A large Salesforce customer in the consumer goods sector increased win rates by 48% by focusing on the best Opportunities. Service Post-sale customer support is crucial. Service agents need to address challenging cases efficiently. Supervised Learning can recommend articles to resolve current cases based on historical data from at least 1000 cases with knowledge base articles. A large electronics company using Salesforce AI-powered solutions saved 5 hours per agent per week, enhancing productivity. Simplifying Complex Technology Salesforce’s rich history of making complex technology accessible allows businesses to realize ML benefits without needing specialized knowledge. Traditional ML involves multiple steps like data collection, transformation, sampling, feature selection, model selection, score calibration, and integrating results. Salesforce simplifies this with a customizable data model, automated feature engineering, and automatic model building and selection. For example, in model selection, Salesforce runs a “model tournament” to choose the best model with varying hyper-parameters, ensuring the most accurate model is selected without requiring user intervention. Conclusion Salesforce abstracts the complexity of ML behind user-friendly interfaces, making it easier for businesses to leverage powerful technology. Whether it’s predicting customer engagement, personalizing shopping experiences, prioritizing sales opportunities, or enhancing customer support, Salesforce’s ML capabilities can drive significant business value. Discover more about how Salesforce can transform your approach to Machine Learning and help you achieve your business goals. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

March 8, 2024in Data, Technology

07Mar

AI and the Role of Healthcare CIOs

Healthcare leaders see significant potential in data analytics and AI technology to transform the industry over the next five years, according to a new market research report from Arcadia and The Harris Poll. AI and the Role of Healthcare CIOs The report, titled “The Healthcare CIO’s Role in the Age of AI,” examines AI’s impact on the healthcare sector and how decision-makers are preparing to leverage the technology. Notably, 96% of healthcare leaders surveyed believe that adopting AI effectively will provide a competitive edge both now and in the future. While only a third see AI as essential today, 73% expect it to become critical within five years. How Health Systems Are Using AI Around 63% of respondents revealed that their organizations use AI to analyze large patient data sets to identify trends and guide population health management efforts. Another 58% are using AI to analyze individual patient data to identify opportunities for improving health outcomes. Close to half of the leaders indicated that AI is being used to optimize electronic health records (EHR) management and analysis. These trends align with the findings of the recent “Top of Mind for Top Health Systems” survey, conducted by the University of Pittsburgh Medical Center’s Center for Connected Medicine (CCM) in collaboration with KLAS, which identified AI as the most exciting emerging technology in healthcare with transformative potential for both administration and care delivery. The excitement surrounding healthcare AI largely stems from its ability to break down data silos and tap into the wealth of clinical data that healthcare organizations already collect. “Healthcare leaders are thoughtfully preparing to harness the full value of AI in care delivery reform,” said Aneesh Chopra, Arcadia’s chief strategy officer. “As safe, secure data sharing scales, technology leaders prioritize data platforms that organize fragmented patient records into clinically relevant insights at every stage of the patient journey.” A quest for a 360 degree patient view abounds. Using AI to Support Strategic Priorities The Arcadia survey emphasized the importance of using analytics to improve patient care, with 83% of leaders believing that harnessing data will help healthcare organizations remain competitive and resilient while overcoming digital transformation and financial challenges. Eighty-four percent of respondents cited technology as a current priority, with 44% focusing on an enterprise-wide approach to data analytics, 41% prioritizing AI-driven decision-making, and 32% working to simplify technical ecosystems. These efforts are viewed as crucial to advancing other strategic goals, with 40% of leaders prioritizing the patient experience, 35% aiming to improve outcomes, and 29% focusing on patient engagement. Although healthcare leaders view AI adoption positively for strategic advancements, hurdles remain. While 96% of respondents are confident in adopting AI, many feel pressured to move quickly. When asked about the sources of this pressure, 82% cited data and analytics teams, 78% pointed to IT and tech teams, and 73% mentioned executives. However, successfully implementing AI requires talent and resources that some organizations lack. About 40% of leaders identified a lack of talent as a significant barrier to AI adoption, signaling the need for IT and analytics teams to acquire new skill sets. Seventy-one percent of IT leaders reported a growing demand for data-driven decision-making skills, while two-thirds pointed to a rising need for expertise in data analysis, machine learning, and systems integration. Additionally, nearly 60% mentioned the need for roles that focus on training and support for healthcare staff. The Evolving Role of CIOs CIOs and other healthcare leaders are seeing their roles evolve as AI and data become more integrated into healthcare operations. Eighty-seven percent of respondents see themselves as strategy influencers, actively involved in setting and executing AI strategies, while only 13% view themselves as purely focused on implementation. Despite these evolving roles, many CIOs feel constrained by daily operations. Fifty-eight percent reported being primarily focused on tactical execution rather than developing long-term AI strategies, although they believe they should spend 75% of their time on strategic planning to be most effective. Part of these strategies will likely focus on improving communication and workforce readiness. Three out of four leaders cited a lack of effective communication between IT teams and clinical staff as a barrier to leveraging new technologies, and two out of five noted that clinical staff are not fully equipped to make the best use of data analytics. “CIOs and their teams are setting the stage for an AI-powered revolution in patient care and healthcare operations,” said Michael Meucci, Arcadia’s president and CEO. “Our findings highlight a strong consensus that a solid data foundation is necessary to realize the future of AI in healthcare. At the same time, the human workforce, with evolving talent and skills, will shape the real-world impact of AI in healthcare.“ Content updated August 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 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

March 7, 2024in Generative AI, Salesforce Development Services, Salesforce Health and Life Sciences Solutions

03Mar

Demand Generation Web Use Cases for Personalization

Utilize effective personalization techniques adopted by businesses in online campaigns to stimulate demand generation. The term “demand generation” has somewhat faded from the marketing lexicon due to the emphasis on analytics, AI, and metrics for lead conversion. However, where does personalization fit into the broader scope of demand generation? Demand generation web use cases for personalization. Personalization plays a pivotal role in various aspects of demand generation: In lead nurturing, personalization is equally vital: Moreover, personalization is instrumental in lead acquisition efforts by delivering relevant experiences to all of your prospects. To effectively implement personalization, real-time insights into individual behaviors and interactions are essential. A comprehensive personalization solution should unify data from various channels and systems, enabling seamless cross-channel personalization. This includes “stitching” together anonymous and known user profiles, integrating data with complementary systems like CRMs and marketing platforms, and facilitating real-time omni-channel personalization. The key to successful personalization lies in understanding and addressing each individual’s unique needs and preferences. By adopting a customer-centric approach and setting clear objectives aligned with business goals, organizations can leverage personalization to enhance customer experiences, boost conversion rates, and drive measurable business growth. To execute a successful personalization strategy, organizations must: By following these steps and continuously optimizing personalization efforts, organizations can build stronger customer relationships, drive business growth, and maximize marketing ROI. Website personalization serves as the starting point for many companies embarking on their personalization journey. This entails ensuring that returning visitors encounter pages tailored to their previous experiences or recent purchases. It can also involve presenting new customers with product recommendations based on their current browsing session. The return on this initial investment can be substantial, with many companies witnessing a significant increase in conversion rates, sometimes by as much as 50% or more. For instance, a site converting 2% of visitors might see that figure rise to 3%, a dream scenario for digital marketers. Moreover, this boost in conversion rates can have far-reaching effects across marketing programs, leading to a reduction in overall customer acquisition costs. Tectonic now offers Personalization Implementation Solutions. The next stage in personalization maturity involves integrating a customer’s web and email experiences. This seamless connection between two major channels for customer engagement brings organizations closer to achieving an omni-channel personalization experience. Timely and relevant follow-up messages after a customer’s website visit or purchase can deepen relationships and enhance lifetime value without significant additional marketing expenditure. Finally, the ultimate goal is to extend personalization across all channels, ensuring consistent and tailored experiences wherever customers interact with your brand. However, achieving this can be challenging due to fragmented customer data across multiple channels, teams, and systems. An effective personalization solution should consolidate and synthesize this cross-channel information by maintaining unified customer profiles and enabling real-time omni-channel personalization. Testing is a crucial aspect of successful personalization efforts, allowing organizations to optimize campaigns and maximize engagement, conversions, and revenue. A robust personalization solution should facilitate A/B testing, measuring lift over control, evaluating impacts against specific goals, and filtering results by segment. Effective website personalization lays the foundation for broader personalization efforts across channels. By seamlessly integrating web and email experiences and extending personalization to all touchpoints, organizations can deliver tailored experiences that drive engagement, loyalty, and ultimately, business growth. By Tectonic’s Salesforce Marketing Platform Architect Shannan Hearne Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

March 3, 2024in Einstein Insights, Generative AI, Salesforce, Salesforce Einstein, Salesforce Marketing Cloud, Salesforce Optimization, Salesforce Sales Cloud

23Feb

Virtual Event Management Plan

Have You Recently Attended an Information-Packed Webinar? Think back to your experience: from how you first learned about the event to its promotion and eventual execution. It might seem like organizing a webinar is straightforward, but… Virtual event management requires meticulous planning, from the initial concept and promotion to post-event tasks. Read on to discover how you can plan your online events in Salesforce with ease and what you’ll need for success. What is Virtual Event Management Plan in Salesforce? Virtual event management encompasses all the activities needed to ensure your online event runs smoothly. It’s how you prepare to share your insights—or those of other experts—virtually. Why plan your events in Salesforce? All your data stays integrated within your CRM, allowing you to manage every aspect of your event, from registration and ticketing to marketing and attendee engagement, without the hassle of multiple tools or disorganized planning. Types of Virtual Event Management Plans in Salesforce Choosing the right virtual event format can be overwhelming, but here are some common options: How to Plan Virtual Events in Salesforce: A 4-Step Guide 1. Create a Virtual Event Concept When planning a virtual event, don’t treat it like an in-person one. Virtual events require their own set of strategies. Start by answering these questions: Remember, seasonal holidays or other events can impact attendance. Avoid scheduling events during low-attendance periods, like the summer or late December. 2. Select an Event Management Tool You need the right technology to manage online events effectively. Salesforce offers robust functionality for this. When selecting a tool for Salesforce event management, look for these features: 3. Outline Content and Strategy Crafting a virtual event that resonates with your audience requires more than just setting a date and topic. You need a compelling content strategy. Here’s how to make it work: 4. Design an Event Microsite Like in-person events, virtual ones benefit from a dedicated event page or microsite. On your Salesforce Experience Cloud site, you can: The Ultimate Virtual Events Checklist Final Thoughts Virtual event management isn’t daunting if approached wisely. With a clear plan, engaging content, and the right tools, success is within reach. Follow these steps, and your next virtual event will be a breeze. 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

February 23, 2024in Data, Enterprise, Marketing Automation, Salesforce, Salesforce Experience Cloud, Technology

20Feb

Salesforce Pro Suite

Revolutionizing CRM: Introducing Salesforce Pro Suite In today’s dynamic business technology landscape, Salesforce has established itself as a leader in customer relationship management (CRM) solutions. The launch of Salesforce Pro Suite marks a significant milestone in their mission to empower businesses with cutting-edge tools designed to optimize operations, enhance customer engagement, and drive growth. This article explores the features, benefits, and potential of Salesforce Pro Suite, showcasing why it stands out as a transformative solution for businesses of all sizes. What is Salesforce Pro Suite? Salesforce Pro Suite is a comprehensive collection of integrated tools and services designed to augment the capabilities of Salesforce’s CRM platform. Tailored for modern businesses—from startups to large enterprises—it incorporates advanced functionalities such as artificial intelligence (AI), automation, and data analytics to boost productivity, foster collaboration, and facilitate informed decision-making. Unlock growth and deepen customer relationships with Pro Suite—the all-in-one CRM suite with marketing, sales, service, and commerce tools that scale with your business. Get the flexibility to automate tasks and customize your CRM to fit your specific needs with Pro Suite. Key Features of Salesforce Pro Suite Benefits of Salesforce Pro Suite Use Cases of Salesforce Pro Suite What Can You Do with Pro Suite? Conclusion Salesforce Pro Suite represents a significant advancement in CRM technology, offering a comprehensive suite of tools that cater to the diverse needs of modern businesses. By harnessing AI, automation, and advanced analytics, Pro Suite empowers organizations to optimize operations, enhance customer engagement, and make informed, data-driven decisions. Whether you’re a small startup or a large enterprise, Salesforce Pro Suite provides the scalability, flexibility, and security required to thrive in today’s competitive landscape. 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

February 20, 2024in Artificial Intelligence, Data, Enterprise, Salesforce, Technology

20Feb

Marketing Cloud Growth Extends The Platform

Marketing Cloud Growth extends the platform capabilities to enhance your team’s marketing endeavors. It allows you to integrate multiple data sources with Data Cloud, create content using Digital Experiences, orchestrate complex customer journeys with Flow Builder, and optimize campaigns with Einstein AI. Required Editions: Available in Salesforce Enterprise and Unlimited Editions with Marketing Cloud Growth Edition. Marketing Cloud Growth Extends The Platform Today, Salesforce unveiled Marketing Cloud Growth, a new edition tailored for small businesses to drive efficient growth through CRM, AI, and data integration. Marketing Cloud Growth integrates marketing automation with sales, service, and commerce functionalities on Salesforce’s trusted customer platform, Einstein. Furthermore, Salesforce announced that marketers can leverage Data Cloud at no cost, enabling them to access trusted first-party data crucial for AI-driven, personalized customer experiences. Why it matters: Studies show that 51% of marketers use generative AI to streamline tasks like content creation, copywriting, and market data analysis. However, without high-quality first-party data, AI-generated content lacks the accuracy necessary for businesses to trust and utilize it effectively. AI has significant potential to benefit small businesses, which spend nearly 11 hours per week drafting emails—time that could be saved through AI-driven automation for content creation, personalization, and optimized customer communication timing. By consolidating CRM, AI, and data within a unified platform, these innovations empower businesses to deliver compelling, interconnected customer experiences. Steve Hammond, EVP and GM, Marketing Cloud, Salesforce perspective: “Marketers want to leverage AI to fuel creativity, drive efficiency, and grow their business, but often lack the necessary data for accurate, trustworthy results. By consolidating CRM, AI, and data within a single platform, these innovations empower businesses to deliver the compelling connected experiences customers expect.” With Marketing Cloud Growth, small businesses gain access to Data Cloud and generative AI directly within their workflow, integrating multi-channel marketing with sales, service, and commerce on a single platform. New customers can easily start leveraging data and generative AI to: Additionally, Data Cloud, available at no cost to Salesforce customers, enables: Go deeper: Data Cloud enables companies to consolidate trapped data into Salesforce, creating a comprehensive 360-degree view of customers across products, services, and interactions. Einstein 1 seamlessly integrates with Data Cloud to unlock organizational data for superior customer experiences, AI-driven employee augmentation, and enhanced profitability. Manage Your Marketing App: Salesforce admins, Data Cloud admins, and marketing admins configure and manage Marketing Cloud Growth. Determine whether these roles are consolidated or managed by multiple individuals. Increase Productivity with AI: Predictive and generative AI tools from Einstein in Marketing Cloud Growth enhance work outcomes and day-to-day productivity. Comply with Privacy Regulations: Stay compliant with privacy and consent regulations using Marketing Cloud Growth’s consent management tools, including default marketing communication subscriptions and a built-in email preference page. Target Audiences with Marketing Cloud Growth: Utilize Data Cloud data to filter segments, ensuring your campaigns reach the right audience. Manage Marketing Efforts with Campaigns: Design and automate campaigns in a centralized hub with templated options for content creation. Manage Content in Marketing Cloud Growth: Organize and create various content types within the Content tab powered by Salesforce CMS. Measure Success in Marketing Cloud Growth: Monitor performance and campaign success with Data Cloud reports available in the Analytics tab. Marketing Cloud Growth will initially launch in the United States and Canada, with plans to expand to EMEA by year-end and additional regions thereafter. Salesforce customers with Sales or Service Enterprise Edition (EE) or above can access Data Cloud at no cost. 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

February 20, 2024in Marketing Automation, Salesforce, Salesforce Data Cloud, Salesforce Einstein

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