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09Sep

Predictive Analytics

Industry forecasts predict an annual growth rate of 6% to 7%, fueled by innovations in cloud computing, artificial intelligence (AI), and data engineering. In 2023, the global data analytics market was valued at approximately $41 billion and is expected to surge to $118.5 billion by 2029, with a compound annual growth rate (CAGR) of 27.1%. This significant expansion reflects the growing demand for advanced analytics tools that provide actionable insights. AI has notably enhanced the accuracy of predictive models, enabling marketers to anticipate customer behaviors and preferences with impressive precision. “We’re on the verge of a new era in predictive analytics, with tools like Salesforce Einstein Data Analytics revolutionizing how we harness data-driven insights to transform marketing strategies,” says Koushik Kumar Ganeeb, a Principal Member of Technical Staff at Salesforce Data Cloud and a distinguished Data and AI Architect. Ganeeb’s leadership spans initiatives like AI-powered Salesforce Einstein Data Analytics, Marketing Cloud Connector for Data Cloud, and Intelligence Reporting (Datorama). His expertise includes architecting vast data extraction pipelines that process trillions of transactions daily. These pipelines play a crucial role in the growth strategies of Fortune 500 companies, helping them scale their data operations efficiently by leveraging AI. Ganeeb’s visionary work has propelled Salesforce Einstein Data Analytics into the forefront of business intelligence. Under his guidance, the platform’s advanced capabilities—such as predictive modeling, real-time data analysis, and natural language processing—are now pivotal in transforming how businesses forecast trends, personalize marketing efforts, and make data-driven decisions with unprecedented precision. AI and Machine Learning: The Next Frontier Beginning in 2018, Salesforce Marketing Cloud, a leading engagement platform used by top enterprises, faced challenges in extracting actionable insights and enhancing AI capabilities from rapidly growing data across diverse systems. Ganeeb was tasked with overcoming these hurdles, leading to the development of the Salesforce Einstein Provisioning Process. This process involved the creation of extensive data import jobs and the establishment of standardized patterns based on consumer adoption learning. These automated jobs handle trillions of transactions daily, delivering critical engagement and profile data in real-time to meet the scalability needs of large enterprises. The data flows seamlessly into AI models that generate predictions on a massive scale, such as Engagement Scores and insights into messaging and language usage across the platform. “Integrating AI and machine learning into data analytics through Salesforce Einstein is not just a technological enhancement—it’s a revolutionary shift in how we approach data,” explains Ganeeb. “With our advanced predictive models and real-time data processing, we can analyze vast amounts of data instantly, delivering insights that were previously unimaginable.” This innovative approach empowers organizations to make more informed decisions, driving unprecedented growth and operational efficiency. Real-World Success Stories Under Ganeeb’s technical leadership, Salesforce Einstein Data Analytics has delivered remarkable results across industries by leveraging AI and machine learning to provide actionable insights and enhance business performance. In the past year, leading companies like T-Mobile, Fitbit, and Dell Technologies have reported significant improvements after integrating Einstein. Ganeeb’s proficiency in designing and scaling data engineering solutions has been critical in helping these enterprises optimize performance. “Scalability with Salesforce Einstein Data Analytics goes beyond managing data volumes—it ensures that every data point is converted into actionable insights,” says Ganeeb. His work processing petabytes of data daily underscores his commitment to precision and efficiency in data engineering. Navigating Data Ethics and Quality Despite the rapid growth of predictive analytics, Ganeeb emphasizes the importance of data ethics and quality. “The accuracy of predictive models depends on the integrity of the data,” he notes. Salesforce Einstein Data Analytics addresses this by curating datasets to ensure they are representative and free from bias, maintaining trust while delivering reliable insights. By implementing rigorous data quality checks and ethical considerations, Ganeeb ensures that Einstein Analytics not only delivers actionable insights but also fosters transparency and trust. This balanced approach is key to the responsible use of predictive analytics across various industries. Future Trends in Predictive Analytics The future of predictive analytics looks bright, with AI and machine learning poised to further refine the accuracy and utility of predictive models. “Success lies in embracing technological advancements while maintaining a human touch,” Ganeeb notes. “By combining AI-driven insights with human intuition, businesses can navigate market complexities and uncover new opportunities.” Ganeeb’s contributions to Salesforce Einstein Data Analytics exemplify this balanced approach, integrating cutting-edge technology with human insight to empower businesses to make strategic decisions. His work positions organizations to thrive in a data-driven world, helping them stay agile and competitive in an evolving market. Balancing Benefits and Challenges – Predictive Analytics While predictive analytics offers vast potential, Ganeeb recognizes the challenges. Ensuring data quality, addressing ethical concerns, and maintaining transparency are crucial for its responsible use. “Although challenges remain, the future of AI-based predictive analytics is promising,” Ganeeb asserts. His work with Salesforce Einstein Data Analytics continues to push the boundaries of marketing analytics, enabling businesses to harness the power of AI for transformative growth. 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

September 9, 2024in Salesforce Data Cloud, Salesforce Einstein, Salesforce Marketing Cloud

23May

Service Cloud Digital Engagement

Salesforce Enhances Service Cloud Digital Engagement for Unified Customer Interactions Salesforce has unveiled new enhancements to Service Cloud Digital Engagement, aimed at unifying unstructured conversational data from various digital channels, departments, and devices within a single platform. Built on the Einstein 1 Platform, these enhancements enable service leaders to gain a more holistic view of customers, enhancing the value delivered in every interaction. Importance of Enhancements Detailed Enhancements Service Cloud Digital Engagement is designed to deliver seamless, personalized conversational experiences across channels at scale. By connecting to Salesforce Data Cloud, which unifies structured and unstructured enterprise and customer data, companies can engage in more meaningful conversations. Key enhancements include: With Service Cloud built on the Einstein 1 Platform, companies can integrate sales, service, and marketing data into one platform, facilitating more relevant customer experiences and driving business growth. Salesforce’s Perspective Kishan Chetan, EVP & GM of Service Cloud, commented, “As customers interact with companies across more touch points and channels, they are looking for more personalization and a higher-touch experience. With Service Cloud built on the Einstein 1 Platform, companies can bring in sales, service, and marketing data on one platform to deliver more relevant customer experiences and drive business growth.” Customer Reactions Olivia Boles, Director of Operations Projects at PenFed, said, “Being able to see all the communication — chat transcripts, emails, phone calls — on the member’s profile page has totally transformed the agent and member experiences.” Availability 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

May 23, 2024in Data, Einstein 1 Platform, Enterprise, Salesforce, Salesforce Data Cloud

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

20Aug

Big Data and Data Visualization Explained

Data Visualization: Turning Complex Data into Clear Insights Data visualization is the practice of converting information into visual formats, such as maps or graphs, to make data more accessible and understandable. The primary purpose of data visualization is to highlight patterns, trends, and outliers within large data sets, allowing users to quickly glean insights. The term is often used interchangeably with information graphics, information visualization, and statistical graphics. The Role of Data Visualization in Data Science Data visualization is a crucial step in the data science process. After data is collected, processed, and modeled, it must be visualized to draw meaningful conclusions. It’s also a key component of data presentation architecture, a discipline focused on efficiently identifying, manipulating, formatting, and delivering data. Importance Across Professions Data visualization is essential across various fields. Teachers use it to display student performance, computer scientists to explore AI advancements, and executives to communicate information to stakeholders. In big data projects, visualization tools are vital for quickly summarizing large datasets, helping businesses make informed decisions. In advanced analytics, visualization is equally important. Data scientists use it to monitor and ensure the accuracy of predictive models and machine learning algorithms. Visual representations of complex algorithms are often easier to interpret than numerical outputs. Historical Context of Data Visualization Data visualization has evolved significantly over the centuries, long before the advent of modern technology. Today, its importance is more pronounced, as it enables quick and effective communication of information in a universally understandable manner. Why Data Visualization Matters Data visualization provides a straightforward way to communicate information, regardless of the viewer’s expertise. This universality makes it easier for employees to make decisions based on visual insights. Visualization offers numerous benefits for businesses, including: Advantages of Data Visualization Key benefits include: Challenges and Disadvantages Despite its advantages, data visualization has some challenges: Data Visualization in the Era of Big Data With the rise of big data, visualization has become more critical. Companies leverage machine learning to analyze vast amounts of data, and visualization tools help present this data in a comprehensible way. Big data visualization often employs advanced techniques, such as heat maps and fever charts, beyond the standard pie charts and graphs. However, challenges remain, including: Examples of Data Visualization Techniques Early computer-based data visualizations often relied on Microsoft Excel to create tables, bar charts, or pie charts. Today, more advanced techniques include: Common Use Cases for Data Visualization Data visualization is widely used across various industries, including: The Science Behind Data Visualization The effectiveness of data visualization is rooted in how humans process information. Daniel Kahneman and Amos Tversky’s research identified two methods of information processing: Visualization Tools and Vendors Data visualization tools are widely used for business intelligence reporting. These tools generate interactive dashboards that track performance across key metrics. Users can manipulate these visualizations to explore data in greater depth, and indicators alert them to data updates or important events. Businesses might use visualization of data software to monitor marketing campaigns or track KPIs. As tools evolve, they increasingly serve as front ends for sophisticated big data environments, assisting data engineers and scientists in exploratory analysis. Popular data visualization tools include Domo, Klipfolio, Looker, Microsoft Power BI, Qlik Sense, Tableau, and Zoho Analytics. While Microsoft Excel remains widely used, newer tools offer more advanced capabilities. Data visualization is a vital subset of the broader field of data analytics, offering powerful tools for understanding and leveraging business data across all sectors. 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

August 20, 2023in Salesforce

21Jul

The Evolution of Salesforce Data Cloud

The Evolution of Salesforce Data Cloud Salesforce’s journey to Data Cloud started with its acquisition of Krux in 2016, which was later rebranded as Salesforce DMP. This transformation gained momentum in 2019 when Salesforce introduced its customer data platform (CDP), incorporating Salesforce DMP. Subsequent acquisitions of Datorama, MuleSoft, Tableau, and Evergage (now Interaction Studio) enriched Salesforce CDP’s functionality, creating today’s robust Data Cloud. Understanding Customer Data Platforms (CDPs) A customer data platform (CDP) aggregates customer data from multiple channels to create a unified customer profile, enabling deeper insights and real-time personalization. A CDP serves as a centralized customer data repository, merging isolated databases from marketing, service, and ecommerce to enable easy access to customer insights. Salesforce’s “State of Marketing” report highlights the impact of CDPs, noting that 78% of high-performing businesses use CDPs, compared to 58% of underperformers. This analysis explores the evolution of CDPs and their role in transforming customer relationship management (CRM) and the broader tech ecosystem, turning customer data into real-time interactions. Key Functions of a Customer Data Platform (CDP) CDPs perform four main functions: data collection, data harmonization, data activation, and data insights. Origins of Customer Data Platforms (CDPs) CDPs evolved as the latest advancement in customer data management, driven by the need for a unified marketing data repository. Unlike earlier tools that were often limited to specific channels, CDPs enable real-time data synchronization and cross-platform engagement. Advances in AI, automation, and machine learning have made this level of segmentation and personalization attainable. The Future of Customer Data Platforms (CDPs) The next generation of CDPs, like Salesforce’s Data Cloud, supports real-time engagement across all organizational functions—sales, service, marketing, and commerce. Data Cloud continuously harmonizes and updates customer data, integrating seamlessly with Salesforce products to process over 100 billion records daily. With Data Cloud, organizations gain: Benefits of a Customer Data Platform (CDP) CDPs provide comprehensive insights into customer interactions, supporting personalization and cross-selling. Beyond segmentation, they serve as user-friendly platforms for audience analysis and data segmentation, simplifying day-to-day data management. Data Cloud allows organizations to transform customer data into personalized, seamless experiences across every customer touchpoint. Leading brands like Ford and L’Oréal utilize Data Cloud to deliver connected, real-time interactions that enhance customer engagement. The Need for Customer Data Platforms (CDPs) CDPs address critical data management challenges by unifying disjointed data sources, resolving customer identities, and enabling seamless segmentation. These capabilities empower companies to maximize the potential of their customer data. CDP vs. CRM CDPs are an evolution of traditional CRM, focusing on real-time, highly personalized interactions. While CRMs store known customer data, CDPs like Data Cloud enable real-time engagement, making it the world’s first real-time CRM by powering Salesforce’s Customer 360. Selecting the Right CDP When choosing a CDP, the focus often falls into two areas: insights and engagement. An insights-oriented CDP prioritizes data integration and management, while an engagement-focused CDP leverages data for real-time personalization. Data Cloud combines both, integrating real-time CDP capabilities to deliver unmatched insights and engagement across digital platforms. Content updated October 2024. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more 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

July 21, 2023in Data, Mulesoft, Salesforce, Salesforce Data Cloud

15Jun

Scale Data and Analytics in the Cloud

Winning in the Data Economy In the rapidly growing data economy, enterprises are eager to gain a competitive edge. This data economy, which revolves around the global supply and demand for data and data-driven applications, continues to expand as more organizations seek critical insights to drive their success. Scale Data and Analytics in the Cloud. The value of data isn’t a new concept. Companies acquired other companies for the sole purpose of obtaining their data – customers, prospects, etc. The value of actionable data is a bit newer. Whereas we once marketed to prospects based primarily on historical data, data-driven applications let us market at the right time on the right channel with the right message. To understand what it takes to excel in the new data economy, Tableau partner Snowflake surveyed business and technology leaders. Their research highlighted the characteristics of the leaders and laggards, emphasizing the importance of a strong data strategy for achieving successful outcomes. Industries like financial services, health and life sciences, and retail are still struggling to fully benefit from the data economy, often finding it challenging to unlock the full value of their data. Here are four key actions that can help organizations win in today’s data economy and achieve tangible results: 1. Create a Strong Data Culture A robust data culture is foundational for realizing the value of data. Organizations that prioritize becoming data-driven see significant benefits: Jennifer Belissent, Principal Data Strategist at Snowflake, emphasizes how a cloud-enabled data culture accelerates time-to-value by breaking down organizational silos. Tableau offers a playbook to help organizations build, expand, and mature their data capabilities. 2. Adopt an AI-Driven, Enterprise-Ready Analytics Platform Data leaders utilize AI-driven enterprise analytics platforms like Tableau, which provide trusted predictions and insights to scale decision-making. Traditional solutions often fall short in delivering speed to insight and self-service capabilities. Tableau, particularly with Tableau Cloud, offers an easy-to-scale solution that manages and analyzes data across various sources, supporting meaningful impact and agility. Tableau Cloud’s Advanced Management capabilities enhance security, usability, and scalability. Additionally, Tableau Accelerators—over 100 ready-to-use, in-product dashboard starters—support various industries, enabling comprehensive analysis and problem-solving. 3. Migrate to the Cloud Cloud adoption is accelerating as organizations pursue data-driven digital transformations. The cloud offers flexibility, agility, scalability, reduced IT overhead, and increased resilience and performance. Key considerations for cloud migration include: Whether opting for on-premise, hybrid, or full cloud migration, Tableau connects to data wherever it resides, fueling insights across the business. Tableau’s own journey to the cloud involved evaluating criteria, enhancing collaboration, and applying new data management processes, resulting in a unified source of truth. 4. Choose the Right Partners to Scale Cloud-Native Analytics Selecting partners that facilitate cloud-native analytics is crucial. Ideal partners should offer: Snowflake and Tableau exemplify these qualities, addressing data and organizational demands. Snowflake provides extensive data storage and processing, while Tableau offers intuitive, self-service analytics. This partnership has helped enterprises like Cart.com achieve significant revenue growth by embedding Tableau analytics in Snowflake’s platform. Embrace the Data Economy with Cloud-Native Analytics Regardless of where your organization stands in the data economy, taking steps to leverage cloud-native analytics can unlock numerous opportunities. Tableau continues to invest in its platform to help organizations thrive with data in the cloud, offering expert advice, solutions, and valuable partnerships. By adopting these strategies, your organization can become a leader in the data economy and achieve remarkable results. 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

June 15, 2023in Salesforce Data Cloud, Snowflake

06Jun

Race to AI for CX

AI emerges as a transformative force revolutionizing the customer experience (CX) landscape in the dynamic world of global e-commerce. Its ability to handle extensive data and facilitate large-scale automation empowers brands to offer tailored and seamless CX journeys, fostering customer loyalty and satisfaction. The great race to AI for CX is upon us. In the era of rapid technological advancements, organizations worldwide are in a race to integrate AI-driven capabilities across their operations. The widespread adoption of AI is fueled by its recognition not just as a technological advancement but as a strategic imperative. Businesses invest in AI to enhance operational productivity, reduce costs, elevate customer experiences, and maintain competitiveness. AI’s impact on customer experience extends to substantial improvements in Customer Relationship Management (CRM) systems. Automation of tasks like data entry, lead scoring, and follow-up reminders, coupled with intelligent insights such as predicting high-converting leads, empowers sales teams to optimize their efforts. Considering the pivotal role customers play for every business, CRM has become a launchpad for AI-led transformations throughout enterprises. Businesses swiftly integrate AI-powered experiences into sales, marketing, service, and e-commerce use cases. However, for AI investments to meet expectations, they must be built on robust data practices and trust. Data readiness, reflecting an organization’s preparedness to access and use quality data across its business, is crucial for successful AI outcomes. Ensuring trust in AI, free from data-security concerns or incorrect outcomes, is equally essential. Many companies, lacking mature data practices for advanced AI capabilities like generative AI (genAI), express significant trust concerns; nevertheless, the imperative to progress prompts continued AI investments. The deployment of AI-powered chatbots enables customer service teams to deliver convenient, 24/7 support. These chatbots, exemplified by Zendesk bots, operate round the clock, offering real-time assistance even when support agents are offline. Generative AI-powered conversational bots enhance customer self-service, reduce resolution times, and improve satisfaction by maintaining case-specific tonality and context in real time. Personalized marketing, beyond being a trend, has become a cornerstone strategy for businesses aiming to establish profound connections with their audiences. Crafting messages that resonate personally not only captures attention but also cultivates conversations and fosters lasting brand loyalty. In a digital age where user experience can make or break a brand, strategic partnerships become crucial. The race to AI for CX is on and you can’t afford to be left behind. Enhancing digital user experiences often requires collaboration with specialized partners. Regpack, a versatile payment and registration solution, exemplifies this approach by collaborating with Webeo, specialists in B2B website personalization. This partnership resulted in a 565% increase in site conversion, a 302% rise in average time spent on the site, and a significant 30% drop in bounce rates. Webeo’s personalization software enabled Regpack to identify and adapt to the diverse needs of its clientele through advanced behavioral personalization techniques. Race to AI for CX AI’s impact on marketing extends beyond being an add-on tool, serving as a fundamental game-changer for crafting bespoke customer experiences. AI seamlessly bridges the digital and physical realms, particularly in ecommerce and retail sectors, dynamically adapting products and content based on consumer behavior. AI-driven technologies interpret vast data points, allowing brands to offer hyper-personalized interactions. Real-time data analysis and pattern recognition capabilities make AI a powerful tool for creating engaging and emotionally resonant personalized experiences. In essence, AI architects a new era in marketing, where experiences are not merely personalized but dynamically respond to evolving consumer desires and expectations. Leveraging AI, brands can create narratives that consumers feel intrinsically part of, fostering profound connections. For instance, Calian IT & Cyber Solutions employs personalized marketing tactics to understand and address the unique challenges and needs of each business they serve, fostering strong, long-term relationships with clients. The key takeaway for marketers is clear – the era of generic messaging is fading. A more nuanced, data-driven, and empathetic approach is emerging. Brands that embrace this shift, continuously innovate, and create experiences that customers feel a part of will thrive. As technology advances and consumer expectations evolve, mastering the art of personalization becomes crucial to redefine the marketing landscape. Key Strategies for Exceptional Customer Experience with AI: AI and Customer Experience (CX): AI impacts the entire customer journey, from predictive and prescriptive analytics to sentiment analysis, journey mapping assistance, orchestration, dynamic pricing, virtual try-ons, and augmented reality, providing an interactive and engaging shopping experience. AI and Employee Experience (EX): Efficiencies introduced by AI in employee tasks directly benefit customers. When repetitive tasks are automated, employees gain time for critical and value-added tasks, leading to increased productivity, reduced workload, fewer errors, and improved job satisfaction. Delivering Exceptional Customer Experience with AI: As customer expectations evolve, AI offers a scalable approach for brands to exceed expectations, resulting in memorable customer experiences shaped by clear communication, seamless journeys, and engaging personalized interactions. The transformative potential of AI for CX success is evident in its ability to reshape the marketing landscape. 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

June 6, 2023in Salesforce Einstein

18Mar

Marketing Cloud Intelligence For Data Integration

What exactly is Salesforce Datorama, now referred to as Marketing Cloud Intelligence? It is a versatile, cloud-based marketing data platform offering a suite of solutions aimed at enhancing data integration, reporting, analysis, and optimization. Marketing Cloud Intelligence For Data Integration. However, the question arises: Does Marketing Cloud Intelligence truly deliver the cloud-based Marketing Intelligence as Salesforce touts? Let’s dive into what this platform offers and dissect its capabilities without the fluff. Understanding the Platform: Salesforce’s Marketing Cloud Intelligence, formerly known as Datorama, serves as an analytics tool meticulously designed to integrate and visualize various forms of marketing performance data. It strikes a balance, catering to both analytically inclined marketers and seasoned analysts seeking to bridge data with conventional BI tools like Tableau. Flexible SaaS with Tailored Customization: Despite its Software-as-a-Service (SaaS) nature, Datorama surprises with its flexibility. It can function autonomously, handling data storage, modeling, ETL, and visualization, or seamlessly integrate with other platforms like Azure Databricks or Looker. While it accommodates numerous data use cases, its primary focus remains on Performance Marketing. Marketing Cloud Intelligence often gets misclassified as a traditional Business Intelligence or Analytics platform, but it truly excels in data management. For those contemplating its adoption, familiarity with its functionalities through resources like “Getting to Know Marketing Cloud Intelligence” or video walkthroughs is encouraged. Transition to Marketing Cloud Intelligence: The rebranding from Datorama to Marketing Cloud Intelligence was proposed in early 2022, gaining momentum recently. Despite the name change, the platform’s features and capabilities remain intact. Origins and Evolution: Originating from an Israeli-based technology firm in 2012, Datorama swiftly gained traction under the stewardship of its founders Ran Sarig, Efi Cohen, and Katrin Ribant. In 2018, Salesforce acquired Datorama, integrating it into the Marketing Cloud suite alongside Account, Engagement, Personalization, and Data Cloud platforms. However, as of February 2, 2023, the original founders and core engineering teams have moved on, possibly signaling a shift in the platform’s trajectory. Functionalities and Capabilities: Marketing Cloud Intelligence boasts robust data onboarding and connectivity features, with a rich assortment of connectors and retrieval mechanisms supporting popular data management platforms like SAP Hana, AWS, Oracle, Vertica, and SQL Server. It excels in ingesting and managing aggregated marketing performance data, with the capacity to handle event-level data as well. Pricing and Competitors: While its pricing model revolves around data row consumption and user seats, the platform may become cost-prohibitive at higher volumes. However, recent enhancements like Data Lake offer expanded row count flexibility without escalating costs. Its primary competitors include Domo, Adverity, NinjaCat, Improvado, Looker, PowerBI, and Google Data Studio. Use Cases and Industries: Marketing Cloud Intelligence serves marketers and advertisers across various industries, including communications, media, technology, healthcare, finance, manufacturing, automotive, retail, and publishing. Its versatility lies in supporting six specific marketing data use cases, ranging from building a single source of data to producing informative dashboards. Continuous Evolution: With frequent product releases, Marketing Cloud Intelligence remains dynamic, adapting to evolving market needs and technological advancements. Its commitment to enhancing analytics, visualization, connectivity, and marketplace apps ensures its relevance in the ever-changing landscape of marketing data management. Future Outlook: As Salesforce navigates the competitive analytics space, the future of Marketing Cloud Intelligence remains intriguing. While challenges like pricing pressures persist, the platform’s integration within the Marketing Cloud ecosystem and ongoing enhancements hint at a promising trajectory. Whether it evolves into a fully integrated analytics solution or retains its standalone utility, only time will tell. But one thing is certain: Salesforce’s promotion of Marketing Cloud Intelligence will continue to shape its evolution and market positioning moving forward. 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 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

March 18, 2023in Google Analytics, Salesforce Communications Cloud, Salesforce Marketing Cloud

19Oct

Salesforce Genie Announced

Salesforce Genie announced this year is an innovative data platform recently unveiled at Dreamforce 2022, heralding the world’s first real-time CRM. Genie is the driving force behind Salesforce’s entire Customer 360 platform, delivering hyper-scale, real-time data capabilities. With Genie, any business can harness the power of data to create magical customer experiences, offering seamless, personalized interactions across sales, service, marketing, and commerce. It adapts effortlessly to evolving customer needs. Consider scenarios we encounter daily: the frustration of lengthy customer support calls navigating purchase history, or the challenge of locating specific items on cluttered e-commerce websites. These situations underscore the demand for real-time updates in every customer interaction, a demand that Genie aims to fulfill. In the last 12 hours alone, the volume of stored customer data worldwide has doubled, explaining the delays in customer support. However, with Salesforce Genie, businesses can make sense of their data regardless of source, system, or channel. This unified data drives unprecedented levels of personalization, akin to magic. Salesforce Genie’s Key Features: Genie is pivotal for various industries leveraging Salesforce, like banks managing vast customer records and administrative tasks. Salesforce aims to enhance data utilization without altering existing approaches. Comparison with Salesforce CDP: Genie transcends traditional Customer Data Platforms (CDPs) by: How Genie Works: Genie ingests and stores real-time data streams at scale, integrating them seamlessly with Salesforce data. It consolidates data from diverse channels, legacy systems via MuleSoft, and proprietary data lakes through connectors. Core Pillars of Salesforce Genie: Salesforce Genie’s Extensibility: Genie partners with leading data providers such as Snowflake and Amazon SageMaker, enabling seamless integration and real-time data sharing without data movement. Unified Customer 360 Use Cases: Genie unifies data across Salesforce’s Customer 360 products for various departments: In essence, Salesforce Genie revolutionizes data integration and utilization, enabling businesses to deliver unparalleled customer experiences across all touchpoints. 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

October 19, 2022in Hyperforce, Mulesoft, Salesforce, Salesforce Data Cloud, Salesforce Marketing Cloud, Salesforce Optimization, Salesforce Sales Cloud, Salesforce Slack, Snowflake

02Jun

What is the Difference Between Datorama and Tableau?

In the current business environment, customer and prospect data serve as the driving force in most everything we do, emphasizing the importance of analyzing, understanding, and acting on accurate data for informed decision-making. Business Intelligence (BI) tools like Datorama and Tableau play an important role in facilitating these processes. This insight conducts a comparative analysis of Datorama vs. Tableau, covering features, capabilities, pricing, support, and training options. Tectonic’s goal is to assist businesses in making informed decisions aligned with their specific needs. If you are choosing between these two tools, contact Tectonic for assistance. Overview of Datorama: Datorama, a cloud-based BI platform, specializes in providing insights into data across a variety of marketing channels. Offering real-time analytics and pre-built connectors for various marketing platforms, Datorama serves as a comprehensive tool for marketing analytics. Its dashboard provides a centralized view of marketing data, automates real-time processing, and incorporates AI-powered insights generated by Salesforce Einstein. Overview of Tableau: Tableau, a widely used BI platform, facilitates easy data connection and visualization. With a user-friendly interface, it allows users to build interactive dashboards and visualizations without coding expertise. Tableau’s adaptability enables it to connect to various data sources, create interactive visualizations, offer data blending, and include forecasting capabilities. Key Features of Datorama and Tableau: Datorama Features: Tableau Features: Pricing Models: Datorama: Custom plans with varying costs based on specific business needs, starting at $3,000 USD per month. Tableau: Tiered plans with pricing ranging from $12 to $70 per user per month. Support and Training: Datorama: Knowledge base, community forums, training courses, and a certification program. Tableau: 24/7 support, online courses, and live training sessions. Choosing the Right BI Solution: Datorama: Suited for businesses with complex data integration needs, ideal for multi-channel marketing analytics and forecasting, offers advanced AI-powered insights. Tableau: Suited for businesses with data visualization and reporting needs, ideal for ad-hoc data analysis and dashboarding, offers powerful visualization capabilities. Benefits of Integration: Final Thoughts: Both Datorama and Tableau excel as BI tools, offering unique strengths. Datorama is tailored for marketing analytics with real-time insights, while Tableau provides versatility in connecting and visualizing data from various sources. Choosing the right solution depends on specific business needs, goals, and budget considerations. Contact Tectonic today for assistance. Like2 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

June 2, 2022in Data, Salesforce, Salesforce Einstein

01Jun

Salesforce Marketing Cloud Intelligence Explained

What is Marketing Cloud Intelligence? Salesforce’s Marketing Cloud Intelligence, formerly known as Datorama, is an analytics tool designed to integrate and visualize marketing performance data across various platforms. It caters to analytically driven marketers and seasoned analysts, providing an easy-to-use interface while offering connections to traditional BI tools like Tableau. Marketing efforts generate extensive data across multiple platforms, and Marketing Cloud Intelligence consolidates all these marketing tools into a centralized source. It serves as a comprehensive solution for reporting, measurement, and optimization. Market intelligence involves gathering real-time data from the market to understand customers, trends, behaviors, and more, enabling a company to stay competitive and meet market demands. By leveraging out-of-the-box connections, Marketing Cloud Intelligence seamlessly links platforms like Google, YouTube, Instagram, and others without the need for complex coding. The tool, now known as Marketing Cloud Intelligence, reveals trends, tracks progress against goals, and quantifies the ROI of marketing initiatives once connected. The system features a connected library of over 170 connectors for acquiring data from major advertising, commerce, CRM, and database vendors. The unique universal connector, powered by AI, allows effortless connection of any data stream within minutes, even from sources lacking an API connection. Marketing Cloud Intelligence addresses the challenge of data consistency by providing an out-of-the-box marketing data model. It helps organize data into a clear and consistent taxonomy, enriching it with naming conventions, data classification, and automated maintenance alerts for trustworthy decision-making. Beyond reporting and dashboards, Marketing Cloud Intelligence, with the assistance of Einstein, provides actionable insights. Marketers can select a KPI to improve and create a perpetual pipeline of AI insights, addressing overarching questions or specific areas like reducing spend or analyzing creative impacts. What can marketers do with Marketing Cloud Intelligence? Marketers can efficiently compile multiple sources of data in Marketing Cloud using various KPIs, creating at-a-glance and visually appealing dashboards and reports. Marketing Cloud Intelligence, powered by Datorama, facilitates the organization and analysis of diverse data within Marketing Cloud. What does Marketing Cloud Intelligence do? Marketing Cloud Intelligence integrates data from marketing and advertising platforms, web analytics, CRM, e-commerce, and more. It offers a unified view for optimizing campaign performance and real-time insights. The tool optimizes marketing spend and customer engagement with unified performance data, automated reporting, and AI-driven insights. Why is marketing intelligence important in Salesforce? Marketing intelligence tools help businesses gather and analyze market data. CRM and CDP tools, such as Salesforce Marketing Cloud Intelligence, unite data from disparate sources to provide a fuller picture of their customers and the marketplace. 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

June 1, 2022in Data, Google, Salesforce, Salesforce Marketing Cloud, Technology

03May

Employ Marketing Cloud Data with Datorama

Unlocking the Power of Salesforce Marketing Cloud with Dataorama-Employ Marketing Cloud Data with Datorama (now Salesforce Marketing Cloud Intelligence) In the realm of modern marketing, success hinges on data-driven insights rather than creative chaos. Salesforce Marketing Cloud’s Dataorama tackles the challenges associated with marketing data, offering a robust platform to store, visualize, and leverage data from diverse sources. What is Datorama? Originally developed to streamline reporting for advertising technology companies, Datorama is now a pivotal feature within Salesforce Marketing Cloud. It caters not only to advertising but also to industries spanning automotive to publishing. Datorama empowers marketers to consolidate marketing spend, campaign results, and trends into a unified and accessible platform. Key Features and Use Cases of Dataorama (now Salesforce Marketing Cloud Intelligence): Advantages and Limitations of Datorama-Marketing Cloud Intelligence: Implementation and Adoption: To implement Datorama-Marketing Cloud Intelligence within your organization: Salesforce Marketing Cloud’s Intelligence empowers marketers to shift focus from mundane reporting tasks to creative and strategic endeavors. By harnessing the power of data integration, visualization, and AI-driven insights, organizations can elevate their marketing performance and drive business growth effectively. Employ Marketing Cloud Data with Datorama Content updated September 2023. 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

May 3, 2022in Einstein Insights, Salesforce, Salesforce Marketing Cloud

09Feb

Datorama Salesforce

What is Datorama Salesforce? Datorama is a channel and partner agnostic platform that can help marketing organizations in 6 specific ways: Build a single source of all data, at enterprise scale — augmented with Data Lake and CDP. What is the purpose of Datorama Salesforce? Datorama takes all your raw marketing data and connects and unifies it through a better unified data model. Byeliminating siloed data. You can easily retrieve constantly changing data sources into automated dashboards and reports, too. And in real time. What are the benefits of Datorama? Datorama solves many of the major integration challenges of combining and analyzing data from multiple media platforms. Through native data connectors and TotalConnect. It allows you to visually present your analysis to your audience in a more appealing way. Are Datorama and Tableau the same thing? Datorama is tailored towards marketing analytics and provides real-time insights into marketing success with AI-powered insights. Tableau is a more versatile tool that can connect and visualize data from various sources. Tableau can provide a comprehensive view of business performance through personalized visualization and allow users to explore data in real-time with interactive dashboards. U.S. sales and marketing software company Salesforce signed an agreement to acquire Datorama. Datorama was an Israeli cloud-based artificial intelligence marketing platform. Datarama Salesforce is now known as Marketing Cloud Intelligence. 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 9, 2022in Salesforce

19Jan

Datorama Features from Salesforce

Datorama serves as an all-in-one platform for monitoring and managing marketing data, investments, and key performance indicators (KPIs). As a Software as a Service (SaaS) data platform, Datorama facilitates the onboarding and visualization of marketing data from various sources, including ad servers, search, social, DSPs, POS, and CRM. Key features of this marketing suite include: AI-powered insights designed to drive optimizations. Datorama Reports are available in two versions: standard and advanced. The standard version, known as Datorama Reports (now Intelligence Reports for Engagement), includes dashboards, pivot tables, and intuitive reports displaying simple statistics. Additionally, Datorama Reports for Marketing Cloud provide detailed analyses of email campaigns, push notifications, and customer journey data at the campaign level, revealing deep marketing insights and campaign performance. Datorama Features – Now Marketing Cloud Intelligence Datorama, now known as Marketing Cloud Intelligence, is Salesforce’s cloud-based AI-powered marketing intelligence and analytics tool. This platform enables marketers to harness business intelligence by consolidating various marketing sources into a unified data model. Datorama addresses three main aspects of a customer’s business through its platform: Connect and Mix, Analyze & Act, and Visualize. This marketing intelligence platform allows users to connect their entire MarTech stack, offering flexibility and control. Datorama’s Marketing Integration Engine bridges marketing data across the entire technology stack into a single source, enabling the creation of real-time reports at scale. The implementation timeline for Datorama varies based on project complexity. Moderate to semi-complex projects with eight to 12 data sources may take between eight to ten weeks. Complex projects with 15 to 25 or more data sources could take between 14 to 18 weeks. As of July 2022, Datorama is now referred to as Marketing Cloud Intelligence. Content updated July 2022. 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

January 19, 2022in Salesforce

06Dec

Datorama vs Tableau – What About Both?

Datorama vs Tableau – What about both for your Salesforce org? When comparing Datorama vs Tableau it becomes clear they each have compelling reasons for their use. Datorama Tableau What’s the difference between Datorama and Tableau? Tableau is primarily a data visualization and reporting tool, while Datorama is a marketing analytics platform. “So it’s not surprising that their functions are somewhat different, ”explains the business development manager. Selecting a BI tool that meets all your business goals can be a very complicated task. There are many aspects to take into account, and there will be some cases that would make you lean towards one solution or another. Datorama (currently Marketing Cloud Intelligence) and Tableau, both solutions from Salesforce, are available on the market for companies that want to incorporate BI into their management. In the following, we will describe some of their main characteristics and a comparison of two, taking into account factors that can help you decide on their use according to the needs or possibilities of your company. Did you know that Datorama and Tableau can work together? Benefits of Datorama and Tableau Integration Datorama’s integration with Tableau powers results in the unified analysis of both business and marketing data, enabling the following: Like2 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

December 6, 2021in Salesforce

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