Enterprise Archives - gettectonic.com

11Aug

AI Strategy and Tectonic

AI Strategy and Tectonic Recent advancements in artificial intelligence (AI) have showcased the immense potential of this technology to transform both business and society. However, as organizations scale AI systems, they must ensure these systems are structured and governed responsibly to prevent bias and errors. The widespread use of AI can have significant implications, and without proper safeguards, businesses risk costly outcomes. As your organization leverages diverse datasets to apply machine learning and automate workflows, it’s critical to implement strong guardrails to maintain data quality, ensure compliance, and promote transparency within AI systems. Tectonic is here to help you implement AI responsibly, focusing on areas where it can quickly and ethically deliver real business benefits. Our comprehensive portfolio of enterprise-grade AI products and analytics solutions is designed to minimize the challenges of AI adoption, establish a solid data foundation, and optimize for positive outcomes while ensuring responsible AI use. Global enterprises turn to Tectonic as a trusted partner in their AI transformation journeys. As a leading AI consulting firm, we enhance the value of AI and cloud technologies in driving business transformation. By working with our own advanced AI technologies and an open ecosystem of partners, we deliver AI models on any cloud, all guided by the principles of ethics and trust. 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 11, 2024in Artificial Intelligence, Data, Enterprise, Technology

10Aug

Generative AI Tools

One of the most significant use cases for generative AI in business is customer service and support. Most of us have likely experienced the frustration of dealing with traditional automated systems. However, today’s advanced AI, powered by large language models and natural language chatbots, is rapidly improving these interactions. While many still prefer human agents for complex or sensitive issues, AI is proving highly capable of handling routine inquiries efficiently. Here’s an overview of some of the top AI-powered tools for automating customer service. Although the human element will always be essential in customer experience, these tools free up human agents from repetitive tasks, allowing them to focus on more complex challenges requiring empathy and creativity. Cognigy Cognigy is an AI platform designed to automate customer service voice and chat channels. It goes beyond simply reading FAQ responses by delivering personalized, context-sensitive answers in multiple languages. Cognigy’s AI Copilot feature enhances human contact center workers by offering real-time AI assistance during interactions, making both fully automated and human-augmented support possible. IBM WatsonX Assistant IBM’s WatsonX Assistant helps businesses create AI-powered personal assistants to streamline tasks, including customer support. With its drag-and-drop configuration, companies can set up seamless self-service experiences. The platform uses retrieval-augmented generation (RAG) to ensure that responses are accurate and up-to-date, continuously improving as it learns from customer interactions. Salesforce Einstein Service Cloud Einstein Service Cloud, part of the Salesforce platform, automates routine and complex customer service tasks. Its AI-powered Agentforce bots manage “low-touch” interactions, while “high-touch” cases are overseen by human agents supported by AI. Fully customizable, Einstein ensures that responses align with your brand’s tone and voice, all while leveraging enterprise data securely. Zendesk AI Zendesk, a leader in customer support, integrates generative AI to boost its service offerings. By using machine learning and natural language processing, Zendesk understands customer sentiment and intent, generates personalized responses, and automatically routes inquiries to the most suitable agent—be it human or machine. It also provides human agents with real-time guidance on resolving issues efficiently. Ada Ada is a conversational AI platform built for large-scale customer service automation. Its no-code interface allows businesses to create custom bots, reducing the cost of handling inquiries by up to 78% per ticket. By integrating domain-specific data, Ada helps improve both support efficiency and customer experience across omnichannel support environments. More AI Tools for Customer Service There are numerous other AI tools designed to enhance automated customer support: While AI tools are transforming customer service, the key lies in using them to complement human agents, allowing for a balance of efficiency and personalized care. 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 10, 2024in AI Tools, Data, Enterprise, Generative AI, Salesforce, Salesforce Einstein

07Aug

Selling is Both an Art and a Team Effort

Selling is both an art and a team effort, making it essential for your sales managers, business development reps, and account executives to have everything they need within their workflow. By streamlining the user experience, you can accelerate deal closures without the frustration of navigating through multiple tabs and tools. This article dives into how Salesforce Relationship Selling can enhance buyer identification, data entry, and enrichment to optimize your sales process. Ensure Your Team’s Efficiency Managing multiple accounts, opportunities, and stakeholders requires having full context and accurate data at all times. This allows sales teams to engage the right person at the right time with ease. Why Enterprises Need Multiple Salesforce Orgs B2B selling is complex, typically involving six to ten stakeholders. According to Gartner, 75% of B2B buyers prefer a rep-free experience, making any rep interaction highly personalized and contextual. Salesforce Relationship Selling provides powerful tools to make both your sales teams and customers more satisfied. With fewer manual steps, reps can focus on what truly matters—building relationships with customers and prospects. Automatically Create Contacts Data entry is rarely a favorite task for Salesforce users, especially when automation can handle it. Salesforce’s Automatic Contact Creation eliminates the need for sellers to manually create contacts for the accounts they are working on. For those using Einstein Activity Capture, this feature may already be familiar. Once enabled, new contacts are automatically created based on emails or meetings identified in the user’s inbox and calendar. The system matches contacts to accounts using email addresses and additional recipients, providing a high-confidence match when contacts already exist. Sales teams can also set thresholds for contact creation, such as requiring up to three interactions (emails or meetings) before a new contact is created. These suggestions are displayed on the Seller Home in the Contact Suggestions widget. Out-of-the-Box Enrichment Salesforce’s Automated Contact Enhancement leverages AI to enrich contact records with critical information like Seniority Level, Department Group, and Buyer Attributes. These fields, once added to your layouts and list views, allow your team to easily identify key stakeholders, sponsors, or detractors. Contacts created via the Automatic Contact Creation feature are continuously updated as relationships evolve, ensuring accuracy. This enrichment also extends to other standard fields, such as Phone and Title, with ongoing support for emails in English. Visualize and Interact with Buying Committees The Buyer Relationship Map is a game-changer for visualizing contacts tied to an account or opportunity. Once enabled, this feature provides a clear view of stakeholders and their roles. Contacts with populated Seniority Level and Department Group fields are displayed on the map, which allows sellers to easily fill in missing information or create new contact roles—all without leaving the map interface. Clicking on any contact within the map opens a side panel with more details, including options to edit, send emails, or review past activity. Sellers can also view insights across the map, such as identifying detractors or missing decision-makers. Actionable Insights in the Flow of Work Relationship Maps are not confined to accounts—they’re available for opportunities too, with seamless access through the “View Relationship Map” button. Whether your team is working within Prospecting Center, Pipeline Inspection, or Account Plan pages, relevant insights are available wherever they are needed to drive action. Selling is Both an Art and a Team Effort While relationship selling is not new, Salesforce’s suite of tools provides a fresh, automated approach to this time-tested concept. By automatically creating and enriching contacts, visualizing relationships, and surfacing insights across workflows, the entire seller experience can be optimized in minutes. With Salesforce Relationship Selling, your team can focus on what really matters—building meaningful connections with customers. 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 7, 2024in Data, Enterprise, Salesforce

13Jul

Where Will the Data Scientists Go

What Is to Become of the Data Scientist Role? This question frequently arises among executives, particularly as they navigate the changing roles of data teams, such as those at DataRobot. Where Will the Data Scientists Go may not be as relevant as what new places can they go with AI? The short answer? While tools may evolve, the core of data science remains steadfast. As the field of data science continues to expand, the role of the data scientist becomes increasingly vital. The need will grow, even as the role changes. Trust in AI is dependant upon human oversight. Beyond the Hype of Consumer AI The surge in consumer AI products has raised concerns among data scientists about the implications for their careers. However, these technologies are built on data and generate vast amounts of new data, presenting numerous opportunities. The real transformative potential lies in enterprise-scale automation. Enterprise-Scale Automation: The Data Scientist’s Domain Enterprise-scale automation involves creating large-scale, reliable systems. Data scientists are crucial in this effort, as they bring expertise in data exploration and systematic inference. They are uniquely positioned to identify automation opportunities, design testing and monitoring strategies, and collaborate with cross-functional teams to bring AI solutions from concept to implementation. As automation grows, the role of the data scientist is essential in ensuring these systems function effectively and safely, particularly in environments without human oversight. New Skills for Data Scientists: The Guardians of AI Applications Data scientists will need to acquire new skills to manage automation at scale, including securing the systems they build. Generative AI introduces new risks, such as potential vulnerabilities to prompt injections or other security threats. Governance and ensuring positive business impacts will become increasingly important, requiring a data science mindset. Building Great Data Teams in the Age of AI The future of data science will not be about automation replacing data scientists but about the evolution of roles and skills. Data scientists need to focus on the core foundations of their discipline rather than the specific tools they use, as tools will continue to evolve. Teams must be built intentionally, encompassing a range of skills and personalities necessary for successful enterprise automation. Business Leaders: Navigating the AI Landscape Business leaders will need to excel in decision-making, understanding the problems they aim to solve, and selecting the appropriate tools and teams. They will also need to manage evolving regulations, particularly those related to the design and deployment of AI systems. Data Scientists: Precision Thinkers at the Forefront Contrary to the belief that AI could replace coding skills, the essence of data science lies in precise thinking and clear communication. Data scientists excel in translating business needs into data-driven decisions and AI applications, ensuring that solutions are not only technically sound but also aligned with business objectives. This skill set will be crucial in the era of AI, as data scientists will play a key role in optimizing workflows, designing AI safety nets, and protecting their organization’s brand and reputation. The Evolving Role of Data Science The demand for precise, data-literate thinkers will only grow with the rise of enterprise AI systems. Whether they are called data scientists or another name, professionals who delve deeply into data and provide critical insights will remain essential in navigating the complexities of modern technology and business landscapes. 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 13, 2024in Data, Enterprise, Generative AI, Salesforce, Technology

10Jul

Alphabet Abandons Acquisition for HubSpot

Alphabet Abandons Acquisition Plans for HubSpot The integration between Salesforce and Hubspot could have changed drastically. The HubSpot-Salesforce integration allows you to pass data between HubSpot and Salesforce seamlessly, and maintain consistency between your marketing and sales teams. Current HubSpot Google integration includes: ability to log emails sent from Gmail into HubSpot CRM with one click, so your team spends less time on busy work and more time doing what they do best. HubSpot integrates with your Google Calendar to help you book more meetings in less time. Google parent Alphabet has abandoned its plans to acquire HubSpot, according to sources familiar with the matter. This decision puts to rest what would have been one of the year’s largest takeovers. HubSpot, Inc. is an American developer and marketer of software products for inbound marketing, sales, and customer service. HubSpot was founded by Brian Halligan and Dharmesh Shah in 2006. The talks between Alphabet and HubSpot never progressed to due diligence and fell apart shortly after the companies held initial discussions on a potential deal, the source said, on condition of anonymity to discuss confidential matters. HubSpot’s shares, a customer relationship management company, plummeted by as much as 19 percent on Wednesday (Jul 10) in New York trading, marking the most significant drop since 2020. The shares closed down 12 percent at $492.31, giving the company a market value of approximately $25 billion. Earlier this year, Alphabet had expressed interest in a potential deal with HubSpot. However, the two sides never progressed to detailed discussions or due diligence, said the sources, who requested anonymity due to the confidentiality of the matter. Representatives for Alphabet did not immediately comment. A HubSpot spokesperson also declined to comment. Any acquisition of HubSpot would have been among the largest tech deals of the year, comparable to Synopsys’s pending $34 billion acquisition of Ansys, according to data compiled by Bloomberg. HubSpot recently suffered a hack attack. HubSpot, which builds marketing software for small and medium-sized businesses, has specialized in so-called inbound marketing, where consumers start engagement with a brand. HubSpot customers apply its software to make advertising content that consumers can click on. CEO Yamini Rangan said in May on HubSpot’s financial results call that customer demand had weakened, as small businesses worried about the economic impact of high interest rates. Acquiring Cambridge, Massachusetts-based HubSpot, which caters to small and midsize enterprises, would have bolstered Alphabet’s competitiveness against rivals like Microsoft, Oracle, and Salesforce. 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 10, 2024in Data, Enterprise, Google, Salesforce

01Jul

Marketing Personalization Explained

It feels like you’ve found “the holy grail” — a customer ready for a long-lasting brand relationship built on personalized marketing leading to customer loyalty. But then, just as quickly as the sparks fly, they fizzle out. Engagement plummets, and those once-enthusiastic customers cool or even disappear. What went wrong? Marketing Personalization Explained. In the world of personalized marketing, making the wrong moves can turn a promising relationship into a fleeting encounter. Or even a downright negative experience. Salesforce data shows that 81% of customers expect faster interactions as technology advances, and 73% crave better personalization. Without these, poor service can drive customers away, which is the number one reason they stop purchasing. Customers today value their experience with a company almost as much as their experience with the product or service. Customer experiences can be greatly improved with personalization. And we don’t just mean inserting their first name into an email. With timely data at your fingertips, influencing customer behavior seems straightforward. But there’s a catch: failing to utilize all available data can negatively impact customer experiences — pushing customers away faster than they can click “unsubscribe.” At the end of the day, as consumers, we are well aware that our data is being captured and we are willing for that to be so as long as the data is utilized to improve customer experiences. If I’ve just opted out of shoes in your custome preference center and then get an advertisement via email or web site experience pushing shoes, I quickly recognize you are not using the data you are collectig on me. At least not for personalization. So what are you doing with it? How can you build one cohesive personalized marketing journey instead of a series of disjointed interactions? First, let’s define personalized marketing and then cover some do’s and don’ts for fostering long-term customer relationships. What is Personalized Marketing? Personalized marketing ditches the one-size-fits-all approach, using data to tailor messages and offerings to individual customers. This can range from including a customer’s name in an email, to recommending products based on past purchases, to tailoring customer conversations with AI-powered chatbots. Done right, it fosters loyalty and boosts revenue. Done wrong, it becomes annoying and intrusive. Personalized Marketing in Practice Personalization continues to evolve, with more than half of marketers now adopting a lifecycle approach. They target potential customers with awareness campaigns and nurture existing ones with product support and loyalty programs. Marketers engage customers across an average of 10 channels, which is what customers expect. However, accessing up-to-date data across all channels can be challenging. Just like any relationship, personalized marketing requires effort to succeed. Companies must responsibly collect and analyze customer data, translate it into clear audience segments, and share it across departments to create a connected experience. Every interaction, big or small, can make or break a relationship. Maintaining personalization also requires constant monitoring and adaptation, a challenge for businesses with limited resources. Real-time data driven marketing is powerful. Large enterprises often have more data and the infrastructure to execute complex strategies, while small businesses may rely on simpler tactics. The core idea remains the same — understanding your audience and tailoring your marketing to resonate with them. But, rushing things or being overly clingy can lead to disaster. The Do’s and Dont’s of Personalized Marketing Imagine getting served irrelevant ads or recommendations for something you already bought. Perhaps even at a better price than you paid. Building trust with your audience is key to avoiding this. Turn your relationship from doomed to devoted with these tips: Personalized Marketing in Action The honeymoon stage is blissful in relationships as well as consumer interactions, but it’s the next phase that makes or breaks the relationship. Here’s how personalized marketing done right can keep your customers coming back for more. Example: National Time Outside (NTO) NTO, a fictional outdoor apparel retailer, faced stagnant conversion rates. They knew personalization was key but needed to cater to a diverse customer base. Here’s how they tackled the problem: By delivering personalized shopping experiences, NTO saw a significant increase in conversion rates. Waterfall segmentation helped prioritize various audience subsets, retain loyal customers, and avoid oversaturation of promotions. Customers received offers and communications that were highly targeted to their interests. Tent campers weren’t receiving ads for RV accessories, and bikers weren’t receiving communications for horseback riding. Example: Salesforce At Salesforce, they use their own product, Data Cloud, to cut the time between a lead expressing interest and it being sent to the correct sales rep from 25 minutes to 45 seconds. Processing over 20 million leads annually, Salesforce’s own system, now built on their automation platform Flow, unifies customer data from all sources, making it accessible and actionable across departments. Personalized marketing is a balancing act requiring resources and expertise. However, truly personalized marketing depends on shared, accessible, and actionable data across the entire business. Ditch the one-size-fits-all approach, invest in your data strategy, and watch your customer relationships blossom with relevant recommendations and experiences that keep them coming back for more. Personalization is about building relationships, and just like in love, every interaction counts. 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

July 1, 2024in Data, Enterprise, Marketing Automation, Salesforce, Salesforce Data Cloud, Salesforce Marketing Cloud, Salesforce Marketing Cloud Account Engagement (Pardot), Salesforce Optimization, Salesforce Personalization, Salesforce Sales Cloud, Technology

30Jun

Gearset’s Features Empower Salesforce Teams

Gearset, a leading Salesforce DevOps platform, is introducing a new suite of features aimed at accelerating and improving reliable release management for Salesforce teams. Gearset’s Features Empower Salesforce Teams. These enhancements, including Archiving, expanded Compare and Deploy capabilities, and Flow Navigator, address critical user feedback and deliver tools for optimizing data and enhancing visibility throughout the DevOps lifecycle. According to Matt Dickens, CPO and co-founder of Gearset, effective DevOps strategies rely on accurate and consistent data to deploy applications at the pace of innovation. The latest features empower teams to manage and apply relevant data in real-time, supporting organizations in navigating continuous changes to drive business growth on Salesforce confidently. Gearset Archiving provides organizations with control over Salesforce data storage by consolidating backup, sandbox seeding, and monitoring solutions into a unified platform. By eliminating outdated data from Salesforce orgs, enterprises can reduce storage costs and prevent performance degradation. Key benefits of Archiving include: Dickens explains that Gearset Archiving allows teams to safely store obsolete or legacy data off-platform while maintaining accessibility for future use, without impacting org performance. Maintaining clean and consistent metadata across the organization is crucial for Gearset. Recognizing limitations in Salesforce deployment tools, Gearset’s enhanced Compare and Deploy capability now enables DevOps teams to quickly analyze and compare metadata, facilitating efficient issue identification and resolution during deployments. This update streamlines operations, ensuring faster delivery of business-critical functionality to maximize ROI. Gearset’s Flow Navigator tool introduces visual comparison capabilities for Salesforce deployments, addressing challenges with Flow versioning and enhancing transparency in deployment processes. By presenting flows in their native Salesforce format, Flow Navigator enables teams to better manage deployments and mitigate potential conflicts. Dickens emphasizes that Gearset remains committed to user-driven innovation, aiming to continuously address Salesforce challenges and deliver solutions that save time, reduce stress, and improve efficiency for all customers. In summary, Gearset’s latest release underscores its dedication to empowering Salesforce teams with robust tools tailored to enhance efficiency and reliability across the DevOps lifecycle. 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 30, 2024in Data, Enterprise, Salesforce

20Jun

Agentic AI is Here

Embracing the Era of Agentic AI: Redefining Autonomous Systems A new paradigm in artificial intelligence, known as “Agentic Artificial Intelligence,” is poised to revolutionize the capabilities of the known autonomous universe. This cutting-edge technology represents a significant leap forward in AI-driven decision-making and action, promising transformative impacts across various industries including healthcare, manufacturing, IT, finance, marketing, and HR. Agents are the way to go! There is no two ways about this. Looking into the progression of the Large Language Model based applications since last year, its not hard to see that the Agentic Process (agents as reusable, specific and dedicated single unit of work) — would be the way to build Gen AI applications. What is Agentic AI? Agentic Artificial Intelligence marks a departure from traditional AI models that primarily focus on passive observation and analysis. Unlike its predecessors, which often require human intervention to execute tasks, Agentic AI systems possess the autonomy to initiate actions independently based on their assessments. This allows them to navigate much more complex environments and undertake tasks with a level of initiative and adaptability previously unseen. At least outside of sci-fy movies. Real-World Applications of Agentic Artificial Intelligence Healthcare In healthcare, Agentic AI systems are transforming patient care. These systems autonomously monitor vital signs, administer medication, and assist in surgical procedures with unparalleled precision. By augmenting healthcare professionals’ capabilities, these AI-driven agents enhance patient outcomes and streamline care processes. Augmenting is the key word, here. Manufacturing and Logistics In manufacturing and logistics, Agentic AI optimizes operations and boosts efficiency. Intelligent agents handle predictive maintenance of machinery, autonomous inventory management, and robotic assembly. Leveraging advanced algorithms and sensor technologies, these systems anticipate issues, coordinate complex workflows, and adapt to real-time production demands, driving a shift towards fully autonomous production environments. Customer Service Within enterprises, AI agents are revolutionizing business operations across various departments. In customer service, AI-powered chatbots with Agentic Artificial Intelligence capabilities engage with customers in natural language, providing personalized assistance and resolving queries efficiently. This enhances customer satisfaction and allows human agents to focus on more complex tasks. Marketing and Sales Agentic Artificial Intelligence empowers marketing and sales teams to analyze vast datasets, identify trends, and personalize campaigns with unprecedented precision. By understanding customer behavior and preferences at a granular level, AI agents optimize advertising strategies, maximize conversion rates, and drive revenue growth. Finance and Accounting In finance and accounting, Agentic AI streamlines processes like invoice processing, fraud detection, and risk management. These AI-driven agents analyze financial data in real time, flag anomalies, and provide insights that enable faster, more informed decision-making, thereby improving operational efficiency. Ethical Considerations of Agentic Artificial Intelligence The rise of Agentic AI also brings significant ethical and societal challenges. Concerns about data privacy, algorithmic bias, and job displacement necessitate robust regulation and ethical frameworks to ensure responsible and equitable deployment of AI technologies. Navigating the Future with Agentic AI The advent of Agentic AI ushers in a new era of autonomy and innovation in artificial intelligence. As these intelligent agents permeate various facets of our lives and enterprises, they present both challenges and opportunities. To navigate this new world, we must approach it with foresight, responsibility, and a commitment to harnessing technology for the betterment of humanity. 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 20, 2024in Artificial Intelligence, Data, Enterprise, Marketing Automation, Salesforce, Salesforce Health and Life Sciences Solutions, Salesforce Hospitality Travel and Transportation, Salesforce Public Sector Solutions, Salesforce Sales Cloud, Technology

11Jun

Salesforce Cross-Channel Marketing

As technology evolves, cross-channel marketing will become even more sophisticated, leveraging artificial intelligence, machine learning, and predictive analytics to deliver hyper-personalized and proactive customer experiences. Businesses that adopt this approach will stay ahead of the curve, fostering stronger customer relationships and achieving long-term success.

June 11, 2024in Agentforce Platform, AI Tools, Artificial Intelligence, Data, Einstein 1 Platform, Einstein Insights, Enterprise, Generative AI, Google, Google Analytics, Hyperforce, Life Sciences Cloud, Marketing Automation, Mulesoft, Public Sector Solutions, Salesforce, Salesforce Commerce Cloud, Salesforce CPQ, Salesforce Data Cloud, Salesforce Development Services, Salesforce Einstein, Salesforce Experience Cloud, Salesforce Financial Services Solutions, Salesforce for Nonprofits, Salesforce Health and Life Sciences Solutions, Salesforce Health Cloud, Salesforce Hospitality Travel and Transportation, Salesforce Implementation Services, Salesforce Managed Services, Salesforce Manufacturing Automotive Energy, Salesforce Marketing Automation, Salesforce Marketing Cloud, Salesforce Marketing Cloud Account Engagement (Pardot), Salesforce Nonprofit Cloud, Salesforce Optimization, Salesforce Personalization, Salesforce Public Sector Solutions, Salesforce Sales Cloud, Salesforce Service Cloud, Salesforce Shield, Salesforce Slack, Salesforce Success Stories, Salesforce Tableau, Snowflake, Technology

04Jun

Salesforce with SharpLaunch

Supercharge Your Salesforce with SharpLaunch Streamline Your Sales ProcessIntegrate Salesforce with SharpLaunch to simplify and automate your commercial real estate (CRE) operations. Key Features Push Leads Directly to SalesforceSay goodbye to manual data entry. Automatically transfer valuable leads from SharpLaunch to Salesforce and focus on closing deals. Continuously Sync DataKeep your CRM updated effortlessly. Lead data captured in SharpLaunch syncs automatically to your Salesforce fields, ensuring accuracy and up-to-date information. Boost ProductivityBy connecting SharpLaunch with Salesforce, you can streamline workflows, reduce administrative tasks, and accelerate your sales cycle. Why SharpLaunch Stands Out Fully Customizable Designs Tailor every digital asset to match your brand.From property websites to interactive maps, SharpLaunch delivers personalized, client-facing solutions that elevate your brokerage’s presence. Enterprise-Level Integrations Unify your tech stack seamlessly.SharpLaunch integrates with any tools you’re already using, fitting into your workflows to maximize efficiency with minimal effort. World-Class Service Enjoy dedicated, personalized support.Skip the chatbots and ticket queues. Work directly with your Customer Success Manager from setup to success. Complete Data Ownership Keep control of your information.With SharpLaunch, you retain full ownership of your data, ensuring sensitive client and property information stays secure and private. Ready to Transform Your Salesforce Experience? Connect SharpLaunch to Salesforce today and empower your sales team to close deals faster while maintaining full control over your data and brand identity. 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 4, 2024in Data, Enterprise, Salesforce

24May

The Growing Role of AI in Cloud Management

AI technologies are redefining cloud management by automating IT systems, improving security, optimizing cloud costs, enhancing data management, and streamlining the provisioning of AI services across complex cloud ecosystems. With the surging demand for AI, its ability to address technological complexities makes a unified cloud management strategy indispensable for IT teams. Cloud and security platforms have steadily integrated AI and machine learning to support increasingly autonomous IT operations. The rapid rise of generative AI (GenAI) has further spotlighted these AI capabilities, prompting vendors to prioritize their development and implementation. Adnan Masood, Chief AI Architect at UST, highlights the transformative potential of AI-driven cloud management, emphasizing its ability to oversee vast data centers hosting millions of applications and services with minimal human input. “AI automates tasks such as provisioning, scaling, cost management, monitoring, and data migration,” Masood explains, showcasing its wide-ranging impact. From Reactive to Proactive Cloud Management Traditionally, CloudOps relied heavily on manual intervention and expertise. AI has shifted this paradigm, introducing automation, predictive analytics, and intelligent decision-making. This evolution enables enterprises to transition from reactive, manual management to proactive, self-optimizing cloud environments. Masood underscores that this shift allows cloud systems to self-manage and optimize with minimal human oversight. However, organizations must navigate challenges, including complex data integration, real-time processing limitations, and model accuracy concerns. Business hurdles like implementation costs, uncertain ROI, and maintaining the right balance between AI automation and human oversight also require careful evaluation. AI’s Transformation of Cloud Computing AI has reshaped cloud management into a more proactive and efficient process. Key applications include: “AI enhances efficiency, scalability, and flexibility for IT teams,” says Agustín Huerta, SVP of Digital Innovation at Globant. He views AI as a pivotal enabler of automation and optimization, helping businesses adapt to rapidly changing environments. AI also automates repetitive tasks such as provisioning, performance monitoring, and cost management. More importantly, it strengthens security across cloud infrastructure by detecting misconfigurations, vulnerabilities, and malicious activities. Nick Kramer of SSA & Company highlights how AI-powered natural language interfaces simplify cloud management, transforming it from a technical challenge to a logical one. With conversational AI, business users can manage cloud operations more efficiently, accelerating problem resolution. AI-Enabled Cloud Management Tools Ryan Mallory, COO at Flexential, categorizes AI-powered cloud tools into: The Rise of Self-Healing Cloud Systems AI enables cloud systems to detect, resolve, and optimize issues with minimal human intervention. For instance, AI can identify system failures and trigger automatic remediation, such as restarting services or reallocating resources. Over time, machine learning enhances these systems’ accuracy and reliability. Key Applications of AI in Cloud Management AI’s widespread applications in cloud computing include: Benefits of AI in Cloud Management AI transforms cloud management by enabling autonomous systems capable of 24/7 monitoring, self-healing, and optimization. This boosts system reliability, reduces downtime, and provides businesses with deeper analytical insights. Chris Vogel from S-RM emphasizes that AI’s analytical capabilities go beyond automation, driving strategic business decisions and delivering measurable value. Challenges of AI in Cloud Management Despite its advantages, AI adoption in cloud management presents challenges, including: AI’s Impact on IT Departments AI’s growing influence on cloud management introduces new responsibilities for IT teams, including managing unauthorized AI systems, ensuring data security, and maintaining high-quality data for AI applications. IT departments must provide enterprise-grade AI solutions that are private, governed, and efficient while balancing the costs and benefits of AI integration. Future Trends in AI-Driven Cloud Management Experts anticipate that AI will revolutionize cloud management, much like cloud computing reshaped IT a decade ago. Prasad Sankaran from Cognizant predicts that organizations investing in AI for cloud management will unlock opportunities for faster innovation, streamlined operations, and reduced technical debt. As AI continues to evolve, cloud environments will become increasingly autonomous, driving efficiency, scalability, and innovation across industries. Businesses embracing AI-driven cloud management will be well-positioned to adapt to the complexities of tomorrow’s IT 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

May 24, 2024in Data, Enterprise, Generative AI

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

09Apr

What is Salesforce Einstein 1?

The bold new future of enterprise AI requires a new type of platform. What is Salesforce Einstein 1? One platform that can handle terabytes of disconnected data, gives you the freedom to choose your AI models, and connects directly into the flow of work, all while maintaining customer trust. The Einstein 1 Platform unifies your data, AI, CRM, development, and security into a single, comprehensive platform. It empowers IT, admins, and developers with an extensible AI platform, facilitating fast development of generative apps and automation. What is Salesforce Einstein 1 Einstein 1 has a mixture of artificial intelligence tools on the platform, and it kind of mirrors the way the core Salesforce platform is built, standardized and custom. We have out of the box AI features such as sales email generation in Sales Cloud, and service replies in Service Cloud. What is Einstein One? Einstein One seamlessly integrates our robust data platform with Data Cloud, offering a comprehensive AI and data-driven solution within our CRM service. As the leading comprehensive AI for CRM, Salesforce Einstein transforms the Customer Success Platform by incorporating a suite of integrated AI technologies, making it more intelligent and accessible to innovators worldwide. Introducing the Einstein One Platform The future of enterprise AI demands a groundbreaking platform capable of managing terabytes of diverse data, providing the flexibility to select AI models, and seamlessly integrating into daily workflows while maintaining customer trust. The Einstein One Platform consolidates data, AI, CRM, development, and security into a singular, comprehensive platform. It empowers IT, administrators, and developers with an extensible AI platform, facilitating rapid development of generative apps and automation. Salesforce has made significant investments in enhancing the Einstein One platform by introducing two prompt engineering features – a testing center and prompt engineering suggestions, demonstrating the company’s commitment to advancing AI capabilities. Data-driven and AI-driven customer experiences are vital in constructing Data Cloud. Salesforce’s predictive AI, Einstein, has been operational since 2016, conducting over a trillion predictions per week. The company continuously evolves its capabilities, introducing generative AI products like Einstein GPT, discussed at Dreamforce [2023]. ‘Customer 360′ now represents Salesforce customers’ ability to transform into customer-centric entities, delivering integrated and cohesive experiences across sales, marketing, service, and commerce. Leveraging Data Cloud, structured and unstructured engagement data comes alive, offering a personalized perspective of customer interactions. Einstein is accessible through various Salesforce products, including Sales Cloud, Service Cloud, Marketing Cloud, Salesforce Platform, Analytics Cloud, and Community Cloud. What is the Einstein One platform? Salesforce’s Einstein One is a transformative platform that securely integrates data, connects multiple Salesforce products, and empowers customer-centric businesses to create AI-driven apps, revolutionizing CRM interactions. What applications are connected with the Einstein One platform? Einstein Trust Layer: Ensuring the security of generative AI applications within Salesforce, this application acts as a safeguard for data, preventing unauthorized access. Data Cloud: Unifying structured and unstructured data, Data Cloud completes the customer 360 profile, integrating seamlessly with the Einstein One platform and making data actionable. Einstein Copilot: A built-in conversational assistant, Einstein Copilot enables users to ask questions in Natural Language and receive intelligent answers, actions, and more. Copilot Studio: An essential component of Einstein One, Copilot Studio manages Einstein One and Einstein Copilot, allowing businesses to control user access and use generative AI in their workspace. Prompt Builder, Skill Builder, Model Builder: Tools within Copilot Studio, these components empower businesses to create trusted AI prompts, add skills to user access, and choose AI models. What is Data Cloud for Einstein One? Data Cloud, combined with the Einstein Trust Layer, provides secure access to a unified data repository, forming a reliable resource for complete customer profiles and supporting AI assistants. Data Cloud facilitates valuable visualizations through reports, dashboards, and tools like Tableau, offering insights to enhance understanding of customers and business operations. What will Einstein One do for businesses? Einstein One aims to: Increase productivity Reduce operational costs Enhance the delivery of exceptional customer experiences The debut of Einstein One marks a significant stride for Salesforce and businesses, offering a secure path to boost productivity through AI technologies, ensuring continuous access to cutting-edge technologies for businesses. Where can generative AI impact businesses today? Generative AI has the potential to impact businesses by enhancing repetitive processes, making them faster. Exploring text-based processes, such as repetitive emails or form filling, is a great starting point for businesses looking to enhance capabilities. What can generative AI do for sales, service, field service teams? Generative AI can positively impact teams by automating processes, offering intelligent insights, and improving overall efficiency. Specific use cases for generative AI in sales, service, and field service teams can be explored through Salesforce’s 101 video series. What does Einstein One Tableau do? Einstein One Data Cloud, formerly known as Genie, serves as a metadata management tool connecting data from various sources. It makes data usable for AI and analysis, integrating with Einstein One, Tableau, and Salesforce’s CRM applications. Is Salesforce Einstein the same as Tableau? Formerly known as Einstein Analytics, Tableau CRM is Salesforce’s premium analytic platform, offering a powerful way to explore data, especially for current Salesforce users. Salesforce has renamed Einstein Analytics to Tableau CRM, reflecting its commitment to empowering users to make better decisions faster. In essence, the Einstein One platform combines Salesforce Data Cloud, Einstein Copilot, and the Einstein Trust Layer, providing a comprehensive solution for secure and connected data, facilitating generative AI on a comprehensive platform. Salesforce’s Einstein One Platform & the Data-Driven Revolution This innovation has the potential to revolutionize the way businesses interact with their customers. In this insight, we delve deeper into this transformative development, offering valuable insights, considerations for implementation, and the indispensable expertise of Tectonic as a data-oriented technology partner. Salesforce Data Cloud and Einstein AI are now seamlessly integrated into the Einstein One Platform. This integration empowers companies to effortlessly connect their diverse data sources, enabling the creation of AI-driven applications with minimal coding effort. Moreover, it forges a cohesive view of your data across

April 9, 2024in Artificial Intelligence, Data, Einstein 1 Platform, Einstein Insights, Enterprise, Generative AI, Google, Mulesoft, Salesforce, Salesforce Data Cloud, Salesforce Einstein, Salesforce Sales Cloud, Technology

27Mar

Salesforce Bot Planning

Careful Planning: Key to an Effective Bot and Happy Customers When building your bot, thoughtful planning is essential to ensure it efficiently serves customers and meets their needs. Supported Editions Technical Planning Voice and Tone Planning Careful planning in these areas will help ensure your Einstein Bot delivers a smooth, efficient experience for your customers. 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 27, 2024in Enterprise

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

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