LPI Archives - gettectonic.com

15Sep

More Cool AI Tools

In today’s fast-paced digital world, AI is no longer a luxury but a necessity for maximizing work efficiency. With the right AI tools, businesses and individuals can automate tasks, enhance creativity, improve customer engagement, and streamline operations. Here’s a breakdown of the Top 21 AI tools you should explore to elevate your productivity and stay ahead of the curve! 1️⃣ Video CreationSynthesiaWebsite: SynthesiaAn AI video creation tool that lets you generate high-quality videos from text. Ideal for creating marketing, training, and explainer videos quickly and professionally. VeedWebsite: VeedVeed helps you create, edit, and share professional videos with ease, incorporating AI to streamline the process of adding captions, effects, and edits. SubmagicWebsite: SubmagicSubmagic uses AI to automatically generate subtitles for videos, improving accessibility and viewer engagement. 2️⃣ Customer Relationship Management (CRM)HubSpotWebsite: HubSpotHubSpot’s AI-powered CRM system streamlines customer interactions, helping businesses improve customer satisfaction, sales, and retention. FreshworksWebsite: FreshworksThis tool offers AI-driven solutions for customer service, sales, and marketing, helping companies improve relationships and resolve issues faster. HighLevelWebsite: HighLevelHighLevel integrates AI to improve customer management processes, including lead nurturing and campaign tracking. 3️⃣ Website Design and BrandingWizard AIWebsite: Wizard AIA design tool that helps you create stunning visuals and branding for your website using AI. Whether you’re looking to revamp your website or create a logo, Wizard AI makes it simple. LookaWebsite: LookaLooka offers AI-powered logo creation, making it easy for businesses and startups to design professional logos in just minutes. TurbologoWebsite: TurbologoTurbologo is another intuitive logo maker that uses AI to generate custom logo designs based on your business type and preferences. 4️⃣ Project Management and CollaborationMondayWebsite: MondayAn all-in-one project management platform that uses AI to automate workflows, track progress, and enhance team collaboration. ClickUpWebsite: ClickUpClickUp leverages AI to provide real-time project insights, task automation, and comprehensive team collaboration tools for businesses of all sizes. Golf AIWebsite: Golf AIGolf AI helps golfers refine their game with AI insights, but its technology can also be applied in the professional world, improving focus, strategy, and decision-making in various projects. 5️⃣ Marketing and Lead GenerationPipedriveWebsite: PipedriveA popular tool that helps businesses track leads and automate marketing workflows, making lead generation more efficient and scalable. Apollo AIWebsite: Apollo AIApollo enables businesses to automate sales and lead generation by using AI to find and reach potential customers, helping you connect with decision-makers faster. EnvizWebsite: EnvizThis platform uses AI to provide intelligent data analysis and insights, allowing businesses to fine-tune their marketing strategies. 6️⃣ AI for Audio and VoiceMurf AIWebsite: Murf AIAn AI voice generator that converts text into lifelike voiceovers. Ideal for creators, marketers, and educators who want to generate high-quality audio content. SpeechifyWebsite: SpeechifySpeechify turns written text into audio, helping users consume content faster. It’s perfect for multitaskers and individuals with reading disabilities. ElevenLabsWebsite: ElevenLabsElevenLabs offers state-of-the-art AI technology to generate and clone natural-sounding voices, ideal for podcasts, audiobooks, and interactive audio experiences. 🌐 Explore More AI-Powered ToolsUnlock your productivity potential with these top AI tools. Whether you’re managing projects, creating content, or building customer relationships, AI is your key to efficiency. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

September 15, 2024in AI Tools, Data, Technology

13Sep

IntraEdge Higher Education

PHOENIX–(BUSINESS WIRE)–IntraEdge, Inc., a leading global technology products and services provider, recently announced its expanded investment in itsHigher Education division with the addition of new leadership to bolster their Salesforce service offerings. The new leaders each possess over 20 years of higher education experience and have a proven track record of building innovative and high performing consulting practices. “Our team has a proven track record of success in helping higher education institutions achieve their goals. We look forward to partnering with colleges and universities to leverage the power of Salesforce to improve student outcomes and operational efficiency.” The Higher Education division leadership team consists of Vince Salvato, Todd Edge, and Ryan Clemens. Salvato, who will be leading the division, is a recognized pioneer in Salesforce implementations for higher education. He brings a wealth of experience from his years working with higher education leaders, Salesforce, and ISV Partners. Edge and Clemens have a long history implementing Salesforce and other technologies for higher education leveraging global capabilities to assemble well balanced implementation teams. Together, this team boasts a proven track record of serving over 150 higher education institutions. Their collective history of successful Salesforce and technology implementations within higher education, coupled with IntraEdge’s 3,000+ global resources and complimentary product and service offerings, positions IntraEdge to deliver exceptional solutions. “We are thrilled to welcome Vince, Ryan, and Todd to the IntraEdge team,” said Kal Somani, CEO of IntraEdge. “Their combined experience and knowledge of the higher education landscape make them invaluable assets as we expand our footprint in this industry. By leveraging Salesforce’s powerful platform with IntraEdge’s full breadth of technology capabilities, we are confident in our ability to deliver exceptional solutions that address the unique challenges and opportunities facing higher education institutions.” IntraEdge redefines the typical implementation approach by delivering accelerated, cost-effective, and highly successful implementations. The company’s proven methodology and global delivery capabilities, combined with a team of seasoned higher education experts, will enable institutions to maximize the value of Salesforce while minimizing disruption to campus operations. IntraEdge’s Higher Education division offers a comprehensive suite of Salesforce-based solutions tailored to the specific needs of colleges and universities. With implementation, consulting, and value-add products and services, institutions can maximize the value of their Salesforce investment, including but not limited to Data Integration and Visualization, Digital Experience Strategy, Digital Content Strategy and Development, Managed and Capacity Services, AI Governance and Compliance Software. “We are excited to join IntraEdge and be a part of a world-class higher education practice,” said Salvato, Senior Vice President of Higher Education at IntraEdge. “Our team has a proven track record of success in helping higher education institutions achieve their goals. We look forward to partnering with colleges and universities to leverage the power of Salesforce to improve student outcomes and operational efficiency.” IntraEdge is proud to be a trusted partner to higher education institutions across North America. Our company is committed to delivering exceptional results and exceeding client expectations. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

September 13, 2024in Salesforce

13Sep

Create Delightful Experiences

Ever had one of those unexpected moments when you reach out to customer service to resolve an issue, and by the end of the conversation, you’ve ended up purchasing something new—and actually feel good about it? Salesforce can help you Create Delightful Experiences. It’s those delightful experiences—when a company truly understands you—that make all the difference. Yet, far too often, these moments are the exception rather than the rule. Why is that? Despite having access to mountains of data from every click, call, and transaction, many companies still fail to create the seamless, personalized experiences that customers expect. In fact, 80% of customers believe their experiences should be better, given the wealth of data available. However, many organizations remain trapped in silos, with marketing, sales, and service teams working in isolation. The data exists, but it’s not being utilized effectively. Siloed data, un-unified data, and restricted access data make your agents seem less emphathetic. Customers expect them to know everything about them there is to know. For CMOs, this presents both a challenge and an opportunity. Positioned at the intersection of every customer touchpoint, many find themselves navigating disjointed strategies from different departments. But what if we could turn the tide? What if every interaction across any channel—whether in marketing, sales, or service—felt like one continuous conversation? From Silos to Synergy: Maximizing Every Customer Interaction The reality is that customers don’t recognize the internal barriers we’ve erected. They don’t care about the silos of marketing, sales, and service; to them, it’s one relationship. What matters most to them is being understood and treated consistently, regardless of whom they are engaging with. Create Delightful Experiences This is where a more unified approach comes into play. It’s not about collecting more data—we already have plenty of that. Instead, it’s about piecing together a puzzle where each interaction reveals a bigger picture. By doing so, we can anticipate customer needs and respond in ways that feel personal and relevant. Consider Fisher & Paykel. By integrating data from their online stores and marketing efforts, they gain a clearer understanding of their customers’ buying habits. Whether someone is a one-time buyer or a frequent shopper, they can tailor the experience accordingly. For instance, if a customer purchases a new fridge, rather than suggesting another fridge during their next visit—as if they were unaware of the previous purchase—the system might recommend relevant accessories like water filters. Plus, with connected device data, they can send timely reminders when it’s time for a replacement part. Now, picture a customer calling in with a service issue. Instead of merely resolving the problem, the representative is empowered by AI to suggest the next best action—perhaps offering a discount on a recently viewed product or an option for self-service. By leveraging AI insights from browsing behavior and purchase history, service teams can present timely offers that build trust and drive future purchases. This transformation turns service interactions into opportunities for building loyalty and generating revenue while ensuring customers feel valued and understood. With customer acquisition costs rising by 60% over the last five years, strategies like upselling, cross-selling, and referral marketing can yield new revenue at a fraction of the cost of traditional channels. The Technology That Ties It All Together None of this is feasible without the right technology. To craft these interconnected experiences, we need systems that consolidate data from every corner of the business. Salesforce’s Data Cloud accomplishes this by centralizing customer data and layering Einstein AI on top to generate meaningful, actionable insights. If your marketing chops are your muscles, your Salesforce org is your tool box. Gone are the days of guessing what customers need—you’ll know exactly when and how to engage them, transforming transactional interactions into those delightful moments that keep customers coming back. Take Air India as an example. Faced with managing over 550,000 monthly service cases within a decentralized system, they utilized Salesforce’s Data Cloud to unify customer data from various sources, providing service teams with a 360-degree view of every passenger. With AI-driven recommendations from Einstein AI, Air India’s teams can offer personalized services, such as seat upgrades during delays or tailored travel deals based on past trips. This approach not only enhances customer satisfaction but also streamlines operations and fosters business growth. The Strategic Imperative for CMOs So, what’s the key takeaway for marketers? We must think beyond our traditional roles and collaborate across the entire customer journey. It’s crucial to advocate for breaking down silos, aligning teams, and integrating data throughout our organizations. However, let’s be realistic: this is easier said than done. Internal politics can complicate efforts to unify departments, with leaders often fixated on their own priorities. The key lies in fostering a spirit of collaboration, not competition—demonstrating to other leaders how a unified approach benefits everyone. By working closely with other departments, marketing can evolve from merely a function into a pivotal part of the broader business strategy, helping to drive consistent customer experiences, increased revenue, and long-term loyalty. The future of marketing isn’t about doing more; it’s about being smarter. It’s about crafting personalized, meaningful experiences that reach the right customers at precisely the right moment, transforming every touchpoint into an opportunity to build lasting relationships. Unified data is the cornerstone of achieving this goal. Ultimately, the companies that understand their customers best will thrive—and that journey begins with us. Create Delightful Experiences with technology and AI for your customers. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are

September 13, 2024in Data, Salesforce, Salesforce Marketing Automation, Technology

12Sep

ChatGPT Memory Announced

We’re testing memory with ChatGPT to make your experience more seamless by saving important details across chats, so you won’t have to repeat yourself. This feature helps make future conversations more helpful. You’re fully in control of ChatGPT’s memory. You can ask it to remember something, view what it recalls, and even delete specific memories either conversationally or through settings. Memory can also be turned off completely. This week, we’re rolling out memory to a small group of free and Plus users to gather feedback. Broader rollout plans will be shared soon. How Memory Works As you interact with ChatGPT, it can remember key details from your conversations, improving the quality of future responses. For instance: You’re In Control You can turn memory off at any time (Settings > Personalization > Memory). With memory off, ChatGPT won’t store or use any memories. To delete specific memories, simply ask ChatGPT to forget or manage them in settings. Memory works across interactions, meaning deleting a chat doesn’t erase its associated memory—you’ll need to delete the memory itself. ChatGPT may use the content you provide, including memories, to improve its models for everyone, unless you opt out through Data Controls. Note that content from Team and Enterprise accounts won’t be used to train models. Temporary Chat for No Memory If you’d prefer a conversation without memory, use temporary chat. These conversations won’t appear in history, won’t store memories, and won’t contribute to model training. Custom Instructions and Memory Custom Instructions let you guide ChatGPT on how to respond, while memory captures information shared in conversations. This combination allows ChatGPT to become more personalized and responsive over time. Privacy and Safety Standards We’re evolving our privacy and safety protocols to address memory’s impact. ChatGPT is designed to avoid remembering sensitive information, like health data, unless explicitly requested. Memory for Team and Enterprise Users For Team and Enterprise users, memory helps increase efficiency by learning individual preferences and reducing the need for repetitive instructions. For example, ChatGPT can remember your preferred tone and structure for content or your preferred coding languages for programming tasks. Memory in Team and Enterprise accounts remains secure and excluded from model training, with full control over how and when memories are used. Account owners can disable memory for the organization at any time. Memory for GPTs GPTs, too, will have distinct memories. Builders can choose to enable memory, and each GPT will store its own memories. For example, a book recommendation GPT can remember your favorite genres for tailored suggestions. To interact with memory-enabled GPTs, you’ll need memory on. Each GPT will have its own separate memory, so details shared with ChatGPT won’t carry over unless re-entered. Memory is now available to ChatGPT Free, Plus, Team, and Enterprise users. Based on user feedback, ChatGPT will notify you when a memory is updated, and you can easily review or delete those updates by accessing the “Manage memories” option in settings. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

September 12, 2024in Salesforce

12Sep

Introhive Relationship Intelligence Platform

FREDERICTON, New Brunswick, September 12, 2024 – Introhive, the leading Relationship Intelligence platform, today announced that it is enabling its market leading, AI-Powered Relationship Intelligence for Salesforce Data Cloud empowering clients to understand in real-time the Relationship Intelligence associated with sales Opportunities Bringing Salesforce Data Cloud and AI together for enhanced insights Introhive’s integration brings the Customer 360 vision to life by providing a unified and enriched view of contact and relationship data, enabling organizations to derive advanced insights by overlaying their existing sales opportunities. As a leader in relationship intelligence and CRM data automation, Introhive provides unmatched data accuracy, ensuring reliable insights and actions from Data Cloud applications and AI tools like Salesforce Einstein Copilot. By transforming relationship data into actionable insights, organizations are empowered to make critical business decisions with confidence and turn connections into tangible business value. Enhanced decision-making with Salesforce Data Cloud “Our Relationship Intelligence capability for Salesforce Data Cloud enhances the solution we offer our clients and elevates Introhive’s role as a top-tier Data Ecosystem Partner on the Salesforce platform,” said Lee Blakemore, CEO of Introhive. “Clients will now enjoy all the benefits of Introhive’s Data Share, enhanced by Salesforce’s powerful platform, ensuring real-time access to trusted relationship data. This combination empowers firms to make critical business decisions with confidence and precision.” Lightning Web Components boost Salesforce Data Cloud integration To further strengthen its Salesforce offering, Introhive announced the launch of Lightning Web Components that seamlessly integrate powerful relationship intelligence in users flow of work. This strategic addition elevates relationship intelligence in Salesforce by making insights more contextual, accessible, and actionable. The components dynamically surface relevant relationship data, top contacts, and interaction history directly within Salesforce pages. This allows users to take proactive steps in managing their relationships, resulting in improved productivity, enhanced client retention, and accelerated revenue growth – all without disrupting existing workflows. Addressing data challenges with Salesforce Data Cloud integration In today’s data-driven business environment, organizations rely heavily on analytics for decision-making, recognizing that the quality and timeliness of information are crucial for effective data-driven strategies. Yet, siloed data, information overload, and constant context switching often lead to missed critical relationship insights, impeding businesses from fully leveraging their relationship capital to drive growth, retention, and informed business decisions. Unlocking the full potential of relationship data with Salesforce Data Cloud The addition of Introhive’s lightning web components and Data Cloud integration address these challenges by transforming how businesses manage and activate their relationship data to fuel business insights and inform decision making. This includes identifying open opportunities based on relationship strength and leveraging the best connected individuals to target accounts for strategic decision making and warm introductions. “With our integration with Salesforce Data Cloud, we’re tackling a major challenge businesses face: fully unlocking the value of their relationship data,” said Leyla Samiee, Chief Product Officer at Introhive. “Our goal is to eliminate data silos that hinder organizations from obtaining crucial relationship insights. By consistently delivering clean, reliable data, we’ve been leading this charge. This new partnership takes our efforts further by enabling smooth integration of data and interactions across various systems that impact our clients’ goals. Our Lightning Web Components, now enhanced with machine intelligence, provide real-time, actionable insights more efficiently. Through our collaboration with Salesforce Data Cloud, these services are integrated with Salesforce’s interactive platforms, offering improved visibility into relationship strength and key connections. This empowers organizations to strategically engage with their most valuable accounts, fostering growth and maximizing their relationship capital.” Salesforce Data Cloud empowers growth across industries As Salesforce maintains its position as the global CRM leader, Introhive’s enhanced offering strategically empowers organizations across industries such as accounting, consulting, legal and commercial real estate, to fully capitalize on their collective relationship network to drive their business forward. For more information about Introhive’s Data Cloud integration and Lightning Web Components, visit our website. About Introhive Introhive is the leading Relationship Intelligence Platform that empowers professional services firms to dismantle silos, fuel their CRM, and activate relationship data to foster collaboration and increase revenue. Trusted by world-renowned brands, Introhive supports over 750,000 users in 90+ countries. With offices in the US, Canada, and the UK, we’re committed to helping businesses optimize their revenue opportunities. Learn more at www.introhive.com. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

September 12, 2024in Salesforce

09Sep

Army of AI Bots

Salesforce Inc. has announced a significant upgrade with the launch of Industries AI, a new automation platform designed to handle a wide range of time-consuming tasks, enhancing productivity across various sectors. We are NOT advocating that the next war will be fought with AI Bots. We aren’t even suggesting there is anything negative about these bots. However, if the next war were to be information and data based, who knows. Industries AI will be integrated into all 15 of Salesforce’s cloud platforms, including Sales Cloud, Data Cloud, Service Cloud, Commerce Cloud, and Marketing Cloud. This expansive solution is capable of managing over 100 common tasks, from matching patients with clinical trials and providing maintenance alerts for vehicles and machinery, to streamlining recruitment processes and enhancing government services. The launch of Industries AI responds to findings from Salesforce’s Trends in AI for CRM Report, which indicated that over 75% of business leaders are concerned about missing out on AI advancements if they do not adopt the technology soon. With a 700% increase in urgency to implement AI over the past six months, many organizations struggle with the resources and expertise needed to develop and train AI models. Salesforce aims to address this by offering a ready-made framework for creating AI agents tailored to industry-specific needs, utilizing each customer’s proprietary data within the Salesforce platform. Industries AI will provide a foundation for quickly deploying autonomous agents, with setup times estimated at just a few minutes. To assist customers in leveraging AI automation, Salesforce has created use case libraries for each of its cloud platforms, featuring over 100 capabilities at launch. These capabilities span multiple industries: Salesforce will begin rolling out Industries AI capabilities in October 2024, with some features available by February 2025. The company plans to regularly update Industries AI with new capabilities as part of its annual Salesforce releases. Jeff Amann, executive vice president and general manager of Salesforce Industries, emphasized that this innovation aims to make powerful AI accessible to all enterprises, regardless of size or budget. “Organizations can now easily start with AI solutions tailored to their specific challenges, enhancing efficiency and productivity across various functions,” he said. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

September 9, 2024in Generative AI

09Sep

AI-Powered Field Service

Salesforce has introduced new AI-powered field service capabilities designed to streamline operations for dispatchers, technicians, and field service leaders. Leveraging the Salesforce platform and Data Cloud, these innovations aim to expedite time-consuming processes and enhance customer satisfaction by making field service operations more proactive and efficient. Why it matters: Field service teams currently spend only 32% of their time interacting with customers, with the remaining 68% consumed by administrative tasks like manually entering case notes. With 78% of field service workers in AI-enabled organizations reporting that AI helps save time, Salesforce’s new tools address these inefficiencies head-on. Key AI-driven innovations for Field Service: Availability: Paul Whitelam, GM & SVP of Salesforce Field Service, notes, “The future of field service lies in the seamless integration of AI, data, and human expertise. Our new capabilities set new standards for efficiency and service delivery.” Rudi Khoury, Chief Digital Officer at Fisher & Paykel, adds, “With Salesforce Field Service, we’re not just embracing AI and data-driven insights — we’re advancing into the future of field service, achieving unprecedented efficiency and exceptional service.” Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

September 9, 2024in Einstein Insights, Salesforce Development Services, Salesforce Manufacturing Automotive Energy, Salesforce Service Cloud

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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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

08Sep

AI in Performance Management

AI in Performance Management: Benefits and Use Cases AI is making its way into all aspects of the workplace, and performance management is no exception. While the technology can streamline performance reviews and enhance feedback quality, HR leaders should be mindful of potential drawbacks, such as impersonal or overly generic feedback. Here’s a look at how AI can be used in performance management, along with its advantages and some challenges to consider. 4 Benefits of Using AI in Performance Management AI can offer several advantages for companies in terms of improving employee feedback and overall performance. Here are four key benefits: 1. Faster Employee Feedback Creation AI can help managers draft initial feedback for employees, saving time and effort. By setting parameters like years in the role or specific job metrics, AI-generated feedback can be more accurate. However, managers should review and personalize the feedback to ensure it feels relevant and human. 2. Enhanced Feedback Quality AI tools can analyze performance review drafts, identifying issues like repetitive wording, biased language, or inappropriate tone. By refining the text, AI helps managers deliver more thoughtful and effective feedback. 3. Better Reporting and Dashboards AI can analyze performance data and generate reports or dashboards, providing senior leaders and HR teams with a clear overview of employee performance. This capability is especially useful for large companies with substantial data, helping decision-makers track progress and identify trends. 4. Boosted Employee Performance By simplifying the review process, AI can encourage managers to provide feedback more frequently. Regular, timely feedback keeps employees focused, motivated, and aligned with company goals, enhancing their development and overall experience. 4 Use Cases for AI in Performance Management AI’s role in performance management goes beyond feedback creation. Here are four specific ways AI can streamline the process: 1. Employee Data Analysis AI can aggregate and analyze various employee data sources—such as past performance reviews or internal communications—summarizing key insights for managers. This saves time spent on manual data gathering, though managers should still verify the data and focus on the most relevant information. 2. Generating Discussion Topics AI can generate discussion prompts for managers to use in one-on-one meetings with employees, such as future career goals or project challenges. While this saves time, managers should tailor the AI suggestions to the individual employee to ensure relevance. 3. Career Path Generation AI can suggest potential career paths for employees, pointing out skills or training required for advancement. While helpful, managers should rely on company-specific career progression frameworks when available, as these tend to be more tailored to the organization’s needs. 4. Feedback Reminders AI can automatically remind managers to provide feedback to their direct reports, helping maintain a regular cadence of performance reviews. Additionally, AI can flag anomalies in feedback frequency, ensuring that employees receive consistent input throughout the year. Key Takeaways for HR Leaders While AI can significantly enhance the efficiency and effectiveness of performance management, it’s essential to remember that human oversight is critical. AI can automate processes and improve feedback, but managers should always review AI-generated content for accuracy and appropriateness to maintain a personal connection with their employees. By leveraging AI thoughtfully, companies can improve performance management processes, offer more frequent feedback, and drive better employee outcomes. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

September 8, 2024in Salesforce

06Sep

Strong AI Scalability

The rapid pace of digital transformation has made scalability essential for any business looking to remain competitive. The stakes are high—without the ability to scale, businesses risk falling behind as customer demands and market conditions shift. So, what does it take to build a scalable business that can grow without compromising performance or customer satisfaction? In this Tectonic insight, we’ll cover key steps to future-proof your operations, avoid common pitfalls, and ensure your business doesn’t just keep pace with the market, but leads it. Master Scalability with Scale Center Scalability doesn’t have to be overwhelming. Salesforce’s Scale Center, available on Trailhead, provides a comprehensive learning path to help you optimize your scalability strategy. Why Scalability Is a Must-Have Scalability is critical to long-term success. As your business grows, so will the demands on your applications, infrastructure, and resources. If your systems aren’t prepared, you risk performance issues, outages, lost revenue, and dissatisfied customers. Unexpected spikes in demand—from increased customer activity or internal changes like onboarding large numbers of employees—can push systems to their limits, leading to overloads or downtime. A strong scalability plan helps prevent these issues. Here are three best practices to help scale your operations smoothly and sustainably. 1. Prioritize Proactive Scale Testing Scale testing should be a key part of your application lifecycle. Many businesses wait until performance issues arise before addressing them, which can result in maintenance headaches, poor user experiences, and challenges in supporting growth. Proactive steps to take: 2. Use the Right Tools for Seamless Scalability Choosing the right technology is crucial when scaling your business. Equip your team with tools that support growth management, and follow these tips for success: By integrating the right tools and technologies, you’ll not only stay ahead of the curve but also build a culture ready to scale. 3. Focus on Sustainable Growth Strategies Scaling requires a long-term approach. From development to deployment, a strategy that emphasizes scalability from the outset can help you avoid costly fixes down the road. Key practices include: DevOps Done Right Building secure, scalable AI applications and agents requires bridging the gap between tools and skills. Focus on crafting a thoughtful DevOps strategy that supports scalability. Scalability: A Marathon, Not a Sprint Scaling effectively is an ongoing process. Customer needs and market conditions will continue to change, so your strategies should evolve as well. Scalability is about more than just handling increased demand—it’s about ensuring stability and performance across the board. Consider these steps to enhance your approach: Committing to Scalability Scalability isn’t a one-time achievement—it’s a continuous commitment to growing smarter and stronger across all areas of your business. By embedding best practices into your day-to-day operations, you’ll ensure that your systems meet demand and prepare your business for future breakthroughs. As you develop your scalability strategy, remember that customer experience and trust should always guide your decisions. Tackling scalability proactively ensures your business can thrive no matter how market conditions change. It’s more than just a bonus feature—it’s a critical element of a smoother user experience, reduced costs, and the flexibility to pivot when necessary. By embracing these strategies, you’ll not only avoid potential challenges but also build lasting trust with your customers. In a world where loyalty is earned through exceptional experiences, a strong scalability plan is your key to long-term success. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

September 6, 2024in Data, Hyperforce, Salesforce, Technology

05Sep

Co-opetition

Tech companies frequently partner for mutual benefit-Co-opetition, but in the customer service and contact center sector, the competition is heating up. Established players like Genesys, Five9, and Nice are now facing significant competition from tech giants such as AWS, Microsoft, and Google. To strengthen their positions, longtime partners Genesys and Salesforce introduced a joint platform called CX Cloud earlier this year. This platform combines Salesforce’s advanced Service Cloud and CRM with Genesys’ leading contact center as a service (CCaaS) solution- the very epitome of Co-opetition. It integrates telephony, journey management, and employee-focused workforce engagement management tools to optimize contact center operations and track agent satisfaction. While both companies compete in areas like AI, digital engagement, and generative AI, the CX Cloud partnership exemplifies their “coopetition” strategy. Salesforce runs the desktop interface, while Genesys excels in workforce management. By integrating their technologies, the two companies offer customers a flexible solution, enabling them to use the tools that best suit their needs—whether it’s managing digital channels through Salesforce or Genesys. This collaboration eliminates competition in key areas, with both Salesforce and Genesys sales teams working closely together. The partnership between the two companies is not new; their integration dates back to 2015. However, the recent deeper integration, which now covers not just voice but also digital channels, offers customers a unified view of their data. This allows users to harness customer conversation data across both platforms more effectively, giving them the flexibility to use tools from either Genesys or Salesforce. In addition to competition from one another, both Genesys and Salesforce face challenges from cloud hyperscalers like AWS, Microsoft, and Google, which also offer contact center tools. Despite this, Genesys’ and Salesforce’s CX Cloud collaboration stands out by offering a unified framework that benefits customers through combined capabilities. As an example of this complex tech landscape, AWS is both a competitor and a top partner for reselling Genesys Cloud. Both companies agree that the real focus isn’t on competing with each other, but on helping customers solve challenges around customer engagement in an efficient and cost-effective way. The joint platform also integrates with other technologies, such as Google’s Contact Center AI and AWS tools like Lambda and Polly, making it adaptable to diverse enterprise needs. Both Genesys and Salesforce emphasize the importance of an open platform with pre-built integrations, allowing customers to get more value from both platforms faster than before. CX Cloud has seen adoption across various industries and company sizes, from large enterprises to smaller, faster-moving companies. Smaller businesses, in particular, have been quick to adopt this innovation, as it allows them to access enterprise-level integrations without needing to build custom solutions. Larger enterprises, such as ADP, have also benefitted from CX Cloud by using it to deliver proactive customer experiences, addressing potential issues before they arise. Overall, the partnership between Genesys and Salesforce exemplifies Co-opetition-a collaborative approach in a highly competitive market, enabling customers to leverage the strengths of both platforms for enhanced contact center operations. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

September 5, 2024in Generative AI

Linus Torvalds Insights

Linus Torvalds Shares Insights on the Future of Programming with AI Linus Torvalds, the mastermind behind Linux and Git—two cornerstones of modern software development—recently shared his perspective on how artificial intelligence (AI) is reshaping the world of programming. His candid insights offer a balanced view of AI’s capabilities and limitations, coming from one of the industry’s most influential voices. If you prefer a quick breakdown over watching a full interview, here are the key takeaways from Torvalds’ conversation. AI in Programming: Evolution, Not Revolution Torvalds describes AI, particularly large language models (LLMs), as “autocorrect on steroids.” These tools excel at predicting the next word or line of code based on established patterns but aren’t “intelligent” in the human sense. Rather than a seismic shift, AI represents the next step in a long history of automation in coding. From the days of machine language to today’s high-level languages like Python and Rust, tools have continuously evolved to make developers’ lives easier. AI is just another link in this chain—helping write, refine, and debug code while boosting productivity. AI as a Developer’s Supercharged Assistant Far from being a replacement for human programmers, Torvalds sees AI as a powerful assistant. Tools like GitHub Copilot are already enhancing the coding process by suggesting fixes, spotting bugs, and speeding up routine tasks. The vision? A future where programmers can abstract tasks even further, possibly instructing AI in plain English. Imagine simply saying, “Build me a tool to manage my expenses,” and watching it happen. However, for now, AI is an incremental improvement, not a groundbreaking leap. The Shift Toward AI-Generated Code One of Torvalds’ more intriguing predictions is that AI may eventually write code in ways incomprehensible to human programmers. Since AI doesn’t require human-readable syntax, it could optimize code in ways that only it understands. In this scenario, developers might transition from writing code to managing AI systems that generate and refine it—shifting from hands-on creators to overseers of automated processes. AI in Code Review: Smarter Intern or Future Partner? When it comes to code review, AI’s potential is clear. Torvalds notes that AI could efficiently catch simple errors—like typos or syntax mistakes—freeing up human reviewers to focus on more complex logic and functionality. While AI might streamline tedious tasks, it’s far from perfect. Issues like “hallucinations,” where AI confidently produces incorrect results, highlight the need for human oversight. AI can assist, but it still requires developers to verify its output. A Balanced Take on AI and Jobs Torvalds dismisses fears of AI taking over programming jobs, pointing out that technological advancements historically create new opportunities rather than eliminate roles. AI, in his view, is less about replacing humans and more about augmenting their abilities. It’s a tool to make developers more efficient—not a harbinger of obsolescence. Final Thoughts: Embrace AI, But Stay Grounded Linus Torvalds envisions AI as a valuable, evolving tool for programmers, not a threat to their livelihood. While it’s set to change how we code, the shift will be gradual rather than revolutionary. Whether you’re a seasoned developer or a newcomer, now is the time to explore AI-powered tools, embrace their potential, and adapt to this new era of programming. Instead of fearing change, we can use AI to push the boundaries of what’s possible. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

September 4, 2024in Artificial Intelligence

31Aug

AI and Big Data

Over the past decade, enterprises have accumulated vast amounts of data, capturing everything from business processes to inventory statistics. This surge in data marked the onset of the big data revolution. However, merely storing and managing big data is no longer sufficient to extract its full value. As organizations become adept at handling big data, forward-thinking companies are now leveraging advanced analytics and the latest AI and machine learning techniques to unlock even greater insights. These technologies can identify patterns and provide cognitive capabilities across vast datasets, enabling organizations to elevate their data analytics to new levels. Additionally, the adoption of generative AI systems is on the rise, offering more conversational approaches to data analysis and enhancement. This allows organizations to extract significant insights from information that would otherwise remain untapped in data stores. How Are AI and Big Data Related? Applying machine learning algorithms to big data is a logical progression for companies aiming to maximize the potential of their data. Unlike traditional rules-based approaches that follow explicit instructions, machine learning systems use data-driven algorithms and statistical models to analyze and detect patterns in data. Big data serves as the raw material for these systems, which derive valuable insights from it. Organizations are increasingly recognizing the benefits of integrating big data with machine learning. However, to fully harness the power of both, it’s crucial to understand their individual capabilities. Understanding Big Data Big data involves extracting and analyzing information from large quantities of data, but volume is just one aspect. Other critical “Vs” of big data that enterprises must manage include velocity, variety, veracity, validity, visualization, and value. Understanding Machine Learning Machine learning, the backbone of modern AI, adds significant value to big data applications by deriving deeper insights. These systems learn and adapt over time without the need for explicit programming, using statistical models to analyze and infer patterns from data. Historically, companies relied on complex, rules-based systems for reporting, which often proved inflexible and unable to cope with constant changes. Today, machine learning and deep learning enable systems to learn from big data, enhancing decision-making, business intelligence, and predictive analysis. The strength of machine learning lies in its ability to discover patterns in data. The more data available, the more these algorithms can identify patterns and apply them to future data. Applications range from recommendation systems and anomaly detection to image recognition and natural language processing (NLP). Categories of Machine Learning Algorithms Machine learning algorithms generally fall into three categories: The most powerful large language models (LLMs), which underpin today’s widely used generative AI systems, utilize a combination of these methods, learning from massive datasets. Understanding Generative AI Generative AI models are among the most powerful and popular AI applications, creating new data based on patterns learned from extensive training datasets. These models, which interact with users through conversational interfaces, are trained on vast amounts of internet data, including conversations, interviews, and social media posts. With pre-trained LLMs, users can generate new text, images, audio, and other outputs using natural language prompts, without the need for coding or specialized models. How Does AI Benefit Big Data? AI, combined with big data, is transforming businesses across various sectors. Key benefits include: Big Data and Machine Learning: A Synergistic Relationship Big data and machine learning are not competing concepts; when combined, they deliver remarkable results. Emerging big data techniques offer powerful ways to manage and analyze data, while machine learning models extract valuable insights from it. Successfully handling the various “Vs” of big data enhances the accuracy and power of machine learning models, leading to better business outcomes. The volume of data is expected to grow exponentially, with predictions of over 660 zettabytes of data worldwide by 2030. As data continues to amass, machine learning will become increasingly reliant on big data, and companies that fail to leverage this combination will struggle to keep up. Examples of AI and Big Data in Action Many organizations are already harnessing the power of machine learning-enhanced big data analytics: Conclusion The integration of AI and big data is crucial for organizations seeking to drive digital transformation and gain a competitive edge. As companies continue to combine these technologies, they will unlock new opportunities for personalization, efficiency, and innovation, ensuring they remain at the forefront of their industries. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

August 31, 2024in Data, Enterprise, Generative AI, Google, Salesforce, Technology

30Aug

Detecting the Hot Chatbot

All the tech giants are eager to prove their chatbot is the hottest in the market. Like wild stallions fighting over the mares, Google, Meta, Microsoft, and OpenAI are competing to show that their AI models have the most momentum. Companies with built-in AI like Salesforce occupy a broader sector. Detecting the Hot Chatbot is the challenge for the consumer. Why Detecting the Hot Chatbot Matters These companies have poured immense resources—both talent and money—into developing their models and adding new features. Now, they’re keen to showcase that these investments are yielding results. What’s Happening In the past few dayss, several major players have released new usage statistics: The Big Picture Generative AI is still in its early stages, and the entire industry faces the challenge of proving that these products deliver real value—whether by capturing market share from the lucrative search industry or by helping companies save money through increased productivity. How are you Detecting the Hot Chatbot. In the short term, however, everyone is eager to show they’re leading the pack. TV commercials for generative AI are now common, with Meta, Google, and Microsoft all airing spots, although the effectiveness of these ads varies. Some companies even boast that their commercials were created using AI—not necessarily the most convincing selling point. Between the Lines The competition isn’t just about consumer popularity; it’s also spilling over into the battle to secure business customers. On Wednesday’s earnings call, Salesforce CEO Marc Benioff made a point of distinguishing Salesforce’s new Agentforce AI sales assistant from Microsoft’s Copilot offerings. “This is not Copilot,” Benioff said. “So many customers are disappointed with what they bought from Microsoft Copilot because they’re not getting the accuracy and response they want. Microsoft has let down many customers with AI.” Microsoft quickly responded in a comment to CNBC. “We are hearing something quite different from our Copilot for Microsoft 365 customers,” said corporate VP Jared Spataro. “When I talk to CIOs directly, and if you look at recent third-party data, organizations are betting on Microsoft for their AI transformation.” The Bottom Line The competition is heating up as tech giants vie to prove they have the upper hand in the AI race and the Hot Chatbot. Customers will ultimately decide. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

August 30, 2024in Generative AI, Salesforce Financial Services Solutions, Salesforce for Nonprofits, Salesforce Health and Life Sciences Solutions, Salesforce Hospitality Travel and Transportation, Salesforce Implementation Services, Salesforce Manufacturing Automotive Energy, Salesforce Public Sector Solutions

29Aug

Salesforce Einstein SDR and Sales Coach Agents

Salesforce Introduces Autonomous AI Sales Agents: Einstein SDR Agent and Einstein Sales Coach Agent Salesforce, the leading CRM for sales, has announced two new fully autonomous AI sales agents: Einstein Sales Development Rep (SDR) Agent and Einstein Sales Coach Agent. These groundbreaking agents, set to be generally available in October, are designed to help sales teams accelerate growth by handling key sales functions autonomously. Built on the Einstein 1 Agentforce Platform, these agents are poised to transform how sales teams operate, allowing them to focus on more complex deals while automating routine tasks. Einstein SDR Agent: Automating Pipeline 24/7 The Einstein SDR Agent autonomously engages with inbound leads, nurturing pipelines around the clock. Unlike traditional chatbots, which can only respond to pre-programmed queries, the Einstein SDR Agent uses advanced AI to make decisions, prioritize actions, and handle various lead interactions. Whether it’s answering product questions, managing objections, or booking meetings, the SDR Agent ensures that every response is trusted, accurate, and personalized, grounded in your company’s CRM and external data. Key features of the Einstein SDR Agent include: Einstein Sales Coach Agent: Enhancing Seller Performance Through AI-Driven Role-Play Einstein Sales Coach Agent takes sales enablement to the next level by autonomously engaging in role-plays with sellers. Whether simulating a buyer during discovery, pitch, or negotiation calls, the Sales Coach Agent uses generative AI to convert text into speech, providing a realistic training environment. This agent helps sellers refine their skills by offering personalized feedback based on real deal contexts. Key features of the Einstein Sales Coach Agent include: Accenture’s Collaboration with Salesforce Accenture, a global leader in business consulting, will leverage these new AI agents to enhance deal team effectiveness, scale support for more deals, and allow their sales teams to concentrate on the most complex transactions. According to Sara Porter, Global Sales Excellence Lead at Accenture, these AI-driven tools will empower their sales practitioners with advanced technology and processes to drive more intelligent customer conversations and accelerate revenue. Salesforce’s Vision for AI in Sales Salesforce sees these autonomous AI agents as a key part of the future of sales. By integrating AI that can generate high-quality pipeline and provide personalized coaching, sales teams can focus on higher-value deals and better prepare for them. Ketan Karkhanis, EVP and GM of Sales Cloud, emphasizes that every AI conversation must translate into ROI, and these new agents are designed to do just that by augmenting human sales teams to accelerate growth. Availability Both Einstein SDR Agent and Einstein Sales Coach Agent will be generally available in October, with additional functionalities expected to be rolled out throughout the year. Learn More: Note: Any unreleased services or features mentioned here are not currently available and may be subject to changes. Customers should base their purchasing decisions from Salesforce on currently available features. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

August 29, 2024in Agentforce Platform, Generative AI, Salesforce Einstein

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