Marketing - gettectonic.com - Page 14
Consumer Chatbot Technology
07Jun

Consumer Chatbot Technology

The Reality Behind AI Chatbots and the Path to Autonomous AI In the rush to adopt the latest Consumer Chatbot Technology, it’s easy to overlook a fundamental reality: consumer chatbot technology isn’t ready for enterprise use—and it likely never will be. The reason is simple: AI assistants are only as effective as the data that powers them. Most large language models (LLMs) are trained on data from public websites, which lack the specific business and customer data that enterprises need. This means consumer bots can’t adequately assist employees in selling products, marketing merchandise, or improving productivity, as they lack the necessary personalization and business context. To achieve the vision of AI that goes beyond simple chatbots performing basic tasks—like drafting emails, essays, blogs, or graphics—to a more advanced role where AI acts autonomously and addresses business-critical needs, a different approach is needed. This vision involves AI taking action with minimal human intervention, using digital agents to identify and respond to these needs. At Salesforce, we are pursuing a clear path to AI that not only takes action but also automates routine tasks, all while adhering to established business rules, permissions, and context. Instead of relying solely on LLMs, which primarily focus on generating human-like text, future AI assistants will depend on large action models (LAMs) that integrate decision-making and action-taking capabilities. The Journey Toward AI Autonomy Our journey towards this vision began with the Salesforce Data Cloud, a robust data engine built on the Einstein 1 Platform. This platform integrates data from across the enterprise and third-party repositories, enabling companies to activate their data, automate workflows, personalize customer interactions, and develop smarter AI solutions. Recognizing the shift from generative AI to autonomous AI, Salesforce introduced Einstein Copilot, the industry’s first conversational, enterprise-class AI assistant. Integrated across the Salesforce ecosystem, Einstein Copilot utilizes an organization’s data, whether it’s behind a firewall or in an external data lake, to act as a reasoning engine. It interprets user intents, interacts with the most suitable AI model, solves problems, generates relevant content, and provides decision-making support. Expanding the Role of AI in Business Since its launch in February 2024, Salesforce has been expanding Einstein Copilot’s library of actions to meet specific business needs in sales, service, marketing, data analysis, and industries like ecommerce, financial services, healthcare, and education. These “actions” are akin to LEGO blocks—discrete tasks that can be assembled to achieve desired project outcomes. For example, a sales representative might use Einstein Copilot to generate a personalized close plan, gain insights into why a deal may not close, or review whether pricing was discussed in a recent call. Einstein Copilot then orchestrates these tasks, provides recommendations, and compiles everything into a detailed report. The ultimate goal is for AI not only to gather and organize information but also to take proactive action. Imagine a sales representative instructing their digital agent to set up meetings with top prospects in a specific territory. The AI could not only identify suitable contacts but also suggest meeting times, plan travel schedules, draft emails, and even create talking points—all of which it could execute autonomously with the representative’s approval. Tectonic dreams of the day AI is smart enough to interpret our search engine typos and produce the results for what we were actually looking for! The Future of AI Autonomy The possibilities for semi-autonomous or fully autonomous AI are vast. As we continue to develop and refine these technologies, the potential for AI to transform business processes and decision-making becomes increasingly tangible. At Salesforce, they are committed to leading this charge, ensuring that our AI solutions not only meet but exceed the expectations of enterprises worldwide. Salesforce is in a strong position to deliver on all of them because of the volume and breadth of data housed in Data Cloud, the heavy workflow traffic in our Customer 360 CRM, and the fact we’ve delivered an enterprise-class copilot that is rapidly expanding its library of actions. It will not happen overnight. The technology needs to advance, organizations and people have to be able to trust AI and be trained to use it in the right ways, and more work will need to be done to ensure the right balance between human involvement and AI autonomy. But with our continued investment in CRM, data, and trusted AI, we will achieve that vision before too long. Salesforce is in a strong position to deliver on all of them because of the volume and breadth of data housed in Data Cloud, the heavy workflow traffic in our Customer 360 CRM, and the fact we’ve delivered an enterprise-class copilot that is rapidly expanding its library of actions. Jayesh Govindarajan, Senior Vice President, Salesforce AI 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

Read More
June 7, 2024in Einstein 1 Platform, Generative AI, Salesforce Data Cloud
Salesforce hospitality and analytics
03Jun

Hospitality Email Marketing Ideas

Recently we were asked by a hospitality client to come up with some email marketing campaign ideas. We want to share them with you all. Hospitality Email Marketing Ideas. – Pre-Arrival stream 3 weeks, 2 weeks, 1 week out- (“We are excited to have you staying with us. This is what you need to know before arriving on The Ranch” “Parking Instructions” etc) – Post Stay email stream (“Please give a review” / “Share your Ranch photos on social media” / “Book Another Stay”) – Abandon Web Browser (“You have not completed your reservation…” “You left items in your cart” “The date’s you were looking at are nearly sold out”) – Good Will (“Daily Happy Birthday Email or Anniversary Email” “Emailer to the Community” “Discount for Next Stay if You Book By”} – Program Announcements (“:Upcoming 7 and 9 Day Programs” “New Programs” “At Home Programs Launching or Updates” } – Monthly or Quarterly Updates (“Milestones in the Sustainability Program” “Satisfied Customer Testimonials”) -True Newsletters – Content Announcements (“A New Blog Post” “A New Product”} – Upcoming Events {Concerts” “Local Events in the area that might attract repeat guests”} – Bonus Brainstorm (“Since you stayed with us last year for the XYZ event…” “Since you enjoyed your stay, bring your whole company/family etc next time” What Hospitality Email Marketing Ideas have you had success with at your location? Share in the comments section below. By Tectonic Salesforce Marketing Architect, Shannan Hearne 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

Read More
June 3, 2024in Salesforce
Is AI a Bubble?
02Jun

Is AI a Bubble?

Scott Galloway, Prof Marketing, NYU Stern • Host, CNN+ • Pivot, Prof G Podcasts • Bestselling author, The Four, The Algebra of Happiness, Post Corona, published an insightful look at artificial intelligence last month. Originally appearing in Medium.com Content repurposed with credit to author here. Five years ago, Nvidia was a second-tier semiconductor company, primarily known for enhancing the resolution of Call of Duty. Today, it is the third-most-valuable company globally, commanding an impressive 80% share in AI chips, the processors driving an unprecedented $8 trillion value creation in history. Since the release of ChatGPT by OpenAI in October 2022, Nvidia’s value has surged by $2 trillion, equating to Amazon’s market worth. Last week, Nvidia reported exceptional quarterly earnings, with its core business of selling chips to data centers experiencing a 427% year-over-year increase. Last year, at Cannes, Jensen Huang introduced himself to author, Scott Galloway, mentioning his admiration for Galloway’s videos. Not recognizing Huang, Galloway offered to take a photo, which Huang accepted before Galloway continued on his way. Since then, Nvidia has added $1.3 trillion in value. Galloway, on the other hand, underwent Ketamine therapy, abstained from drinking for 17 days, and installed a router with YouTube’s help. It’s been a significant year for both. There is widespread consensus on the revolutionary potential of the AI market, which explains the soaring AI stock prices. However, this unanimity raises concerns about a potential bubble. According to Scott Galloway, the situation mirrors the 1630s tulip mania, where people bid up tulips not for their beauty or utility but because they believed they could sell them at higher prices later—a phenomenon known as the “greater fool” theory. This logic also applies to meme stocks, which embody the “greatest fool” theory. Galloway advises skepticism toward any movement urging people to “stick it to the man,” as it often leaves them vulnerable. Galloway describes the dynamics of economy-distorting bubbles, where speculative psychology meets genuine economic potential. Such bubbles grow as increasing stock prices validate assumptions, attracting more speculators. Low-interest rates can fuel these bubbles, which typically have an enduring technology at their core. He draws parallels to previous bubbles: the dot-com bubble, the housing market bubble, and the cryptocurrency bubble, noting that AI appears to follow a similar trajectory. The financial media often debates whether AI represents a bubble or a genuine technological breakthrough. Galloway argues that AI’s economic promise is real, making a bubble inevitable. He cites the rapid increase in market value among AI-driven companies like Alphabet, Amazon, and Microsoft as indicative of an overvaluation bubble. Nvidia, the standout in the AI sector, faces the challenge of maintaining its valuation by dominating another market as significant as AI. Galloway highlights that the current narrative around Nvidia resembles that of Cisco during the dot-com bubble. Both companies were seen as essential investments in their respective eras, but Cisco’s stock eventually crashed along with the broader market. Timing a bubble’s burst is notoriously difficult. Galloway recounts how past investors, like John Paulson and Michael Burry, timed their bets on housing correctly, but others, like Julian Robertson and George Soros, faced significant losses by mistiming the dot-com bubble. He emphasizes that most people cannot predict market turns accurately and advises diversification and caution. Galloway speculates on how an AI market downturn might occur. A significant non-tech company scaling back its AI investments could trigger a chain reaction of declining stock prices and speculative sell-offs. This scenario mirrors the dot-com bubble’s collapse in 2000 and the housing bubble’s burst in 2007. He concludes that while the AI bubble feels more akin to the dot-com bubble than the housing crisis, its growing size could have broader economic repercussions. The AI bubble’s eventual deflation might resemble Cisco’s post-dot-com trajectory, where long-term value persists despite short-term losses. Ultimately, Nvidia’s current status as a “safe” investment suggests that it might offer returns aligned with the market, rather than the spectacular gains of past tech giants like Amazon. Scott Galloway encapsulates this analysis with a warning: when a “sure thing” stock becomes frothy, it is no longer a safe bet. Investors should be prepared for both the potential risks and rewards, securing their metaphorical tray tables as they navigate the turbulent AI investment 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 Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more Top Ten Reasons Why Tectonic Loves the Cloud The Cloud is Good for Everyone – Why Tectonic loves the cloud You don’t need to worry about tracking licenses. Read more

Read More
June 2, 2024in Salesforce Einstein
Einstein Personalization and Copilots
30May

Einstein Personalization and Copilots

Salesforce launched a suite of new generative AI products at Connections in Chicago, including new Einstein Copilots for marketers and merchants, and Einstein Personalization. Einstein Personalization and Copilots To gain insights into these products and Salesforce’s evolving architecture, Bobby Jania, CMO of Marketing Cloud was interviewed. Salesforce’s Evolving Architecture Salesforce has a knack for introducing new names for its platforms and products, sometimes causing confusion about whether something is entirely new or simply rebranded. Reporters sought clarification on the Einstein 1 platform and its relationship to Salesforce Data Cloud. “Data Cloud is built on the Einstein 1 platform,” Jania explained. “Einstein 1 encompasses the entire Salesforce platform, including products like Sales Cloud and Service Cloud, continuing the original multi-tenant cloud concept.” Data Cloud, developed natively on Einstein 1, was the first product built on Hyperforce, Salesforce’s new cloud infrastructure. “From the start, Data Cloud has been able to connect to and read anything within Sales Cloud, Service Cloud, etc. Additionally, it can now handle both structured and unstructured data.” This marks significant progress from a few years ago when Salesforce’s platform comprised various acquisitions (like ExactTarget) that didn’t seamlessly integrate. Previously, data had to be moved between products, often resulting in duplicates. Now, Data Cloud serves as the central repository, with applications like Tableau, Commerce Cloud, Service Cloud, and Marketing Cloud all accessing the same operational customer profile without duplicating data. Salesforce customers can also import their own datasets into Data Cloud. “We wanted a federated data model,” Jania said. “If you’re using Snowflake, for example, we virtually sit on your data lake, providing value by forming comprehensive operational customer profiles.” Understanding Einstein Copilot “Copilot means having an assistant within the tool you’re using, contextually aware of your tasks and assisting you at every step,” Jania said. For marketers, this could start with a campaign brief created with Copilot’s help, identifying an audience, and developing content. “Einstein Studio is exciting because customers can create actions for Copilot that we hadn’t even envisioned.” Contrary to previous reports, there is only one Copilot, Einstein Copilot, with various use cases like marketing, merchants, and shoppers. “We use these names for clarity, but there’s just one Copilot. You can build your own use cases in addition to the ones we provide.” Marketers will need time to adapt to Copilot. “Adoption takes time,” Jania acknowledged. “This Connections event offers extensive hands-on training to help people use Data Cloud and these tools, beyond just demonstrations.” What’s New with Einstein Personalization Einstein Personalization is a real-time decision engine designed to choose the next best action or offer for customers. “What’s new is that it now runs natively on Data Cloud,” Jania explained. While many decision engines require a separate dataset, Einstein Personalization evaluates a customer holistically and recommends actions directly within Service Cloud, Sales Cloud, or Marketing Cloud. Ensuring Trust Connections presentations emphasized that while public LLMs like ChatGPT can be applied to customer data, none of this data is retained by the LLMs. This isn’t just a matter of agreements; it involves the Einstein Trust Layer. “All data passing through an LLM runs through our gateway. Personally identifiable information, such as credit card numbers or email addresses, is stripped out. The LLMs do not store the output; Salesforce retains it for auditing. Any output that returns through our gateway is logged, checked for toxicity, and only then is PII reinserted into the response. These measures ensure data safety beyond mere handshakes,” Jania 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 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

Read More
May 30, 2024in Einstein 1 Platform, Generative AI, Hyperforce, Salesforce, Salesforce Data Cloud, Salesforce Einstein, Snowflake
Engagement Frequency Dashboard
29May

Engagement Frequency Dashboard

The Einstein Engagement Frequency Dashboard The Einstein Engagement Frequency Dashboard provides a comprehensive overview of your contacts’ email saturation levels. By analyzing this data, you can understand how your email sending frequency influences engagement metrics like opens, clicks, and unsubscribes over time. The What-If analyzer is a handy tool within the dashboard, allowing you to experiment with different sending frequencies to maximize your On Target saturation levels. Accessing the Dashboard To access the Einstein Engagement Frequency Dashboard: Once on the dashboard, you can click “View Details” at the top to check your data quality scores and get tips on how to improve them. This will give you an idea of how reliable your email or mobile engagement data is. Note on Data Quality If Einstein lacks sufficient data for certain contacts, it will assign frequency scores based on global model data. This can sometimes cause discrepancies between the Einstein Engagement Frequency dashboard and activity-level analytics in specific journeys. What-If Analyzer The What-If Analyzer is a feature on the dashboard that allows you to test different future saturation levels based on varying message frequencies. The goal is to increase the number of contacts in the “On Target” range for engagement. The analyzer provides a bar chart that predicts how adjusting your email frequency can shift contacts from being “Saturated” or “Undersaturated” to “On Target.” This tool helps you fine-tune your communication strategy to optimize engagement across your contact base. 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

Read More
May 29, 2024in Salesforce
AI in Marketing
29May

AI in Marketing

John Dutton recently posted in his blog about AI “representatives” who talk to you. It’s an interesting look into the “creep” factor potentially in artificial intelligence and certainly provides plenty of food for thought on robots and AI in marketing. Read it here. Summarized below. When the media or the internet shares a look at this wierd generated image talking, its easy to spot. When not flagged, it is getting a little harder to know for sure-is it real or is it Memorex. Unveiling AI in Ukraine Last week, Ukraine’s Ministry of Foreign Affairs introduced Victoriya Shi, a “digital representative” and AI-produced avatar. Shi delivers official statements in videos shared on the Ministry’s online social channels. According to Ukrainian Foreign Minister Dmytro Kuleba, Shi was created to “save time and resources” for diplomats. Given the ongoing conflict in Ukraine, this rationale seems reasonable. However, the introduction of such an AI avatar raises questions about the future and the potential for dystopian developments. A key concern is the ease of deepfaking an already artificial persona. This challenge has been addressed by the MFA through a smart yet simple solution: a QR code in the corner of each video that directs viewers to the official text version of the announcement on the Ministry’s website. It’s worth noting that the official statements themselves are not AI-generated, which could set a worrying precedent. While the Ukrainian version’s reception is unknown, the English version of Victoriya Shi struggles to escape the “uncanny valley” of artificial humans. Her sign-off, “I look forward to our fruitful cooperation,” has an eerie, robotic undertone. This unsettling impression might not be entirely negative. Navigating the Age of AI We are deeply entrenched in the Age of AI, where trust has become a scarce commodity. The concept of “fake news” emerged well before generative AI, gaining prominence in late 2016 with the rise of certain political figures. A search on Google Trends reveals the sudden spike in terms like “fake news” and “post-truth” during that period. With AI’s potential to create convincing deepfakes, the challenge of distinguishing real from fake is intensifying. A recent incident in Hong Kong saw an employee deceived by an AI-generated video, leading to a $25 million fraud. This highlights the need for secure credentialing, especially in large organizations and potential metaverse meetings. However, in-person meetings remain immune to such digital deceptions. AI’s Role in Authenticity Ironically, AI might help combat its own deceptions. OpenAI’s recent collaboration with the Coalition for Content Provenance and Authenticity (C2PA) aims to develop tools for identifying AI-generated content. As deepfakes become more sophisticated, the absence of C2PA authentication could become a red flag. If this leads to a heightened skepticism towards digital media, it might not be entirely negative. AI could bolster our defenses against scams, encouraging a healthy suspicion of the digital content we consume. The Balance of Authenticity and Truth The distinction between authenticity and truth is crucial. A government-created AI avatar can be fake in its artificiality but still deliver authentic, official statements. As generative AI advances, we must fine-tune our skepticism. Victoriya Shi’s name reflects Ukraine’s hope for “victory” and the integration of AI (“Shi” in Ukrainian). The war may ultimately hinge on intelligent tech use rather than sheer military might. Update and Reflections Following the newsletter’s release, it was revealed that WPP, the world’s largest ad agency network, nearly fell victim to a deepfake scam, with the CEO’s voice being replicated by AI. The Dystopia/Utopia Dichotomy The generative AI revolution has begun, and its trajectory could lead to either a utopian or dystopian future. My novel, “2084,” explores a world where life appears superficially perfect, masking underlying issues. Artistic AI Innovations One of my book’s main characters is a sculptor, a profession I initially believed immune to AI. However, Monumental Labs, founded in 2022, uses “sensors and AI” to produce sculptures at a fraction of traditional costs. This reality mirrors the AI-driven world imagined in “2084.” Genetic Modifications and Luxury Fresh Del Monte’s Rubyglow® pineapple, an ultra-premium, genetically modified fruit, exemplifies the future of designer foods. My novel envisions similar advancements with patented food items and drone-pollinated plants. The Challenger Mindset Adam Morgan, an expert in the challenger brand mindset, emphasizes the importance of maintaining a challenger attitude regardless of market position. Companies like Netflix exemplify this, adapting and thriving in a competitive landscape by retaining a challenger’s drive. The Right to Repair and Brand Identity The US Government Accountability Office highlights the “softwareification” of cars, making independent repairs difficult. Similarly, Apple’s restrictive policies on iPhone repairs underline the broader trend of manufacturers controlling repair markets. Cult of Brand Identity The Gray Area podcast discusses how modern consumers interact with brands, focusing on identity over product quality. This shift underscores the evolving landscape of commercial competition and consumer behavior. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more Guide to Creating a Working Sales Plan Creating a sales plan is a pivotal step in reaching your revenue objectives. To ensure its longevity and adaptability to Read more Salesforce Artificial Intelligence Is artificial intelligence integrated into Salesforce? Salesforce Einstein stands as an intelligent layer embedded within the Lightning Platform, bringing robust Read more

Read More
May 29, 2024in Generative AI, Salesforce Einstein
Growing Family of Einstein Copilots
27May

Growing Family of Einstein Copilots

Salesforce made several announcements this month, regarding the Growing Family of Einstein Copilots. By unveiling AI-powered Einstein Copilots for marketing and merchants. These new Copilots build on the previously announced Copilots for retailers and shoppers and are integrated into the Einstein 1 platform. They can communicate with each other, effectively bridging marketing and commerce, and have full access to Salesforce Data Cloud. “Welcome to the AI enterprise,” said Ariel Kelman, Salesforce President and CMO, during his keynote at Salesforce Connections in Chicago. Kelman outlined four waves of AI: Predictive (e.g., lead scoring), Generative, Autonomous, and AI General Intelligence. “We are starting to enter the third wave,” he stated, where AI will begin to take actions independently. Copilots are a step in that direction, although for now, a human remains in control. The Path to the AI Enterprise Kelman described five steps towards creating an AI enterprise: Regarding the last point, new Slack AI tools were demonstrated for summarizing interactions and importing actionable data from Data Cloud into Slack. The strategy for Einstein Copilots aims to empower business users in marketing, commerce, and other functions to execute complex tasks, such as creating personalized customer journeys, using natural language prompts. Einstein Copilots for Marketing and Merchants The marketing Copilot can generate marketing briefs and content, and create email campaigns. Through Data Cloud, it can ingest and execute a brand’s datasets, including customer data from repositories like AWS, Snowflake, and Databricks. By automating routine tasks and time-consuming projects like data connection and analysis, the Copilot aims to free up marketers to engage more thoughtfully with their audiences. The commerce Copilot, part of Salesforce’s commerce offerings, responds to natural language prompts to create online storefronts, improve product discoverability, write product descriptions, and make product recommendations. Other Announcements 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

Read More
May 27, 2024in Einstein 1 Platform
Copilot A Step Up For Merchandising
23May

Copilot A Step Up For Merchandising

A Leap Forward in Merchandising Merchants face the ongoing challenge of enhancing loyalty, conversion rates, and shopper lifetime value. Enter Einstein Copilot, ushering in automation to boost productivity and inject intelligence for an elevated customer experience in unprecedented ways. Salesforce asserts that early AI adopters are saving an average of 6.4 hours per week. Copilot A Step Up For Merchandising. Einstein Copilot empowers merchants to swiftly craft personalized product promotions to attract new customers and target slow-moving stock based on inventory insights. Additionally, it optimizes site traffic with search engine optimization (SEO) content, generates product descriptions, and enhances checkout conversion with AI recommendations tailored to specific objectives. Copilot A Step Up For Merchandising Prior to Einstein Copilot, other generative AI copilot solutions operated as separate applications, disconnected from the workflow, and lacked the ability to securely leverage trusted company data for generating relevant or consistent results from large language models. Einstein Copilot integrates seamlessly within the world’s leading AI CRM and harnesses data from any Salesforce application to deliver more precise AI-powered recommendations and content. Through natural language prompts, Einstein Copilot facilitates a range of tasks, including: Sales: Conducting account research, preparing for meetings, and automatically updating account information in Salesforce. Summarizing highlights, gauging customer sentiment, and extracting next steps from video calls. Searching for specific details in customer calls and auto-generating sales emails to match tone and style while aligning with customer context. Drafting clauses and embedding them directly within customer contracts. Service: Automatically responding to customers with personalized, relevant answers sourced from trusted company knowledge across various channels like email, SMS, live chat, or social media. Empowering service teams to resolve customer issues swiftly using generative answers integrated seamlessly into their workflow. Automating tasks like summarizing support cases and field work orders. Marketing: Generating email copy for marketing campaigns, refining campaign segmentation with Data Cloud, creating website landing pages based on personalized consumer preferences, and auto-populating contact forms with each customer’s unified profile in Salesforce. Generating surveys following online actions to enhance long-term engagement and purchasing. Commerce: Assisting in building high-converting digital storefronts, automating complex tasks like managing multi-product catalog data, crafting product descriptions in multiple languages, generating personalized product promotions, and optimizing SEO metadata for conversion. Customizing and designing storefront components using natural language prompts. Developers: Converting natural language prompts into Apex code, offering suggestions for more effective and accurate code, and proactively scanning for code vulnerabilities within the developer environment. Tableau: Transitioning swiftly from raw data to actionable insights through a conversational interface, enhancing data analyst productivity with a natural language assistant for faster data exploration, building relevant visualizations, automating repetitive tasks, and facilitating efficient data curation. 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

Read More
May 23, 2024in Einstein 1 Platform, Generative AI, Salesforce
Salesforce Commerce Cloud and Einstein Copilot Capabilities
23May

Salesforce Commerce Cloud and Einstein Copilot Capabilities

Salesforce Enhances Commerce Cloud and Einstein Copilot Salesforce has announced a double whammy of upgrades to its Commerce Cloud and Einstein Copilot solutions, aiming to supercharge customer service and experience offerings for merchants. And yes, they’re pulling out all the stops – think of it as giving your online store a superhero cape and a sidekick with a PhD in customer satisfaction. Salesforce Commerce Cloud and Einstein Copilot Capabilities. Enhancements to Commerce Cloud Commerce Cloud is getting three major innovations designed to help businesses create more sophisticated commerce sites, boost personalization, and drive revenue growth. Salesforce promises to tackle rising customer expectations by providing a seamless, integrated experience across all channels. In other words, they’re turning your website into a mind-reading wizard, minus the beard and wand. But probably wearing a cool purple cape with stars. According to Michael Affronti, GM and SVP of Commerce Cloud, these new features will enable Salesforce’s customers to deliver superior shopping experiences: “Commerce companies are looking to architect high-caliber ecommerce sites that can swiftly adapt to changing customer expectations and continue to foster strong customer relationships. With the combined power of data, AI, and CRM, Commerce Cloud gives brands the choice of the right tool so they can build superior shopping experiences their way.” New Commerce Cloud Capabilities Einstein Copilot Advancements Salesforce is pulling out the big AI guns, leveraging generative AI (GenAI) to enhance Einstein Copilot with new marketing and merchandising capabilities alongside its traditional sales and service functions. It’s like your old assistant got a brain transplant and now has the IQ of Einstein, the charm of James Bond, and the work ethic of a coffee-fueled startup founder. Ariel Kelman, President and CMO of Salesforce, emphasized the importance of these advancements: “Marketing and commerce leaders need a trusted advisor to help them tap into the promise of generative AI. With the Einstein 1 Platform we’re giving organizations the power to unify all of their data on one trusted platform. This is the key to getting results from generative AI that are actually useful in driving your business forward.” Key Features of Einstein 1 for Marketing and Commerce Expanding Partnerships and Enhancing AI and Data Offerings In addition to these product enhancements, Salesforce has expanded its partnership with IBM to improve AI and data offerings. The collaboration aims to merge IBM’s watsonx.ai platform with Salesforce’s Einstein 1 software, providing customers with the ability to make data-driven decisions and access actions directly within their workflows. It’s like pairing up Batman and Superman to fight the evil forces of inefficiency and bad data. The partnership includes bidirectional data integration, flexible large language models (LLMs), prebuilt CRM solutions, and a focus on responsible AI development. IBM will also join Salesforce’s Zero Copy Partner Network, ensuring that data moves as smoothly as butter on hot toast. Salesforce Commerce Cloud and Einstein Copilot Capabilities These enhancements and partnerships underline Salesforce’s commitment to providing innovative solutions that enhance customer experiences and drive business growth, all while making sure your digital commerce experience is smoother than a jazz saxophone solo. 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

Read More
May 23, 2024in Einstein 1 Platform, Generative AI, Salesforce, Salesforce Commerce Cloud
Service Cloud Digital Engagement
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 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

Read More
May 23, 2024in Einstein 1 Platform, Salesforce, Salesforce Data Cloud
Generative AI and Service Cloud
23May

Generative AI and Service Cloud

Salesforce Service Cloud users are set to receive more Einstein 1 generative AI tools in June and October. A key development is the expansion of automated customer conversations across more sales and marketing platforms. Generative AI and Service Cloud family of tools is growing. This insight aims to uncover the numerous use cases of generative AI in the modern contact center. We’ll help you understand how generative AI can fast track your contact center’s efficiency, improve data analysis capabilities, streamline QA and coaching processes, and make customers’ experiences better.  Today, Salesforce launched Unified Conversations for WhatsApp, which automates bot responses to customer inquiries related to targeted marketing messages on the popular messaging app. Additionally, Salesforce plans to extend support to Line, a messaging app popular in Japan, later this year. These services are built on Salesforce’s Einstein 1 generative AI platform. The platform’s bots aggregate structured and unstructured CRM, product, service, and other data through Salesforce Data Cloud to generate personalized responses. These new features enable conversations to be routed to the digital channels where a Salesforce user’s customers are the most active. And to move omnichannel as customers needs change. Salesforce is also introducing a “bring your own channel” connector to support digital channels not natively covered by the platform. Current examples might include TikTok, Discord, and South Korea’s KakaoTalk, according to Ryan Nichols, Chief Product Officer for Salesforce Service Cloud. Generative AI and Service Cloud “It’s about getting data from all your conversations with customers from Service Cloud into Data Cloud and using that to not just deliver excellent customer service, but also grow your business,” Nichols said. Salesforce Einstein Conversation Mining, a Service Cloud feature currently in beta, aggregates conversations across customer channels to surface insights on the topics customers need help with. This aims to turn inbound customer service from a cost center into a revenue center, a goal long pursued at conferences like Dreamforce and ICMI. This massive change drives more than revenue, it drives ROI. Performance metrics such as time-to-answer and hold-time reduction have traditionally pressured agents to minimize call duration to retain their jobs. Now Salesforce is going to help them. While some skeptics question if generative AI can achieve this ambitious goal, Constellation Research analyst Liz Miller suggests it might be possible. Having previously managed a contact center herself, Miller recognizes the transformative potential of generative AI. With the aid of data, bots, and copilot counterparts assisting humans, agents could save time and access the right information to upsell customers during service engagements. Here are some of the ways Generative AI will change customer service forever. 1. Monitor and Ensure Compliance Maintaining compliance is crucial for fostering customer trust, preserving a positive brand image, and avoiding hefty privacy and compliance fines. In a contact center, compliance mistakes can quickly escalate into costly lawsuits and revenue losses. Generative AI allows your compliance team to proactively manage compliance by quickly identifying trends and addressing issues in real time. Instead of waiting for a compliance issue to escalate, you can fine-tune your AI model to provide compliance insights whenever necessary. For instance, you can ask: This approach offers more comprehensive insights than scorecards, which often lack context and accuracy. Generative AI’s analytical capabilities provide actionable insights to improve compliance across your contact center. 2. Get Insights About Your Call Center Performance at a Glance Generative AI language models make it easier than ever to gain insights into your contact center’s performance. Simply ask the model for the information you need. For example, you can inquire about the real-time average handling time (AHT) by asking, “What is the average handling time today?” But that’s just the beginning. With an advanced language model, you can compare metrics across different quarters or generate ideas for coaching plans by asking for each agent‘s strengths and weaknesses and suggestions for improvement. 3. Automate Post-Call Work Generative AI assistants can act as real-time notetakers, summarizing 100% of calls and freeing agents from manual note-taking. This automation makes after-call work effortless, generating comprehensive and compliant notes with a single click. 4. Capture Coachable Moments Easily Incorporating real-world coachable moments into your sessions is essential for tangible performance improvements. Generative AI can identify areas where agents typically struggle without requiring hours of call listening and note-checking. Traditional methods mean compromising on the specificity of coaching due to time constraints, especially when managing large teams. Generative AI solutions, however, enable call center managers to obtain detailed insights about each agent’s performance quickly. This allows for personalized coaching plans that address individual shortcomings efficiently. You can ask: 5. Improve Decision Making With Efficient Root-Cause Analysis Effective decision-making can transform your contact center. However, many managers struggle to identify the root causes of performance issues. Generative AI algorithms can analyze vast amounts of data and customer interactions, uncovering patterns and trends in customer and agent behavior. These insights help pinpoint the issues most impacting performance and customer satisfaction, allowing you to make informed decisions. The process is nearly fully automated, freeing your team from time-consuming data collection tasks. 6. Reduce Manual Work and Focus on Improvement Improving contact center performance requires extensive data, which is resource-intensive to collect manually. Generative AI simplifies this by analyzing customer interactions and providing actionable insights on demand. This saves time and money, allowing you to focus on improvements that deliver a higher ROI. 7. Scale What Works Discovering and scaling best practices is essential for team-wide success. Generative AI and Natural Language Processing (NLP) models can analyze customer interactions to identify effective strategies and coaching opportunities. For example, if a representative handles challenging situations well, AI can generate tips for other team members based on these successful interactions. Generative AI can identify top-performing agents and analyze their calls to extract best practices, providing a more comprehensive approach than focusing on a single agent. Queries you might use include: 8. Generate Agent Scripts Generative AI enables you to draft and fine-tune agent scripts for various customer interactions. Instead of relying

Read More
May 23, 2024in Generative AI, Salesforce Data Cloud, Salesforce Einstein, Salesforce Service Cloud
Einstein 1 Marketing and Commerce Tools
22May

Einstein 1 Marketing and Commerce Tools

Salesforce Unveils New Einstein 1 Marketing and Commerce Innovations to Enhance the Customer Journey with Unified Data and Trusted AI Einstein 1 Marketing and Commerce Tools announced at 2024 Connections event in Chicago, IL. Einstein Copilot for Marketers and Merchants: These tools enable brands to automatically generate campaign briefs, personalized content, and promotions using trusted data. Data Cloud for Commerce: Unifies business and customer data to deliver smart insights, allowing merchandisers to launch personalized promotions, offers, and shopping experiences, thus enhancing customer loyalty and boosting sales. Einstein Personalization: Uses the unified customer data profile in Data Cloud to automatically trigger the next best interaction based on customer behavior and history with a brand. Salesforce Expands Einstein Copilot Capabilities Today at Connections, Salesforce (NYSE: CRM), the leading AI CRM platform, announced new features for its Einstein Copilot. This trusted conversational AI assistant now aids marketers and merchants with daily tasks, in addition to its existing functionalities for sales and service. Salesforce also introduced new tools for unifying business and commerce data, along with an AI-powered personalization engine to enhance customer interactions at every touchpoint. “With the Einstein 1 Platform, we’re giving organizations the power to unify all their data on one trusted platform. This is key to achieving actionable AI-driven results.” Ariel Kelman, President and CMO of Salesforce Why It Matters Personalization is essential for customer satisfaction and business success. However, many organizations struggle to connect the right data and touchpoints to fully utilize AI for personalization. What’s New Einstein 1 Marketing and Commerce Tools Unified Data Platform: Brands can now unlock and unify all their data on a single platform, enabling personalized engagements across marketing, commerce, sales, and service. Key innovations include: Einstein Copilot for Marketers: Einstein Copilot for Merchants: Data Cloud for Commerce: Einstein Personalization: Unified AI Assistants Powered by Trusted Data Salesforce’s Einstein Copilot for Marketers and Merchants stand out due to their integration with the Einstein 1 Platform and Salesforce metadata. Unlike typical LLMs, Einstein Copilot uses metadata to interpret prompts with complete context, ensuring relevant and secure data usage. Einstein Trust Layer: Ensures the confidentiality of data within AI responses, maintaining security, privacy, and governance. Customer Perspective Matthew Randall, Head of Software and Integration at Aston Martin, praised Salesforce for enabling personalized, VIP experiences through unified data and AI capabilities. “The Einstein 1 Platform allows us to grow and enable our AI enterprise.” Availability Einstein 1 Marketing and Commerce Tools are evolving. 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

Read More
May 22, 2024in Einstein 1 Platform

Subscribe to our mailing list. Join our mail list to receive our newsletter

We'll keep you up to date with our latest news, insights, free resources, and much more.
Don't worry, we won't spam you.
gettectonic.com