B2B Archives - gettectonic.com - Page 6
b2b marketing cloud salesforce
08Feb

What is B2B in Marketing Cloud?

In the context of Salesforce Marketing Cloud, “B2B” refers to the Business-to-Business aspect of marketing, meaning engaging with other businesses, rather than individual consumers, to drive sales. Salesforce Marketing Cloud B2B provides tools for businesses to manage their B2B marketing efforts, including lead generation, nurturing, and campaign management.  Key aspects of Salesforce Marketing Cloud B2B: In essence, B2B marketing within Salesforce Marketing Cloud focuses on the unique needs and behaviors of business customers, providing the tools to nurture and engage with them effectively.  Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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February 8, 2024in Data, Marketing Automation, Salesforce, Salesforce Marketing Cloud
Improve Customer Experience
07Jan

Improve Customer Experience

The Importance of Customer Experience: Turning Every Interaction into a Lasting Impact Customer experience (CX) refers to every interaction a customer has with your brand—from the first touchpoint through to post-purchase support. While the term is often used broadly, its meaning is more nuanced, encompassing the entire customer journey. From the initial ad they see to the quality of their engagement with your customer support, CX reflects the customer’s perception of your brand, compared to the promises you’ve made. Improve Customer Experience. What Is Customer Experience (CX)? At its core, CX measures how customers perceive their interactions with your organization. It goes beyond customer service and spans every touchpoint, whether it’s the ease of navigating your website, the tone of your marketing emails, or the post-purchase support experience. A strong customer experience is critical for fostering brand loyalty and meeting customer expectations at every step of their journey. Why Customer Experience Matters In today’s competitive marketplace, customer expectations are at an all-time high. According to research, 80% of customers say that the experience a company provides is just as important as its products or services. Whether you’re in B2C or B2B, an exceptional customer experience translates into loyalty, brand advocacy, and revenue growth. Some key benefits of prioritizing CX include: Key Elements of a Great Customer Experience Our research highlights several factors that customers deem essential for a great experience: However, many companies fall short of these expectations. For example, 56% of customers report needing to repeat themselves to different representatives, and 55% say it feels like they’re interacting with separate departments rather than a single, unified brand. The good news? A subpar experience can be quickly remedied with exceptional customer service—75% of customers will forgive mistakes after receiving excellent support. How to Measure Customer Experience Measuring CX is essential for understanding what works and where improvements are needed. Popular methods include: Building a Successful CX Management Strategy An effective CX management strategy aligns your entire business around the customer’s needs. It should include continuous feedback loops, data-driven decision-making, and a focus on creating a customer-centric culture. Improve Customer Experience. Key Pillars of a CX Strategy: How to Improve Customer Experience Delivering a standout customer experience requires a combination of people, processes, and technology. Here are five best practices for enhancing your CX: The Role of Experience Management Customer experience management (CXM) goes hand-in-hand with a broader experience management strategy. This includes not only customer interactions but also employee experiences, product quality, and brand perception. By implementing an experience management framework, companies can align technology, culture, and six core competencies to optimize all aspects of customer engagement. The Bottom Line: Customer Experience Drives Success With Salesforce Customer experience is no longer just a buzzword—it’s a critical factor for business success. By understanding and improving the customer journey, you can foster loyalty, reduce churn, and create a long-term competitive advantage. Start by building a strong CX framework, empowering your teams, and making data-driven decisions to lead the way in customer satisfaction. Content updated August 2024. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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January 7, 2024in Data, Google, Marketing Automation, Salesforce Copilots, Technology
Salesforce Einstein Commerce
03Jan

Salesforce Einstein Commerce

Elevate Your Commerce Store Experience with Commerce Einstein Transform your commerce store with the advanced capabilities of Commerce Einstein, which includes features like Goals and Recommendations, the Commerce Concierge bot, Smart Promotions, and SEO-optimized meta tags. Salesforce Einstein Commerce, Enhance Store Performance with Goals and Recommendations Achieve key performance objectives for your store such as increased site conversion, higher site traffic, and greater average order value. Utilize an intuitive framework powered by AI recommendations to implement intelligent actions quickly and efficiently, facilitating the setup and growth of your store. Track progress with insights from Data Cloud. This feature is available for B2B Commerce and D2C Commerce in the Enterprise, Unlimited, and Developer editions. Access it through the Goals and Recommendations option in the Commerce App Navigation menu. Optimize Shopping Experience with the Commerce Concierge Bot Enhance the shopping experience by providing conversational product recommendations and reordering capabilities with the Commerce Concierge bot. Build a new bot using the Commerce Concierge template to connect your store to a new Einstein bot, or upgrade an existing bot with new Commerce Concierge bot blocks. This allows customers to authenticate, manage multiple accounts, reorder, and utilize Einstein’s generative AI features. Craft Intelligent Promotions with Einstein Create promotions effortlessly using Einstein and reliable data from Commerce Cloud. Employ natural language instructions and generative AI to quickly generate both simple and advanced promotions, making your promotional efforts smarter and more effective. Enhance SEO with Einstein Meta Tags Boost your SEO performance by using Einstein’s generative AI to create Page Title Tags and Page Meta Descriptions for products. This enriches search engines with relevant information, improving your store’s visibility. Alternatively, you can manually create and manage page meta tags through the SEO tab on a product record. Reduce Return Rates with Einstein Return Insights Analyze return reasons to refine product listings and minimize return rates. Einstein helps you identify up to 20 high return-rate products and provides analyzed and categorized return reasons, enabling you to make strategic improvements. Facilitate Product Discovery with AI-Powered Search (Generally Available) Improve your customers’ product discovery experience with Einstein semantic search. Using natural language processing, this feature interprets queries to deliver relevant results, accommodating synonyms, alternative spellings, typos, and more. For example, it matches terms like “couch” and “sofa” or “jumper” and “sweater,” aligning with the searcher’s intent. Enhance your commerce store with these innovative features from Commerce Einstein to drive growth, improve customer experience, and optimize operational efficiency. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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January 3, 2024in Generative AI, Salesforce, Salesforce Einstein
Generative AI Trends for 2024
31Dec

Generative AI Trends for 2024

It’s hard to believe that ChatGPT is only a year old. The number of exciting new product launches over the past 12 months has been astonishing — and there’s no sign of slowing down. In fact, quite the opposite. Earlier in November, OpenAI hosted DevDay, where the company announced extensive offerings across B2C and B2B markets. Cohere has doubled down on its knowledge search capabilities and private deployments. Amazon Web Services launched PartyRock, its no-code gen AI app-building playground. Generative AI Trends for 2024 you can expect to see. We believe that last month’s activity sets the stage for 2024 in the gen AI space. Here are six major trends happening across the space: While the technology’s possibilities continue to grow, we believe there are four principles for CEOs to consider as they drive their gen AI agendas. These principles draw from our experiences building gen AI applications with our clients throughout the year, as well as decades of delivering digital and analytics transformations. Be Intentional: Set Gen AI Strategy Top-Down Gen AI is a gold rush. Everyone from shareholders to employees to boards is scrambling to deploy the latest and most powerful gen AI tools, and many large organizations have over 150 gen AI use cases on backlog. While we share their excitement and admire their ambition, allowing dozens of gen AI projects to spawn across an organization puts at-scale value creation at risk. Generative AI Trends for 2024 With recent developments in the gen AI space, the proliferation of use cases and opportunities will continue to split the already divided attention of leadership teams. C-suites must bring focus with a top-down gen AI strategy, constantly asking how the technology can create enduring strategic distance between the organization and its competitors. Here are some examples from first movers: Smart organizations are taking a 2×2 approach: identifying two fast use cases to register quick wins and excite the organization while working on two slower, more transformational use cases that will change day-to-day business operations. Reimagine Entire Domains Rather Than Isolated Use Cases During 2023, most organizations began experimenting with gen AI, building one-off prototypes and buying off-the-shelf solutions. Yet, as these solutions are rolled out to end users, organizations are struggling to capture value. For example, some organizations that invested in GitHub Copilot have yet to figure out how the value capture is passed back to the business. Organizations need to reframe from isolated use cases to the full software delivery lifecycle. Scrum teams need to commit to shipping more product features, or sales need to offer more competitive pricing to win more business. Stopping at just buying a new shiny tool means the productivity gains will not translate to bottom-line gains. This often means reimagining entire workflows and domains. This serves two purposes: 1) it creates a more seamless end-user experience by avoiding point solutions; and 2) organizations can more easily track value against clear business outcomes. For example, an insurer we worked with is reimagining its end-to-end claims process — from first notice of loss to payment. For each step along the way, the insurer has identified gen AI, digital, and analytics opportunities, while never losing sight of the claims adjuster’s experience. Ultimately, this comprehensive approach made a step-change impact on end-to-end handling time. Buy Selectively, Build Strategically Matching the pace of innovation, many new startups and software offerings are entering the market, leaving enterprises with a familiar question: “Buy or build?” On the “buy” side, organizations are wary about investing in capabilities that will eventually be available for a fraction of the cost. These organizations are also skeptical of off-the-shelf solutions, unsure if the software will perform at scale without significant customization. As these solutions mature and prove their value, “buy” strategies will continue to play a central role in any gen AI strategy. Meanwhile, some organizations find compelling business cases to “build.” These players start by identifying use cases that create strategic competitive advantages against their peers by compounding existing strengths in their domain expertise, workflow integration, or regulatory know-how. For example, deploying gen AI to accelerate drug discovery has become standard in the pharmaceutical industry. Additionally, organizations are investing in data and IT infrastructure to enable their portfolio of gen AI use cases. For many organizations, there has been little to no investment in unstructured data governance. Now is the time. Build Products, Not Proofs of Concept (POCs) With the new tooling available, a talented engineer can build a proof-of-concept over a weekend. In some cases, this might be sufficient to serve an enterprise need (e.g., a summarization chatbot). However, for most use cases in a large enterprise context, proofs-of-concept are not sufficient. They do not scale well into production and their performance degrades without the appropriate engineering and experimentation. At OpenAI’s Dev Day, engineers demonstrated how hard it is to turn a POC into a production-grade product. Initially, a demo POC only achieved 45% accuracy for a retrieval task. After a few months and numerous experiments (e.g., fine-tuning, re-ranking, metadata tagging, data labeling, model self-assessment, risk guardrails), the engineers achieved 98% accuracy. Implications of Generative AI Trends for 2024 This has two implications. First, organizations cannot seek near-perfection on every use case. They need to be selective about when it is worthwhile to invest scarce engineering talent to develop high-performance gen AI applications. For some situations, 45% accuracy may be sufficient to deliver business benefits. Second, organizations need to scale their gen AI capabilities to meet their ambitions. Most organizations have identified hundreds of gen AI use cases. Therefore, organizations are turning to reusable code components to accelerate development. Dedicated engineers, often in a Center of Excellence (COE), codify best practices into these code components, allowing subsequent gen AI efforts to build off the lessons learned from pioneering projects. We have seen these components accelerate delivery by 25% to 50%. Throughout the past year, there has been an endless stream of gen AI news and hype. The coming year will likely be similar

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December 31, 2023in Generative AI
Salesforce Integrated Ecommerce Storefronts
20Dec

Salesforce eCommerce & Commerce Cloud

Salesforce eCommerce & Commerce Cloud: Everything You Need to Know What is Salesforce eCommerce? Salesforce eCommerce, powered by Salesforce Commerce Cloud, is a comprehensive, cloud-based solution that helps businesses scale, create intelligent shopping experiences, and drive revenue growth. A Unified Digital Commerce Platform Salesforce Commerce Cloud encompasses: With Commerce Cloud, businesses can build and manage their entire eCommerce operation—from responsive storefronts to complex logistics like shipping and inventory tracking. Key Features of Salesforce Commerce Cloud Commerce Cloud Digital Create fully responsive, omnichannel eCommerce websites with advanced search capabilities, secure mobile payments, and personalized customer journeys. Storefront Reference Architecture (SFRA) Launch professional eCommerce sites quickly using best-in-class tools, pre-built wireframes, and integrated digital technologies for easy customization and maintenance. Endless Aisle Enhance the shopping experience with pre-ordering, wishlists, back-in-stock alerts, and exclusive online promotions—reducing lost sales and improving inventory management. Commerce Portals Build account portals, loyalty programs, and customer communities to foster long-term engagement and brand loyalty. Order Management Optimize order processing with automated payments, easy returns, real-time order tracking, and a seamless purchasing experience. Intuitive Platform Leverage no-code tools, commerce APIs, and built-in templates to design eCommerce experiences without deep technical expertise. Unified Commerce Deliver a seamless shopping experience across digital and physical channels, ensuring consistency and convenience for customers. How Salesforce eCommerce Benefits Your Business AI-Powered Predictive Intelligence Commerce Cloud integrates Einstein AI, offering:✅ Personalized product recommendations✅ Automated marketing insights✅ Cart abandonment reduction✅ Smart search enhancements Personalized Customer Journeys Tailor every interaction with AI-driven recommendations, customized content, and omnichannel engagement strategies. Seamless Multi-Storefront Management Easily manage multiple brands, international storefronts, and localized experiences with multi-currency, multi-language, and cross-border commerce capabilities. Scalability Without Limits Handle high transaction volumes, traffic spikes, and expansive product catalogs with ease as your business grows. 24/7 Support & Strategic Guidance Benefit from Salesforce’s extensive support ecosystem, including advisory services, webinars, and AI-driven best practices to accelerate success. Salesforce Commerce Cloud + Marketing Cloud: The Perfect Pairing Salesforce eCommerce seamlessly integrates with Salesforce Marketing Cloud, enabling businesses to:🔹 Automate retargeting and abandoned cart recovery campaigns🔹 Personalize customer engagement at scale🔹 Track and analyze customer behaviors in real-time🔹 Enhance product recommendations with AI-powered insights By combining Commerce Cloud and Marketing Cloud, businesses can craft end-to-end, data-driven shopping experiences that drive higher conversion rates and customer satisfaction. Ready to Transform Your eCommerce Strategy? Whether launching a new online store or optimizing an established brand, Salesforce eCommerce offers limitless possibilities. Let’s explore how Commerce Cloud, AI, and automation can elevate your business. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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December 20, 2023in Data, Salesforce, Salesforce Commerce Cloud, Salesforce Marketing Cloud
Improve Customer Experience
18Oct

Shifting Trends in Customer Experience

Shifting Trends in Customer Experience Technology Amid Economic Challenges The customer experience technology market has expanded significantly over the past decade. However, the current economic climate is causing a slowdown in sales for this previously unstoppable industry. This shift reflects changes in how decision-makers approach purchasing customer experience software today. The Rise and Current State of CCaaS In recent years, there has been a surge in the adoption of CCaaS (Contact Center as a Service) within the customer experience technology stack. CCaaS is a cloud-based customer service solution that allows companies to operate a contact center without maintaining physical infrastructure or extensive on-premises equipment. Many leaders in CCaaS companies describe their current sales cycles as “weird,” indicating that inflation and global economic instability have finally impacted customer experience technology. Challenges in the Sales Process Brian Millham, Salesforce’s Chief Operating Officer, noted that Salesforce is experiencing “elongated deal cycles, deal compression, and high levels of budget scrutiny.” This means that getting a B2B sales prospect to say “yes” takes longer, clients are paying less, and more people are involved in the decision-making process, causing further delays. This results in frustration for software sales teams, uncertainty for marketing budgets, and broader impacts on related industries. Impact on Other SaaS Providers Workday, a SaaS application business, has lowered its revenue forecasts for the year, citing that larger customers are taking longer to finalize deals in a wavering economy. CEO Carl Eschenbach highlighted that although win rates remain strong, there is increased deal scrutiny compared to previous quarters. This sentiment is echoed across vendors selling customer experience or employee experience software. Marketing Budget Constraints Marketing leaders at customer experience software companies have described the current situation as a “tin-can” scenario when looking for marketing budgets. Despite many companies claiming that their customers are their top priority, economic anxiety leads to cuts in customer experience technology investments. Leaders are questioning the critical need for such technology, and many industries are answering with caution, reflecting a shift in technology purchasing decisions. The Role of AI in Customer Experience There were high expectations for new AI additions to software products, but the results have been mixed. Cosimo Spera, founder of Minerva CQ, noted that many companies testing AI solutions to improve customer experience have reported slow adoption by agents, resulting in increased agent handling time and costs without significant improvements in customer satisfaction or net promoter scores. Joe Fernandez, who founded Klout and is now building AllUp, remarked that companies are in a “wait and see” mode regarding AI, preferring to see stable outcomes before investing heavily in new products. Customer Experience Declines A recent WSJ article reported that customer experience in the U.S. has declined for the third year in a row, based on a Forrester report analyzing consumer perceptions. Consumers are skeptical, feeling that higher prices are not yielding better experiences. This global trend impacts various industries, underscoring the interconnected nature of today’s economy. Rethinking Contact Center Strategies Contact center consultant Michele Crocker, who has nearly 30 years of industry experience, advises companies to rethink their contact center operations rather than making sweeping cuts. She suggests optimizing organizational design and staffing, eliminating unnecessary recurring subscriptions, renegotiating vendor prices, auditing IT expenses, and considering more shared services. Crocker emphasizes the need for a leadership talent assessment to ensure the right leaders are in place to implement strategic growth agendas. She also highlights the potential savings in software costs through renegotiations and the importance of closely monitoring software licenses to avoid waste. A Contrarian Approach In times of economic downturn, a contrarian approach might be beneficial. Despite the slowdown in B2B spending, doubling down on customer experience initiatives could yield significant long-term benefits. Superior customer experiences lead to higher retention rates, increased word-of-mouth referrals, and greater customer loyalty. As many companies cut back on customer experience programs, those that maintain or enhance their efforts will be well-positioned to excel once the economy stabilizes. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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October 18, 2023in Technology
Account Planning With Salesforce
25Sep

CRM Analytics Limits

When using CRM Analytics, keep these limits in mind. API Call Limits These limits apply to all supported editions. API Call Limit Maximum concurrent CRM Analytics API calls per org 100 Maximum CRM Analytics API calls per user per hour 10,000 Dataset Row Storage Allocations per License In Salesforce org, your total row storage limit for all registered datasets combined depends on your license combination. Each license allocates a different number of rows. Baseline Row Allocation Allocated Rows CRM Analytics Plus 10 billion CRM Analytics Growth 100 million Sales Analytics 25 million Service Analytics 25 million Event Monitoring Analytics 50 million B2B Marketing Analytics 25 million CRM Analytics for Financial Services Cloud 25 million CRM Analytics for Health Cloud 25 million Extra Data Rows license 100 million Your total row storage limit is a combination of your active licenses. For example: Because the CRM Analytics Plus license includes the Sales Analytics and Service Analytics licenses, your total row allocation remains 10 billion. Similarly, the CRM Analytics Growth license includes the Sales Analytics and the Service Analytics licenses, so your total row allocation remains 100 million. However, if you obtain another Sales Analytics or Services Analytics license, your row limit increases by 25 million for each added license. Dataset Row Limits Each dataset supports up to 2 billion rows. If your Salesforce org has less than 2 billion allocated rows, each dataset supports up to your org’s allocated rows. Dataset Field Limits Value Limit Maximum number of fields in a dataset 5,000 (including up to 1,000 date fields) Maximum number of decimal places for each value in a numeric field in a dataset (overflow limit) 17 decimal placesWhen a value exceeds the maximum number of decimal places, it overflows. Both 100,000,000,000,000,000 and 10,000,000,000,000,000.0 overflow because they use more than 17 decimal places. A number also overflows if it’s greater (or less) than the maximum (or minimum) supported value. 36,028,797,018,963,968 overflows because its value is greater than 36,028,797,018,963,967. -36,028,797,018,963,968 overflows because it’s less than -36,028,797,018,963,967.When a number overflows, the resulting behavior in CRM Analytics is unpredictable. Sometimes CRM Analytics throws an error. Sometimes it replaces a numeric value with a null value. And sometimes mathematical calculations, such as sums or averages, return incorrect results. Occasionally, CRM Analytics handles numbers up to 19 digits without overflowing because they are within the maximum value for a 64-bit signed integer (263 – 1). But numbers of these lengths aren’t guaranteed to process.As a best practice, stick with numbers that are 17 decimal places or fewer. If numbers that would overflow are necessary, setting lower precision and scale on the dataset containing the large numbers sometimes prevents overflow. If your org hasn’t enabled the handling of numeric values, the maximum number of decimal places for each value in a numeric field in a dataset is 16. All orgs created after Spring ’17 have Null Measure Handling enabled. Maximum value for each numeric field in a dataset, including decimal places 36,028,797,018,963,967For example, if three decimal places are used, the maximum value is 36,028,797,018,963.967 Minimum value for each numeric field in a dataset, including decimal places -36,028,797,018,963,968For example, if five decimal places are used, the minimum value is -36,028,797,018,9.63968 Maximum number of characters in a field 32,000 Data Sync Limits If you extract more than 100 objects in your dataflows, contact Salesforce Customer Support before you enable data sync. Value Limit Maximum number of concurrent data sync runs 3 Maximum number of objects that can be enabled for data sync, including local and remote objects 100 Maximum amount of time each data sync job can run for local objects 24 hours Maximum amount of time each data sync job can run for remote objects 12 hours Data sync limits for each job:Marketo Connector (Beta)NetSuite ConnectorZendesk Connector Up to 100,000 rows or 500 MB per object, whichever limit is reached first Data sync limits for each job:Amazon Athena ConnectorAWS RDS Oracle ConnectorDatabricks ConnectorGoogle Analytics ConnectorGoogle Analytics Core Reporting V4 ConnectorOracle Eloqua ConnectorSAP HANA Cloud ConnectorSAP HANA Connector Up to 10 million rows or 5 GB per object, whichever limit is reached first Data sync limits for each job*:AWS RDS Aurora MySQL ConnectorAWS RDS Aurora PostgresSQL ConnectorAWS RDS MariaDB ConnectorAWS RDS MySQL ConnectorAWS RDS PostgreSQL ConnectorAWS RDS SQL Server ConnectorGoogle Cloud Spanner ConnectorMicrosoft Azure Synapse Analytics ConnectorMicrosoft Dynamics CRM ConnectorSalesforce External ConnectorSalesforce Contacts Connector for Marketing Cloud EngagementSalesforce OAuth 2.0 Connector for Marketing Cloud Engagement Up to 20 million rows or 10 GB per object, whichever limit is reached first Data sync limits for each job*:Amazon Redshift ConnectorAmazon S3 ConnectorCustomer 360 Global Profile Data Connector (Beta)Google BigQuery for Legacy SQL ConnectorGoogle BigQuery Standard SQL ConnectorHeroku Postgres ConnectorMicrosoft Azure SQL Database ConnectorSnowflake Input Connector Up to 100 million rows or 50 GB per object, whichever limit is reached first *When using these connectors, Salesforce Government Cloud org data is protected in transit with advanced encryption and can sync up to 10 million rows or 5 GB for each connected object, whichever limit is reached first. Note When using a Salesforce local input connection, CRM Analytics bulk API usage doesn’t count towards Salesforce bulk API limits. Use of the external Salesforce connection and output connection impacts your limits. The dataflow submits a separate bulk API call to extract data from each Salesforce object. The dataflow uses a batch size of 100,000–250,000, depending on whether the dataflow or the bulk API chunks the data. As a result, to extract 1 million rows from an object, the dataflow creates 4–10 batches. Recipe and Dataflow Limits Important In Winter ‘24, recipe runs over 2 minutes are counted against the limit. Previously, the recipe run counts weren’t correct. For more information, see Known Issue – Recipe runs are not counting towards the daily maximum run limit. Value Limit Maximum amount of time each recipe or dataflow can run 48 hours Maximum number of recipes 1,000 Maximum number of dataflows definitions (with data sync enabled) 100 Maximum number of dataflow and recipe runs in a rolling

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September 25, 2023in Data, Google, Google Analytics, Salesforce, Salesforce Government Cloud, Snowflake
06Jun

Race to AI for CX

AI emerges as a transformative force revolutionizing the customer experience (CX) landscape in the dynamic world of global e-commerce. Its ability to handle extensive data and facilitate large-scale automation empowers brands to offer tailored and seamless CX journeys, fostering customer loyalty and satisfaction. The great race to AI for CX is upon us. In the era of rapid technological advancements, organizations worldwide are in a race to integrate AI-driven capabilities across their operations. The widespread adoption of AI is fueled by its recognition not just as a technological advancement but as a strategic imperative. Businesses invest in AI to enhance operational productivity, reduce costs, elevate customer experiences, and maintain competitiveness. AI’s impact on customer experience extends to substantial improvements in Customer Relationship Management (CRM) systems. Automation of tasks like data entry, lead scoring, and follow-up reminders, coupled with intelligent insights such as predicting high-converting leads, empowers sales teams to optimize their efforts. Considering the pivotal role customers play for every business, CRM has become a launchpad for AI-led transformations throughout enterprises. Businesses swiftly integrate AI-powered experiences into sales, marketing, service, and e-commerce use cases. However, for AI investments to meet expectations, they must be built on robust data practices and trust. Data readiness, reflecting an organization’s preparedness to access and use quality data across its business, is crucial for successful AI outcomes. Ensuring trust in AI, free from data-security concerns or incorrect outcomes, is equally essential. Many companies, lacking mature data practices for advanced AI capabilities like generative AI (genAI), express significant trust concerns; nevertheless, the imperative to progress prompts continued AI investments. The deployment of AI-powered chatbots enables customer service teams to deliver convenient, 24/7 support. These chatbots, exemplified by Zendesk bots, operate round the clock, offering real-time assistance even when support agents are offline. Generative AI-powered conversational bots enhance customer self-service, reduce resolution times, and improve satisfaction by maintaining case-specific tonality and context in real time. Personalized marketing, beyond being a trend, has become a cornerstone strategy for businesses aiming to establish profound connections with their audiences. Crafting messages that resonate personally not only captures attention but also cultivates conversations and fosters lasting brand loyalty. In a digital age where user experience can make or break a brand, strategic partnerships become crucial. The race to AI for CX is on and you can’t afford to be left behind. Enhancing digital user experiences often requires collaboration with specialized partners. Regpack, a versatile payment and registration solution, exemplifies this approach by collaborating with Webeo, specialists in B2B website personalization. This partnership resulted in a 565% increase in site conversion, a 302% rise in average time spent on the site, and a significant 30% drop in bounce rates. Webeo’s personalization software enabled Regpack to identify and adapt to the diverse needs of its clientele through advanced behavioral personalization techniques. Race to AI for CX AI’s impact on marketing extends beyond being an add-on tool, serving as a fundamental game-changer for crafting bespoke customer experiences. AI seamlessly bridges the digital and physical realms, particularly in ecommerce and retail sectors, dynamically adapting products and content based on consumer behavior. AI-driven technologies interpret vast data points, allowing brands to offer hyper-personalized interactions. Real-time data analysis and pattern recognition capabilities make AI a powerful tool for creating engaging and emotionally resonant personalized experiences. In essence, AI architects a new era in marketing, where experiences are not merely personalized but dynamically respond to evolving consumer desires and expectations. Leveraging AI, brands can create narratives that consumers feel intrinsically part of, fostering profound connections. For instance, Calian IT & Cyber Solutions employs personalized marketing tactics to understand and address the unique challenges and needs of each business they serve, fostering strong, long-term relationships with clients. The key takeaway for marketers is clear – the era of generic messaging is fading. A more nuanced, data-driven, and empathetic approach is emerging. Brands that embrace this shift, continuously innovate, and create experiences that customers feel a part of will thrive. As technology advances and consumer expectations evolve, mastering the art of personalization becomes crucial to redefine the marketing landscape. Key Strategies for Exceptional Customer Experience with AI: AI and Customer Experience (CX): AI impacts the entire customer journey, from predictive and prescriptive analytics to sentiment analysis, journey mapping assistance, orchestration, dynamic pricing, virtual try-ons, and augmented reality, providing an interactive and engaging shopping experience. AI and Employee Experience (EX): Efficiencies introduced by AI in employee tasks directly benefit customers. When repetitive tasks are automated, employees gain time for critical and value-added tasks, leading to increased productivity, reduced workload, fewer errors, and improved job satisfaction. Delivering Exceptional Customer Experience with AI: As customer expectations evolve, AI offers a scalable approach for brands to exceed expectations, resulting in memorable customer experiences shaped by clear communication, seamless journeys, and engaging personalized interactions. The transformative potential of AI for CX success is evident in its ability to reshape the marketing landscape. Like1 Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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June 6, 2023in Salesforce Einstein
Slack and Salesforce
19May

Amaze Your Customers With Slack and Service Cloud For Improved Customer Service

Surpass your customers’ expectations with the combined power of Service Cloud and Slack. Drive down operating costs, enhance team productivity, and exceed customer expectations by leveraging the capabilities of Service Cloud and Slack. Understanding the current service landscape: The digital transformation, accelerated by the pandemic, has propelled customers and businesses into a new era, marked by the extensive use of diverse tools for day-to-day operations. Since 2020, Salesforce’s data indicates that achieving transparency and fostering active engagement are crucial to meeting heightened customer expectations, evident in a notable 47% surge in video support. However, a significant number of organizations face a challenge as their technology systems do not fully align with these evolving expectations. We all know it’s hard to make a good paper mache airplane if you only have a piece of paper. And technology is no different. According to Intercom, 46% of support leaders express that their tech stack acts as a hindrance to achieving organizational goals. Operating across various applications diminishes team productivity and hinders business expansion. To effectively cater to your customers, service teams must innovate and adapt to the multitude of tools, contact channels, isolated teams, and fragmented data. Support operations personnel need to address key questions: The solution lies in adopting Slack as the productivity hub, coupled with Salesforce’s Service Cloud integration. This dynamic combination unlocks your full productivity potential, fostering increased customer loyalty. Break down organizational silos and expedite case resolution for enhanced customer experiences. In the ever-evolving digital marketplace, customers demand seamless service without being transferred between agents or repeating their information. A staggering 83% of customers expect complex issues to be addressed by a single point of contact. However, traditional tiered-support models fall short of meeting these expectations. The solution lies in providing teams with a comprehensive view of the entire customer journey. By leveraging the combined capabilities of Service Cloud and Slack, organizations can achieve significant cost reductions and enhance service team productivity. Service Cloud has been shown to lower support costs by 27%, while Slack increases employee productivity by 26%, according to the 2022 Salesforce Success Metrics Global Highlights study. Swarming Swarming, facilitated by Service Cloud and Slack, revolutionizes the support approach. Unlike traditional tiered support, swarming brings service agents, engineers, and issue analysts together in real-time, eliminating the need for case escalations and customer department bouncing. The swarm team collaborates efficiently, sharing information with customers proactively. The Field Service mobile app further facilitates instant connections with experts, reducing the need for unnecessary on-site visits. Service Cloud and Slack, working together, use out-of-the-box workflows to automatically assemble cross-functional experts and create Slack channels for collaborative efforts on complex cases. This approach eliminates messy handoffs and siloed decision-making, promoting transparency. Swarming ensures that everyone involved can access the entire conversation, participate in Slack huddles, and search for resolutions to similar cases. Automation and streamlined collaboration are paramount for providing exceptional service experiences. The time factor, particularly time to resolution and time on hold, is a significant barrier. Many service agents (78%) struggle to balance speed and quality due to the challenge of working across multiple systems. The integration of Service Cloud and Slack addresses this issue by extending workflows throughout the organization. Soon, Slack GPT will further enhance CRM and conversational data, providing AI-generated summaries and enabling the creation of no-code workflows. Workflow Builder and Flow Builder, no-code tools from Slack and Salesforce, respectively, collaborate seamlessly to automate daily tasks and enhance transparency, agility, and cross-team collaboration. Successful Integration The success of this integration is evident in the substantial improvements seen by service organizations using Slack, including a 32% increase in Net Promoter Score, 27% decrease in service/support costs, 30% increase in agent productivity, and a 30% increase in customer retention. The ever-changing level of customer expectations underscores the importance of service professionals as frontline ambassadors for your brand. With 88% of customers valuing their experience with a company as much as its products, swarming becomes a strategic approach to surpass expectations. Slack Connect facilitates direct access to support for partners, vendors, and B2B customers through a dedicated channel, fostering collaborative issue resolution. Slack clips and white-glove service further enhance the support process. Clips allow users to record audio, video, and screen shares, creating a searchable database of demonstrations. Private support channels in Slack provide key customers with white-glove service, allowing them to record and upload technical issues for prompt resolution. slack and service cloud In the current remote and decentralized business workforce, Service Cloud and Slack offer an opportunity to exceed customer expectations, transform service cases into lasting relationships, cut costs, and boost team productivity. If your average call handle time is too long, if your data is too siloed, or if your customer service teams are overwhelmed, contact Tectonic today to explore a Slack and Salesforce Service Cloud Integration. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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May 19, 2023in Salesforce for Nonprofits, Salesforce Health and Life Sciences Solutions, Salesforce Hospitality Travel and Transportation, Salesforce Manufacturing Automotive Energy, Salesforce Public Sector Solutions, Salesforce Service Cloud, Salesforce Slack
Shifting KPIs With Real-Time Intelligence
25Apr

Shifting KPIs With Real-Time Intelligence

Marketing without metrics is akin to driving blindfolded. To gauge the effectiveness of their efforts, marketers are investing in analytics capabilities to gain a precise understanding of how their messages, campaigns, and marketing expenditures impact their objectives. The ability to swiftly unlock these insights empowers marketers to promptly address customer needs and make well-informed decisions to propel business growth. This is bringing about Shifting KPIs With Real-Time Intelligence In contrast to 61% of underperforming marketers, a significant 72% of high-performing marketers can analyze marketing performance in real time. This real-time analysis provides them with a distinct advantage in responding to and optimizing campaign performance. However, a notable 33% of marketers still rely on manual processes for marketing attribution, a figure that has seen marginal improvement from 34% in 2020. In 2022, 68% of marketers claim they can analyze marketing performance in real time. For organizations aiming to enhance efficiency and maximize value, identifying the right metrics to track is imperative. As marketing budgets face rigorous scrutiny, analytics offer leaders the insights needed to optimize spending and reduce acquisition costs, reinforcing the value of marketing efforts. Shifting KPIs With Real-Time Intelligence The landscape of analytics has expanded, with marketers now monitoring a comprehensive set of metrics, including year-over-year revenue and customer satisfaction. Personalization and customer touchpoints have gained prominence, leading to increased tracking of web/mobile analytics, content engagement, and customer lifetime value. Marketers are now monitoring an extensive array of key performance indicators (KPIs), encompassing revenue, customer satisfaction metrics (CSAT), web and mobile analytics, customer acquisition costs, B2B sales funnel statistics, content engagement, customer retention rates, customer referral rates, and customer lifetime value. Despite the growing sophistication in tracking various metrics, marketers highlight measuring marketing ROI/attribution as their second most significant challenge. This indicates a continued need for streamlining the reporting process to enhance efficiency and effectiveness. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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April 25, 2023in Salesforce Einstein
Cloud First
19Apr

Advances in Generative AI

What is generative AI?  Generative AI focuses on creating new and original content, chat responses, designs, synthetic data or even deepfakes.  While predictive AI worked on predefined, human supplied rules, generative AI functions somewhat autonomously. Advances in Generative AI have been groundbreaking. Advances in generative AI represent a significant advancement beyond established technologies like predictive AI, and business leaders are eagerly embracing its potential. A remarkable 91% recognize generative AI as a major advantage, driven by its diverse applications, from content creation to software development. Despite its novelty, generative AI is rapidly progressing, causing over three-quarters of business leaders to express concerns about potentially missing out on its benefits. In particular, marketing leaders are apprehensive about not fully leveraging generative AI in their workflows, with 88% worried that their companies are lagging behind. Insight Generation and Decision-Making: Going beyond traditional data analysis, generative AI excels by not only analyzing existing data but also generating potential scenarios. This predictive modeling empowers businesses to anticipate market shifts, understand consumer preferences, and identify potential risks, fostering proactive strategies over reactive ones. Generative AI’s Global Impact: Generative AI has captivated global attention, with ChatGPT becoming the fastest-growing software program in history, reaching a hundred million users within two months of its public debut. This surge has sparked an arms race among tech giants like Microsoft and Google, and AI chip maker Nvidia has witnessed increased business. Unlike previous AI programs that provided numeric scores, generative AI, including programs like Stability AI’s Stable Diffusion and OpenAI’s DALL-E, reproduces elements of the real world. Amazon announced in 2023 that its voice assistant Alexa now comes with generative AI capabilities. Apple is developing a large array of features that use generative AI, including a new version of Siri expected to launch in 2024. Mixed Modality in AI: The concept of mixed modality or “multi-modality” is taking center stage, enabling programs to fuse text, images, physical space representations, sounds, video, and entire computer functions as smart applications. This approach enhances program capabilities and contributes to continuous learning, potentially advancing the goal of “embodied AI” and robotics. Evolution of Generative AI: Generative AI will continue evolving, contributing to advancements in translation, drug discovery, anomaly detection, and the generation of new content, spanning text, video, fashion design, and music. A generative AI chatbot, for example, is a type of conversational AI system that uses deep learning and natural language processing techniques to generate human-like text responses in real-time. These chatbots can hold text-based conversations with users, understand user input, and generate contextually relevant responses. Transformative Trends in Marketing and Sales Operations: Generative AI is reshaping marketing and sales operations with key trends, including hyper-quick sales and marketing content creation, automation of repetitive tasks (e.g., keyword research, administrative work, content formatting, and data analysis), and the facilitation of sales enablement and custom materials. What is the Main Goal of Generative AI? The answer likely would vary depending on who you ask, but commonly we expect generative AI tools to change the calculus of knowledge work automation. Generative AI isn’t going to eliminate the need for human workers, but it will assist them with the ability to produce human-like writing, images, audio, or video in response to plain-English text prompts. The potential to collaborate with human partners to generate contact that represents practical work is exciting. Curious how generative AI could help your business? Contact Tectonic today to learn more. Like1 Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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April 19, 2023in Salesforce Einstein
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