Einstein Insights Archives - gettectonic.com

21Jun

Lead Assignment Automation for Salesforce

Automating Lead Assignment for Salesforce Platforms with Lead Assignment Automation for Salesforce Effective lead assignment within Salesforce is critical to ensure that sales-ready leads are directed to the appropriate individuals at the right moment. This process should never be overlooked. Lead assignment ensures that when a lead is marketing qualified or sales qualified it is contacted. Lead assignment plays a pivotal role in ensuring that sales-ready leads are promptly delivered to the right sales representatives, which underscores the significance of automating this process across various Salesforce platforms, from Account Engagement to Sales Cloud and Marketing Cloud to Sales Cloud. The primary goal for marketers is to assign inbound leads in the most efficient manner possible, and Salesforce’s lead assignment features empower us to achieve precisely that. With automation! Whether to queues or designated account representatives, this frees up your time to go back to marketing. If you’ve been manually assigning leads up until now, get ready for a transformative experience. Lead Assignment Automation for Salesforce And for those already leveraging automated lead assignment features in your Salesforce accounts, don’t rush to stop reading just yet. Stay tuned to ensure you’re adhering to best practices and making lead assignment (also known as lead routing) as seamless as possible with this insight from Tectonic. For this insight, we’ll assume you’re using Sales Cloud alongside Account Engagement and/or Marketing Cloud. This involves two essential components to ensure smooth lead assignment: integrating and configuring your Salesforce products to work harmoniously together and setting up Lead Assignment Rules in Salesforce. Part 1 – Configuring Your Salesforce Products Integration The initial crucial step is to establish connectivity between your platforms using the Salesforce Connector for Account Engagement or Marketing Cloud Connect, depending on your usage. Connecting Marketing Cloud Account Engagement and Sales Cloud via the Salesforce Connector is relatively straightforward, enabling the two platforms to communicate and share data seamlessly, eliminating the need for manual data imports and exports by marketers. You’ll find the Salesforce Connector on the AppExchange, and Salesforce provides an implementation guide, which includes pre-installation considerations. Tectonic can assist. Ensure you’re utilizing the V2 Connector; if you’re currently using the connector but haven’t upgraded, make that your first step. Marketing Data Sharing Upon installing the Account Engagement-Salesforce Connector, you’ll encounter ‘Marketing Data Sharing,’ which allows you to control which Leads, Contacts, Opportunities, or custom objects are eligible for syncing from Salesforce to Account Engagement. This feature is ideal for organizations with multiple Business Units and can also benefit those with a single unit. MDS offers greater control over when prospect and lead records are created, contributing to effective lead management. Understanding Sync Behaviors Once your platforms are connected, make time to fully understand how data syncs between them. You can designate either Account Engagement or Salesforce as the ‘master’ values, ensuring consistency in case of discrepancies between the platforms. Additionally, you can opt to use the ‘most recently updated record’ as the standard. This option ensures data is up to date regardless of which platform it was last updated in. For Account Engagement and Sales Cloud, prospects’ records typically sync every two to four minutes, with immediate syncing for most records. However, Account Engagement processes sync queues with over 400 records in batches. Standard batch processing syncs 12,000 records per hour. Certain activities can trigger a sync, which can occur at a prospect, trigger, or system level. We recommend reviewing a comprehensive guide to Account Engagement and Salesforce sync behaviors for newcomers to this topic or to validate your current sync settings for accuracy and error-free operations. Part 2 – Setting Up Lead Assignment Planning Lead Assignment and Criteria Assuming successful integration and syncing of accounts, you’re now poised to plan and implement lead assignment using predefined criteria. Differentiate between implicit and explicit leads based on lead scoring and grading: The perfect sales-ready or marketing qualified lead will meet both explicit and implicit criteria. Therefore, your first task is to collaboratively define and document what constitutes a qualified lead, involving both marketing and sales teams. Only after establishing a clear definition of a sales-ready lead can you proceed to map out who should receive such leads, when, and how. Consider the following: Utilize these considerations to outline more precise criteria: Document your lead assignment plan offline before implementing changes in Salesforce accounts. This aids in gaining a clear understanding of the workflow and allows for validation before modifying settings that could lead to issues later. For that matter you should always document system modifications. Creating a Lead Assignment Rule in Salesforce Navigate to the ‘Marketing’ section in Salesforce and access ‘Lead Assignment Rules.’ Here, you can create a Lead Assignment Rule; note that only one rule can be active at a time. Specify the processing order for each criterion when creating a rule, prioritizing the most important criteria first. Once criteria are entered (ensuring you have necessary data values to match the rule), select the assignment action: To assign a lead to a ‘Queue,’ first create the Queue in Salesforce’s Administration > Users > Queues section. For instance, set up Queues for each region’s sales team with relevant users as members (e.g., ‘Leads – UK’ or ‘Leads – Germany’). Once activated, all leads will be assigned based on the active rule. Consider adding a final criteria to catch all other leads and assign them to a default user or queue for review and manual assignment if needed. Triggering LARs from Account Engagement/Marketing Cloud Lead assignment complexities arise when determining how leads are assigned in Salesforce via Account Engagement or Marketing Cloud. Account Engagement In Account Engagement, formerly Pardot, prospects must have an assigned user to sync with Salesforce initially. However, an assigned user bypasses the Salesforce Lead Assignment Rule. For organizations preferring a Lead Assignment Rule in Salesforce to automate large lead volumes among multiple users, select ‘Assign Prospect Via Salesforce Active Assignment Rule’ within the Completion Actions (for forms, form handlers, custom redirects, emails, and page actions), Automation Rules, or Engagement

June 21, 2023in Einstein Insights, Salesforce, Salesforce Marketing Cloud, Salesforce Marketing Cloud Account Engagement (Pardot), Salesforce Optimization, Salesforce Sales Cloud

23May

Customize Forecast Insights

Tailor your forecasts page to align with your specific business requirements by leveraging Lightning App Builder. Craft bespoke forecasts pages that integrate all necessary information crucial for your sales leaders to generate precise forecasts tailored to your unique business demands. Construct pages comprising both standard and custom components meticulously tailored to complement your distinct sales processes. Customize Forecast Insights in Salesforce. For precise forecasting based on the Opportunity, Opportunity Product, or Line Item Schedule objects, utilize a custom number field as a measure. The forecasts grid provides insights into forecasts for individual months or quarters and offers flexibility in defining the range of months or quarters, catering to your preferences. While a default one-month forecast period is established, it can be adjusted as needed to suit your requirements. Forecast categories categorize opportunities within the sales cycle based on their respective opportunity stages. Standard forecast categories such as Pipeline, Best Case, Commit, Omitted (excluded from forecasts), and Closed are available. Salesforce administrators can further enhance forecasting capabilities by introducing a Most Likely category in Lightning Experience and renaming categories for both single category rollups and cumulative category rollup scenarios. Customize Forecast Insights to see the information most important. Different users can have different views. To modify forecast categories in Salesforce: Customize the presentation of standard and custom forecast columns on the forecasts page, allowing for tailored visualization. For instance, arrange a custom Most Likely column to be positioned alongside the Open Pipeline column. For adjusting forecasts in Salesforce: Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

May 23, 2023in Einstein Insights, Salesforce Sales Cloud

17Apr

Salesforce Einstein Explained

Einstein serves as Salesforce’s integrated AI layer, intricately woven into nearly every Salesforce Cloud. Salesforce Einstein Explained. While certain features, like Opportunity Scoring in Salesforce, are now offered at no cost, many Einstein functionalities are premium add-ons for essential Salesforce products like Sales, Service, Commerce, and Marketing Cloud. A notable development came in March 2023 when Salesforce introduced Einstein GPT, an extension of the Einstein product. This groundbreaking application leverages the ChatGPT platform from OpenAI, renowned for its widespread popularity, and is anticipated to be released later this year. Thereby incorporating generative AI into many Salesforce cloud features. Salesforce AI delivers trusted, extensible AI grounded in the fabric of our Platform. Utilize our AI in your customer data to create customizable, predictive, and generative AI experiences to fit all your business needs safely. Bring conversational AI to any workflow, user, department, and industry with Einstein. Salesforce Einstein is the only comprehensive Artificial Intelligence for CRM. It is data ready to work in your Salesforce org and clouds. Einstein is an integrated set of AI technologies that make the Customer Success Platform smarter. Einstein is the only comprehensive AI for CRM. It is: Einstein enables you to become an AI-first company so you can get smarter and more predictive about your customers. What can you do with Einstein? Drive productivity and personalization with predictive and generative AI across the Customer 360 with Salesforce Einstein. Create and deploy assistive AI experiences natively in Salesforce, allowing your customers and employees to converse directly with Einstein to solve issues faster and work smarter. Empower sellers, agents, marketers, and more with AI tools safely grounded in your customer data to make every customer experience more impactful. Build and customize a conversational AI assistant for CRM. Einstein Copilot is a trusted, generative-AI powered assistant built into the user experience of every Salesforce application. Whether employee-facing or customer-facing, Einstein Copilot can automatically reason through tasks based on pre-built skills. Use prompts, APIs, apex, and more to customize your own AI assistant. Like2 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

April 17, 2023in Artificial Intelligence, Data, Einstein Insights, Generative AI, Salesforce, Salesforce Einstein

07Apr

Salesforce Einstein and Your Data

Einstein Lead Scoring is a robust tool, equipping sales teams to accelerate deal closures. Integrated into Salesforce’s Sales Cloud Einstein platform, this tool harnesses the power of artificial intelligence (AI) to analyze historical sales data, identifying leads with the highest likelihood of conversion. Salesforce Einstein and Your Data. Utilize AI to score leads based on their alignment with your company’s historical successful conversion patterns. Empower your sales team to prioritize leads according to their lead scores, and understand which fields most influence each lead score. Einstein Lead Scoring employs data science and machine learning to show patterns in your business’s lead conversion. Predicting which current leads to prioritize based on your business’s conversion patterns, Einstein offers a more straightforward, faster, and accurate solution compared to traditional rules-based lead scoring approaches. The tool examines past leads to identify commonalities with previously converted leads, scoring leads using various lead fields. Admins can exclude fields that don’t impact lead quality. Einstein also categorizes certain lead text fields, such as job titles or industries, creating associations for better pattern recognition. Einstein creates a predictive model for your organization, reanalyzing lead data every 10 days to ensure it captures emerging trends. Whether using a global model or a personalized one based on your data, Einstein Lead Scoring adds a Lead Score field to leads, allowing sales reps to prioritize work effectively. Sales representatives benefit from Einstein Lead Scoring’s ability to effortlessly identify and prioritize promising leads. The system, utilizing machine learning algorithms, scrutinizes data linked to lead records, recognizing patterns indicative of a heightened probability of conversion. Salesforce Einstein and Your Data Crafting a lead scoring model becomes a streamlined process with Einstein’s automated approach. The tool examines standard and custom fields associated with the Lead object, employing diverse predictive models like Logistic Regression, Random Forests, and Naive Bayes. Monthly model updates ensure ongoing accuracy and relevance, while leads receive scores hourly for the latest predictions. Einstein Lead Scoring facilitates lead segmentation and prioritization, offering insights into factors influencing conversion probabilities. These factors are prominently displayed on each lead record, enabling sales reps to prepare swiftly for every call, essentially providing each representative with a personal data scientist, elevating connection and conversion rates. Learn more about the lead prioritization process facilitated by Einstein Lead Scoring. Einstein Lead Scoring utilizes data science and machine learning to unveil patterns in your business’s lead conversion history, predicting which current leads to prioritize. This approach, leveraging machine learning, provides a simpler, faster, and more accurate solution compared to traditional rules-based lead scoring. The Scoring Model: Einstein analyzes past converted leads, including custom fields and activity data, to determine conversion patterns. Identifying current leads with commonalities to prior converted leads, Einstein builds one or more scoring models for your organization. During setup, Salesforce admins can choose to score all leads together or group them into segments based on field criteria. A separate scoring model is built for each lead segment, allowing admins to omit certain lead fields if necessary. The global model, utilizing anonymous data from multiple Salesforce customers, is employed when there isn’t enough lead data initially. As your organization accumulates sufficient lead data, Einstein shifts to a personalized model for better results. Einstein models are refreshed every 10 days or whenever admins update Lead Scoring configurations. Lead scores are updated at least every six hours for real-time predictions. Factors That Contribute to Scores: Einstein displays the lead’s field values with the most significant positive and negative effects on its score. These fields, known as top positives and top negatives, offer insights into why leads are likely to convert or not. However, in some cases, a lead’s score may be influenced by multiple fields with slight effects, and in such instances, top positives or top negatives may not be displayed. When Scores Don’t Appear: Several reasons may lead to a score not appearing on a particular lead: When Scores Don’t Change: Scores may not change on some leads for reasons such as: In medium to large enterprises, Sales agents manage numerous leads from various channels, and sorting through them can be overwhelming. Lead Scoring, assigning a score to a lead based on its ranking among prospects, provides a valuable indicator for Sales teams looking to focus on promising leads. Lead Scoring Definition: Lead Scoring is a score assigned to a lead, ranking it in relation to others, indicating the likelihood of conversion. In the vast sea of leads, a higher lead score serves as a handy indicator, helping Sales teams prioritize their attention effectively. While Lead Scoring has been a longstanding practice, the challenge lies in creating a consistent and effective lead scoring model. Without a reliable framework, ranking leads becomes arbitrary, leading to issues such as unknown or undocumented conversion patterns, models based on incorrect assumptions, or reliance on stale or non-relevant data. Sales Cloud Einstein addresses these challenges with Einstein Lead Scoring, utilizing machine learning and data science to discover patterns in lead conversion history. The tool autonomously selects the best predictive model for each customer, eliminating the need for statistical or mathematical expertise. Monthly model updates ensure ongoing accuracy, and leads receive scores hourly, providing businesses with the latest and most precise predictions. Einstein Lead Scoring, a key capability of Sales Cloud Einstein, revolutionizes lead conversion for sales reps. It automates the analysis of historical sales data, identifying top factors determining lead conversion likelihood. Sales reps can segment and prioritize leads, gaining insights into the factors influencing conversion probabilities, displayed prominently on each lead record. Einstein Lead Scoring acts as a personal data scientist for each sales representative, enhancing connection and conversion rates. Tectonic, as your Salesforce implementation success partner, can tailor Salesforce solutions aligned with your business needs, leveraging the power of tools like Einstein Lead Scoring. Based in Colorado, Tectonic is a Salesforce Consulting Partner, boasting a skilled team of certified Consultants, Developers, Analysts, and Project Managers. Contact us today to explore innovative Salesforce solutions for your business. Like1 Related Posts Salesforce OEM

April 7, 2023in Einstein Insights, Salesforce Einstein

Salesforce Einstein and Einstein Automate

12Jan

Einstein Lead Scoring is Based on:

Understanding What Lead scoring looks at explains how Einstein gives each lead a score based on how well the lead matches the company’s conversion patterns. Einstein Scoring Model considers: Einstein Lead Scoring uses data science and machine learning to discover the patterns in your business’ lead conversion history, and to predict which current leads to prioritize. By using machine learning, Einstein Lead Scoring provides a simpler, faster, and more accurate solution than traditional rules-based lead scoring approaches. The Scoring Model Einstein analyzes your past converted leads, including custom fields and activity data, to determine your conversion patterns. It then identifies which of your current leads have the most in common with your prior converted leads. Based on this analysis, Einstein builds one or more scoring models for your organization. During setup, Salesforce admins can choose to score all of your leads together, or group leads into segments based on field criteria. Einstein builds a separate scoring model for each lead segment. For each lead segment, admins can also choose to omit certain lead fields. When Einstein builds your scoring model, the omitted fields are ignored. When you score all leads together without creating segments, and you don’t have enough lead conversion data to build your own predictive model, Einstein uses a global model. The global model uses anonymous data from many Salesforce customers. When you accumulate enough lead data, Einstein builds a scoring model with your data and uses the model with the better results. Einstein models are refreshed every 10 days, or whenever the admin updates how Lead Scoring is configured. Lead scores are updated at least every six hours as needed. Factors That Contribute to Scores With each lead score, Einstein displays the lead’s field values that have the most significant positive and negative effects on its score. These fields are the lead’s top positives and top negatives. Sometimes, a lead’s score is due to a combination of several fields with only slight positive or negative effects, rather than a few very positive or very negative fields. In this case, Einstein doesn’t display top positives or top negatives for the lead. Like Related Posts Salesforce’s Quest for AI for the Masses The software engine, Optimus Prime (not to be confused with the Autobot leader), originated in a basement beneath a West Read more Public Sector Salesforce Solutions Public Sector Solutions revolutionize public service delivery through flexible and secure e-government tools supporting both service providers and constituents. Designing 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 Salesforce AI Einstein Next Best Action Salesforce AI Einstein Next Best Action is a feature designed to identify the most effective actions available to agents and Read more

January 12, 2023in Einstein Insights

22Nov

Preparing Salesforce Sales Cloud Data for Salesforce Einstein

Data quality holds significant importance in your CRM, even in the absence of AI, as it aids sales representatives in enhancing efficiency, fostering customer trust, and utilizing Salesforce more effectively. preparing Sales Cloud Data for Salesforce Einstein When AI is integrated, the significance of data quality is further heightened. The predictive models underlying Sales Cloud Einstein rely on your Salesforce data; hence, having complete and accurate data is crucial for Einstein to provide optimal predictions, recommendations, and insights. However, data quality isn’t the sole factor in the AI equation—data quantity is equally vital. Sales Cloud Einstein leverages machine learning to identify patterns in vast data sets, and these patterns yield reliable intelligence. To facilitate pattern identification, Sales Cloud Einstein requires a substantial amount of historical data. Einstein Readiness Assessor The Einstein Readiness Assessor is a tool that evaluates whether you meet the prerequisites for specific Sales Cloud Einstein features. This tool analyzes your Salesforce implementation, generating a personalized report indicating which Einstein features you can use immediately and which ones need further preparation. When analyzing your data, your Salesforce administrator should focus on identifying missing records, duplicate records, data standardization issues, incomplete records, and stale data. Dimensions such as age, completeness, accuracy, consistency, duplication, and usage can be used to assess data quality. To address data quality issues, the Salesforce AppExchange offers various packages and tools that provide access to reports and dashboards with just a few clicks. Once you’ve assessed the health of your data, you can develop and implement a data management plan. A typical plan establishes standards for creating, processing, and maintaining data, including naming conventions, formatting for dates and money, and standardizing field data with picklists. Workflows and Automations Workflows and automations should be implemented around processes for record creation, reviewing, updating, and archiving to maintain data integrity. Company-wide standards for data quality, ownership, responsibility for changes, and notifications for data changes should be established. Appropriate privacy levels for data, considering regulatory, legal, and contractual requirements, along with roles and permission sets for users, should be determined and set up. Monitoring, with an outlined process for quality control of data, is essential to ensure that your Salesforce data remains Sales Cloud Einstein ready. This includes determining the frequency, scope, owners, and checks for updating data, preventing duplicates, merging records, adding records, and archiving records. Preparing Sales Cloud Data for Salesforce Einstein Salesforce’s flexibility allows customization to support your company’s data management plan. Ensure all required fields for your business are mandatory in Salesforce, and use validation rules and data governance to enforce correct entries for numeric fields. Workflow rules can automate standard internal procedures and processes, saving time and preventing human error. Modify page layouts to display only relevant data to users, and use data enrichment tools available through Data Apps on the AppExchange to append data accurately. Duplicate management tools built into Salesforce help prevent the creation of new duplicates, contributing to accurate and healthy data. Data integrity, encompassing security, accuracy, and overall data quality, is crucial for every measurable success metric in your business, whether you use Salesforce as a standalone tool or in conjunction with add-ons like Sales Cloud Einstein. If the task of getting your Salesforce data Sales Cloud Einstein ready is overwhelming, the Tectonic team offers assistance. For those starting to implement Salesforce, Tectonic’s Salesforce Quickstarts are worth exploring. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

November 22, 2022in Einstein Insights, Salesforce Sales Cloud

29Jul

Einstein Opportunity Insights

What is Salesforce Einstein Opportunity Insights? Opportunity Insights provides predictions on potential deal success, reminders for follow-ups, and notifications for key milestones in a deal. Each insight is accompanied by relevant metrics that explain why it is being displayed. Where do Opportunity insights appear? Opportunity insights are visible in the Einstein Insights component on both the Home page and opportunity records. Important Changes: Einstein Account Insights and Opportunity Insights will be retired in all Salesforce orgs as of Summer ’23, effective August 16, 2023. Salesforce is directing its development efforts towards features like Pipeline Inspection and Einstein Relationship Insights. Affected Editions and Availability: This change impacts Lightning Experience in Enterprise, Unlimited, and Performance editions with the Sales Cloud Einstein add-on. After August 16, 2023, Opportunity Insights and Account Insights will no longer be accessible. Specific Retirement Date: Opportunity Insights will be officially retired on November 14, 2023. It is recommended to transition to Einstein Deal Insights for Pipeline Inspection. Reason for Retirement: Salesforce is retiring Einstein Opportunity Insights to concentrate on the development of Einstein Deal Insights for the future. Implications for Users: After November 14, 2023, Einstein Insights will be discontinued. Recommended Action: It is advisable to enable Einstein Deal Insights for Pipeline Inspection to leverage new features and enhancements. Detailed information can be found in the provided article. Consequences of Inaction: If no action is taken, Opportunity Insights will cease to appear in the component after November 14, 2023. Identifying Affected Users: Users assigned with the Sales Cloud Einstein user permission set are likely to be affected. Content updated August 2023. Like2 Related Posts 50 Advantages of Salesforce Sales Cloud According to the Salesforce 2017 State of Service report, 85% of executives with service oversight identify customer service as a Read more Salesforce’s Quest for AI for the Masses The software engine, Optimus Prime (not to be confused with the Autobot leader), originated in a basement beneath a West Read more How Travel Companies Are Using Big Data and Analytics In today’s hyper-competitive business world, travel and hospitality consumers have more choices than ever before. With hundreds of hotel chains Read more Marketing Cloud Account Engagement and Salesforce Campaigns The interplay between Account Engagement and Salesforce Campaigns often sparks confusion and frustration among users. In this insight, we’ll demystify Read more

July 29, 2022in Einstein Insights, Salesforce Sales Cloud

24Jun

Salesforce Send Time Optimization Einstein

Einstein Send Time Optimization (STO) in Marketing Cloud Engagement revolutionizes message delivery by leveraging machine learning to predict the most effective times for engagement. This feature aids marketers in enhancing email and push notification engagement by automating the analysis of each contact’s optimal send time. Key Highlights of Einstein Send Time Optimization: Einstein Send Time Optimization, available with Marketing Cloud Einstein terms, offers a powerful tool for marketers seeking to personalize and optimize the timing of their email and mobile messages, thereby maximizing engagement. Content updated February 2024. Like1 Related Posts 50 Advantages of Salesforce Sales Cloud According to the Salesforce 2017 State of Service report, 85% of executives with service oversight identify customer service as a 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 Salesforce’s Quest for AI for the Masses The software engine, Optimus Prime (not to be confused with the Autobot leader), originated in a basement beneath a West Read more Salesforce Data Studio Data Studio Overview Salesforce Data Studio is Salesforce’s premier solution for audience discovery, data acquisition, and data provisioning, offering access Read more

June 24, 2022in Einstein Insights, Marketing Automation, Salesforce Marketing Cloud

03May

Employ Marketing Cloud Data with Datorama

Unlocking the Power of Salesforce Marketing Cloud with Dataorama-Employ Marketing Cloud Data with Datorama (now Salesforce Marketing Cloud Intelligence) In the realm of modern marketing, success hinges on data-driven insights rather than creative chaos. Salesforce Marketing Cloud’s Dataorama tackles the challenges associated with marketing data, offering a robust platform to store, visualize, and leverage data from diverse sources. What is Datorama? Originally developed to streamline reporting for advertising technology companies, Datorama is now a pivotal feature within Salesforce Marketing Cloud. It caters not only to advertising but also to industries spanning automotive to publishing. Datorama empowers marketers to consolidate marketing spend, campaign results, and trends into a unified and accessible platform. Key Features and Use Cases of Dataorama (now Salesforce Marketing Cloud Intelligence): Advantages and Limitations of Datorama-Marketing Cloud Intelligence: Implementation and Adoption: To implement Datorama-Marketing Cloud Intelligence within your organization: Salesforce Marketing Cloud’s Intelligence empowers marketers to shift focus from mundane reporting tasks to creative and strategic endeavors. By harnessing the power of data integration, visualization, and AI-driven insights, organizations can elevate their marketing performance and drive business growth effectively. Employ Marketing Cloud Data with Datorama Content updated September 2023. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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

11Apr

Drive Sales and Service With Real Time Data

Sales and Service Personalization: drive sales with real time data Enhance customer and prospect interactions by integrating real-time engagement data directly into your sales and service consoles. Provide service teams with the ability to proactively address queries and deliver effective case resolutions by swiftly accessing a customer’s recent interactions across diverse business touchpoints. Empower your sales teams with deeper insights into an account or prospect’s purchase journey, enabling more relevant conversations and offers based on real-time knowledge of consumed content, viewed products, or time spent on your site. Know your buyers. Attain a comprehensive view of your buyers by combining 1st and 3rd party data with the robust capabilities of Salesforce’s industry-leading Customer Data Platform (CDP). Imagine closing prospects instantly. With real-time data, it’s possible! Real-time sales data enables you to identify recent changes, such as mergers, acquisitions, new job openings, or promotions. Equip your sales team with a competitive advantage, allowing them to promptly contact potential customers and initiate sales activities. So, what is real-time data, how does it work, and how can you implement it without a complex data infrastructure? This article explores all these aspects and highlights the benefits of utilizing accurate B2B data for real-time sales. What is real-time data? Real-time data refers to immediate and continuous access to information about sales activities, customer interactions, and market trends. For your sales and marketing teams, this means capturing, analyzing, and utilizing up-to-date data to make informed decisions, enhance sales processes, create personalized experiences, and strengthen customer relationships. Real-time data is crucial because it offers numerous benefits for B2B businesses. This insight will explore some tangible benefits that real-time data can provide for your company: Access up-to-the-minute information on customer behaviors, preferences, and buying patterns, allowing your B2B sales team to engage with prospects immediately. Real-time insights into events like funding, promotions, or team expansions can trigger timely sales activities, such as emails, LinkedIn messages, or call invitations. Immediate updates from real-time sales insights enable businesses to adjust pricing based on market fluctuations or competitive moves. Real-time data collection helps track competitor pricing, customer demand, and inventory levels, allowing for optimized pricing strategies and instant adjustments with minimal effort from your sales team. Incorporate robust key management for data security to safeguard sensitive information and avoid additional risks. When a prospect expresses interest or takes specific actions, such as visiting a website or filling out a form, you can immediately engage with them. Define sales triggers and actions, such as emailing to schedule a demo after a prospect visits your pricing page. Real-time data processing allows for automated nurturing of prospects, eliminating the need for manual tracking and outreach. Gain real-time actionable insights into sales performance, leading to accurate sales forecasting. Sales managers can monitor sales data in real time, track progress against targets, adjust strategies, and manage pipeline visibility for more precise financial projections aligned with future financial planning. Instant data offers the opportunity to personalize customer interactions more effectively. Access real-time data analytics on customer preferences, purchase history, and previous interactions to tailor relevant recommendations and provide a personalized customer experience. Real-time data analysis provides instant visibility into sales performance metrics. Sales representatives can monitor their performance, including call activity, conversion rates, and revenue generated, in real time. Immediate feedback enables reps to course-correct, improve sales techniques, and achieve better results. By monitoring real-time market trends, competitor activities, and customer feedback, sales managers can make data-driven decisions, adjust sales strategies, and seize emerging opportunities. Business intelligence tools offering real-time data services help sales teams promptly address customer issues or concerns. By tracking customer behavior, feedback, complaints, and inquiries in real time, sales reps can proactively contact customers and help resolve issues. How does real-time data work? Real-time data involves capturing specific actions on the go, such as customers’ activities on your website or offsite, like visiting sales pages, checking your company’s LinkedIn profile, or exploring similar sites. Events are collected before storing any information, allowing for instant management of sales data and predictive analytics. Marketing and Sales Use of Real-Time Data: Updating lead records in real time results in better sales performance and cost savings across the entire business. Real-time big data can be used in various ways for better business decisions, such as: Examples of Real-Time Data: Real-time intent data helps identify potential customers actively researching or showing interest in products like you are selling. This data can be gathered from various sources, including website tracking, social media monitoring, and content consumption patterns. Ultima used a real-time data solution to access intent data and direct dials, resulting in ROI in just 8 weeks. Real-time data is a valuable asset for B2B businesses, offering timely opportunities, dynamic pricing, immediate lead engagement, accurate forecasting, personalized customer interactions, instant sales performance insights, agile sales strategies, and prompt issue resolution. Understanding how real-time data works and leveraging it effectively can significantly enhance the performance and efficiency of your sales and marketing teams. How do you use data to drive sales? What is an example of a data-driven sales? A B2B company that manufactures and sells industrial equipment can use a data-driven approach that involves analyzing purchasing data from their CRM, tracking industry trends, and using customer feedback surveys to understand what customers truly value. To drive sales with real time data, you need a tool like Salesforce and Salesforce Data Cloud. A real-time data sales strategy is a strategy that focuses on delivering immediate responses from customers. The methodology of real time selling is a way for brands to interact with their customers using stuff that’s actually happening at that time. The real time sales are based on insights into a customer’s online actions. The insights are analyzed and utilized quickly with AI. Drive sales real time data. 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

April 11, 2022in Einstein Insights, Salesforce, Salesforce Commerce Cloud, Salesforce Sales Cloud, Salesforce Service Cloud

21Jan

Lead Conversion at the Speed of Einstein

The primary challenges faced by businesses today revolve around lead generation and conversion. Lead conversion with Einstein is fast. Tectonic proudly offers comprehensive solutions for both challenges through the implementation and customization of Salesforce Einstein Lead Scoring. Salesforce Einstein Lead Scoring, a pivotal feature within Sales Cloud Einstein, leverages artificial intelligence to empower sales representatives in converting leads more efficiently. By analyzing historical sales data, Einstein Lead Scoring determines the likelihood of a lead converting into an opportunity. This predictive intelligence enables sales teams to segment and prioritize leads for faster conversion. Tectonic and Lead Conversion with Einstein Let Tectonic’s’ customization and implementation services ensure that your company maximizes the value derived from Sales Cloud Einstein, setting your sales representatives up for success. The factors influencing lead conversion, as predicted by Einstein Lead Scoring, are conveniently displayed on each lead record in Salesforce, aiding sales reps in quick preparation for calls and interactions. Lead Conversion with Einstein Einstein Lead Scoring models are uniquely built for each customer and organization, analyzing standard and custom fields through various predictive models. The machine learning behind Einstein continuously improves accuracy by updating models monthly. This ensures that leads are scored every hour using the latest model, promptly adapting to any changes in lead data. Truly, the power of Einstein Lead Scoring lies in its ability to discover insights, predict lead conversion likelihood, and provide automatic insights into the newly determined score. Studies indicate that AI-powered companies spend less time prospecting and more time actively growing revenue. Einstein Lead Scoring allows your company to focus more on selling and less on prospecting, leading to faster lead conversion and shorter sales cycles. Tectonic assists in automating sales and marketing processes, integrating the capabilities of Einstein Lead Scoring into your business. With zero setup requirements, custom lead score-driven workflows, and smart lead lists. Einstein Lead Scoring ensures that your sales teams work smarter and faster. The Lead Score Your Lead Score field added by Einstein Lead Scoring in your Salesforce org lets sales and marketing teams prioritize leads. This is based on similarities to prior converted leads. Through data science and machine learning, Einstein Lead Scoring offers a faster and more accurate solution. When compared to traditional rules-based lead scoring. Your Salesforce admin, or Tectonic’s Salesforce team, can set up Einstein Lead Scoring to score all leads together. Or group them into segments based on field criteria. The dashboard provides key lead score metrics. By offering insights into average lead score by lead source, conversion rate by lead score, and lead score distribution across converted and lost opportunities. Sales Cloud Einstein Sales Cloud Einstein, with Einstein Lead Scoring, is a ready-to-use set of tools that learn from Salesforce CRM data and activities, continuously enhancing its predictions. Because Sales Cloud Einstein includes additional features such as Salesforce Inbox and Einstein Activity Capture. Einstein Opportunity Insights offers smart reminders or tasks for nurturing customer relationships. Einstein Lead Scoring helps prioritize leads for conversion. Incorporating Sales Cloud Einstein and Einstein Lead Scoring into your sales and marketing strategy can yield a great return. Your Salesforce investment will fill your opportunity pipeline. Contact Tectonic for a free consultation to explore how Sales Cloud Einstein can accelerate lead conversion for your business. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

January 21, 2022in Artificial Intelligence, Data, Einstein Insights, Salesforce, Salesforce Einstein, Salesforce Sales Cloud

19Jul

Einstein Opportunity Scoring Boosts Sales

Your business thrives on seizing the right opportunities to drive more deals. Identifying these pivotal sales chances is crucial for prioritizing and capitalizing on prospects to secure successful outcomes. Enter Einstein Opportunity Scoring Boosts Sales. Enter Salesforce’s Einstein Opportunity Scoring system, designed to gauge the likelihood of an opportunity’s success, ranging from scores of 1 to 99, powered by artificial intelligence analysis. These scores offer a clear indication of each opportunity’s potential, empowering you to prioritize effectively and maximize your business’s deal closure rates. So, how does this innovative system function? In today’s digital age, Salesforce’s Einstein Opportunity Scoring leverages AI to analyze past opportunities, scrutinizing both closed-won and closed-lost instances to identify key factors influencing scores. These factors encompass various opportunity details, historical data, and product information, culminating in accurate scoring models refreshed every few hours to ensure precision. Moreover, you have the flexibility to customize your scoring model to align with specific business needs, modifying criteria by adding or removing records or custom fields. This adaptability extends further with regular scoring model updates every 10 days, reflecting the dynamic nature of the business landscape. Accessing this feature is simple—users with a Sales Cloud Einstein license can leverage Einstein Opportunity Scoring. And even if you lack this specific license or the Sales Cloud Einstein product suite, fret not, as this feature gradually rolls out to all customers, irrespective of license status. What advantages does Opportunity Scoring offer your business? Firstly, the opportunity scorecard presents a comprehensive overview of each deal, highlighting positive and negative influencing factors, aiding in focused deal analysis. Additionally, the system offers actionable suggestions for score improvement, ensuring optimal deal management. Furthermore, Opportunity Scoring aids in opportunity tracking, preventing deal slippage, and facilitating informed decision-making. Sales representatives can leverage low opportunity scores to seek guidance from sales managers, ultimately boosting deal conversion rates. To maximize the effectiveness of Einstein Opportunity Scoring, continuous improvement is key. Ensure proper opportunity segregation, timely entry of opportunities, and accurate data updates to enhance scoring accuracy and increase deal success rates. In instances where scores may not appear, reasons could range from initial feature setup time to opportunity closure or admin exclusion. Meeting specific data requirements, including closed-won and closed-lost opportunities, and regular updates, ensures robust scoring outcomes. In conclusion, harness the power of Salesforce’s Einstein Opportunity Scoring to unlock valuable insights and predictive capabilities, driving sales success and propelling your business forward. For further insights into Einstein Opportunity Scoring, explore our blogs section for comprehensive information. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

July 19, 2021in Einstein Insights, Salesforce, Salesforce Einstein

09Apr

Einstein Opportunity Scoring

Let Salesforce’s artificial intelligence help you and your team focus on the right opportunities so you can close more deals with Einstein Opportunity Scoring. Each opportunity in Salesforce is given a score, from 1 to 99, which is available on opportunity records and list views. Sales reps use these opportunity scores to identify top opportunities. If you use Collaborative Forecasts, opportunity scores are also available on the forecasts page. Plus, use scores with reports, Process Builder, and workflows. Einstein Opportunity Scoring is available to users with or without a Sales Cloud Einstein license. Opportunity scores tell you the likelihood that an opportunity will be closed won. For each opportunity score, Einstein shows the factors that have contributed the most to the score, both positively and negatively. Einstein uses your team’s past closed opportunities, won and lost, to create a predictive scoring model. This model helps identify which opportunities are most likely to result in a win. Einstein Opportunity Scoring in Lightning In Lightning Experience, the score is shown on the compact layout of opportunity records or on the Details tab. Hover over the score to see a list of factors that contribute to the score. For example, a score could be relatively high because the opportunity is moving quickly through the stages compared to other opportunities. In Salesforce Classic, the score is shown on the record detail of opportunity records. The contributing factors are shown. You can add the Opportunity Score field to any of your opportunity list views. If you don’t see the score on public list views, ask your Salesforce admin to add it. In Lightning Experience, hover over the score in the list view to see the factors that contribute to the score. In Salesforce Classic, the contributing factors aren’t available from the list views. Instead, navigate to the opportunity record detail page. The opportunity score can be calculated using a variety of factors, such as market demand, competitive landscape, the potential ROI, and the resources required to pursue the opportunity. Einstein Opportunity Scoring provides an unbiased, objective prediction on the likelihood of a deal closing, based on data patterns from previously closed deals. Then, take the guesswork out of forecasting. Einstein Forecasting uses AI technology to bring more certainty and visibility to your forecasts. Improve forecasting accuracy, get forecast predictions, and track how sales teams are doing. What is the difference between Einstein Lead Scoring and opportunity scoring? Einstein Opportunity Scoring is part of Sales Cloud Einstein Scoring, which also includes Einstein Lead Scoring. In the hierarchy, Einstein Lead Scoring comes under Salesforce’s Sales Cloud Einstein model. Opportunity scores tell the salesperson the likelihood of an opportunity to be won. Like1 Related Posts 50 Advantages of Salesforce Sales Cloud According to the Salesforce 2017 State of Service report, 85% of executives with service oversight identify customer service as a 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 Salesforce’s Quest for AI for the Masses The software engine, Optimus Prime (not to be confused with the Autobot leader), originated in a basement beneath a West Read more How Travel Companies Are Using Big Data and Analytics In today’s hyper-competitive business world, travel and hospitality consumers have more choices than ever before. With hundreds of hotel chains Read more

April 9, 2021in Einstein 1 Platform, Einstein Insights, Salesforce Einstein, Salesforce Sales Cloud

18Feb

Opportunity Scoring with Einstein

Salesforce has placed significant emphasis on developing their new Artificial Intelligence engine, Einstein, in recent years. One standout feature that has garnered attention is Einstein Opportunity Scoring, which will become available for free following the Summer ’20 release. This feature is offered to all Salesforce customers. So, what exactly is Einstein Opportunity Scoring? It’s a system that leverages data science and machine learning to score sales opportunities, enabling users to prioritize their actions effectively. Here’s how it works: The advantages of opportunity scoring are manifold: So, how does Einstein Opportunity Scoring operate? To implement Einstein Opportunity Scoring, certain prerequisites must be met: Building the prediction set involves defining positive and negative examples based on various criteria such as past outcomes, opportunity progress, and account activity. Implementation entails setting up the prediction using the Einstein Prediction Builder, defining the segment, specifying prediction outcomes, and selecting relevant fields. After deployment, users can monitor the prediction set status and review the predictions to ensure they align with business objectives. Over time, real-life data can be analyzed to assess the accuracy and effectiveness of the predictions. To enhance opportunity scores, users are advised to maintain accurate data, progress opportunities through stages promptly, and ensure completeness of opportunity records. Access to Einstein Opportunity Scoring is included in the Sales Cloud Einstein product suite at no additional cost, accessible through the Sales Cloud Einstein For Everyone permission set. By leveraging Einstein Opportunity Scoring, Salesforce customers can optimize their sales processes, improve efficiency, and make more informed decisions to drive business success. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

February 18, 2021in Einstein Insights

11Aug

Key Features of Sales Cloud Einstein

We all get excited when new technology emerges in the marketplace. Understanding its potential impact, however, can be challenging. Sales people tend to oversell it, accounting people undersell it, and lay people misunderstand it. In the Salesforce world, new tools are coming fast and furious. Features of Sales Cloud Einstein are one of the most exciting. Do you wonder why? Let’s look at Sales Cloud Einstein to provide insights into how it can empower your organization to boost sales. The key features of Sales Cloud Einstein encompass Einstein Lead Scoring, Einstein Email Insights, Salesforce Inbox, Einstein Automated Contacts, Einstein Activity Capture, Einstein Opportunity Scoring, Einstein Opportunity Insights, Einstein Forecasting, and the Sales Analytics App. Below is an overview of the features. More in depth looks can be found in the Tectonic blog. Here’s what each feature does: Incorporating Sales Cloud Einstein Incorporating Sales Cloud Einstein into your business strategy enhances sales efficiency, forecasting accuracy, and overall performance. Features of Sales Cloud Einstein can boost your team’s productivity at every stage of the sales process with key predictions, intelligent recommendations, and timely automation. It is like having your own data science team that learns from your sales team’s selling activities and CRM data. Contact Tectonic for a comprehensive consultation on leveraging Sales Cloud Einstein to drive sales growth. To generate the most reliable intelligence, you must meet data requirements for each Sales Cloud Einstein feature. Raady for Sales Cloud Einstein? Wondering whether you’re ready for Sales Cloud Einstein or whether it can help your sales reps? Run the Sales Cloud Einstein Readiness Assessor to find out. Tectonic can help. We analyze your Salesforce implementation, in either a production or sandbox environment, and then send you a personalized report. The report tells you which Einstein features you’re ready to use now and which ones require extra steps. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

August 11, 2020in Einstein Insights, Salesforce, Salesforce Sales Cloud

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