Author: Lyza-Jane DeVera

  • Lane Four’s Mass Merge Package: The Smart Solution to Eliminate Duplicates and Elevate Data Quality

    Lane Four’s Mass Merge Package: The Smart Solution to Eliminate Duplicates and Elevate Data Quality

    Bad data, big costs. Improving the data quality of your business will give you a competitive edge. Why consider paying extra attention to this? Because bad data leads to costly errors and inefficiencies across all levels, which leads to more time spent correcting inaccuracies instead of addressing root causes. Duplicate records are a key component of bad data because it leads to inconsistencies, inaccurate reporting, and, on top all that, negative feedback from prospects. 

    Over time, data can get jumbled up and be filled with duplicates. This is why certain system clean-up or tech debt exercises, such as that for a data migration, requires careful planning with a clear and detailed scope. During the execution phase of a data migration, cleansing the data may be necessary. Something like this calls for bringing in our own Mass Merge tool—if you couldn’t already tell, we’ve come across and dealt with enough bad data in our line of work that we needed to create a tool to manage it. If you’re already familiar with Salesforce’s out-of-the-box Duplication Rule, then you can only imagine how massive this is! 

    Mass Merge is a deduplication solution for Salesforce that we built for our clients, enhancing data accuracy through identifying and consolidating duplicate records more efficiently. With a guided process logic builder, Mass Merge can help enforce consistency and accuracy in data entry, reduce data redundancy, improve data quality, and enhance the overall user experience in a handful of steps.

    Like we mentioned earlier, Salesforce provides the Duplication Rule out-of-the-box, which is quite convenient when starting out and finding out the best way to maintain quality control over your ever-growing collection of customer records catered to your business requirements. You can set up the criteria that you’re looking for using the Duplication Rule and combine up to three records at a time. So, how does this compare to Mass Merge?

    Well, what happens when it gets to the point where three records aren’t enough? The process of manually managing duplicates can become time-consuming and inefficient, especially when faced with a high volume of records. As your business grows, so should the way the business needs to operate.

    From our experience, our focus tends to narrow in on the three common objects that usually attract the most duplicated records: Lead, Account, and Contact. Rules are then set up to find which records could be potential duplicates.

    Now, let’s imagine that an Account was created by a different Sales Representative every time a customer revisited or reconnected with the company, but each time, the record was created differently. One could be just have captured their email and name; another could have included their name, role, and industry.

    At this stage, users can choose to search for duplicates across all accounts or by setting up a duplicate set page to define the criteria to identify potential duplicate records. Mass Merge then searches for records through Salesforce’s Duplicate Rule and generates Duplicate Record Sets that match the criteria and creates a log for review. This log helps to identify duplicates are correctly matched before proceeding with the merge. From here, Mass Merge provides options to determine which record amongst the list of duplicated records should be the Surviving record. When you merge duplicate records, the record that you keep is often referred to as the ‘Winning’ or ‘Surviving record’. This record will consolidate all important details, with the other records being merged into it and then removed, to ensure that only a single accurate record holds all important details for a single customer.

    This involves bundling all related tasks and events that were previously spread out across different Salesforce records. All related records will be reparented to the surviving record, which will ensure that no data is lost during the merge. It combines data from the duplicates while keeping the original information on the surviving record. Unless a more advanced Apex Script method is used, existing data on the surviving record will not be overwritten during the merge.

    To really show the potential of Mass Merge, let’s bring in a scenario where there are 50+ duplicates for a single person and multiple individuals that need to be deduplicated. Mass Merge can handle up to 100 records at a time per person and process multiple people simultaneously.

    Mass Merge provides a simulation mode that lets you preview the final winning record before confirming the deduplication. Our clients have found this particularly helpful, as it offers a clear visual of the final result before any changes are made, ensuring confidence in the deduplication process. Now that’s data freshness! 

    At the moment, all of our Lane Four Labs packages are free and available to Lane Four clients with active support agreements. Curious to learn more or feeling ready for more efficient processing and up-to-date information about your customers? Let’s chat!

    Author: Terrence Wong
    Salesforce Administrator

    Let’s chat!

  • Salesforce Flows Tests: Creation and Configurations

    Salesforce Flows Tests: Creation and Configurations

    Why should you consider using Flow tests? In a previous post, we covered the fundamentals and shared our experiences on how embracing this practice has benefited us internally, with our clients, and why we strongly recommend it for anyone building Flows in Salesforce. But now, let’s dive into the “how.” Keep reading to discover how to set up and configure Flow tests effectively.

    Time to Create and Configure Your Flow Tests!

    There are two ways to set up a flow test for a record-triggered flow:

    1) Create Scenarios for Unit Tests

    Open the Flow Builder and navigate to the specific record-triggered flow you want to test. Click on the “View Tests” button. This is the testing framework for record-triggered flows.  If this is your initial setup for flow tests, you’ll be directed to a welcome screen featuring a “Create” button. Click the “Create” button to begin creating your first flow test.

    Step 1: Set Test Details, Triggers, and Path

    • Add a label for your test. It is important to assign meaningful labels to each test case. These labels should accurately describe the scenario being tested.
    • When you add a label to a test, the API Name is automatically generated by combining the Flow Name with the Test Scenario label. For better clarity and simplicity in identification, it is recommended to remove the Flow Name prefix from the API Name.
    • In the Description field, provide a detailed explanation of the test scenario and clearly state the expected outcomes.
    • Next, specify the trigger condition for the test—choose whether the test should run when a record is created or updated, depending on the specific scenario you are testing.
    • Finally, select the “Path for Test” to determine which path within the flow should be executed during the test. This step ensures that the correct sequence of actions is evaluated to validate the flow’s functionality accurately.
    For example: Let’s take a flow that is designed to update the “Follow_Up_Priority__c” field in a lead record, which is determined by the lead’s “Rating” and “Region.” Specifically, if a lead is created or updated with a “Rating” of ‘Hot’ and is located in ‘North America’, then the “Follow_Up_Priority__c” field is automatically set to ‘Urgent’. Conversely, if a high-rated lead is from any region other than North America, the “Follow_Up_Priority__c” field should automatically be updated to ‘Normal’.

    Let’s set up a test for a scenario where a new lead is created, rated as High and located in North America!

    STEP 2: Set Initial Triggering Record

    • In this step, we will set up the test data. It’s important to note that the record created or updated during the flow tests will automatically be rolled back once the test concludes. Therefore, it will not be permanently committed to the Salesforce database after the test run.
    • For our test case, we will create a new lead record with the following details: the name “Elizabeth Tareen,” a rating of “Hot,” located in the region “North America,” and associated with “Test Company 1.”

    STEP 3: Set Assertions

    • Assertions are checkpoints within a test designed to verify that specific conditions are fulfilled. They are crucial for validating that the outcomes of a test match the expected results.
    • Users can include one or more assertions within a test to ensure that the flow follows the expected path. Additionally, assertions can be used to verify that specific fields are set to predetermined values. During the test run, the results are compared against these assertions; if the actual outcomes align with the expected results outlined in the assertions, the test is considered pass. If they do not match, the test fails.

    To save your test, simply click the “SAVE” button. If you wish to execute a test, use the dropdown menu next to the test and choose “Run Test and View Details.” To run one, multiple or all tests simultaneously, select the checkboxes next to each test and then click the “RUN” button located at the bottom right corner of the screen.

    After executing the test, Salesforce Flow Builder will display the specific flow path that the test followed. Additionally, it will provide the actual values from the assertions, allowing you to verify the test outcomes against the expected results.

    2) Convert Debug Run to Flow Test

    • When debugging a flow, you typically configure various parameters and inputs. What’s convenient is that you can easily transform a debug run into a flow test with just a click. After completing a successful debug run, look for the “Convert to Test” button located at the top-right of the page, adjacent to the “Edit Flow” button. Clicking on “Convert to Test” will bring up a modal where you can convert your debug run into a flow test.
    • Do note that if your debug run fails for any reason, the “Convert to Test” button will be disabled (greyed out), and you won’t be able to initiate a new test from that run. Ensure that your flow successfully completes the debug run before attempting to convert it into a flow test.
    • Add a meaningful label to your test and configure any necessary assertions to validate the expected outcomes. Once you’ve set these up, save the test and run it.

    And there you have it! By now, you should not only have a good start to understanding the what and the why of Salesforce Flow tests, but also know how to create and configure them.

    Always keep in mind, thorough testing is your go-to strategy for ensuring your Flows stay solid and dependable. So, make it a habit to test, test, and test some more before anything hits production. Stick around for more tips and insights on mastering Flow testing. Happy testing!

    Need some more advice on testing your automations within Salesforce? Let’s chat!

    Author: Nupur Patel

    Automation Specialist & Junior Salesforce Developer at Lane Four

    Let’s chat!

  • Elevate Your Digital Interactions with Experience Cloud

    Elevate Your Digital Interactions with Experience Cloud

    When customers come to Lane Four seeking a solution to enhance their interactions with customers, partners, and employees, right away (of course, pending a better understanding of the exact use cases), we usually point them in the direction of Salesforce Experience Cloud.

    Why? A lot of the time, they’re looking to build a customizable platform where they can create branded digital experiences that cater to the unique needs of their business. That’s exactly what Salesforce Experience Cloud offers! Also known in market as “Salesforce Communities”, “Salesforce sites” or “Cloud Experience”, this tool lets you share information, foster collaboration, and build a sense of community with those who matter most to your business.

    From creating customer support hubs that deliver top-notch service to developing partner portals that make necessary collaboration a way more efficient, Salesforce Experience Cloud offers a variety of use cases and features tailored to enhance business interactions.

    Need a space for employees to engage and stay informed? Or perhaps a hub for sharing knowledge and training resources? Experience Cloud has got you covered.

    In this blog post, we get into what Salesforce Experience Cloud is all about, explore its versatile use cases, and highlight the key features that make it a game-changer for businesses of all sizes. Let’s go!

    What Are the Primary Use Cases for Experience Sites?

    Experience Cloud is super versatile and actually designed to meet a wide array of business needs! Here are the primary use cases:

    • Customer Support Hubs: Create a centralized platform where customers can easily find answers, submit queries, and receive top-notch service.
    • Partner Portals: Develop seamless collaboration spaces that enable partners to access resources, share information, and work together efficiently.
    • Employee Engagement Centers: Foster a connected and engaged workforce with a dedicated portal for internal communication, updates, and team collaboration.
    • Knowledge Sharing Hubs: Build comprehensive knowledge bases where users can access, contribute, and share valuable information.
    • Training Portals: Design interactive training environments to support continuous learning and development for employees, partners, and customers.

    What Are the Building Blocks for Creating These Hubs?

    Check out some of the key features of Experience Cloud:

    Branded
    Communities

    Create and customize branded communities and portals to engage with your customers, partners, and employees.

    Personalized
    Experiences

    Tailor content and user experiences based on user roles, preferences, and behaviour to ensure relevant and engaging interactions.

    Knowledge
    Base

    Offer a comprehensive knowledge base where users can find articles, FAQs, and documentation to resolve their issues independently.

    Collaboration
    Tools

    Utilize Chatter for real-time collaboration and communication within the community, enhancing teamwork and information sharing.

    Case
    Management

    Integrate with Salesforce Service Cloud to enable case management, allowing users to submit, track, and resolve support cases.

    Customization and Branding

    Manage and distribute content efficiently with built-in content management features.

    Mobile
    Optimization

    Provide a seamless mobile experience for users, ensuring that your community or portal is accessible and functional on any device.

    Content
    Management

    Manage and distribute content efficiently with built-in content management features.

    Analytics and
    Reporting

    Gain insights into user engagement, community activity, and other key metrics with built-in analytics and reporting tools.

    Third-Party
    Integrations

    Integrate with various third-party applications and services to extend the functionality of your digital experience.

    Security and
    Access Control

    Ensure data security and control access with robust security features, including role-based access and authentication.

    So, there you have it—a quick snapshot of what Salesforce Experience Cloud can do for you and your business. It offers the look and feel of a website while ensuring your team stays connected with prospects and customers by staying connected to the data within your CRM. Still need convincing, have questions, or just curious if an Experience site is right for your business? Let’s chat.

    Let’s chat!

  • Data Migrations: Planned, Prepped, and Ready to Execute!

    Data Migrations: Planned, Prepped, and Ready to Execute!

    You hit the ground running in your early planning stages and have a clearer view of the data migration tasks ahead—thanks to that awesome Entity Relationship Diagram (ERD) you built and shared with the team. With the data prepped, you can now move on to the actual migration into Salesforce. The data dependencies highlighted in the ERD will guide the order of your imports. You may want to start by importing objects without dependencies, followed by those that rely on already imported objects. This ensures all data relationships remain intact as we transfer everything to the target system.

    The value in building and preparing an Entity Relationship Diagram (ERD) early on:

    • Data Structure Visualization: ERDs visually represent data structures, showing entities, attributes, and relationships, helping everyone understand data complexities.
    • Facilitates Communication: ERDs act as a common language for stakeholders, ensuring a shared understanding of the data model and aligning expectations.
    • Identifies Data Integrity Issues: ERDs help spot potential data integrity issues like missing relationships and redundancies early in the project.
    • Guides Database Design and Development: ERDs serve as blueprints for designing the target database schema, ensuring proper structure and optimization.
    • Ensures Comprehensive Data Mapping: ERDs aid in creating detailed data mapping documents, ensuring all necessary data is accounted for and accurately transformed during migration.

    Migrating into a sandbox

    Outside of planning and prepping the data, we recommend starting every migration by importing a sample set into a sandbox environment. This will enable you to safely test and, if necessary, refine your approach before deploying to Production. You should try to execute as much of your test plan as possible in the sandbox. If any failures occur, you must find and fix each root cause until the sample migration works flawlessly.

    For added confidence before migrating everything into the Production system, be sure to get sign-off from all stakeholders—both internal and external—on the results of the sample migration into the sandbox.

    Moving the data into Production

    Like you did in the sandbox, you will initially import a representative sample dataset into the Production system and then run your tests on it. After importing data, you should always check the import logs of your migration tool for successes and failures. If a failure occurs, go back and troubleshoot until you find the root cause, and then be sure to fix it! Then, you can try importing the failed records again.

    Important:

    IF there’s something in the logs that you don’t understand, always ask someone about it. Get the support you need before moving forward again.

    IF problems arise during the migration that weren’t detected in the sandbox, notify your supervisor immediately. Do not take further action until instructed to do so.

    When you have achieved a clean import of the sample set, your end users can then proceed with UAT, if applicable. You can import the balance of the data after the client has tested the sample set to their satisfaction.

    Define the criteria and implications that indicate when the migration is considered “complete.” Is it when testing is finished? When the client signs off on a specific document? Ensure this is clear and agreed upon to confidently confirm that all data has been migrated and transformed, allowing the teams to operate independently of your support.

    Cleansing the data

    If it is part of your responsiblities to cleanse the data in any way, including deduplication, you can design and execute a data cleansing process that produces the desired result. Lane Four Labs tools like Mass Merge and A2C Sync, or external tools like RingLead, can help with deduplication!

    Finishing up

    After the data has been successfully migrated to the new system and (optionally) cleansed, it’s time for that final sign-off. However, you should expect the unexpected, especially for large projects. After seeing the results of a migration, clients sometimes ask for changes and we must be prepared to accommodate their requests.

    And that’s a wrap! Remember, keeping your systems updated and tidy is key to success. Need a hand figuring out how to keep your go-to-market tech stack clean and optimized for attracting the right kind of business? Or maybe you have more questions about data migration? We’re here to help. Let’s chat!

    Let’s chat!

  • An Intro to Flows Tests: What, Why and Some Considerations

    An Intro to Flows Tests: What, Why and Some Considerations

    Remember those handy testing posts we shared? No worries if you missed them—we’ve got you covered. Here are a few from our QA series to get you started:


    But today, we’re diving into something a bit more specific: Salesforce Flows tests!

    Testing Flows in Salesforce, similar to any other (necessary) testing, involve giving your automated processes a thorough check-up to make sure they’re in tip-top shape before hitting production, giving you that extra confidence to ensure everything runs smoothly.

    In this post, we’ll give you the lowdown on what Flow tests are, why you should run them, and some handy considerations and best practices to keep in mind. This is just the beginning—stay tuned for more Flow-testing goodness coming your way soon! Let’s get started.

    What are Flow Tests?

    Flow Tests are automated unit tests within Salesforce that allow users to validate the functionality of their flows. These tests are designed to simulate user interactions and data inputs to ensure that flows execute correctly and handle data accurately across different scenarios. Salesforce provides the capability to create unit tests directly within the Flow Builder interface, using a straightforward and accessible UI.

    Why Flow Tests?

    • Flow tests ensure the robustness and reliability of your Flows, particularly when modifications are made. They serve as a safeguard against errors and oversights, helping maintain the integrity of our automated processes.
    • It minimizes the testing effort for end users by ensuring that every node and branch of the flow is thoroughly tested. It saves time doing regression testing as well. 
    • The interface is user-friendly and straightforward to use, as it primarily involves creating or updating records and adding assertions to test scenarios.
    • Unlike Apex classes, which capture code coverage in terms of percentages, flow tests measure coverage by tracking the nodes that are activated during the test. When you select “Run Test and View Details,” the path that the test covers will be highlighted in yellow, visually representing the flow’s coverage from the start node to the end node. This method illustrates which parts of the flow are actually being tested and which parts are not.
    • We can also test triggers and the sequence of execution that occurs downstream from the flow.

    Best Practices to Consider

    • Before activating a record-triggered flow, it is essential to test it thoroughly to ensure it produces the expected results and to identify any potential runtime failures. Make it a routine practice to unit test your record-triggered flows before activation. Thorough testing of all flow paths enhances reliability.
    • Always develop and test your flows in a Sandbox or Developer org prior to deploying them into production. 
    • Aim to cover as much of your flow branches or nodes as possible with tests. 


    Key points to remember:

    • Flow tests do not automatically execute with flow deployments.
    • Flow tests exist as a separate Metadata Component
    • Flow Tests must be deployed independently of flows
    • Flow tests are independent of flow versions; creating a new version of a flow does not copy its tests.
    • Unlike Apex Classes, flow tests require manual execution post-deployment; they will not run automatically.
    • Flow tests support both packaging and change sets, facilitating easier management in different environments.
    • The Salesforce CLI (SFDX Commands) can be used to retrieve and deploy flow tests, offering additional flexibility and control.

    And there you have it! By now, you should have a good start to understanding what Flow tests are, why they’re essential, and some best practices to ensure your automated processes are rock-solid.

    Remember, thorough testing is your best friend when it comes to maintaining the integrity and reliability of your Flows. So, make it a routine to test, test, and test again before moving anything into production. Stay tuned for more insights and tips on Flow testing coming your way soon. Happy testing! 

    Need some more advice on testing your automations within Salesforce? Let’s chat!

    Author: Nupur Patel
    Automation Specialist & Junior Salesforce Developer at Lane Four

    Let’s chat!

  • Prepping Your Data for a Migration

    Prepping Your Data for a Migration

    Now that you’ve nailed down the planning stage for your upcoming data migration, it’s time to dive into the next critical step: prepping the data. How do you ensure the data is clean and ready to move? What steps are necessary to validate and prepare the data for its new home in Salesforce?

    Preparing the data is essential to avoid any hiccups during the transition. This involves backing up and transforming the data to align with the target system’s requirements while giving you and your team confidence that you can refer back to historical data if and when it’s needed. In this blog, we’ll cover the key steps and best practices for getting your data ready for a smooth and successful migration.

    Backing Up Data

    Before interacting with the source and target systems, we must ensure that all of the data is fully backed up. If anything goes wrong, you would want to be able to restore the original data and start over. Typically, companies will design and discuss a rollback plan for such situations. It’s important to agree early on with all parties involved about where the data will be stored. To keep everyone informed and to solidify the agreement, ensure the appropriate people obtain official sign-offs once the process is confirmed and before any backups are created.

    In addition, determine with the appropriate stakeholders what happens with any “out-of-scope data”—will it still be retained somewhere, or will it be deleted? For example, if the company wants to keep this data, it may be decided that they will need to make provisions for storing it securely. Will it be your responsibility or someone elses? Make sure you and your team know! Taking these steps not only safeguards your data but also ensures a smoother transition with minimal disruptions.

    Transforming Data

    If you’ved been tasked with also transforming the company’s data for import into Salesforce, it is best practice to design and execute a data transformation process that produces the desired result.

    In Salesforce, it is likely that a company uses specific formats for fields such as dates and place names. Data formats in the company’s source system, however, may not match those in Salesforce. Therefore, you must identify any mismatched formats and determine what kind of transformation is needed to align them with the client’s Salesforce formatting. For example, you may need to convert U.S. state names into standard, two-letter state codes before you can import this data into Salesforce.

    When you export data from the source system, you must ensure that you keep the original IDs, which will become foreign keys (or external IDs) in Salesforce. You can use these foreign keys to identify each original record and confirm that data relationships in the target system match what you expect to see. During testing, foreign keys are the matching criteria that can be used to verify success. 

    After deploying to the Production system, you need to verify that the data has arrived complete and intact without disrupting the client’s Salesforce system. All automation, data relationships, and reports should remain unchanged. To achieve this, you must devise a strategy to conclusively measure the migration’s level of success. If failures occur, the testing should help identify the issues and point toward solutions. We mentioned some test strategies we recommend for data migrations in a previous post, but here are a few more articles to help guide you in determining the best testing approaches for your projects!

    Stay tuned for our next blog on executing the data migration! Got a burning question that can’t wait? Let’s chat!

    Let’s chat!

  • The Power of Salesforce Einstein: A Highlight of Some Key Features

    The Power of Salesforce Einstein: A Highlight of Some Key Features

    We took a high-level stance on all things AI recently. It’s here and it’s not going anywhere. More specifically, AI continues to transform the landscape of customer relationship management (CRM), with Salesforce’s Einstein AI stands out as a game-changer in the world of RevOps. At Lane Four, we’ve fully embraced this technology and are excited to get more of our clients on board as well. In this post, we’ll provide more insights on some key features across the Clouds that we have seen positively impact our clients’ operations. Understanding these aspects is crucial for anyone looking to harness the full potential of AI in their business operations.

    Einstein Copilot

    Einstein Copilot serves as an all-encompassing AI assistant built into Salesforce applications to ensure a seamless user experience. It can answer questions, generate content, and automate actions, boosting productivity, improving customer relationships, and increasing margins. Think ChatGPT built right into your Salesforce org!

    • Insight: Unlike other AI assistants, Einstein Copilot uses your organization’s unique data and metadata to deliver valuable customer insights and recommendations, all while maintaining privacy and data governance and without needing costly AI model training. Copilot seamlessly integrates with different Salesforce products. Take Data Cloud for example, this powerful combination allows users to engage with AI through conversational prompts, providing clear and actionable responses. With capabilities such as querying and summarizing records, creating custom actions, and generating guided action plans, Einstein Copilot leverages data from multiple sources, including your CRM and external systems and tools outside of Salesforce, to gather all active data and drive business efficiency. 

    Sales Cloud

    Einstein Lead Scoring – Einstein Lead Scoring analyzes historical sales data to predict which leads are most likely to convert. By leveraging machine learning, it provides sales teams with a prioritized list of leads, allowing them to focus their efforts where they’re most likely to succeed.

    • Insight: The ability to prioritize leads based on AI-driven predictions means sales teams can allocate their resources more efficiently, increasing conversion rates and driving revenue growth.
    •  

    Einstein Opportunity Insights – This feature offers predictive insights and recommendations on opportunities, helping sales reps understand which deals are most likely to close! It analyzes patterns and signals from CRM data, providing actionable advice on the next best actions.

    • Insight: By leveraging AI to identify high-potential opportunities, sales teams can strategically focus on the most promising deals, improving win rates and shortening sales cycles.

    Service Cloud

    Einstein Case Classification – Einstein Case Classification automates the process of categorizing and routing customer service cases. It uses natural language processing (NLP) to analyze case details and assign the appropriate category and priority.

    • Insight: Automation of case classification not only speeds up the resolution process but also ensures that cases are handled by the right agents, enhancing customer satisfaction and operational efficiency.

    Einstein Bots – Einstein Bots are AI-powered chatbots that handle routine customer inquiries and tasks. They can resolve common issues, answer frequently asked questions, and escalate complex cases to human agents when necessary.

    • Insight: By automating routine interactions, Einstein Bots free up human agents to focus on more complex issues, improving response times and customer experiences while reducing operational costs.

    Einstein Service Replies – Einstein Chat and Email Replies, as well as Reply Recommendations, provide AI-driven suggestions for responses to customer inquiries based on machine learning and historical data. It analyzes the context of the conversation to recommend the most appropriate replies, tailored to the medium being used.

    • Insight: The ability to offer contextually relevant replies for both chat and email ensures that customer service agents can maintain a consistent and efficient communication style across different channels. This reduces response times and enhances the overall customer experience by providing quick, accurate, and personalized responses.

    Data Cloud

    Einstein Data Discovery – Einstein Data Discovery analyzes large datasets to uncover patterns, trends, and actionable insights. It uses advanced algorithms to perform predictive and prescriptive analytics, providing businesses with a deeper understanding of their data.

    • Insight: The ability to automatically discover insights from vast amounts of data empowers businesses to make informed decisions, identify new opportunities, and mitigate risks more effectively.

    Einstein Analytics – Einstein Analytics offers a CRMA suite of tools for data visualization, reporting, and dashboard creation. It allows users to explore data in real-time, uncover insights, and share findings across the organization.

    • Insight: Real-time data visualization and analytics enable businesses to stay agile and responsive, quickly adapting to changing market conditions and internal performance metrics.

    Platform Development

    After learning about the advantage of Einstein for Developers at TrailblzerDX in the Spring, we thought we’d reshare some great benefits of this tool to Devs working within Salesforce. Now available in VSCode (and actively being used by our own team members!), Einstein for Developers is an AI-powered tool with access to org data, enabling it to analyze context and deliver answers with greater accuracy. Here are three of the primary features we’ve been finding super useful:

    • Generate Apex code: Ability to enter natural language instructions to describe the expected functionality and receive Apex code suggestions directly within your editor.
    • Inline Autocomplete: Receive inline suggestions while coding in Apex and LWC files, allowing you to easily select the most suitable option.
    • Test Case Generation: Ability to quickly generate test cases for apex methods, by right  clicking on an apex method and selecting ‘Generate a test’

    Some other cool Dev AI features…

    Einstein Vision and Language – Einstein Vision and Language APIs allow developers to build AI-powered apps that can analyze images and text. These capabilities include image recognition, sentiment analysis, and language translation, among others.

    • Insight: By integrating powerful AI functionalities into custom apps, businesses can enhance user experiences, automate complex tasks, and unlock new revenue streams through innovative solutions.

    Einstein Prediction Builder – Einstein Prediction Builder enables developers to create custom AI models tailored to specific business needs without requiring advanced data science skills. It leverages existing CRM data to build predictive models that can forecast outcomes and suggest actions.

    • Insight: Custom AI models tailored to unique business requirements provide a significant competitive advantage, allowing companies to proactively address challenges and seize opportunities based on accurate predictions.

    Salesforce Einstein is revolutionizing the way businesses approach CRM by providing powerful AI-driven tools across the system. At Lane Four, we’re not only harnessing these capabilities to optimize our operations but also empowering our clients to leverage AI for their success. By staying informed about these features, businesses can unlock the full potential of AI and thrive in an increasingly competitive landscape.

    Let’s chat!

  • Embracing AI: Our Journey with Salesforce Einstein

    Embracing AI: Our Journey with Salesforce Einstein

    No beating around the bush here: the surge in AI has surely shaken up the town in recent years. While it’s actually been around for a while now, with Salesforce first launching Einstein in 2016, the platform has grown and transformed exponentially since then, integrating more sophisticated features, expanding its capabilities across the Salesforce ecosystem, and making AI accessible to a wider range of CRM users in different roles. This progression reflects the growing importance of AI in business operations and its potential to drive transformative outcomes. 

    Now, with the launch of Einstein 1, Salesforce is bringing in advanced GenAI features, with newer capabilities seamlessly blending with existing predictive tools, all supported by a comprehensive, reliable, automated, and open Customer 360 platform.

    So, what do we think about it?

    Our journey with Einstein, and well, AI in general, began with curiosity and a touch of skepticism, and we’re sure we weren’t alone in that. But as we dove into its capabilities, especially over the past year, our confidence in AI skyrocketed. From predictive analytics to intelligent automation, Einstein has empowered us to make data-driven decisions with more precision, just feeding our curiosity for what else it can help us achieve. In turn, this newfound confidence hasn’t just improved our operations; it’s also enabled us to positively recommend AI features to our clients.

    As consultants in the RevOps space, the focus has consistently been on optimizing strategies around processes, people, tools, and data to help teams work smarter (not harder), while ensuring alignment and maximizing the performance of their revenue engine. Salesforce Einstein fits perfectly into this narrative, providing actionable insights and automating routine tasks. This allows our clients to concentrate on what truly matters: building relationships and driving revenue.

    Incorporating AI is trending, for sure. But after trying and applying it internally and now making recommendations, we believe it’s not just a trendy move; it’s a strategic one. It aligns with current industry discussions about the future of work and digital transformation. By embracing Einstein, we’re not only keeping pace with these conversations but also leading them, helping our clients navigate the complexities—and their own skepticism—of AI so that they can take a step forward, harnessing its full potential.

    Understanding these features is crucial for readers because AI is no longer a futuristic concept—it’s a practical tool that can significantly enhance efficiency, productivity, and decision-making. By integrating Salesforce Einstein into their operations, businesses can stay ahead of the curve, deliver better customer experiences and achieve sustainable growth. We’re constantly learning and applying new insights to deliver the most up-to-date and reliable solutions to our clients.

    Stay tuned as we dive deeper into our experiences with AI within Salesforce, sharing how-tos, best practices, insights, and recommendations that will empower you to confidently integrate AI into your own operations. Ready to get ahead and know more? Let’s chat.

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  • Building Effective Salesforce Flows: Considerations of Scope, Scale, and Performance

    Building Effective Salesforce Flows: Considerations of Scope, Scale, and Performance

    Salesforce Flows are a powerful tool for automating business processes, but building effective Flows requires careful planning and consideration of several factors. In this blog, we’ll discuss key considerations for planning, scope, scalability, and performance to help you create efficient and effective Salesforce Flows.

    First, Plan How the New Automation Will Work!

    Before diving into building a new Flow, it’s crucial to plan out the logic. Using tools like Lucidchart, Miro, or other diagram creating tools to map out each Flow can save time and reduce errors. Detailed planning early on helps prevent costly mistakes and ensures that the final product meets the client’s needs.

    Be Aware of Scope

    Understanding and adhering to the scope of the project is critical. Staying focused on the agreed-upon deliverables is essential, even when other issues arise. While it might be tempting to address additional problems, maintaining a clear focus on the agreed-upon project roadmap ensures that the primary objectives are met on time and within budget. This approach helps manage expectations and keeps projects on track.

    The scope is can however, be influenced by the type of Salesforce automation required. Sometimes, the necessary automation exceeds what Flows can handle, and we must resort to using Apex code. Recognizing these limitations early can save time and resources.

    Be Mindful of Scalability

    One common mistake when designing Salesforce automation is focusing solely on immediate needs without considering future growth. Always assume that the organization could experience rapid expansion, and design Flows to be scalable. For instance, using Subflows instead of a single large Flow can enhance scalability and maintainability.

    When we identify areas with limited scalability, it’s important to note these and explore corrective options. Communicating these findings to the client and providing recommendations ensures they understand the potential limitations and future-proofing considerations of their Salesforce implementation.

    Be Mindful of Performance

    Efficiency is key to building effective Salesforce Flows. The simplest solution is often the best, avoiding unnecessary complexity that can lead to performance issues. Structuring Flows to minimize repetition and be economical with resources results in faster and more maintainable automation.

    Thorough testing, especially in mature Salesforce orgs, is crucial to ensure new automation does not negatively impact performance. This step helps identify potential bottlenecks and optimize Flows for better performance.

    Building effective Salesforce Flows requires careful planning and consideration of scope, scalability, and performance. By taking the time to map out the logic, adhering to the project scope, designing for scalability, and optimizing for performance, you can create robust automation that meets client needs and stands the test of time. Remember, thoughtful design and regular reviews are your best allies in delivering high-quality Salesforce solutions. Have some ideas for automations you’d like to take a look at with us? Let’s chat!

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