Tag: ai

  • Pip Tip #8 – Salesforce coloured favicons

    Pip Tip #8 – Salesforce coloured favicons

    Salesforce Coloured Favicons

    A favicon (short for “favorite icon”) is the small icon that appears in a browser tab next to a website’s title. You can find examples of this in your bookmarks, browser history, and sometimes even in shortcut icons on your desktop or mobile device!Navigating multiple Salesforce orgs simultaneously can be confusing, but the Salesforce Colored Favicons Chrome extension offers a simple solution.

    This handy extension changes the default Salesforce favicon to a unique color for each org, making it easier to distinguish between them at a glance.

    With Salesforce Colored Favicons, you can:

    • Reduce Confusion: Quickly identify different orgs by their distinct favicon colors, helping you avoid mistakes and improve efficiency.
    • Enhance Productivity: Streamline your workflow by easily switching between orgs without losing track of which environment you’re working in.
    • Customisation: Tailor the colours to suit your preferences or organisational needs, ensuring a consistent and intuitive browsing experience.
  • Pip Tip #6 – The end of meeting admin with vinton

    Pip Tip #6 – The end of meeting admin with vinton

    The End of Meeting Admin with Vinton

    Vinton is an AI powered meeting assistant and notetaker from the team over at Native Video.

    Once Vinton has been allocated an email address, simply invite it into meetings as you would with any other team member. Vinton will record and transcribe the meeting, before uploading the recording and transcript to relevant Salesforce records.

    Beyond this, Vinton will condense meetings into an executive summary so that concise updates are always available in Salesforce, extract next steps to create and assign tasks in Salesforce, and even draft follow up emails.

    A Vinton component can even be added to your email integration pane for quick access from your mailbox.In summary,

    Vinton frees up your users to focus on their clients rather than handling Salesforce admin and ensures that your org remains up to date with the quality data and relevant information.

  • Pip Tip #4 – Become a flow wizard

    Pip Tip #4 – Become a flow wizard

    Become a Flow Wizard

    The Salesforce Summer ‘24 Release brings even more power to Flow — making it easier than ever to automate, customise, and scale your processes.

    Alongside the classic options like Screen Flows, Auto-Launched Flows, and Record-Triggered Flows, this release introduces new Flow types designed to help you streamline work and accelerate delivery.

    Now, you can choose to:· Start from scratch and build your own workflow· Or kick things off with a pre-built template tailored to common use cases

    Here are a few of the new options you can explore:

    • Send Email Flow: Quickly create a flow that sends an email based on a user action or update
    • Create Records Flow: Automatically generate records based on input or conditions
    • Update Records Flow: Make changes to existing records without manual updates
    • Get Records Flow: Retrieve data from Salesforce based on specific criteria
    • Delete Records Flow: Easily automate the safe removal of records as part of a process
    • Create Screen Flow from Template: Save even more time with guided, pre-designed UI flows

    Whether you’re building your first flow or refining an existing automation, there’s a type to fit every need.Take a look at the new tools and start turning ideas into impact – faster than ever.

  • Pip Tip #1 – How Einstein search can relieve your admin burdens

    Pip Tip #1 – How Einstein search can relieve your admin burdens

    How Einstein Search can Releive Your Admin Burdens

    Einstein Search is an AI-powered search capability that allows users to quickly find relevant information across Salesforce objects, records, and files. It uses natural language processing (NLP) and machine learning to understand the intent behind a user’s search query and provide more relevant and personalised search results.

    Leveraging Einstein Search has many benefits, such as improved search relevance, significant time-savings and contextualised results.

    Explore cases to resolve priority issues faster, locate relevant reports in an instant and easily filter your records with Salesforce’s intuitive search tool.

    How to Use Einstein Search:

    • Enter your search query in the Salesforce search bar using natural language phrases or keywords.
    • Einstein Search will analyse the query and provide a ranked list of relevant records, files, and other Salesforce data based on your intent and permissions.
    • You can refine your search by applying filters, such as object types or fields, to narrow down the results further!
  • Agentforce Pricing Gets Flexible: Salesforce Makes AI Adoption Easier for Trailblazers

    Agentforce Pricing Gets Flexible: Salesforce Makes AI Adoption Easier for Trailblazers

    For the early adopters, digital leaders, and curious innovators who’ve had their eye on Agentforce but felt a little stuck on how to get started, Salesforce has just dropped some news that might clear the runway for takeoff.

    Agentforce is Salesforce’s platform for building AI-powered digital agents – think of them as tireless, always-on teammates who can help with everything from customer service to sales follow-ups to employee onboarding. These agents are trained to handle specific tasks across your org, surfacing information, solving problems, and even triggering actions automatically.

    They’re not chatbots. They’re digital coworkers – and the next evolution of how we get work done.

    But despite the excitement, there’s been one recurring speed bump: pricing.

    Enter Flex Credits!

    Previously, Agentforce’s pricing was based on conversations, which worked well for some use cases but didn’t fit all. With the new Flex Credits model, Salesforce aimed to create something much more flexible, scalable, and digestible for teams looking to explore, test, and expand their digital workforce strategy. “Flex Credits ensure you only pay for the exact actions Agentforce performs‌ – ‌whether that’s updating customer records, automating complex workflows, or resolving cases.” (Salesforce, 2025).

    Here’s what we know:

    • Pay-per-action: You only use credits when an agent takes a real action (like resolving a support case or updating a record).
    • A ‘pack’ of 100,000 credits will be priced at $500
    • 20 credits = 1 action (therefore $0.10 per action)
    • No usage surprises: Clear tracking through your Salesforce Digital Wallet lets you forecast and manage AI spend with confidence.
    • Available now: Already live and available – with Enterprise Edition customers and above having access to 100,000 flex credits with Salesforce Foundations!

    This change allows users to start small, experiment with different agent use cases, and scale what works – without overcommitting upfront.

    The Flex Agreement

    Notably with this announcement, Salesforce is also introducing a Flex Agreement, which allows you to reallocate budget between user licenses and AI ‘labour’. If your headcount shifts or your priorities change, you can adapt your investment accordingly.

    Essentially: if you’re running a dynamic business (and who isn’t these days?), this model works with you – only consuming credits when there are genuine, measurable business outcomes and allowing interchangability between credits and licenses. A truly future-proof offering. 

    How will this new pricing model help?

    Agentforce is powerful – but like any new tech, getting started can feel daunting. These pricing updates make it much easier to:

    • Pilot agents for niche use cases
    • Manage tech budgets encompassing AI
    • Expand success stories across departments
    • Tie investment directly to tangible business outcomes
    • Test, learn, and optimise before scaling
    • Align AI strategy to evolving priorities

    And for those already dabbling in Agentforce? This is your chance to go further, faster, with a pricing structure that truly supports growth.

    Why is this a change for the better?

    Why were people hesitant to invest? The old Agentforce pricing model, which was based on cost-per-conversation (e.g. $2 per conversation), understandably created hesitation for several key reasons:

    1. Unpredictable Costs

    Problem: Conversations are dynamic and variable. Some are short, others spiral into long interactions with multiple steps.

    Impact: It was hard for businesses to accurately forecast spend, especially if adoption scaled quickly or agents were used in more complex ways.

    2. Lack of Cost-to-Value Clarity

    Problem: One “conversation” might result in a small task (like updating a field), while another might resolve a full support case – yet both cost the same.

    Impact: This misalignment made it hard to justify ROI, especially when trying to scale use across various functions.

    3. Discouraged Experimentation

    Problem: With each conversation carrying a flat fee, businesses were reluctant to test or iterate on new use cases for fear of racking up unpredictable charges.

    Impact: It slowed innovation, especially in departments outside of customer support where value might be more indirect or exploratory.

     4. Not Tailored for Non-Conversational Agents

    Problem: Many AI agents now go beyond conversation – automating workflows, updating data, or triaging requests behind the scenes.

    Impact: A “conversation-based” price model didn’t fit these kinds of automations, leading to misalignment with modern use cases.

    5. Perceived as Too ‘One-Size-Fits-All’

    Problem: Businesses come in all shapes and sizes, and their AI strategies are equally diverse.

    Impact: The previous model lacked flexibility for teams who wanted to scale at different paces, try niche use cases, or optimise per department.

    The initial model was rigid and difficult to forecast, making it a challenge for prospects to take the first step confidently. 

    The new Flex Credits model removes those blockers by:

    • Tying cost directly to specific actions
    • Offering full transparency and control
    • Enabling experimentation without financial risk
    • Scaling smoothly with business growth

    Want to Learn More? Come See Us at Agentforce World Tour London!

    If you’re ready to roll up your sleeves and see what Agentforce can really do, join us at the Agentforce World Tour on 11 June at London’s ExCeL Centre.

    Whether you’re just curious or already building agents, our team at Performa – Agentforce specialists since the pilot – will be on hand to guide you through real-world demos, best practices, and how to get started (or get better).

    🎟️ Book your Agentforce consultation

    🧑‍💻 Get hands-on experience

    📈 See how you can achieve real business outcomes with AI-powered agents

    Ready to Get Started?

    If you’re thinking about where Agentforce could fit into your business – or wondering if you’re AI-ready at all – let’s talk.

    Book a call with us today and take the first step toward building your digital workforce.

    Learn More:

    References:Salesforce (2025) Salesforce Introduces New Flexible Agentforce Pricing to Accelerate the Digital Labor Revolution. Available [online] here.

  • Don’t sleep on Einstein

    Don’t sleep on Einstein

    Is Agentforce making Einstein redundant? How do these two Salesforce features compare? Read on to learn the ways in which Salesforce’s generative AI functionality can help you save costs and elevate the customer experience with real-world use cases.

    The Salesforce ecosystem is ablaze with ‘agentic AI’ as Agentforce rapidly accumulates more and more functionality. Recently, a member of our team was asked the question, “Will Agentforce make Einstein redundant?” – so we thought we would answer it in this article!

    The unhelpfully short answer is, ‘no’. To elaborate: different types of AI are good at different things (just like humans), although Agentforce does have some generative functionality (e.g. it creates new content based on the information it has access to), Agentforce’s main differentiator is that it is ‘agentic’, meaning that it can take action (within certain parameters or ‘guardrails’.) It is true that Agentforce and Einstein do overlap in some respects, but Einstein is a great way to explore how AI can fit into your business strategy without plunging into all of the data readiness activity required for Agentforce implementation, or taking on a credit-based payment structure – it can also provide some great, low investment quick-wins! The use cases below explain the tasks that Einstein excels at, without the need for ‘agentic’ AI.

    1. Einstein Discovery

    Einstein Discovery utilises machine learning to analyse data and uncover patterns, providing actionable insights and recommendations. It processes both Salesforce and external datasets to identify trends, correlations, and anomalies.

    Value Add: By offering data-driven insights, Einstein Discovery enables businesses to make informed decisions, optimise operations, and identify new opportunities. It transforms complex data into understandable narratives, facilitating strategic planning.

    Example Use Case: A financial services company employs Einstein Discovery to identify patterns indicating a high risk of churn. By proactively reaching out to these customers with personalised offers and support, the company reduces churn rates and improves customer retention.

    Availability: Einstein Discovery is available as an add-on in the Enterprise, Performance, and Unlimited editions of Salesforce.

    2. Einstein Prediction Builder

    This feature allows users to create custom AI models to predict specific business outcomes, such as customer lifetime value, using clicks instead of code. It leverages historical data to forecast future events.

    Value Add: Einstein Prediction Builder empowers businesses to anticipate customer behaviour and market trends, enabling proactive strategies to enhance customer retention and profitability.

    Example Use Case: A hotel chain implements Einstein Prediction Builder to forecast guest preferences for amenities and services. By analysing historical booking data, the chain predicts which guests are likely to book spa services or dine in-house, allowing for targeted promotions and personalised guest experiences.

    Availability: It is included in the Enterprise, Performance, and Unlimited editions with Sales Cloud Einstein.

    3. Einstein Next Best Action

    This tool delivers context-specific recommendations to employees and customers within their workflow. It considers business rules and predictive models to suggest the most effective actions.

    Value Add: By providing tailored recommendations, Einstein Next Best Action enhances decision-making, improves customer satisfaction, and increases conversion rates.

    Example Use Case: The customer service department in a retail company leverages Next Best Action to provide personalised product recommendations to customers. By analysing purchase history and browsing behaviour, the system suggests relevant products, enhancing the shopping experience and increasing sales.

    Availability: It is available in Essentials, Professional, Enterprise, Performance, Unlimited, and Developer editions, and it offers 5,000 strategy requests per month at no charge.

    4. Einstein Language

    Einstein Language encompasses natural language processing (NLP) capabilities that analyse text to determine sentiment and intent. It can classify text and detect customer emotions and feelings across various communication channels.

    Value Add: Understanding customer sentiment and intent allows businesses to tailor responses, improve service quality, and automate the routing of inquiries to appropriate departments.

    Example Use Case: A public transportation provider implements Einstein Language to analyse customer feedback from social media and service hotlines. By detecting sentiment and intent, the provider identifies areas of dissatisfaction and addresses them promptly, improving overall service quality.

    Availability: Einstein Language is available as an add-on across various Salesforce editions.

    5. Einstein Bots

    This is probably the feature that is most similar to Agentforce functionality. Einstein Bots are a great way to get started with chatbots, offering an affordable and less complex way of lightening the volume of service requests. These bots interact with customers on digital channels, handling routine inquiries and redirecting to human agents when required. They are integrated with CRM data to provide personalised responses. These are a great option if you need help answering day-to-day customer queries, or want to replace a lengthy and non-user-friendly FAQ section.

    Value Add: By automating common customer interactions, Einstein Bots reduce the workload of human agents, provide instant support, and enhance customer engagement.

    Example Use Case: A healthcare provider uses Einstein Bots to answer patients’ questions and manage prescription refill requests. Patients interact with the bot to understand their options and request medication, and the bot collates all the necessary information to present to medical professionals for approval, reducing administrative workload and enhancing patient convenience.

    Availability: Included in the Unlimited edition with 25 Einstein Bot conversations per user per month.

    6. Einstein Vision

    This feature offers image recognition capabilities, allowing businesses to analyse and classify images. It can identify brand logos, objects, and text within images.

    Value Add: Einstein Vision enables companies to monitor brand presence on social media, improve quality control processes, automate image categorisation, and enhance visual search functionalities.

    Example Use Case: Einstein Vision allows customers of an ecommerce company to upload images of desired products, enabling the system to identify and suggest similar items available in the retailer’s inventory. This enhances the shopping experience by making product discovery more intuitive.

    Availability: Available as an add-on in various Salesforce editions.

    7. Einstein Lead Scoring

    Einstein Lead Scoring analyses historical sales data to assign scores to leads based on their likelihood to convert. It identifies patterns that correlate with successful conversions.

    Value Add: By prioritising leads with higher conversion probabilities, sales teams can focus their efforts effectively, improving efficiency and increasing sales.

    Example Use Case: A real estate agency utilises Einstein Lead Scoring to prioritise potential property buyers. By analysing client interactions and property preferences, the agency identifies leads most likely to convert, enabling Sales and Marketing to focus their efforts effectively and increase sales.

    Availability: Part of Sales Cloud Einstein, available in Enterprise, Performance, and Unlimited editions.

    8. Einstein Opportunity Scoring

    Similar to Einstein Lead Scoring, this feature evaluates open opportunities and assigns scores indicating the likelihood of a successful close. It considers factors such as customer engagement and deal progress.

    Value Add: Einstein Opportunity Scoring helps sales representatives prioritise deals, allocate resources wisely, and forecast revenue more accurately.

    Example Use Case: A B2B energy solutions provider uses Einstein Opportunity Scoring to evaluate the potential of various sales opportunities. By assessing factors such as client engagement and proposal responses, the provider allocates resources to deals with the highest likelihood of closure, optimising sales efficiency.

    Availability: Included in Sales Cloud Einstein for Enterprise, Performance, and Unlimited editions.

    9. Einstein Forecasting

    Einstein Forecasting uses AI to predict sales revenue by analysing historical data and current pipeline information. It provides insights into forecast accuracy and potential outcomes.

    Value Add: Accurate sales forecasts enable businesses to set targets, manage resources effectively, and make informed strategic decisions.

    Example Use Case: A hotel chain leverages Einstein Forecasting to predict sales revenue by analysing historical data and current booking information. This enables the company to set realistic targets, manage inventory, and be more confident in their decision making.

    Availability: Available with Sales Cloud Einstein in Performance and Unlimited editions, and as an add-on in Enterprise edition.

    10. Einstein Activity Capture

    This tool analyses emails and calendar events to identify new contacts and relevant information, automatically updating and enriching Salesforce records.

    Value Add: By maintaining up-to-date contact information, businesses enhance data accuracy, reduce manual data entry, and improve relationship management.

    Example Use Case: A bank with a busy, growing sales team employs Einstein to identify new contacts and relevant information, ensuring that no information on potential new customers is lost in cluttered inboxes. The system automatically updates Salesforce records, maintaining up-to-date contact information, supporting the pipeline and enhancing relationship management.

    Availability: Part of Sales Cloud Einstein, available in Performance and Unlimited editions, and as an add-on in Enterprise edition.

    11. Einstein Knowledge Creation

    Einstein Knowledge Creation streamlines the process of expanding an organisation’s knowledge base by automatically drafting new articles based on customer interactions.

    Value Add: By analysing case data and conversation transcripts, Einstein identifies recurring issues and generates relevant content, ensuring that information is up-to-date and readily available for both agents and customers. This proactive approach reduces the time spent on manual article creation and helps in quicker issue resolution.

    Example Use Case: A software company notices a surge in customer inquiries about a specific error message in their application. Einstein Knowledge Creation analyses these interactions and drafts a knowledge article outlining the error, its causes, and step-by-step solutions. After review, the article is published, enabling customers to self-serve and resolve the issue without contacting support, thereby reducing the support team’s workload.

    Availability: Available with Service Cloud Einstein in Performance and Unlimited editions, and as an add-on in Enterprise edition.

    12. Einstein Work Summaries

    Einstein Work Summaries leverages generative AI to draft concise summaries of customer interactions, capturing the main issues and resolutions discussed.

    Value Add: This feature reduces the time spent on reviewing past interactions and ensures that all team members are informed of relevant activity and information.

    Example Use Case: In the healthcare industry, a patient contacts support multiple times regarding issues with accessing their online health records. Einstein Work Summaries compiles these interactions into a coherent summary, highlighting the patient’s concerns and the solutions provided. When the patient reaches out again, the support agent can quickly review the summary to understand the context and offer informed assistance, leading to a more personalised and efficient support experience.

    Availability: Available with Service Cloud Einstein in Performance and Unlimited editions, and as an add-on in Enterprise edition.

    13. Einstein Reply Recommendations (for Live Messaging)

    Einstein Reply Recommendations suggests appropriate responses during live customer chats. It identifies common queries and effective replies, presenting agents with a selection of recommended responses.

    Value Add: This accelerates response times, ensures consistency, and enhances the customer experience.

    Example Use Case: A client of a shipping company sends a chat message about the status of their order. Einstein Reply Recommendations suggests responses such as “Your order has been shipped and is expected to arrive on [date].” The agent can select and send the most appropriate reply, reducing handling time.

    Availability: Available with Salesforce Enterprise, Performance, and Unlimited editions. It requires the Service Cloud Einstein add-on license.

    14. Einstein Service Replies

    Einstein Service Replies utilises generative AI to draft fluent, courteous, and contextually relevant responses for customer service agents. By analysing historical interactions and grounding responses in the company’s knowledge base, it ensures consistency and accuracy in communications.

    Value Add: This feature significantly reduces the time agents spend composing replies, allowing them to focus on more complex customer issues.

    Example Use Case: A customer sends an email to a clothing manufacturer about the return policy for a recent purchase via email. Einstein Service Replies drafts a personalised response detailing the return process, including any necessary steps the customer should follow. The agent reviews and sends the response promptly, enhancing customer satisfaction through swift and accurate communication.

    Availability: Available with Salesforce Enterprise, Performance, and Unlimited editions. It requires the Service Cloud Einstein add-on license.

    By implementing these simple generative Salesforce AI features, organisations can enhance and automate their sales and customer service operations, improving efficiency, consistency, and customer satisfaction. As far as we can see, Einstein isn’t going anywhere. Maybe now is the time to explore which AI features are right for your business – whether that be Einstein, Agentforce, or something else entirely!

    To learn more about how you could be using Salesforce Einstien to enrich your customer experience and streamline your operations, book a call with us today!

  • How to Manage Your Digital Employees: The Agent Performance Review Programme 

    How to Manage Your Digital Employees: The Agent Performance Review Programme 

    As businesses embrace AI-driven automation, Agentforce agents are fast becoming disruptors; making customer service, marketing, operations, communications and sales functions faster and better than ever before. However, like any workforce – digital or human – ongoing management and optimisation are essential to ensure continued performance and efficiency. To get the most out of your Agentforce agents, it’s crucial to adopt best practices and leverage structured support programs designed to maximise their potential and really see those benefits come to life.

    Our Top Five Tips for Managing Your Agentforce Agents

    1. Regularly Review Agent Workflows

    Just like human employees need feedback and refinement, digital employees require ongoing assessment to ensure they’re working at peak efficiency. Schedule regular workflow reviews to identify inefficiencies, redundant steps, or outdated processes that may hinder performance. Regular check-ins can help fine-tune workflows and maintain seamless automation.

    2. Monitor Performance Metrics & KPIs

    To ensure that your digital workforce is delivering value, define key performance indicators (KPIs) such as response times, resolution rates, and customer satisfaction scores. Agentforce provides real-time analytics, allowing businesses to track agent interactions, identify bottlenecks, and optimise processes based on data-driven insights. Your agents need a goal to work towards, just like we do!

    3. Ensure Data Health (even if you aren’t yet using Data Cloud!)

    Autonomous AI-driven agents rely on real-time data to make intelligent decisions, and many Salesforce technologies now come pre-built with Data Cloud, a foundational layer to keep your data unified and ‘speaking the same language’. Keeping your data in check ensures that your agents have access to the most up-to-date and relevant information. Frequent data or Data Cloud reviews ensure your data is clean, structured, and compliant with security and privacy regulations – meaning that your digital agents will be set up for success.

    4. Optimise Agent Training & Knowledge Base

    Your digital employees are only as good as the training they receive. Updating your knowledge base regularly and refining your agent’s natural language processing (NLP) capabilities will enhance accuracy and efficiency. Providing continuous learning opportunities ensures that your AI agents evolve alongside your business needs.

    5. Experiment with New Use Cases

    AI is an evolving field, and businesses should continuously explore new applications for their digital employees. We encourage our customers (and our delivery team) to think outside the box. Where are the admin burdens? Where are the bottlenecks? What processes are the most time-consuming? An added bonus is, because this technology is brand new, if you think of it first – it might just be the thing that sets you above your competition!

    Exclusive Support: Announcing The Performa IT Agent Review Programme

    To help customers manage and optimise their Agentforce implementations, Performa IT offers an exclusive Agent Performance Review Programme – a complimentary support package included with every Agentforce deployment.

    What’s Included in the Agent Performance Review Programme?

    • Bi-Annual Health Checks – Ensure workflows are optimised and performing efficiently to best practice.
    • Annual Data Cloud Health Check – Maintains data integrity and ensures compliance with security protocols.
    • 6 One-Hour, One-to-One Support Sessions – Provide dedicated expert guidance for Q&A, troubleshooting, and eliminating risk.
    • POC Demos for New Use Cases – Facilitate the exploration of new opportunities with confidence, getting your team access to expert advice before full deployment.

    This programme ensures your digital employees continue delivering value and remain aligned with evolving business goals. However, for companies needing more extensive support, Performa IT offers two additional paid service tiers:

    For businesses that require ongoing maintenance, troubleshooting, and expert guidance beyond the complimentary programme, we offer two tailored support options:

    1. Agentforce Amplify – Essential Support & Maintenance

    Designed for businesses without in-house expertise that need on-demand support, minor adjustments, and troubleshooting assistance, the Agent Activation package includes:

    • Bug fixes to ensure smooth agent performance
    • Q&A/help desk service for operational inquiries
    • Ongoing maintenance to keep workflows efficient
    • Expedited support for urgent technical issues
    • Proactive maintenance and management of new releases

    This tier is ideal for organisations that want to retain control over their AI agents and develop their digital workforce, but need expert guidance for continued optimisation.

    2. Fully Managed Services for Agentforce

    For businesses that prefer total peace of mind, our Fully Managed Services option provides a comprehensive, customisable support offering where we take care of everything related to your digital employees and leave you to focus on the more important things. Although our managed service packages are tailored to each individual customer and their requirements, this support model can include benefits such as:

    • Management of Agents and workflows
    • Proactive maintenance and management of new releases
    • Ongoing development and enhancement of new use cases and agents
    • Regular performance evaluations
    • Troubleshooting & bug fixes
    • Ringfenced resource
    • AI-driven innovation to expand capabilities
    • Strategic planning
    • Access to technical architecture and BA support
    • 24/7 support for critical escalations

    With this package, you can focus on scaling your business while we handle the optimisation and evolution of your digital workforce.

    The Key to Maximising Your AI Resources

    Your Agentforce agents are powerful assets that can drive efficiency, improve customer experiences, and streamline business operations. However, ongoing management is crucial to ensure long-term success. With the Performa IT Agent Review Programme, our customers have access to complimentary expert support to keep AI agents performing at their best. And for those needing additional help, our Agent Activation and Fully Managed Services tiers provide flexible, tailored solutions.

    Embrace the future of AI-driven workforces with confidence – because even digital employees perform best with the right support. Contact us today to get started on your Agentforce journey!

    More on Agentforce and the Digital Workforce:

    The Digital Workforce: Which Agent Should I Employ?

    “If Agentforce is so easy to use, then why do I need a Salesforce Partner?”

    Agentforce, a Guide to Onboarding Your Digital Employee

  • Agentforce: A Guide to Onboarding Your Digital Employee

    Agentforce: A Guide to Onboarding Your Digital Employee

    Human employees typically take 6 months to get fully up to speed in an organisation, and Agentforce is similar – it just happens to be a virtual one! Similar to a real employee, agents take time to learn your brand, your expectations, your colleagues and your customers.

    However, while hiring a human employee involves interviews, visual, auditory and kinesthetic training, and integration into company culture, onboarding an Agentforce Agent demands a strong data foundation, extensive testing, and in-house expertise in prompt engineering and automation tools. Here are the top considerations, or prerequisites, before an AI agent joins your team.

    1. Data Readiness: The Fuel for AI

    AI thrives on high-quality, structured data. Just as a human employee needs training materials and business knowledge, an Agentforce Agent needs access to accurate and relevant data to function optimally.

    Why It Matters

    Your digital employees, or agents, are grounded in your Salesforce data, meaning that they rely on data to complete their tasks, such as answering customer questions, processing transactions, and generating insights. If your data is incomplete, outdated, or poorly structured, the agent may provide inaccurate responses, leading to inefficiencies and frustrated users.

    How to Prepare

    • Audit your existing data sources to ensure consistency and accuracy.
    • Centralise relevant data in a structured format, leveraging CRM tools, knowledge bases, and customer interaction history.
    • Define clear security guardrails to protect sensitive information while allowing the agent access to necessary datasets – this is an essential part of building your agent.

    By ensuring your data is clean, structured, and accessible, you set up your digital employee for long-term success.

    2. Depth of the Testing Process

    Onboarding a digital employee is not a “set it and forget it” process. Yes, Agentforce is user-friendly, and much of the set-up can be done declaratively (e.g.point-and-click, rather than coding). However, extensive testing is crucial to ensure that Agentforce Agents perform tasks as expected and improve over time. In many Salesforce implementations, there is a danger of the testing process being overlooked – but this is the part of the process that determins the outputs, ensuring that the results are exactly what your team expect and desires. Think of it like an employee review process, you need to consistently check their work in order to give them room to improve.

    Why It Matters

    AI learns by interacting with data, and using generative AI means that you will get slightly different outputs each time – even from the same input! Therefore, this makes it necessary to thoroughly test and refine its responses before deployment. An improperly tested AI agent may misinterpret queries, provide incorrect information, or fail to escalate issues to human employees when needed.

    When it comes to AI, trust is a big factor – for customers just as much as employees. When done properly, testing ensures that your customers get the best possible experience and reinforces the trust in your brand.

    How to Prepare

    • Conduct rigorous testing before deployment, running 30-40 different test scenarios at a minimum.
    • Simulate real-world interactions to validate responses and identify gaps. The best way to do this is get the whole team on board, as they are best placed to determine the quality of the outputs. When we implement Agentforce for our customers, we ask users to do everything in their power to make the agent give a poor or incorrect response. If they can’t break it, then it’s ready to deploy!
    • Continually refine responses based on feedback and performance analytics.

    Thorough testing ensures your digital employees can handle a variety of scenarios with accuracy and efficiency.

    3. Skills for Prompt Engineering

    A key factor in optimising digital employees is the ability to craft precise prompts that guide their behaviour. Prompt engineering is an essential skill that defines how AI understands and processes information. In essence, a good prompt is a clear and detailed instruction with strict perameters, enabling AI to produce accurate and relevant outputs by providing good context and desired task details.

    Why It Matters

    Just as human employees follow training guides and workflows, AI-driven employees depend on well-structured prompts to operate within predefined boundaries. Poorly engineered prompts can lead to inconsistent outputs, while well-crafted prompts ensure repeatable, reliable results.

    How to Prepare

    • Develop repeatable prompt templates to create consistent, detailed responses aligned with your business needs – these can be over 100 lines long to cover complex workflows.
    • Lean on internal experts to create prompts according to best practices, and leverage Salesforce’s free learning platform, Trailhead, to upskill your team. It is hugely advantageous for all team members to have at least a basic understanding of how the AI technology works.
    • If you lack internal expertise, seek a skilled partner with real-world experience implementing Agentforce and Salesforce AI technologies successfully.

    Companies that invest in strong prompt engineering practices get the most out of their digital employees by ensuring reliable and predictable AI behavior.

    4. Leveraging Your Existing Automation Catalogue

    Agentforce Agents don’t operate in isolation; they integrate with and pull from existing automation tools to streamline operations. Businesses that harness their existing automation infrastructure can deploy digital employees faster and more effectively.

    Why It Matters

    Ensuring smooth integration with Salesforce automation tools like Flow and APEX is essential for scalable and future-proofed AI implementation. And why not leverage the great work that has already been done to make your agents even better?

    How to Prepare

    • Map out your existing automation catalogue and identify where AI can enhance workflows.
    • Use Salesforce Flow and APEX to create new AI-driven actions while maintaining architectural consistency.
    • As mentioned in the prompt engineering section above, ensure that your team has the necessary expertise in automation tools to maximise efficiency.

    By integrating digital employees into your existing automation framework, you create a seamless, scalable AI-powered ecosystem.

    Final Thoughts

    Successfully onboarding digital employees requires a shift in mindset from traditional human hiring processes. To get the best results from your Agentforce Agents, you need to:

    • Ensure data readiness so your AI has accurate information to work with.
    • Conduct extensive testing to refine responses and improve performance.
    • Leverage in-house and partner expertise in prompt engineering to create precise, repeatable AI behaviours.
    • Maximise existing automations to streamline workflows and future-proof your AI implementation.

    By following these four key prerequisites, you can confidently onboard digital employees that enhance productivity, drive efficiency, and seamlessly integrate into your existing operations.

    Are you ready to onboard your first digital employee? Reach out to our team for expert guidance and a complimentary readiness session to kick-start your AI journey!

    More on Agentforce and the Digital Workforce:

    The Digital Workforce: Which Agent Should I Employ?

    How Agentforce Can Drive ROI

    If Agentforce is so easy to use, why do I need a partner?

  • How Tableau by Salesforce Uses AI: Tableau Plus – Trusted Insights with AI

    How Tableau by Salesforce Uses AI: Tableau Plus – Trusted Insights with AI

    As businesses navigate an increasingly data-driven world, the need for fast, reliable, and intelligent analytics has never been greater. Salesforce’s advanced analytics platform, Tableau Plus, leverages AI-driven insights to provide personalised, contextual, and on-demand analytics at scale. With its deep integration of AI capabilities – now including Agentforce – Tableau Plus empowers users with automated recommendations, natural language assistance, and dynamic data exploration.

    Read on to learn how Tableau Plus uses AI to enhance decision-making, simplify data preparation, and help analysts manage ad hoc requests more efficiently. Additionally, we will explore the latest Tableau Pulse Features, designed to further elevate analytics experiences with advanced alerting, discovery, and predictive capabilities.

    What is Tableau?

    Tableau is a powerful data visualisation and business intelligence (BI) platform that enables organisations to analyse, interpret, and share insights from their data. Acquired by Salesforce, Tableau is known for its user-friendly interface, drag-and-drop functionality, and robust analytics capabilities. It allows users to create interactive dashboards, generate reports, and uncover trends across various data sources.

    Tableau is widely used across industries for:

    • Data visualisation: Transforming raw data into easy-to-understand visual reports.
    • Self-service analytics: Enabling users without technical expertise to explore data and metrics such as customer acquisition cost, win rates, average resolution times and customer retention or churn rates.
    • AI-driven insights: Enhancing analytics with machine learning and automation.
    • Collaboration and sharing: Allowing teams to work together and make data-driven decisions.

    Salesforce has further enhanced Tableau’s capabilities by embedding AI to provide more automated and intelligent analytics experiences.

    Who is it for?

    Tableau is designed for a wide range of users across different industries and roles. It is a tool that works best in businesses with lots of data to interpret and digest in order to make informed, confident decisions. Its flexibility and AI-powered capabilities make it a valuable tool for business analysts, data scientists and leadership teams to uncover trends, plan strategies and make predictions.

    AI-Powered Analytics with Tableau Plus

    1. Personalised and Contextual Insights

    One of the key advantages of Tableau Plus is its ability to deliver insights tailored to specific users and business needs. Instead of static dashboards that require manual exploration, Tableau AI dynamically adapts to provide relevant, real-time suggestions and insights based on data trends, past interactions, and organisational goals.

    2. Conversational AI with Tableau Agent

    Tableau Agent, powered by Agentforce, acts as a smart assistant within Tableau, offering:

    • Faster decision-making by surfacing key insights and trends without manual effort.
    • Guided assistance for new users, helping them navigate Tableau’s interface and learn best practices.
    • Conversational data preparation, allowing users to ask natural language queries such as “How do I build x calculation?” or “What are the trends for sales in Q2?”
    • Automated data enrichment, helping analysts clean and prepare data more efficiently.
    • Simplified data storytelling, with AI-generated descriptions of complex patterns and metrics that can be easily shared with stakeholders.

    (Learn more about how Tableau and Agentforce work together here!)

    3. Reducing Analyst Overload with AI Assistance

    Data analysts often face an overwhelming number of ad hoc data requests from different teams. Tableau Plus helps alleviate this burden by:

    • Recommending relevant exploration questions based on past analyses.
    • Providing instant AI-generated answers to common queries.
    • Suggesting optimal ways to visualise and present data for different audiences.

    This ensures that business users can self-serve analytics, reducing their dependency on analysts while maintaining data accuracy and consistency.

    Tableau Pulse Features

    The latest Pulse features are set to enhance Tableau Plus by introducing proactive alerts, intelligent discovery, and predictive analytics. These features ensure users get timely and actionable insights without needing to track changes in their data manually.

    1. Insight-Driven Data Alerting

    Proactive AI-driven alerts notify users of significant metric changes via push notifications, emails, Slack digests, and the Pulse homepage. This eliminates the need for manual checks and ensures business leaders and analysts are always aware of critical changes in their data.

    2. Pulse Discover

    With Pulse Discover, Tableau enables deeper, logically reasoned insights by leveraging:

    • Natural language Q&A for grouped metrics.
    • Flexible mobile-first access for on-the-go analytics.
    • Multilingual support to cater to global teams.
    • Dynamic scope adjustments allow users to refine their insights in real time.

    This feature empowers executives and business users to explore the most important trends effortlessly, without needing extensive data expertise.

    3. Predictions and Forecasting

    AI-powered forecasting helps businesses stay ahead by identifying whether key metrics are on track or at risk. By using historical data and predictive models, Tableau provides proactive insights into:

    • Expected trends for sales, revenue, and customer retention.
    • Forecasted operational performance based on real-time inputs.
    • Risk identification to highlight areas that require immediate attention.

    By leveraging AI-driven predictive analytics, organisations can make informed decisions before issues arise, ensuring better business continuity and strategic planning.

    The Future of AI-Powered Analytics

    Tableau Plus is leveraging AI to transform how businesses interact with data, making analytics more intuitive, automated, and actionable. With AI-driven personalised insights, conversational analytics, and predictive intelligence, Tableau Plus ensures that organisations can move beyond static reporting and make real-time, data-driven decisions – and most importantly, with confidence!

    The introduction of Pulse features further strengthens this vision, offering businesses automated alerting, enhanced data discovery, and forward-looking insights to maximise the value of their analytics investments.

    For businesses looking to stay ahead in a competitive, data-rich world, Tableau Plus represents the future of trusted, AI-powered decision-making. Contact us to learn more about how you can apply your data to accelerate growth, or read more about how Agentforce is partnering with Tableau to provide businesses with agentic, digital data experts in the form of AI agents, ready to support your teams as they harness insights from all of their business data.

    References

    Tableau+: Bring analytics to every corner of your organization (2025) Tableau. Webinar. Available (online) at https://www.tableau.com/learn/webinars/tableau-how-bring-analytics-every-corner-your-organization [Accessed 23/01/2025]

    What Tableau and Agentforce Mean for You (2025) Tableau. 2025 Innovation Preview. Webinar. Available [online] at https://www.tableau.com/learn/webinars/what-tableau-and-agentforce-mean-for-you#video [Accessed 12/03/2025].

  • Don’t Sleep on Einstein! 

    Don’t Sleep on Einstein! 

    Is Agentforce making Einstein redundant? How do these two Salesforce features compare? Read on to learn the ways in which Salesforce’s generative AI functionality can help you save costs and elevate the customer experience with real-world use cases.

    The Salesforce ecosystem is ablaze with ‘agentic AI’ as Agentforce rapidly accumulates more and more functionality. Recently, a member of our team was asked the question, “Will Agentforce make Einstein redundant?” – so we thought we would answer it in this article!

    The unhelpfully short answer is, ‘no’. To elaborate: different types of AI are good at different things (just like humans), although Agentforce does have some generative functionality (e.g. it creates new content based on the information it has access to), Agentforce’s main differentiator is that it is ‘agentic’, meaning that it can take action (within certain parameters or ‘guardrails’.) It is true that Agentforce and Einstein do overlap in some respects, but Einstein is a great way to explore how AI can fit into your business strategy without plunging into all of the data readiness activity required for Agentforce implementation, or taking on a credit-based payment structure – it can also provide some great, low investment quick-wins! The use cases below explain the tasks that Einstein excels at, without the need for ‘agentic’ AI.

    1. Einstein Discovery

    Einstein Discovery utilises machine learning to analyse data and uncover patterns, providing actionable insights and recommendations. It processes both Salesforce and external datasets to identify trends, correlations, and anomalies.

    Value Add: By offering data-driven insights, Einstein Discovery enables businesses to make informed decisions, optimise operations, and identify new opportunities. It transforms complex data into understandable narratives, facilitating strategic planning.

    Example Use Case: A financial services company employs Einstein Discovery to identify patterns indicating a high risk of churn. By proactively reaching out to these customers with personalised offers and support, the company reduces churn rates and improves customer retention.

    Availability: Einstein Discovery is available as an add-on in the Enterprise, Performance, and Unlimited editions of Salesforce.

    2. Einstein Prediction Builder

    This feature allows users to create custom AI models to predict specific business outcomes, such as customer lifetime value, using clicks instead of code. It leverages historical data to forecast future events.

    Value Add: Einstein Prediction Builder empowers businesses to anticipate customer behaviour and market trends, enabling proactive strategies to enhance customer retention and profitability.

    Example Use Case: A hotel chain implements Einstein Prediction Builder to forecast guest preferences for amenities and services. By analysing historical booking data, the chain predicts which guests are likely to book spa services or dine in-house, allowing for targeted promotions and personalised guest experiences.

    Availability: It is included in the Enterprise, Performance, and Unlimited editions with Sales Cloud Einstein.

    3. Einstein Next Best Action

    This tool delivers context-specific recommendations to employees and customers within their workflow. It considers business rules and predictive models to suggest the most effective actions.

    Value Add: By providing tailored recommendations, Einstein Next Best Action enhances decision-making, improves customer satisfaction, and increases conversion rates.

    Example Use Case: The customer service department in a retail company leverages Next Best Action to provide personalised product recommendations to customers. By analysing purchase history and browsing behaviour, the system suggests relevant products, enhancing the shopping experience and increasing sales.

    Availability: It is available in Essentials, Professional, Enterprise, Performance, Unlimited, and Developer editions, and it offers 5,000 strategy requests per month at no charge.

    4. Einstein Language

    Einstein Language encompasses natural language processing (NLP) capabilities that analyse text to determine sentiment and intent. It can classify text and detect customer emotions and feelings across various communication channels.

    Value Add: Understanding customer sentiment and intent allows businesses to tailor responses, improve service quality, and automate the routing of inquiries to appropriate departments.

    Example Use Case: A public transportation provider implements Einstein Language to analyse customer feedback from social media and service hotlines. By detecting sentiment and intent, the provider identifies areas of dissatisfaction and addresses them promptly, improving overall service quality.

    Availability: Einstein Language is available as an add-on across various Salesforce editions.

    5. Einstein Bots

    This is probably the feature that is most similar to Agentforce functionality. Einstein Bots are a great way to get started with chatbots, offering an affordable and less complex way of lightening the volume of service requests. These bots interact with customers on digital channels, handling routine inquiries and redirecting to human agents when required. They are integrated with CRM data to provide personalised responses. These are a great option if you need help answering day-to-day customer queries, or want to replace a lengthy and non-user-friendly FAQ section.

    Value Add: By automating common customer interactions, Einstein Bots reduce the workload of human agents, provide instant support, and enhance customer engagement.

    Example Use Case: A healthcare provider uses Einstein Bots to answer patients’ questions and manage prescription refill requests. Patients interact with the bot to understand their options and request medication, and the bot collates all the necessary information to present to medical professionals for approval, reducing administrative workload and enhancing patient convenience.

    Availability: Included in the Unlimited edition with 25 Einstein Bot conversations per user per month.

    6. Einstein Vision

    This feature offers image recognition capabilities, allowing businesses to analyse and classify images. It can identify brand logos, objects, and text within images.

    Value Add: Einstein Vision enables companies to monitor brand presence on social media, improve quality control processes, automate image categorisation, and enhance visual search functionalities.

    Example Use Case: Einstein Vision allows customers of an ecommerce company to upload images of desired products, enabling the system to identify and suggest similar items available in the retailer’s inventory. This enhances the shopping experience by making product discovery more intuitive.

    Availability: Available as an add-on in various Salesforce editions.

    7. Einstein Lead Scoring

    Einstein Lead Scoring analyses historical sales data to assign scores to leads based on their likelihood to convert. It identifies patterns that correlate with successful conversions.

    Value Add: By prioritising leads with higher conversion probabilities, sales teams can focus their efforts effectively, improving efficiency and increasing sales.

    Example Use Case: A real estate agency utilises Einstein Lead Scoring to prioritise potential property buyers. By analysing client interactions and property preferences, the agency identifies leads most likely to convert, enabling Sales and Marketing to focus their efforts effectively and increase sales.

    Availability: Part of Sales Cloud Einstein, available in Enterprise, Performance, and Unlimited editions.

    8. Einstein Opportunity Scoring

    Similar to Einstein Lead Scoring, this feature evaluates open opportunities and assigns scores indicating the likelihood of a successful close. It considers factors such as customer engagement and deal progress.

    Value Add: Einstein Opportunity Scoring helps sales representatives prioritise deals, allocate resources wisely, and forecast revenue more accurately.

    Example Use Case: A B2B energy solutions provider uses Einstein Opportunity Scoring to evaluate the potential of various sales opportunities. By assessing factors such as client engagement and proposal responses, the provider allocates resources to deals with the highest likelihood of closure, optimising sales efficiency.

    Availability: Included in Sales Cloud Einstein for Enterprise, Performance, and Unlimited editions.

    9. Einstein Forecasting

    Einstein Forecasting uses AI to predict sales revenue by analysing historical data and current pipeline information. It provides insights into forecast accuracy and potential outcomes.

    Value Add: Accurate sales forecasts enable businesses to set targets, manage resources effectively, and make informed strategic decisions.

    Example Use Case: A hotel chain leverages Einstein Forecasting to predict sales revenue by analysing historical data and current booking information. This enables the company to set realistic targets, manage inventory, and be more confident in their decision making.

    Availability: Available with Sales Cloud Einstein in Performance and Unlimited editions, and as an add-on in Enterprise edition.

    10. Einstein Activity Capture

    This tool analyses emails and calendar events to identify new contacts and relevant information, automatically updating and enriching Salesforce records.

    Value Add: By maintaining up-to-date contact information, businesses enhance data accuracy, reduce manual data entry, and improve relationship management.

    Example Use Case: A bank with a busy, growing sales team employs Einstein to identify new contacts and relevant information, ensuring that no information on potential new customers is lost in cluttered inboxes. The system automatically updates Salesforce records, maintaining up-to-date contact information, supporting the pipeline and enhancing relationship management.

    Availability: Part of Sales Cloud Einstein, available in Performance and Unlimited editions, and as an add-on in Enterprise edition.

    11. Einstein Knowledge Creation

    Einstein Knowledge Creation streamlines the process of expanding an organisation’s knowledge base by automatically drafting new articles based on customer interactions.

    Value Add: By analysing case data and conversation transcripts, Einstein identifies recurring issues and generates relevant content, ensuring that information is up-to-date and readily available for both agents and customers. This proactive approach reduces the time spent on manual article creation and helps in quicker issue resolution.

    Example Use Case: A software company notices a surge in customer inquiries about a specific error message in their application. Einstein Knowledge Creation analyses these interactions and drafts a knowledge article outlining the error, its causes, and step-by-step solutions. After review, the article is published, enabling customers to self-serve and resolve the issue without contacting support, thereby reducing the support team’s workload.

    Availability: Available with Service Cloud Einstein in Performance and Unlimited editions, and as an add-on in Enterprise edition.

    12. Einstein Work Summaries

    Einstein Work Summaries leverages generative AI to draft concise summaries of customer interactions, capturing the main issues and resolutions discussed.

    Value Add: This feature reduces the time spent on reviewing past interactions and ensures that all team members are informed of relevant activity and information.

    Example Use Case: In the healthcare industry, a patient contacts support multiple times regarding issues with accessing their online health records. Einstein Work Summaries compiles these interactions into a coherent summary, highlighting the patient’s concerns and the solutions provided. When the patient reaches out again, the support agent can quickly review the summary to understand the context and offer informed assistance, leading to a more personalised and efficient support experience.

    Availability: Available with Service Cloud Einstein in Performance and Unlimited editions, and as an add-on in Enterprise edition.

    13. Einstein Reply Recommendations (for Live Messaging)

    Einstein Reply Recommendations suggests appropriate responses during live customer chats. It identifies common queries and effective replies, presenting agents with a selection of recommended responses.

    Value Add: This accelerates response times, ensures consistency, and enhances the customer experience.

    Example Use Case: A client of a shipping company sends a chat message about the status of their order. Einstein Reply Recommendations suggests responses such as “Your order has been shipped and is expected to arrive on [date].” The agent can select and send the most appropriate reply, reducing handling time.

    Availability: Available with Salesforce Enterprise, Performance, and Unlimited editions. It requires the Service Cloud Einstein add-on license.

    14. Einstein Service Replies

    Einstein Service Replies utilises generative AI to draft fluent, courteous, and contextually relevant responses for customer service agents. By analysing historical interactions and grounding responses in the company’s knowledge base, it ensures consistency and accuracy in communications.

    Value Add: This feature significantly reduces the time agents spend composing replies, allowing them to focus on more complex customer issues.

    Example Use Case: A customer sends an email to a clothing manufacturer about the return policy for a recent purchase via email. Einstein Service Replies drafts a personalised response detailing the return process, including any necessary steps the customer should follow. The agent reviews and sends the response promptly, enhancing customer satisfaction through swift and accurate communication.

    Availability: Available with Salesforce Enterprise, Performance, and Unlimited editions. It requires the Service Cloud Einstein add-on license.

    By implementing these simple generative Salesforce AI features, organisations can enhance and automate their sales and customer service operations, improving efficiency, consistency, and customer satisfaction. As far as we can see, Einstein isn’t going anywhere. Maybe now is the time to explore which AI features are right for your business – whether that be Einstein, Agentforce, or something else entirely!

    To learn more about how you could be using Salesforce Einstien to enrich your customer experience and streamline your operations, book a call with us today!