#Salesforce Agentforce Consulting

[amberwallace]

Salesforce Agentforce Consulting & Implementation Services

Boost sales and service efficiency with Jade Global’s expert Salesforce Agentforce Consulting Services. Explore tailored solutions to transform your CX now!

[thewomanwhobloggedlikeaman]

Marc B*nioff trying to justify laying off thousands of employees each year despite Salesforce's record profits (and having billions in personal wealth himself)

[fexleservices]

Unlock the Full Potential of Salesforce with Expert Consulting

Salesforce is a powerful CRM, but leveraging its full capabilities requires expert guidance. This blog highlights the top Salesforce consulting companies in the USA, known for their expertise in custom implementations, seamless integrations, and business process optimization.

Whether you need Sales Cloud, Service Cloud, Marketing Cloud, or AI-driven automation, these firms help businesses maximize ROI, streamline operations, and stay ahead in the competitive landscape.

Learn more here!

[winklix]

Effective Strategies for DevOps Teams Deploying Salesforce Agentforce 2.0

Salesforce Agentforce 2.0 is a powerful platform designed to streamline customer service operations and enhance agent productivity. For DevOps teams tasked with implementing and managing this solution, adopting best practices is essential to ensure a smooth deployment, optimized performance, and long-term success. Below are key recommendations to guide your DevOps team through the implementation process.

1. Understand the Platform and its Capabilities

Before diving into the implementation, invest time in understanding the core features and functionalities of Agentforce 2.0. Leverage Salesforce’s documentation, training modules, and community resources to:

Learn about Agentforce’s key features like Omni-Channel Routing, AI-driven insights, and Workflow Automations.

Familiarize yourself with the platform’s integration points, especially if you’re connecting it with existing CRM or ITSM systems.

Identify configuration versus customization opportunities to align with business needs.

2. Collaborate Early with Stakeholders

Success starts with collaboration. Engage with stakeholders such as customer support managers, IT teams, and end-users early in the process. Conduct workshops or discovery sessions to:

Gather requirements and prioritize features.

Understand existing workflows and pain points.

Ensure alignment between technical implementation and business objectives.

3. Adopt an Agile Implementation Approach

Given the iterative nature of most Salesforce deployments, an agile approach ensures continuous improvement and quick feedback. Key practices include:

Breaking down the implementation into manageable sprints.

Setting up regular sprint reviews with stakeholders.

Using feedback loops to refine features before full deployment.

4. Automate CI/CD Pipelines

Continuous Integration and Continuous Deployment (CI/CD) are critical for a seamless implementation. Use tools like Salesforce DX, Git, and Jenkins to:

Version control metadata and customizations.

Automate testing and deployments across environments.

Reduce the risk of manual errors while improving deployment speed.

5. Ensure Data Integrity and Security

Data is at the heart of any Salesforce application. Prioritize data integrity and security by:

Conducting thorough data audits before migration.

Setting up field-level, object-level, and record-level security as per organizational policies.

Using tools like Salesforce Shield for encryption and event monitoring.

6. Leverage Sandbox Environments for Testing

Sandbox environments are invaluable for testing configurations and integrations without impacting production data. Follow these guidelines:

Use Full or Partial Copy Sandboxes to simulate real-world scenarios.

Perform rigorous User Acceptance Testing (UAT) with actual stakeholders.

Validate integrations with external systems thoroughly.

7. Utilize Built-in AI and Analytics Features

Agentforce 2.0’s AI-driven tools, like Einstein AI, provide actionable insights to improve customer service. Ensure your implementation maximizes these features by:

Training models with relevant data to enhance predictions.

Setting up dashboards to monitor agent performance and customer satisfaction.

Using analytics to identify trends and optimize workflows.

8. Train Your Team and End Users

The best technology is only as effective as its users. Invest in comprehensive training programs:

Provide role-specific training for agents, admins, and managers.

Create a knowledge base with step-by-step guides and FAQs.

Schedule refresher sessions post-launch to address new updates or challenges.

9. Monitor Performance and Gather Feedback

After deployment, ongoing monitoring and feedback collection are vital. Use tools like Salesforce’s Health Check and AppExchange monitoring solutions to:

Identify bottlenecks in workflows.

Monitor system performance metrics.

Continuously gather feedback from agents and stakeholders to improve processes.

10. Plan for Scalability and Future Upgrades

Agentforce 2.0 is designed to grow with your organization. To future-proof your implementation:

Regularly review and update workflows as business needs evolve.

Stay informed about Salesforce’s roadmap and new feature releases.

Plan for scalability, ensuring infrastructure and licenses can support future growth.

Conclusion

Implementing Salesforce Agentforce 2.0 requires a thoughtful, well-coordinated approach that aligns technical execution with business objectives. By following these best practices, DevOps teams can ensure a successful deployment, delivering value to both customer service agents and the organization as a whole.

Remember, the implementation process is not a one-time effort but an ongoing journey toward innovation and excellence in customer service. Stay agile, stay collaborative, and stay committed to continuous improvement.

[ravaglobal]

🔹 Build Your AI Agent with Salesforce AgentForce: A Step-by-Step Guide

Discover how to automate workflows and enhance customer interactions using Salesforce AgentForce. This comprehensive guide walks you through setting up an AI agent, enabling Einstein AI, building Einstein Bots, and optimizing AI-driven customer service. Learn best practices for training, deployment, and performance monitoring to maximize efficiency. 🚀

Looking for expert assistance? Partner with a Salesforce Consulting Partner USA to implement AI-driven automation tailored to your business needs! 💡

[salesforcesblog]

📈 How Agentforce Can Revolutionize Sales Performance in Your Business

Are you looking to scale sales without scaling headcount? Want to increase rep productivity, shorten sales cycles, and improve lead conversion—all without overhauling your tech stack?

Meet Agentforce, Salesforce’s autonomous AI platform that empowers your sales team to operate at peak performance with less manual effort and more strategic impact.

At Astreca, we help businesses unlock the power of AI in sales—and Agentforce is one of the most transformative tools we’ve seen.

Here’s how it can drive real business outcomes:

🔍 What Agentforce Delivers for Your Business

✅ 24/7 Sales Enablement & Lead Nurturing Agentforce acts as an always-on SDR—automating personalized outreach, following up with leads, and handling inquiries instantly via Slack, SMS, and more.

✅ Data-Driven Sales Coaching at Scale Forget inconsistent coaching. Agentforce trains on your company’s data to deliver tailored feedback to each rep—improving skills, confidence, and close rates without adding management layers.

✅ Custom Agents That Work the Way You Do Build AI agents that match your unique workflows. Whether it's qualifying leads, suggesting next best actions, or syncing tasks across platforms—Agentforce adapts to your processes.

✅ Smarter, Faster Decision Making Integrated with Salesforce, Einstein, and (optionally) Data Cloud, Agentforce analyzes behavior, identifies sales signals, and provides your team with real-time recommendations that accelerate deals.

✅ Secure, Controlled AI Unlike generic AI tools, Agentforce operates within clearly defined guardrails. You control the tone, actions, and boundaries—keeping data secure and decisions aligned with your business goals.

📊 Measurable Business Benefits

Boost Sales Productivity without increasing team size

Reduce Time-to-Close with intelligent deal support

Improve Conversion Rates through personalized, automated follow-ups

Lower Operational Costs by automating manual tasks and workflows

Enhance Customer Experience through timely, consistent communication

🆚 Agentforce vs. Copilot (Microsoft)

FeatureAgentforce (Salesforce)Copilot (Microsoft)FocusSales automation & AI agentsDocument & task automationPlatform IntegrationSalesforce, Slack, custom workflowsOffice 365 (Word, Excel, Outlook, Teams)PersonalizationHigh (trained on your sales data)Medium (document-level assistance)Ideal Use CaseSales teams, pipeline management, lead conversionProductivity, communication tasks

Together, these tools can complement each other—but Agentforce is the only one built specifically to drive sales.

🔗 Learn More

📘 Dive deeper into the use cases and real-world benefits: How Agentforce Is Changing Sales for Reps

🔧 Ready to transform your sales team with Agentforce? Astreca Consulting specializes in helping growing businesses implement AI-powered sales strategies with Salesforce. We tailor each solution to your team, your tools, and your goals.

Let’s build smarter sales—together.

#Salesforce #Agentforce #SalesAI #RevenueGrowth #BusinessIntelligence #SalesTransformation #Astreca #SmartSelling

[salesforceconsultingsol]

https://www.softwebsolutions.com/agentforce-consulting-services.html

Salesforce Agentforce consulting services

[cert007]

Salesforce Agentforce Specialist Exam Questions and Answers

The Salesforce Agentforce Specialist credential represents a comprehensive certification program specifically tailored for professionals responsible for managing and implementing Agentforce solutions within their respective organizations. This prestigious certification serves as a formal validation of your advanced expertise in leveraging Agentforce capabilities, configuring the Salesforce Platform effectively, and implementing cutting-edge generative AI solutions to drive enhanced business performance and elevate customer engagement across multiple touchpoints. Through this certification, professionals demonstrate their ability to harness the full potential of Agentforce technologies while maintaining alignment with organizational objectives and industry best practices. To support candidates in their certification journey, Cert007 provides an extensive collection of the most current Salesforce Agentforce Specialist Exam Questions and Answers, carefully curated and regularly updated to ensure candidates are well-equipped to successfully navigate and pass the certification examination.

Who Should Take the Salesforce Agentforce Specialist Exam?

This certification is ideal for professionals working with Agentforce and AI-driven automation within Salesforce. If you fall into any of the following categories, this exam is a great fit for you:

Salesforce Administrators responsible for configuring and maintaining Agentforce.

AI Specialists integrating generative AI into Salesforce workflows.

Consultants and Developers designing and implementing Agentforce-powered solutions.

Business Leaders and Strategists seeking to optimize AI-driven customer service and sales automation.

Achieving this certification proves your ability to leverage Agentforce for improving sales, customer service, and overall business efficiency.

Salesforce Agentforce Specialist Exam Overview

Before diving into preparation, let’s go over the key exam details:Exam ComponentDescriptionTotal Questions 60 multiple-choice + up to 5 unscored questions Time Duration 105 minutes Passing Score 73% Registration Fee Free (First attempt under AI for All initiative) Retake Fee USD 100 (+ applicable taxes) Exam Delivery Online proctored or in-person at a testing center Reference Materials No hard-copy or online resources allowed Prerequisites None

Salesforce Agentforce Specialist Exam Outline

The exam evaluates candidates on five primary domains, with different weightages assigned to each section:

1. Prompt Engineering (30%)

This section focuses on designing, managing, and executing AI prompts within Agentforce.

You should be able to:

✔ Identify when to use Prompt Builder based on business needs.

✔ Determine the correct user roles for managing and executing prompt templates.

✔ Recognize key factors for creating an effective prompt template.

✔ Understand grounding techniques and their applications in different scenarios.

✔ Follow the correct process to create, activate, and execute prompt templates.

2. Agentforce Concepts (30%)

This section covers fundamental Agentforce functionalities and management.

You should be able to:

✔ Explain how Agentforce works, including its reasoning engine.

✔ Utilize standard and custom topics, agent actions, and automation tools.

✔ Monitor agent adoption rates and user engagement.

✔ Manage user security and access controls for Agentforce.

✔ Test agents using the Testing Center before deployment.

✔ Successfully deploy an agent from a sandbox environment to production.

3. Agentforce and Data Cloud (20%)

This section focuses on how Agentforce integrates with Salesforce Data Cloud to enhance AI responses.

You should be able to:

✔ Improve agent response accuracy using the Agentforce Data Library.

✔ Utilize retrievers in Data Cloud to provide contextually relevant AI-generated answers.

4. Agentforce and Service Cloud (10%)

This section evaluates Agentforce’s role in customer service and support automation.

You should be able to:

✔ Build AI-powered agents that answer questions using Knowledge articles.

✔ Connect an agent to Salesforce digital channels, such as chat, messaging, or email.

✔ Choose the correct generative AI feature in Agentforce for Service Cloud scenarios.

5. Agentforce and Sales Cloud (10%)

This section focuses on how Agentforce enhances sales productivity and automation.

You should be able to:

✔ Identify the right generative AI features in Agentforce for Sales Cloud applications.

✔ Understand when to use Agentforce Sales Agents, such as Sales Development Representatives (SDRs) and Sales Coaches, to optimize lead generation and conversion.

Best Study Resources for the Salesforce Agentforce Specialist Exam

To prepare effectively for the Salesforce Agentforce Specialist exam, consider using the following study resources:

✅ Salesforce Trailhead Modules – The Cert Prep: Agentforce Specialist module includes interactive lessons, hands-on exercises, and flashcards to help you master key concepts.

✅ Salesforce Help Documentation – Explore official Agentforce implementation guides and Salesforce documentation for in-depth knowledge of platform capabilities.

✅ Cert007 Practice Questions – Access the latest exam questions and answers from Cert007 to simulate real test scenarios and improve retention.

✅ Trailblazer Community & Study Groups – Join Salesforce Trailblazer Community forums and Agentforce study groups to discuss key topics and gain insights from certified professionals.

✅ Mock Exams & Practice Tests – Take full-length mock exams to get familiar with the exam format, time constraints, and question difficulty.

✅ Salesforce Release Updates – Stay updated on the latest features and enhancements in Salesforce to ensure your knowledge aligns with the most current exam content.

Final Thoughts

The Salesforce Agentforce Specialist certification is an essential credential for professionals looking to implement AI-powered automation in their sales and service processes. By mastering prompt engineering, data integration, and agent management, you can enhance your expertise in Salesforce’s AI-driven tools and gain a competitive edge in the evolving digital landscape.

Be sure to leverage practice exams, study guides, and Trailhead resources to maximize your chances of passing the exam on your first attempt!

[questdigiflexai]

Salesforce Consulting Services: Trends Shaping 2025

As we navigate through 2025, the landscape of Salesforce consulting services is undergoing significant transformations. Advancements in technology, evolving business needs, and the integration of artificial intelligence (AI) are redefining how organizations leverage Salesforce to drive growth and efficiency. At Digiflex.ai, we are at the forefront of these changes, helping businesses harness the full potential of Salesforce.

The Expanding Salesforce Consulting Market

The Salesforce consulting service market is experiencing robust growth. In 2023, the market was valued at approximately $16.04 billion and is projected to reach $56.99 billion by 2032, exhibiting a compound annual growth rate (CAGR) of 15.3% during this period.

This surge is driven by businesses increasingly seeking expert guidance to optimize their Salesforce implementations and achieve seamless digital transformations.

Key Trends in Salesforce Consulting Services

1. Integration of AI and Automation

Artificial intelligence is revolutionizing Salesforce consulting. The introduction of AI-powered tools, such as Salesforce's Agentforce, enables businesses to automate routine tasks, analyze customer data more effectively, and deliver personalized experiences. This shift allows consultants to focus on strategic initiatives, enhancing overall productivity.

2. Emphasis on Data-Driven Decision Making

With the proliferation of data, organizations are prioritizing data-driven strategies. Salesforce consultants are now focusing on implementing robust analytics solutions that provide real-time insights, facilitating informed decision-making and proactive customer engagement.

3. Rise of Industry-Specific Solutions

Businesses are seeking tailored Salesforce solutions that cater to their unique industry requirements. Consulting services are evolving to offer specialized expertise in sectors such as healthcare, finance, and retail, ensuring that Salesforce implementations align with specific regulatory and operational needs.

4. Focus on Change Management and Training

Successful Salesforce adoption extends beyond technical implementation. Consultants are placing greater emphasis on change management strategies and comprehensive training programs to ensure that organizations can effectively utilize new tools and processes, maximizing return on investment.

5. Expansion of Remote and Hybrid Work Solutions

The shift towards remote and hybrid work models has led to an increased demand for Salesforce solutions that support distributed teams. Consultants are developing strategies to integrate collaboration tools, ensure data accessibility, and maintain security across various work environments.

Digiflex.ai's Commitment to Innovation

At Digiflex.ai, we are committed to staying ahead of these trends to provide our clients with cutting-edge Salesforce consulting services. Our approach includes:

AI Integration: Leveraging AI to automate processes and deliver actionable insights.

Customized Solutions: Developing industry-specific Salesforce implementations that address unique business challenges.

Comprehensive Support: Offering end-to-end services, from strategic planning to change management and training, ensuring seamless adoption and sustained success.

As the Salesforce ecosystem continues to evolve, partnering with a forward-thinking consultant like Digiflex.ai ensures that your organization remains competitive and agile in the face of change.

[cleverhottubmiracle]

Ask the AI-powered “answer engine” Perplexity what’s the best handbag under $1,500 and you won’t see a grid of sponsored results or links to Reddit posts asking the same question.Instead, you’ll get a concise selection of five bags that fit the description, such as Chloé’s Kiss Small bag and Strathberry’s Mosaic, culled from online stories, blog posts and YouTube videos on the subject, as well as prices and a brief rundown of each bag’s key features. Perplexity provides links to where some bags can be purchased, and in certain instances, through its “Buy with Pro” option, can even complete checkout for you.The new shopping feature, available to paying subscribers, launched in November, and the results aren’t perfect. A query about the best zip boots for men returned one result with stiletto heels that it described as a women’s boot. Sometimes the products to buy aren’t the same as those highlighted in the research summary, and as TechCrunch discovered, letting Perplexity handle checkout can be slow, taking hours in one instance. But it illustrates how tech companies are thinking about the next way AI could transform the way consumers find and buy products online — via AI “agents” that can carry out complex tasks for users. Think of them like self-driving cars, but more open-ended in their abilities.In recent months, agents have become the next topic of excitement in AI. Sam Altman, OpenAI’s chief executive, called them “the thing that will feel like the next giant breakthrough” during a question-and-answer session on Reddit. Several of the industry’s largest players are actively developing agents, including ones to help consumers with shopping, or even do it for them.“Imagine taking a photo of something that you like, having the agent understand the style, find similar items across retailers and complete the purchase,” said Vince Koh, head of global solutions for digital commerce at Amazon’s Web Services division, or AWS. Koh described agents that could do things like use computer vision to help organise a user’s closet while learning their style through the visual data to make better product recommendations. “The biggest opportunity, I would say, is in creating seamless experiences that combine all these different types of interactions,” he added.While Perplexity took a lead in the field with its shopping launch, others aren’t far behind. Google and OpenAI are looking into potential uses of agents. Amazon is in the process of prototyping AI agents that could suggest products on its site, or even add them to a user’s shopping cart, Wired reported. In a sign of how valuable the company believes agents could be, AWS aims to provide agents as a service to customers, including brands and retailers. Salesforce already introduced its own platform for the purpose, called Agentforce, with Saks Fifth Avenue among its clients. Shopping with Perplexity. (Perplexity) If agents catch on, they have the potential to reshape online shopping. Many consumers are suffering from information overload and looking for solutions that can do the work of researching and selecting products for them. A report by Salesforce found that AI chatbots helped boost US online sales over the holidays by nearly 4 percent versus the prior year, suggesting consumers are using this simpler form of AI assistance.Agents would offer even more robust abilities. The consultancy Gartner forecasts that, by 2027, just over half of consumers will routinely shop for goods and services using AI shopping agents funded by companies that produce and distribute products.Before that happens, tech companies need to prove agents can actually improve shopping — and convince consumers to use them. It’s easier to see how someone might hand off buying commodity items like batteries, or purely functional ones like microwaves, to a bot versus fashion or beauty, where personal preferences and brand are so important.The Next Big Thing in AIThe idea of AI that shops for you sounds like science fiction, but in a sense it’s an evolution of the efforts retailers have made to remove friction from commerce, such as the one-click checkout Amazon pioneered decades ago. According to Dmitry Shevelenko, Perplexity’s chief business officer, the first phase for the company was changing search by giving people answers to their questions rather than links to read and digest themselves. With shopping, it’s taking the next step by letting consumers transact directly from those answers. Shevelenko said the percentage of shopping queries Perplexity gets has increased by “several multiples” since the launch, though he declined to provide exact numbers.Eventually, Perplexity envisions an agent that can behave proactively, knowing enough about a user to anticipate their needs and wants.“I don’t think the first manifestation of that is we’re just going to go buy something for you and it just shows up at your door,” Shevelenko said. “They start to come in the form of these nudges and notifications and pushes where it’s like, ‘Hey, you should really look at this’ … and then once you have that presented to you, you then have that one-click action [to purchase].”Some people actually enjoy shopping, however, particularly when it comes to fashion or beauty. They might not want to outsource the job to a bot. Shevelenko said the goal for agentic AI isn’t to automate away the joy in shopping but to remove the annoying parts.Google has agents in mind as well. They won’t be the solution for every problem, said Sean Scott, the company’s vice president and general manager of consumer shopping, in an emailed statement. The future of shopping is “assistive, personalised and seamless — in whatever form is most helpful,” he noted. But Google is pondering possibilities for agents like checking nearby stores for you to see if an item is in stock, or initiating a return and arranging a package pickup.Amazon, for one, believes they’ll prove valuable enough to shoppers that brands and retailers will want their own. The company is exploring how AWS can support clients in building agents, said Justin Honaman, head of worldwide retail, restaurants and consumer goods business development at Amazon. Agents don’t just have to be customer-facing, either. They could be focused on internal tasks, like analysing social-media trends or chatter and running visual analysis of inventory to find products that match, to take just one example. Obstacles to OvercomeImplementing them isn’t simple, however. For an agent to check if a product is available nearby, for example, it would need real-time inventory data for every store.“One of the things that we find challenging with legacy retailers is their systems are either not connected or not set up to enable the agent to get access to data,” Honaman said.That’s not the only challenge they face. The large language models that underlie agents work by making probabilistic predictions, without any genuine understanding of the world or their source content. Perplexity’s CEO, Aravind Srinivas, admitted to Fortune that the company doesn’t fully understand how its AI ranks and recommends products. That probabilistic nature makes LLMs prone to errors known as hallucinations. Some experts believe they’re an inherent side effect of how LLMs function, which would mean agents always display some rate of error. An agent could potentially give a shopper incorrect information, or try to purchase something that doesn’t exist. Amazon’s Koh said companies he’s spoken to are concerned about the issue, though he feels as the technology progresses the rate of hallucinations will decline. “I don’t view it as a principal barrier, and I certainly don’t view it as something that has to get managed to zero,” said Jason Goldberg, a retail expert and chief commerce strategy officer for the communications giant Publicis Groupe.Goldberg thinks companies will have to implement measures to mitigate hallucinations, but that shouldn’t prevent them from embracing the technology, which he believes is poised to have a dramatic impact on retail. Replenishment categories, like toilet paper, will be the first affected, but fashion and beauty aren’t beyond reach. An agent that could scrape social media and create a design brief based on the data would be valuable for brands, while one that could sift through the troves of information online to provide an item’s carbon footprint would be desirable for consumers. One unanswered question about shopping agents, however, is how effective they might be in categories where purchases are often emotional and not purely rational.“There’s been a lot of debate about this,” said Gartner analyst Andrew Frank. “I happen to be on the side of the debate that says, as AI learns more about these intangible preferences that people have for brands, it will learn how to reflect those.”One of the superpowers of LLMs is their ability to decipher relationships between nebulous qualities from smells to music styles, which is part of what makes them effective recommendation engines. But Frank sees other issues to be aware of if agents proliferate. “You wonder whose side these agents are really going to be on,” he said. Companies like Google, Amazon and others that shape shopping online make vast sums from advertising, which often means putting advertisers’ sponsored products at the top of search results. If agents are doing the filtering, will they do so to serve consumers or the advertisers? The answer might depend on the specific company and agent. Perplexity’s Shevelenko said, for now at least, the company isn’t even taking affiliate fees on sales because it doesn’t want users to feel like it’s pushing shopping simply to make money.“All it takes is one bad experience for people to give up on this technology,” he said. Source link

[norajworld]

Ask the AI-powered “answer engine” Perplexity what’s the best handbag under $1,500 and you won’t see a grid of sponsored results or links to Reddit posts asking the same question.Instead, you’ll get a concise selection of five bags that fit the description, such as Chloé’s Kiss Small bag and Strathberry’s Mosaic, culled from online stories, blog posts and YouTube videos on the subject, as well as prices and a brief rundown of each bag’s key features. Perplexity provides links to where some bags can be purchased, and in certain instances, through its “Buy with Pro” option, can even complete checkout for you.The new shopping feature, available to paying subscribers, launched in November, and the results aren’t perfect. A query about the best zip boots for men returned one result with stiletto heels that it described as a women’s boot. Sometimes the products to buy aren’t the same as those highlighted in the research summary, and as TechCrunch discovered, letting Perplexity handle checkout can be slow, taking hours in one instance. But it illustrates how tech companies are thinking about the next way AI could transform the way consumers find and buy products online — via AI “agents” that can carry out complex tasks for users. Think of them like self-driving cars, but more open-ended in their abilities.In recent months, agents have become the next topic of excitement in AI. Sam Altman, OpenAI’s chief executive, called them “the thing that will feel like the next giant breakthrough” during a question-and-answer session on Reddit. Several of the industry’s largest players are actively developing agents, including ones to help consumers with shopping, or even do it for them.“Imagine taking a photo of something that you like, having the agent understand the style, find similar items across retailers and complete the purchase,” said Vince Koh, head of global solutions for digital commerce at Amazon’s Web Services division, or AWS. Koh described agents that could do things like use computer vision to help organise a user’s closet while learning their style through the visual data to make better product recommendations. “The biggest opportunity, I would say, is in creating seamless experiences that combine all these different types of interactions,” he added.While Perplexity took a lead in the field with its shopping launch, others aren’t far behind. Google and OpenAI are looking into potential uses of agents. Amazon is in the process of prototyping AI agents that could suggest products on its site, or even add them to a user’s shopping cart, Wired reported. In a sign of how valuable the company believes agents could be, AWS aims to provide agents as a service to customers, including brands and retailers. Salesforce already introduced its own platform for the purpose, called Agentforce, with Saks Fifth Avenue among its clients. Shopping with Perplexity. (Perplexity) If agents catch on, they have the potential to reshape online shopping. Many consumers are suffering from information overload and looking for solutions that can do the work of researching and selecting products for them. A report by Salesforce found that AI chatbots helped boost US online sales over the holidays by nearly 4 percent versus the prior year, suggesting consumers are using this simpler form of AI assistance.Agents would offer even more robust abilities. The consultancy Gartner forecasts that, by 2027, just over half of consumers will routinely shop for goods and services using AI shopping agents funded by companies that produce and distribute products.Before that happens, tech companies need to prove agents can actually improve shopping — and convince consumers to use them. It’s easier to see how someone might hand off buying commodity items like batteries, or purely functional ones like microwaves, to a bot versus fashion or beauty, where personal preferences and brand are so important.The Next Big Thing in AIThe idea of AI that shops for you sounds like science fiction, but in a sense it’s an evolution of the efforts retailers have made to remove friction from commerce, such as the one-click checkout Amazon pioneered decades ago. According to Dmitry Shevelenko, Perplexity’s chief business officer, the first phase for the company was changing search by giving people answers to their questions rather than links to read and digest themselves. With shopping, it’s taking the next step by letting consumers transact directly from those answers. Shevelenko said the percentage of shopping queries Perplexity gets has increased by “several multiples” since the launch, though he declined to provide exact numbers.Eventually, Perplexity envisions an agent that can behave proactively, knowing enough about a user to anticipate their needs and wants.“I don’t think the first manifestation of that is we’re just going to go buy something for you and it just shows up at your door,” Shevelenko said. “They start to come in the form of these nudges and notifications and pushes where it’s like, ‘Hey, you should really look at this’ … and then once you have that presented to you, you then have that one-click action [to purchase].”Some people actually enjoy shopping, however, particularly when it comes to fashion or beauty. They might not want to outsource the job to a bot. Shevelenko said the goal for agentic AI isn’t to automate away the joy in shopping but to remove the annoying parts.Google has agents in mind as well. They won’t be the solution for every problem, said Sean Scott, the company’s vice president and general manager of consumer shopping, in an emailed statement. The future of shopping is “assistive, personalised and seamless — in whatever form is most helpful,” he noted. But Google is pondering possibilities for agents like checking nearby stores for you to see if an item is in stock, or initiating a return and arranging a package pickup.Amazon, for one, believes they’ll prove valuable enough to shoppers that brands and retailers will want their own. The company is exploring how AWS can support clients in building agents, said Justin Honaman, head of worldwide retail, restaurants and consumer goods business development at Amazon. Agents don’t just have to be customer-facing, either. They could be focused on internal tasks, like analysing social-media trends or chatter and running visual analysis of inventory to find products that match, to take just one example. Obstacles to OvercomeImplementing them isn’t simple, however. For an agent to check if a product is available nearby, for example, it would need real-time inventory data for every store.“One of the things that we find challenging with legacy retailers is their systems are either not connected or not set up to enable the agent to get access to data,” Honaman said.That’s not the only challenge they face. The large language models that underlie agents work by making probabilistic predictions, without any genuine understanding of the world or their source content. Perplexity’s CEO, Aravind Srinivas, admitted to Fortune that the company doesn’t fully understand how its AI ranks and recommends products. That probabilistic nature makes LLMs prone to errors known as hallucinations. Some experts believe they’re an inherent side effect of how LLMs function, which would mean agents always display some rate of error. An agent could potentially give a shopper incorrect information, or try to purchase something that doesn’t exist. Amazon’s Koh said companies he’s spoken to are concerned about the issue, though he feels as the technology progresses the rate of hallucinations will decline. “I don’t view it as a principal barrier, and I certainly don’t view it as something that has to get managed to zero,” said Jason Goldberg, a retail expert and chief commerce strategy officer for the communications giant Publicis Groupe.Goldberg thinks companies will have to implement measures to mitigate hallucinations, but that shouldn’t prevent them from embracing the technology, which he believes is poised to have a dramatic impact on retail. Replenishment categories, like toilet paper, will be the first affected, but fashion and beauty aren’t beyond reach. An agent that could scrape social media and create a design brief based on the data would be valuable for brands, while one that could sift through the troves of information online to provide an item’s carbon footprint would be desirable for consumers. One unanswered question about shopping agents, however, is how effective they might be in categories where purchases are often emotional and not purely rational.“There’s been a lot of debate about this,” said Gartner analyst Andrew Frank. “I happen to be on the side of the debate that says, as AI learns more about these intangible preferences that people have for brands, it will learn how to reflect those.”One of the superpowers of LLMs is their ability to decipher relationships between nebulous qualities from smells to music styles, which is part of what makes them effective recommendation engines. But Frank sees other issues to be aware of if agents proliferate. “You wonder whose side these agents are really going to be on,” he said. Companies like Google, Amazon and others that shape shopping online make vast sums from advertising, which often means putting advertisers’ sponsored products at the top of search results. If agents are doing the filtering, will they do so to serve consumers or the advertisers? The answer might depend on the specific company and agent. Perplexity’s Shevelenko said, for now at least, the company isn’t even taking affiliate fees on sales because it doesn’t want users to feel like it’s pushing shopping simply to make money.“All it takes is one bad experience for people to give up on this technology,” he said. Source link

[fexleservices]

Omnichannel Engagement for Seamless Interactions

Agentforce enables businesses to manage customer interactions across email, chat, and social media in one place. This ensures a consistent and personalized experience. Elevate your engagement strategy with an Agentforce implementation partner and stay ahead in customer service

[chilimili212]

Ask the AI-powered “answer engine” Perplexity what’s the best handbag under $1,500 and you won’t see a grid of sponsored results or links to Reddit posts asking the same question.Instead, you’ll get a concise selection of five bags that fit the description, such as Chloé’s Kiss Small bag and Strathberry’s Mosaic, culled from online stories, blog posts and YouTube videos on the subject, as well as prices and a brief rundown of each bag’s key features. Perplexity provides links to where some bags can be purchased, and in certain instances, through its “Buy with Pro” option, can even complete checkout for you.The new shopping feature, available to paying subscribers, launched in November, and the results aren’t perfect. A query about the best zip boots for men returned one result with stiletto heels that it described as a women’s boot. Sometimes the products to buy aren’t the same as those highlighted in the research summary, and as TechCrunch discovered, letting Perplexity handle checkout can be slow, taking hours in one instance. But it illustrates how tech companies are thinking about the next way AI could transform the way consumers find and buy products online — via AI “agents” that can carry out complex tasks for users. Think of them like self-driving cars, but more open-ended in their abilities.In recent months, agents have become the next topic of excitement in AI. Sam Altman, OpenAI’s chief executive, called them “the thing that will feel like the next giant breakthrough” during a question-and-answer session on Reddit. Several of the industry’s largest players are actively developing agents, including ones to help consumers with shopping, or even do it for them.“Imagine taking a photo of something that you like, having the agent understand the style, find similar items across retailers and complete the purchase,” said Vince Koh, head of global solutions for digital commerce at Amazon’s Web Services division, or AWS. Koh described agents that could do things like use computer vision to help organise a user’s closet while learning their style through the visual data to make better product recommendations. “The biggest opportunity, I would say, is in creating seamless experiences that combine all these different types of interactions,” he added.While Perplexity took a lead in the field with its shopping launch, others aren’t far behind. Google and OpenAI are looking into potential uses of agents. Amazon is in the process of prototyping AI agents that could suggest products on its site, or even add them to a user’s shopping cart, Wired reported. In a sign of how valuable the company believes agents could be, AWS aims to provide agents as a service to customers, including brands and retailers. Salesforce already introduced its own platform for the purpose, called Agentforce, with Saks Fifth Avenue among its clients. Shopping with Perplexity. (Perplexity) If agents catch on, they have the potential to reshape online shopping. Many consumers are suffering from information overload and looking for solutions that can do the work of researching and selecting products for them. A report by Salesforce found that AI chatbots helped boost US online sales over the holidays by nearly 4 percent versus the prior year, suggesting consumers are using this simpler form of AI assistance.Agents would offer even more robust abilities. The consultancy Gartner forecasts that, by 2027, just over half of consumers will routinely shop for goods and services using AI shopping agents funded by companies that produce and distribute products.Before that happens, tech companies need to prove agents can actually improve shopping — and convince consumers to use them. It’s easier to see how someone might hand off buying commodity items like batteries, or purely functional ones like microwaves, to a bot versus fashion or beauty, where personal preferences and brand are so important.The Next Big Thing in AIThe idea of AI that shops for you sounds like science fiction, but in a sense it’s an evolution of the efforts retailers have made to remove friction from commerce, such as the one-click checkout Amazon pioneered decades ago. According to Dmitry Shevelenko, Perplexity’s chief business officer, the first phase for the company was changing search by giving people answers to their questions rather than links to read and digest themselves. With shopping, it’s taking the next step by letting consumers transact directly from those answers. Shevelenko said the percentage of shopping queries Perplexity gets has increased by “several multiples” since the launch, though he declined to provide exact numbers.Eventually, Perplexity envisions an agent that can behave proactively, knowing enough about a user to anticipate their needs and wants.“I don’t think the first manifestation of that is we’re just going to go buy something for you and it just shows up at your door,” Shevelenko said. “They start to come in the form of these nudges and notifications and pushes where it’s like, ‘Hey, you should really look at this’ … and then once you have that presented to you, you then have that one-click action [to purchase].”Some people actually enjoy shopping, however, particularly when it comes to fashion or beauty. They might not want to outsource the job to a bot. Shevelenko said the goal for agentic AI isn’t to automate away the joy in shopping but to remove the annoying parts.Google has agents in mind as well. They won’t be the solution for every problem, said Sean Scott, the company’s vice president and general manager of consumer shopping, in an emailed statement. The future of shopping is “assistive, personalised and seamless — in whatever form is most helpful,” he noted. But Google is pondering possibilities for agents like checking nearby stores for you to see if an item is in stock, or initiating a return and arranging a package pickup.Amazon, for one, believes they’ll prove valuable enough to shoppers that brands and retailers will want their own. The company is exploring how AWS can support clients in building agents, said Justin Honaman, head of worldwide retail, restaurants and consumer goods business development at Amazon. Agents don’t just have to be customer-facing, either. They could be focused on internal tasks, like analysing social-media trends or chatter and running visual analysis of inventory to find products that match, to take just one example. Obstacles to OvercomeImplementing them isn’t simple, however. For an agent to check if a product is available nearby, for example, it would need real-time inventory data for every store.“One of the things that we find challenging with legacy retailers is their systems are either not connected or not set up to enable the agent to get access to data,” Honaman said.That’s not the only challenge they face. The large language models that underlie agents work by making probabilistic predictions, without any genuine understanding of the world or their source content. Perplexity’s CEO, Aravind Srinivas, admitted to Fortune that the company doesn’t fully understand how its AI ranks and recommends products. That probabilistic nature makes LLMs prone to errors known as hallucinations. Some experts believe they’re an inherent side effect of how LLMs function, which would mean agents always display some rate of error. An agent could potentially give a shopper incorrect information, or try to purchase something that doesn’t exist. Amazon’s Koh said companies he’s spoken to are concerned about the issue, though he feels as the technology progresses the rate of hallucinations will decline. “I don’t view it as a principal barrier, and I certainly don’t view it as something that has to get managed to zero,” said Jason Goldberg, a retail expert and chief commerce strategy officer for the communications giant Publicis Groupe.Goldberg thinks companies will have to implement measures to mitigate hallucinations, but that shouldn’t prevent them from embracing the technology, which he believes is poised to have a dramatic impact on retail. Replenishment categories, like toilet paper, will be the first affected, but fashion and beauty aren’t beyond reach. An agent that could scrape social media and create a design brief based on the data would be valuable for brands, while one that could sift through the troves of information online to provide an item’s carbon footprint would be desirable for consumers. One unanswered question about shopping agents, however, is how effective they might be in categories where purchases are often emotional and not purely rational.“There’s been a lot of debate about this,” said Gartner analyst Andrew Frank. “I happen to be on the side of the debate that says, as AI learns more about these intangible preferences that people have for brands, it will learn how to reflect those.”One of the superpowers of LLMs is their ability to decipher relationships between nebulous qualities from smells to music styles, which is part of what makes them effective recommendation engines. But Frank sees other issues to be aware of if agents proliferate. “You wonder whose side these agents are really going to be on,” he said. Companies like Google, Amazon and others that shape shopping online make vast sums from advertising, which often means putting advertisers’ sponsored products at the top of search results. If agents are doing the filtering, will they do so to serve consumers or the advertisers? The answer might depend on the specific company and agent. Perplexity’s Shevelenko said, for now at least, the company isn’t even taking affiliate fees on sales because it doesn’t want users to feel like it’s pushing shopping simply to make money.“All it takes is one bad experience for people to give up on this technology,” he said. Source link

[ravaglobal]

The Future of CRM: How Salesforce is Leading the Way

Explore how Salesforce is shaping the future of Customer Relationship Management (CRM) with innovative solutions like Agentforce, an AI-powered platform that automates tasks such as sales outreach and customer support. As a trusted Salesforce Consulting Partner in the USA, RAVA Global Solutions helps businesses leverage these advancements to enhance customer engagement and drive growth.