SalesForce

Using Salesforce to manage accounts and customer relationships? Want to scale customer service quickly at a cost that doesn’t dent your IT budget? With Chatbots for Salesforce, you can leverage AI technology to greatly improve the efficacy of your customer support. What are Salesforce Einstein bots, and third-party chatbots, and how can you implement a Salesforce chatbot? This guide aims to answer these and several more questions. 2016 witnessed the launch of Salesforce Einstein, a natively integrated AI for its leading CRM platform. With Einstein, organizations can the power of a suite of AI technologies across Salesforce Lightning platform as well as Salesforce cloud products. Post the launch of Einstein, businesses, regardless of size and industry, have been building and deploying chatbots – native as well as custom chatbots from third-party developers. Why should you implement them and how do you go about building one? What is a Salesforce chatbot? Salesforce chatbot is a virtual agent grounded in Salesforce's EinsteinAI technology that can engage in text-based conversations with users via regular chat interfaces like messaging apps, mobile apps, and chat windows on websites. Chatbot for Salesforce can help businesses automate their customer support, sales, and marketing by leveraging a 24/7 assistant. Why implement Salesforce chatbots? Salesforce chatbots are ideal for businesses that want to leverage their CRM data to deliver improved customer support. With Chatbot for Salesforce, businesses can streamline: 1. Personalized customer support Salesforce chatbot can answer FAQs, provide intelligent recommendations to guide customers on purchase decisions, schedule, track, and manage appointments, and track orders. Salesforce chatbots draw upon the company knowledge base and customer data to provide tailored responses to them based on their interaction history, behavior, and preferences, translating to improved customer satisfaction. 2. Improved analytics and reporting Chatbots for Salesforce can gather customer data in real-time. For instance, if a customer abandons a conversation with a chatbot at any moment, a specific field in the database can be updated to maintain the record. Sales and support teams can leverage this data to identify trends and make informed decisions. 3. Operational excellence Salesforce chatbots can be easily integrated with other Salesforce cloud products like Sales Cloud, Service Cloud, or Marketing Cloud to deliver seamless customer experiences. Einstein GPT Salesforce recently announced the launch of Einstein GPT – its own GPT assistant for the CRM. Salesforce also announced its commitment to a $250 million Generative AI Fund to push the development of responsible generative AI. What is Einstein GPT? Einstein GPT works pretty much like ChatGPT, except that it is seamlessly integrated with Salesforce Data Cloud to operate on the organization’s entire data. Einstein GPT leverages generative AI to train itself on customer and organizational data to create personalized content for various use cases. And content does not mean only text, Einstein GPT can leverage data to provide insights in seconds or automate mundane tasks thereby driving employee productivity. Einstein GPT can: Generate personalized emails for sales professionals by leveraging customer data. Write personalized and contextual responses for customer service reps to answer common customer questions faster. Automate on-demand tasks like scheduling a meeting. Compose targeted content for marketing professionals to boost campaign response rates. Create articles for the knowledge base automatically from case notes. Provide AI-powered insights such as sales summaries. Accelerate development by auto-generating code. Salesforce has also launched separate EinsteinGPT-powered solutions for different platforms based on use cases such as Marketing GPT, Tableau GPT, and Slack GPT. How to Use Chatbots for Salesforce Chatbots for Salesforce can used in multiple ways depending on the organization. They can be used to support sales, marketing, customer support, HR, engineering, and other departments depending on the use case. All in all, the core objective of a chatbot is to automate engagement and free up employee time so they can work on more complex tasks. One of the greatest benefits of Chatbots for Salesforce is their 24/7 availability. They can respond to customer questions in real time by leveraging CRM data. Salesforce chatbots can be deployed to augment various use cases in different industries. Here are some common use cases for Salesforce chatbots: Customer service: Chatbot for Salesforce can automate customer support by answering common questions quickly, helping customers reset passwords, track orders, renew subscriptions, and more. Salesforce chatbots can leverage the company’s knowledge base to provide personalized answers, search for records, and provide updates. Lead generation: Chatbots can engage website, social media, or app visitors, collect relevant information, and qualify leads in Salesforce. Sales support: Sales professionals can utilize chatbots to schedule/re-schedule meetings, create and send follow-up emails, and update customer records. Marketing automation: Chatbots can automate marketing tasks such as outbound promotional messages. Chatbots for Salesforce have proven to be quite useful in conducting surveys and collecting feedback. Employee support: Just like serving customers, Chatbots can also assist employees with answers to HR inquiries, IT support, managing leave and work schedules, and more. How to Implement a Chatbot in Salesforce Salesforce has made it very easy to get started with chatbots. All you need to do is switch it “on” in Service Cloud. But before deploying your first chatbot on the frontline, you need to consider a few important things. Step One: Establish bot features and set goals Prep yourself up on what Salesforce chatbots can do. Identify the pain points or optimization opportunities and establish if the chatbot can address any of these areas. While some common chatbot use cases have been discussed above, here are some additional chatbot features you should be aware of: Dialog & journey management: Chatbots are not just vanilla messengers. They can handle complex conversations by relying on pre-defined decision trees to ensure an engaging conversation. With the right implementation, they can convert visitors to leads. Focus on tasks that can be automated easily. Work with the relevant teams to build interaction flows that are easy to understand and can be implemented without any human intervention. Intent recognition: Chatbots for Salesforce can be trained to recognize user intent and provide personalized responses based on past interactions, user preferences, and contextual information. We recommend you identify keywords on common customer queries to train the chatbot for optimal performance.  Natural language processing (NLP): Chatbots for Salesforce leverage NLP capability to understand and interpret user queries leading to more human-like, personalized interactions. As a recommendation, you can train your chatbot on your organization’s data for enhanced performance and understanding of customer queries. Multilingual: Chatbots can respond in multiple languages, provided they have access to necessary information and have the right training. If you run a global business with customers in multiple geographies, you can start with one or two languages of your most popular regions. Multiple Channels: Chatbots can engage in conversations across multiple channels such as a website, WhatsApp, and SMS. Identify which channel is the preferred choice of our customers and start from there. While these features will give you a better sense of chatbot capabilities, it is equally important to set clear goals to measure the success of your chatbot performance. The next step is to determine what you want your chatbot to do for your business and how to achieve them. Ensure that the goals you define are clear and measurable to achieve the best results. Once you have established your goals, define the use case, and then build the chatbot to align with it. Step 2 – Determine the implementation options.  There are two ways in which you can implement a Chatbot for Salesforce: Einstein bots and third-party chatbots. Einstein Bots are available natively in Salesforce. Third part chatbots can be implemented by integrating them with Salesforce. Einstein Bots are natively available in Salesforce Classic as well as the Lightning Experience. Salesforce provides an intuitive click-and-drag interface making it easy to set up and start using the chatbots. Einstein Bot is a code-less solution that allows you to get your bot off the blocks quickly. All you need to do is simply include existing objects and data in Salesforce such as Knowledge articles, templates, contact information, and customer data. Einstein bots have Natural Language Processing (NLP) capability so they can understand what your users are asking. And because they are native to Salesforce, you can easily incorporate Apex Code and Flows to build custom logic into your bot conversations allowing you to do much more with them than just answer FAQs. To begin with, you need a Service Cloud license along with a Chat or Messaging license. Each Salesforce org is provided 25 Einstein Bot conversations per user per month with every active subscription. Businesses must get hold of the Service Analytics App to unlock the power of the Einstein Bots Performance page. Einstein bots can be set up in an hour, and you can download templates from AppExchange to get started. Custom chatbots on the other hand are built by third-party developers and then integrated with Salesforce when it is time to deploy these chatbots. If you wish to deploy a third-party chatbot, it's best to align with a certified Salesforce Consulting Partner to derive maximum value. Why build a custom chatbot when a native Einstein chatbot is available? Custom chatbots are much more flexible and offer more options than native chatbots for Salesforce. Custom chatbots can offer much more features and functionality than what you get with Salesforce chatbots. Custom chatbots can be integrated with any of your existing tools and systems such as CRM, or inventory management systems. This leads to a more seamless customer experience and also streamlines internal processes. Custom chatbots can be connected with the latest AI technologies and Large Language Models (LLMs). This can optimize chatbot performance and translate to long-term savings. Einstein chatbots are native to Salesforce and have limited options for customization. They can appear to be generic and impersonal to users. By aligning with a certified Salesforce Implementation Partner, you can tailor your third-party chatbots according to the unique needs of your business. Custom chatbots can bring forth your brand in terms of tone of communication and can be trained by an entire team of experts to understand the language of your users, making customer conversations more engaging and personal. The biggest advantage of a third-party chatbot is that you can add unique functionality as per your business needs, whenever you want. You can keep on adding specific use cases and modify existing ones with the support of the third-party provider. Overall, custom chatbots will give you greater flexibility and personalization compared to native chatbots, making them a better choice to improve the user experience. Summary Einstein Bots are ideal for setting up basic, automated customer-service chatbots without any external integrations. However, for larger businesses that have their data spread across multiple systems, custom chatbots could be a better choice because of their flexibility in integration, not to mention the flexibility in pricing as well for higher volumes. Step Three: Identify a resource and build a chatbot! With Einstein bots, only one developer is allowed to modify chatbots. It’s best to identify one person who can implement and track its performance. Once you have established clear chatbot goals, you can follow these steps to implement a native Salesforce chatbot: Follow the technical setup: Ensure that you connect the chat and match the requirements as recommended by Salesforce. Build your chatbot: Go to Salesforce help articles for tips on how to build your chatbot. These articles will guide you on how to design conversational flows, how to create responses to user queries, and also offer guidance on integrating with Salesforce objects such as Knowledge Base, Apex, and more. Salesforce has a comprehensive library of articles to help you set up Einstein bot features as you need them to be. Test your chatbot: Test, test, test. The more you test, the better your bot will become. This includes testing the conversation flows, bot responses, decision trees, and integration with Salesforce. Repeat until you are satisfied with the answers. Train your chatbot: Connect Natural Language Processing to train your chatbot by providing it with feedback. This will improve the bot’s accuracy over time. Launch, monitor, and optimize: Monitor chatbot performance and optimize periodically. This includes tracking chatbot metrics like customer satisfaction, conversion rates, and bot response times and making the necessary adjustments to optimize performance. If you are a Salesforce customer, deploying a Salesforce AI chatbot can significantly improve your customer service operations. Salesforce chatbots are a quick and efficient way to leverage existing Salesforce data to drive the customer experience. If you wish to implement a custom chatbot, book a meeting with our Salesforce AI services expert today. Our team of experts can help you get off the blocks quickly with a tailored bot solution.

Buyers today seek compelling digital shopping experiences and expect to be able to make purchases in a few clicks. To meet these expectations, brands can incorporate a variety of add-ons, customization tools, and other features into advanced CRM platforms such as Salesforce Sales Cloud. Sales Cloud from Salesforce is a robust and flexible CRM that includes all of the necessary features to help organizations enter new markets, execute result-oriented sales strategies to acquire new customers, and boost conversions. Whether you're a small firm wanting to get started with Sales Cloud or a large corporation looking to optimize your existing sales processes, this guide has you covered. So let's get started on your road to excel with Salesforce Sales Cloud. Whether it's understanding what Sales Cloud is, studying its capabilities, learning about its configuration and implementation, or determining how it outperforms others, this article will answer all these questions. What is Salesforce Sales Cloud? Sales Cloud from Salesforce is a cloud-based solution designed purpose-built to empower sales teams and centralize the complete customer data. With Sales Cloud, sales professionals can track every customer and automate tedious tasks. The platform provides sales reps with a common ground to track customer-related activity, communications, and buying history. Salesforce Sales Cloud has a variety of features for pipeline management, deal monitoring, auto-quote creation, sales forecasting, and customer behavior, all of which help sales professionals close more deals. Sales managers can use Sales Cloud to automate sales processes, increasing team efficiency and productivity. An effective CRM strategy is essential for competing and staying ahead of the competition. A sound CRM strategy is fundamental to robust and efficient sales practices rather than dealing with manual sales and customer service processes. Salesforce Sales Cloud Features Sales Cloud has an abundance of tools and features to fine-tune even the smallest aspects of the sales process, activities, and goals. Salesforce Sales Cloud includes a feature for every purpose that is specifically designed to fit your company models, style, needs, and operations. Here are some key business objectives aligned with Sales Cloud : Acquire More Deals The obvious key to maximizing sales is to acquire more deals. It is easier to close more business by continuously optimizing campaigns based on market response and interacting with channel partners. Lead Management: With Sales Cloud, you can create your own lead machine to boost conversion rates and revenues. Track your leads from start to finish, and optimize campaigns across all channels. Make better selections by investing marketing dollars with comprehensive calculations. Sales Data: To augment effective decision-making, get access to real-time sales data. With the most up-to-date and accurate data, you can easily plan territories and boost your sales and marketing productivity. Close More Deals Higher sales translate to higher revenue. To ensure that your sales reps can maximize deal closure, you will require these Sales Cloud components. Account and Contact Management: Take a comprehensive look at your customers' activity history, important contacts, customer conversations, and internal account discussions. Gain insights from popular social media platforms such as Facebook, Twitter, and LinkedIn using Salesforce Sales Cloud. Opportunity Management: View deals created by your sales reps. Sales Cloud provides access to all stages of the sales lifecycle, as well as products, competitors, quotes, and other services. Keep up with the people and information you need to complete every transaction. Users can collaborate using Chatter cooperation to close sales by soliciting feedback from team members. Close Deals Faster Your teams can leverage the following capabilities of Sales Cloud to close deals quickly. Mobile The Salesforce mobile application transforms your smartphone into a portable office, allowing teams to access the cloud from anywhere. Increase productivity by allowing teams to work when it is convenient for them, logging calls, responding to hot leads and work opportunities, and reviewing dashboards as needed. Workflow and Approvals Visual Workflow helps you to quickly develop and automate business processes using drag-and-drop functionality. Create custom approval processes for sales, offers, expenses, and more. File Sync and Share Share and discuss documents, publish the most relevant ones, and track content in real-time using the File Sync and Share feature. Find what you need instantly, share it securely, and get alerts whenever updates are made. Automation Sales automation streamlines sales operations by deploying automation tools and creating workflows. It streamlines the sales process and reduces manual tasks for sales professionals. Furthermore, contact and opportunity management are well-organized, allowing reps to access data and interaction history in one location. Marketing automation can also help businesses improve the quality of their customer care. Faster Decisions When multiple tools are aligned properly, the decision-making process becomes seamless and thorough. Reports and Dashboards: Dashboards allow you to see real-time information about your business in a single view. Create detailed reports and access them from any device. Sales Forecasting: Get real-time updates on team predictions, modify them, override visibility, support multiple currencies, and more such capabilities to stay on top of your business. Sales Cloud Einstein: Sales Cloud Einstein is a predictive and analytics solution that enables sales representatives to take data-driven actions and boost conversion rates. It provides analysis based on prior data from robust data models and provides accurate sales forecasts to enable smarter decision-making. Best Practices for Sales Cloud Implementation Customize as per Business Needs CRM customization boosts sales process scalability, increases efficiency, and reduces response times. A variety of user-friendly and customizable apps, profiles, dashboard layouts, and UI enable the creation of comprehensive processes, the display of specific data, and permission sets to improve security. Custom Objects and apps can assist in the proper tracking of deals in the pipelines. Furthermore, a sales-support app can be developed to allow reps easy access to information across the system. Develop Salesforce Central in Accordance With How Your Team Works. To ensure the successful implementation of Sales Cloud in your company, make its usage the focal point of the department. Every detail regarding the customer should pass through Sales Cloud, which will later be used to evaluate the rep's performance. Salesforce centralization also improves accountability by ensuring the quality of dashboard setups. Make all meetings and prospective ideas a reliable source of information for the entire team. Automate all Sales Processes According to a Salesforce survey, sales reps spend 28% of their time on core sales activities and the remainder on deal management and data entry. Businesses can increase efficiency by incorporating automation into sales-related processes. When mundane tasks are eliminated, teams have a clear understanding of what and how they should strategize selling. Automated workflows and approvals allow for faster and more efficient decision-making. Utilize Sandboxes Before you launch any new functionality in Sales Cloud, test it thoroughly, and sandboxes are the best place for this. Sandboxes protect your existing system by serving as an identical twin of the operational system, allowing for secure testing. Endorse the use of sandboxes to ensure that the implementation does not disrupt your existing infrastructure. Empower Sales Teams with Data Science Tools Data management is an eclectic combination of science and art, and therefore can be quite a daunting task. Finding the right balance between maintaining and analyzing data that allows the sales staff to make informed decisions is challenging. Sales Cloud Einstein makes things easier by interpreting factual data with artificial intelligence. This processed data generates a network of leads, allowing managers and leaders to take specific actions. Using Sales Cloud Einstein's intelligence, you can discover high-priority leads and focus on their conversion. Salesforce Einstein AI can help you expand your business by providing the features listed above. How Sales Cloud Facilitates Business Growth? Everyone enjoys discussions about how to maximize revenues, scalability, and efficiency in their day-to-day operations. When Sales Cloud is implemented, here are some of the potential benefits for your business: Reliable Reporting Every organization has a humongous amount of data that must be managed, processed, and sifted in order to generate actionable insights that can then be used to develop strategies. Data collection and management are straightforward, but analysis demands intelligence. Sales Cloud organizes data after it has been processed through multiple rounds of analysis, focusing on error elimination. Managers can plan the next best actions using insightful reports and dashboards. Improved Customer Engagement & Service Salesforce captures data that helps the sales team do targeted marketing. When efforts are made in the proper direction, it results in increased customer engagement and service efficiency. When the Sales team is fully aware of their clients' needs, they can deal with them proactively. Boost Productivity with AI Salesforce Sales Cloud's AI capabilities use machine learning and AI technologies to provide deep insights from multiple sales channels. Analyzing sales efforts allows AI to evaluate the effectiveness of a strategy. It also enables the team to automate operations, handle leads, and support teams in closing deals in the shortest possible time. Reasons to Hire a Salesforce Implementation Partner Outsourcing Salesforce implementation to a certified partner can provide various benefits, including: Expertise and Experience Salesforce implementation companies typically use a team of skilled and trained specialists who have a thorough understanding of the platform and its possibilities. They deliver the greatest implementation solution to businesses by following the best business approach. Time and Cost Savings Hiring a Salesforce partner rather than training your internal team will save you time and money. Teams with an implementation partner collaborate more effectively on implementation in less time and at a lesser cost. Customized Solutions The partners offer customized solutions based on business needs and goals. They also thoroughly analyze existing processes to discover gaps and potential for change, and then create a solution appropriately. Reduced Risk Partners mitigate the risks involved with installing a new Salesforce solution, manage complicated projects, and detect possible risks and concerns before they become problems. This can help ensure a smoother installation and reduce business disruption. Ongoing Support They offer ongoing support and maintenance to ensure that your Salesforce solution remains current and adapts to your changing business requirements. They offer training, support, and guidance on how to optimize your Salesforce instance to meet your business goals. Still, looking for a reason to hire? Why not speak with one of our certified Salesforce consultants for a free Sales Cloud demo?

Over 150,000 companies worldwide rely on the Salesforce platform, which unifies data from multiple sources, including users, customers, and integrations. However, the need for effective data management grows along with the amount of data. A crucial element in this process is archiving Salesforce data. Even if your Salesforce data grows over time, you can still manage data efficiently, save storage expenses, and preserve a flawless user experience. What is Salesforce Data Archiving? Some of the data in your Salesforce system eventually becomes less important as it accumulates over time. While not all data needs active access, a large portion of it nevertheless needs to be kept on file in order to comply with legal obligations and for possible future use. Businesses are required by industry-specific norms and data regulation laws to retain various types of data for specified amounts of time. Thus, long-term, safe data storage is required by law in addition to being good practice. Even while maintaining your data is one of your legal responsibilities, these same regulations frequently require that sensitive data be deleted or have access to it restricted after specific periods of time or under pre-defined circumstances. Laws like the California Privacy Rights Act (CPRA) and the General Data Protection Regulation (GDPR) are based on the principle of data minimization, which states that companies should not retain more data than is essential or for longer than is necessary. Difference between Data Archiving and Data Lifecycle? Since both data archiving and data lifecycle management are essential components of data governance, it's easy to mix up the terms. However, these two ideas serve different functions and follow different procedures. The process of managing data throughout its lifecycle, from creation and initial storage to the point at which it becomes outdated and is finally removed, is known as data lifecycle management. It consists of multiple crucial phases that center on the lawful use and preservation of information. Anonymizing production data is essential in this situation to maintain compliance. On the other hand, data archiving is a particular phase in the data lifecycle. It entails transferring dormant data from main storage to a system made especially for preservation over time and sporadic access. Here, keeping data available when needed is important, but it shouldn't clog the system or impair its functionality. To put it briefly, data archiving is the crucial decision on what to do with your data as its operational life draws to a close. Data lifecycle management, then, is a more comprehensive procedure while the data is being used. Gaining a full understanding of these ideas can help you make informed decisions about what data to archive and when, so your Salesforce system will function as efficiently as possible while still adhering to regulations. Why should you archive your Salesforce data? There may be an urgent need to delete data from Salesforce if you are already experiencing system delay. You can improve system performance, simplify your archiving, and maintain compliance with a strong data lifecycle strategy. Data privacy is of utmost importance in the modern world, particularly when it comes to personal data. Strict laws like the CPRA and GDPR necessitate this. But it's important to remember that other factors should also be considered, in addition to data archiving. To respect privacy requirements and maintain the functionality of your data, you should also take data anonymization and pseudonymization into consideration. If you manage these legal obligations well, archiving may only be necessary when system performance is an issue. While you are erasing data, initiating data archiving may seem like a risky idea, but it doesn't have to be. You won't find data deletion or even archiving to be as daunting once you fully grasp the data lifecycle. Your archiving project will be a lot easier to handle if you practice effective data lifecycle management. A backup plan serves as your security. Your backup can act as a safety net in case you ever make a mistake with your archiving criteria, guaranteeing that no important data is lost in the process. Salesforce ensures your safety and security. Large Data Volumes and more complex use cases can be more effectively managed with a third-party archiving solution. Benefits of Salesforce data archiving There are several reasons for organizations to consider Salesforce data archiving. An effective archiving solution can solve: System performance Legal and compliance needs Obsolete data Salesforce data archiving improves system performance Archiving Salesforce data can enhance system performance in these ways: Because there is less data to manage, activities proceed more quickly. In the end, archiving helps systems operate better by preventing restrictions from being reached, such as API call limits and data and file storage capacity constraints. Salesforce data archiving facilitates adherence to legal, regulatory, and data retention policies: Businesses operating in highly regulated industries are frequently required to comply with several regulatory standards, which might vary depending on the business model and regional presence. You cannot keep data in your Salesforce Org permanently since noncompliance might have detrimental financial effects. Sensitive information in your Salesforce data might need to be kept safe in case the necessity to exhibit the documents later on arises. In that scenario, archiving this data would be preferable over completely deleting it. Certain organizations might have regulations requiring the removal of information, while others might have lengthy data retention periods that include keeping a lot of data. Your data must comply with the company's data retention policy, depending on the terms of the policy. By removing data from production Orgs and restricting access to a smaller set of users, archiving Salesforce data can assist in adhering to these laws and standards. This guarantees that should it become necessary in the future, the data will still be searchable and unarchived. Your org can benefit from archiving obsolete Salesforce data It may not always be the best idea to delete outdated data in order to make storage space available because doing so may result in the loss of important business data. You can make sure you have the data in case you need it later by properly archiving Salesforce data rather than deleting it. How do you archive Salesforce data? Identify the data Establish effective ways to help you identify the data that has to be removed. Learn the best practices and go beyond the capabilities of Salesforce native queries by collaborating with a Salesforce consulting company. Retain your data Keep your data safe and unchangeable for extended periods of time by storing it in an encrypted manner. For an audit trail, make sure the data is safe and secure for many years to come. Remove your data Remove data from Salesforce at scale in a safe and organized manner. To maintain data balance, queue up data loads over the course of several days, weeks, or months. Design your User Experience Give your Salesforce users a familiar appearance and feel by creating custom page layouts. Create the connections and relationships that your CRM data needs to have. Best practices for Salesforce data archiving To achieve efficient Salesforce data archiving, thorough planning and analysis are required. Organizations should plan for the following when archiving: Storage and Limits Monitor how much storage your company has available and how much is being used. This can help you determine how much storage space you need to free up, allowing you to outline the scope of your archiving job. Usage Trends To effectively archive data in your Salesforce system, you must first understand the data utilization metrics. Make sure you have the proper tools for assessing data volume and tracking trends. Use APIs based on Salesforce Einstein Analytics to create numerous dashboards and track data usage and trends. The software can also help you identify misuse or strange events. Parent-Child Relationships and Data Integrity To retrieve data from the Salesforce data archive and bring it to production, make sure to keep the archived object's Parent-Child record. Otherwise, the data may be incomplete or inaccurate. For example, unarchiving an account without its related contacts would not be desirable. And, if you intend to delete data from the Salesforce data archive, check with your organization's legal team first, since there may be data integrity consequences, such as Parent-Child Relationships or Field Removal. Determine how often you want to archive Salesforce data. Establish the frequency of archiving and develop archiving processes that allow for automatic archiving. Encrypt your Salesforce data archives Your archived data should be protected both in transit and at rest to ensure that only authorized individuals have access to it. Use the best Salesforce archiving tool When selecting a Salesforce data backup and archiving tool, look for one that is certified by Salesforce and has a proven track record. It must be user-friendly and efficient. Archiving Salesforce data is critical for large-scale businesses. As Salesforce data grows, data archiving becomes increasingly important because it improves Salesforce system efficiency, automates compliance, and reduces storage without losing access to data. For efficient and successful Salesforce data archiving, collaborate with a team of certified Salesforce consultants from Girikon, a Gold Salesforce partner. Here’s what you can do with Girikon Data Archiving Services Organizations looking to archive their Salesforce data at scale need a comprehensive strategy that ensures safe Salesforce data archiving at scale. With over a decade of experience in working with Salesforce customers, Girikon’s professional Salesforce Consulting Services can support the most complex Salesforce data archiving use cases for businesses. Contact us today to learn more.

It is obvious that artificial intelligence (AI) will transform the way solutions are designed. It is time to acknowledge that there is a fundamental change in how one needs to approach architecture. In the past, solutions were developed based on an algorithmic understanding of the problem, guaranteeing consistency in output with the same input. For example, in a CRM system with an account segmentation process, the conventional approach involved defining fields on the account and applying business logic for segmentation, driving other automation in the system. However, in the era of artificial intelligence, models are created using a lot of data, leading to the creation of predictive models. Large language models (LLMs) change the way solutions are designed because they can handle more intricate personalized segmentation and consider a much larger range of data. In order to better comprehend this, let's examine how AI is affecting solution design and delivery by closely examining the following topics. Transforming the user experience The transformative impact of artificial intelligence (AI), especially with regard to generation AI, is responsible for its current surge in popularity. Users can interact with technology using natural language for the first time. This represents a significant paradigm shift since it can now receive requests that fully and accurately match the user's intentions. Moving to a Natural Language Processing (NLP) experience Platforms are starting to focus more on NLP (Natural Language Processing) and less on if-then-else scenarios. The user is spared from having to search through numerous fields. Rather, the user receives an English response to their questions. This streamlines onboarding, increasing its speed and effectiveness without requiring agents to undergo in-depth training. Increased productivity AI empowers businesses to do more with fewer customizations translating to increased work efficiency. The challenges of AI While AI provides benefits, it also presents new challenges, such as: Having to account for a wider range of data in a probabilistic context. Performance guarantees are not identical, therefore factors like error management and observability must be re-evaluated. Without direct insight into how language models work, troubleshooting becomes more challenging. Problems like hallucinations, where the model will make things up – while there are solutions to address these problems, none are completely dependable. Prompts can introduce biases and additional security problems into a language model. In an era where data privacy and trust are paramount, it is critical to create approaches for error management and improving the predictability of AI output in order to secure data security and privacy. How is AI impacting engagement with professional services companies? Even while processes have evolved and agility has increased over the past couple of decades, the traditional approach to delivery has stayed mostly unchanged. This is how AI can change the engagement model with professional services firms: Fast-track every stage of the delivery process. The kinds of jobs that people can have and the kinds of skills they need will change dramatically as a result of NLP. If the volume of data generated by the sales team during the discovery phase can be summarized into a handover, it would save the project team and the customer a lot of time, accelerating all the stages of a typical delivery and making the process more efficient. Maximize human potential Artificial Intelligence provides the capacity to generate commodities for manual labor, particularly in professional services engagements. When carrying out an engagement, be it a Salesforce delivery or anything else, a lot of manual tasks are frequently required to keep everything organized and in sync. With the help of AI, we can do away with that and make it a commodity, freeing up the human brain to focus on more difficult jobs and providing customers with greater commercial value. For intricate CPQ (Configure, Price, Quote) projects, for instance, the user doesn't have to worry about billable hours for manual tasks—instead, they can concentrate on creating appropriate pricing policies and working with customers. Can AI solve everything? AI is pervasive and has an impact on professional services and architecture. Can it resolve every issue? Or is it just a fantastical idea with dubious practical application? Let's examine this in more detail. AI as a co-pilot People have very high expectations of AI. Consequently, there is always a concern about losing jobs to AI. But the reality is that AI helps people do tasks more quickly and easily, freeing up their time to pursue other interests. Approach AI with an open and curious mindset The revolutionary journey of AI has only just begun, and given the hype and its ongoing progress, it's critical to recognize its potential. Instead of seeing AI as a closed subject, but rather as a new frontier, one should approach it with curiosity and a commitment to improvement. The energy impact of AI It is important to pay attention to how AI affects energy. The extensive usage of AI may result in a considerable carbon footprint. Globally, addressing this challenge—which includes data management, data security, and environmental aspects—is imperative, meaning that solutions must be found as quickly as possible. Language generation is no longer just a human ability Natural language generation capability is no longer restricted to humans. Up until recently, language was thought to be an ability unique to humans. Large language models can now mimic complex ideas and emotion-based communication that were previously thought to be specific to humans, even though they don't fully comprehend the material they generate. This is a fundamentally important change that calls into question the idea that language production is exclusively a human ability. AI is ultimately a tool that requires a human at the helm Even with its advances, artificial intelligence still needs clear guidance on our goals. No matter how complicated the task or its execution, human intelligence, and minds are essential for directing AI to get the intended results. Even though AI can expedite activities and increase productivity, in the end, it is still a tool that needs human guidance. How does AI impact innovation? Problem-solving capabilities The evolution of AI signifies a shift in problem-solving capabilities. AI can be utilized in the context of the current technology landscape, by identifying the low-hanging fruits, and determining what can easily be delivered to end-users. Simplifies intent-based testing Important side discussions are frequently overlooked in team communication, especially when testing is involved. Intent-based testing, which can transform the testing process by guaranteeing that user intent and requirements continuously guide testing efforts, may be made possible by AI's capacity to retain a continuous grasp of intent. AI as a solution to persistent issues AI provides a set of tools to solve enduring issues. Artificial Intelligence (AI) has the potential to revolutionize the way that chronic problems in numerous disciplines, like sales pipeline predictability and routing, are approached and improve work efficiency. How does AI impact DevOps? Depth vs. breadth in knowledge When it really gets to understanding and establishing value, it's about depth. In some sectors of the economy, like healthcare, there are generations of expertise where people are retiring after 40 or 50 years of experience. The difficulty lies in archiving that data, incorporating it into a domain-specific large language model (LLM), and utilizing centuries' worth of healthcare-related knowledge at our disposal—all the while being mindful of whether information from the previous century or earlier is still relevant today. Democratizing DevOps Within the DevOps process, the essential phases are plan, develop, build, test, release, and deploy. Testing is the main area of influence. Exploratory testing gives the end user the freedom to simply investigate and identify edge cases. AI has the ability to quickly democratize DevOps, enabling participation from those who have never been able to take part in software delivery. Key security and ethics concerns raised by AI? Large language models give rise to completely new categories of security risks, which the developer community is still learning about. As of this moment, it is unknown how serious these threats are. Regarding the degree of autonomy given to AI-driven processes and the ways in which users can provide feedback, a degree of caution is urged. Simple prompt injection attacks are very successful in tricking the huge language model into going against its instructions. They can even fool the defenses that are currently in place. The conflict between those looking to breach systems and those trying to secure them has long been a part of traditional security. But since we are still learning about and addressing the potential risks associated with generative AI, especially with regard to the newer varieties, we should proceed very cautiously when it comes to defining rights, establishing protocols for monitoring, and including humans at crucial points in the development and implementation of these systems. Want to learn about more ideas, opportunities, and strategies to maximize the value of Salesforce data + AI? As a Gold Salesforce implementation partner with over 300 certified Salesforce professionals spread across 4 continents, our global delivery model has successfully delivered Salesforce RoI to our customers for over a decade.  Connect with one of our Salesforce consultants today for a free consultation

In June 2023, the world’s foremost Customer Relationship Management (CRM) product company announced the launch of AI Cloud, a path-breaking enterprise AI solution. This dependable, open, and business-ready platform is intended to boost organizational productivity by embedding generative AI experiences into all Salesforce apps. This significant achievement demonstrates Salesforce's continued commitment to trusted AI, as well as its ambition to enable businesses regardless of size and industry to digitally transform and provide a 360-degree view of their customers. AI Cloud includes purpose-built tools and functionality to deliver enterprise-grade AI and is Salesforce's latest multidisciplinary endeavor to add AI capabilities to its product line. In many respects, it is a continuation of the company's generative AI program, which was introduced in March 2023 and endeavors to integrate generative AI throughout the Salesforce technology stack. AI Cloud hosts and serves text-generating AI models from a variety of partners, including Amazon Web Services (AWS), Cohere, Anthropic, and OpenAI, on Salesforce's cloud platform. Salesforce's AI research group offers first-party models, which support services such as code creation and business process automation. Customers can also introduce a custom-trained model to the platform, storing data on their own infrastructure. Generative AI Across Salesforce Products Salesforce-built models in AI Cloud enable new capabilities in Salesforce's marquee products – Salesforce Data Cloud, Mulesoft, Tableau, and Salesforce Flow. Einstein GPT in CRM Einstein GPT is the next generation of Einstein, Salesforce's AI engine, which now makes over 210 billion AI-powered predictions per day. By merging proprietary Einstein AI models with ChatGPT or other leading large language models, customers may use natural-language prompts on CRM data to trigger powerful, real-time, tailored, AI-generated content.  Here’s a look at how Einstein GPT helps teams to boost productivity. Einstein GPT for Sales: Automate routine sales tasks such as drafting emails, scheduling meetings, and preparing for follow-ups. Einstein GPT for Service: Automatically generate knowledge articles from past case notes. Auto-generate tailored agent chat responses to boost customer satisfaction through personalized and faster service engagements. Einstein GPT for Marketing: Generate tailored and targeted content in real-time to engage customers and prospects via email, mobile, social media, and advertising. Einstein GPT for Slack: Get AI-powered customer insights such as smart sales summaries via Slack and reveal user behaviors such as knowledge article updates. Einstein GPT for Developers: Leverage Salesforce’s proprietary LLM to boost developer productivity by using an AI-powered chat assistant to generate code for languages such as Apex. Einstein Trust layer What is the key differentiator of AI Cloud? Salesforce is promoting Einstein Trust Layer, a cutting-edge moderation solution that prevents text-generating algorithms from storing sensitive data such as consumer orders and contact information. The Einstein Trust Layer is a powerful set of features and safeguards that protect your data's privacy and security, increase the safety and accuracy of your AI output, and encourage responsible AI use throughout the Salesforce ecosystem. The Einstein Trust Layer, which includes capabilities such as dynamic grounding, zero data retention, and toxicity detection, is intended to let you harness the power of generative AI while maintaining your safety and security standards. A rising number of global corporations have prohibited or restricted the usage of generative AI, such as ChatGPT, citing privacy concerns. Einstein Trust Layer is tailor-made for such enterprises that have stringent compliance and governance constraints that prevent them from adopting generative AI tools. The first question that arises in everyone's mind is how much can we trust generative AI. The Einstein Trust Layer is purpose-built around trust and security and designed to enable these enterprises to approach these new technologies safely and securely. The Einstein Trust Layer acts as a bridge between an app or service and a text-generating model. It detects when a prompt may include sensitive information and automatically deletes it before it reaches the model. This layer can also screen for toxicity (eg. racism or other types of discrimination), whether in a prompt or the model's response. Users who link third-party models to AI Cloud such as Google's Vertex AI can use Einstein Trust Layer. Salesforce's partnership with OpenAI ensures cooperative content moderation by leveraging OpenAI's safety tools and the Einstein Trust Layer. Salesforce is providing a set of prompt templates and prompt template building tools to set AI Cloud apart from other managed AI service offerings available today. The Einstein Trust Layer’s optimized AI prompt templates leverage harmonized data to contextualize outputs generated by the models in alignment with the organization’s needs, improving the quality and relevance of the created content. The Einstein Trust Layer reduces the time and cost to adapt a generative AI model for a particular use case. For instance, a customer could design a template that instructs a model to draft emails in accordance with a particular style, or one that retrieves specific information from a Salesforce record. AI Cloud marks a fundamental shift in the automatic creation of email content – one that is grounded in CRM data. AI Cloud represents the powerful combination of data, customer relationship management, and AI. As prompts become smarter and better, AI Cloud is poised to become an invaluable tool for businesses delivering greater value to customers across the Salesforce technology stack. Trusted AI begins with secure prompts. A prompt is a series of instructions that guides a large language model (LLM) to produce relevant results. The more contextual the prompt, the better will be the outcome. The Einstein Trust Layer allows you to safely enter AI prompts with context about your business while its data masking and zero data retention capabilities ensure the data's privacy and security when delivered to a third-party LLM. Seamless privacy and data controls. Utilize the scale and cost-effectiveness of third-party LLMs while ensuring your data's privacy and security at every stage of the generating process. Data Masking Before providing AI prompts to third-party LLMs, automatically mask sensitive data such as personally identifiable information and payment information and customize the masking settings as per your company's requirements. The availability of the Data masking capabilities of EinsteinGPT varies by feature, language, and geography. Dynamic Grounding Generate AI prompts with business context securely from structured or unstructured data by taking advantage of multiple grounding methodologies and prompt templates that can be scaled across your organization. Secure Data Retrieval Allow secure data access and contextualize every generative AI prompt while retaining permissions and data access limits. Your data is the real product. Salesforce allows customers complete control over the use of their data for AI. Whether you use Salesforce-hosted models or third-party models such as OpenAI, AI Cloud does not retain any context. Once the output is generated, the LLM forgets both the prompt as well as the output. Eliminate toxic and harmful outputs. Scan and evaluate each prompt and output for toxicity and empower employees to share only suitable content. Ensure that no output is shared unless a moderator or designated content approver accepts or rejects it, and save every step as metadata to leave an audit trail to promote compliance at scale. Securely Unlock Enterprise-Grade Generative AI with AI Cloud Einstein, Data Cloud, Flow, Tableau, and Mulesoft all benefit from AI Cloud's capabilities. Salesforce AI Cloud empowers organizations to unlock the future of their AI journey with a solution that is trustworthy, open, and intelligent. Developing trust and embracing openness The Einstein GPT Trust Layer enables businesses to employ generative AI with confidence by facilitating the deployment of relevant models for a range of tasks. This trust layer allows enterprises to use a variety of large-language models (LLMs) while adhering to their trust and openness standards, which prioritize data privacy, security, and compliance. Leveraging capabilities of Third-party Large Language Models (LLMs) Salesforce's AI Cloud promotes open development by integrating third-party LLMs such as Amazon Web Services (AWS), Cohere, and others. These LLMs are hosted within Salesforce's secure infrastructure, so user prompts and responses stay within the Salesforce environment. Salesforce has also formed a trusted partnership with OpenAI, utilizing their Enterprise API and security capabilities, as well as the Einstein GPT Trust Layer, to secure data retention within Salesforce. Salesforce's own large language models such as CodeTF, CodeGen, and CodeT5+, assist companies in reducing talent gaps, lowering implementation costs, improving team efficiency, and detecting incidents that require immediate attention. Bring Your Own Model With AI Cloud, companies that have trained their unique models elsewhere to integrate seamlessly with their desired infrastructure. These custom models, whether built with Google's Vertex AI, Amazon's SageMaker, or any other platform, can connect directly to AI Cloud over the secure Einstein GPT Trust Layer. Organizations can maintain control and privacy over their information by storing it within their trusted perimeter. Enterprise Ready Solution Salesforce predicts that by the end of 2030, Generative AI will drive $15 trillion in global economic growth and increase GDP by over 25%. These are remarkable numbers and Salesforce believes that AI Cloud will propel businesses to new heights, with efficiency and productivity being the key differentiators. Prompt Template and Builders With AI Cloud, Salesforce has created a user-friendly solution that generates AI prompts that rationalize data and ensure that the content provided is in complete alignment with an organization's unique context. As a young company (we are only a decade old!), we are driven by the immense potential of emerging technologies such as Generative AI to deliver value to our clients and help them bring their ideas to fruition. To fully explore the potential of AI Cloud, connect with a trusted and certified Salesforce implementation partner. Our Salesforce AI services help marketing, sales, service, commerce, engineering, and IT teams work seamlessly with generative AI.  To know more about how we can tailor unique scalable solutions for you by leveraging the power of generative AI to enhance the customer experience, connect with an  https://www.youtube.com/watch?v=qxyQDcap4Ic – video

While the secret to understanding customers lies in your data, making sense of that data is a totally different ball game. Evolution in technology and concerns around user privacy have mushroomed new challenges for marketers to know their audience and deliver data-driven experiences. An AI-powered customer data platform (CDP) addresses these challenges and more. CDPs can connect with a single storehouse of data – one that is proprietary, trusted, and acquired with consent. Salesforce’s own CDP, Marketing Data Cloud, takes things up a notch. It puts marketers in control of the entire customer journey, allowing them to connect, unify, and act on data across all marketing touchpoints and enhance the customer experience across teams and departments – from sales, marketing, service, commerce, and more. Marketing Data Cloud from Salesforce accomplishes four primary functions: It connects. Connect all your customer data across apps, channels, and devices with out-of-the-box connectors, at scale. It harmonizes. Aggregate all your data into a single customer profile, autonomously. Data across multiple channels and teams all integrate seamlessly using configurable rules. It engages. Empower all departments with unified customer profiles and update them in real-time via AI-powered analytics. It delivers an experience. Data activated from Marketing Data Cloud drives real-time, tailored, timely customer experiences. In this article, we talk about eight use cases of how Marketing Data Cloud applies these aspects to resolve common challenges faced by marketers, along with their colleagues in sales, service, and commerce. From enhancing engagement to winning customer loyalty, these data-driven methodologies ensure a robust CDP can make every interaction count.  The Engagement Booster Engage your customers at the right moment with real-time data. Benefits: Better engagement with improved efficiency KPIs: Email Click-Through Rates, Conversions, Revenue Data Involved: Customer engagement data, web data, sales data, web and app visits, browsing history. CONNECT. CDP connects data from all sources within and outside of Salesforce. HARMONIZE. The customer's unified profile is created in the CDP. It includes all their engagement activity from across multiple channels and departments. And automatically updates the data in real time with every interaction. And if a customer opts in, CDP can automatically send personalized texts with tailored offers at the right time. ENGAGE. Geolocation data from a customer’s phone activates an engagement action. And when they walk into a physical store, a tailored offer is sent to their phone via the Salesforce messaging app to nudge them to make a purchase. EXPERIENCE. A customer is out shopping for a new smartphone that they have been eyeing for a while. To their surprise, they get a discount on the exact same product that they wanted to buy, right when they get to the aisle. The Smart Advertiser Make every dollar spent on ads count. Benefits: Higher Efficiency KPI: Return on Ad Spend Data Involved: Customer loyalty status, purchase history, case history, email interactions, browsing history, and geo-location history. CONNECT. CDP connects all customer data within as well as outside Salesforce – loyalty, purchases, case history, engagement data, demographics, and affinity data. HARMONIZE. CDP pulls out the customer’s unified profile and creates AI-powered segments.  Segment-level data insight from ad partners is incorporated to refine customer segments further for eg, customers looking for specific products and services. ENGAGE. CDP activates these segments on popular ad platforms to hyper-personalize ads for customers, all this while protecting the customer’s privacy. At the same time, CDP also suppresses ads to customers with unresolved service cases, customers who already purchased the item or returned it, and those unlikely to engage. EXPERIENCE. Customers view ads of products or upgrades, precisely what they had in mind and within their preferred price band. The Shopper Styler Drive Increase revenue with hyper-personalized e-commerce. Benefits: Higher Conversions KPIs: E-commerce Revenue Data Involved: Purchase history, browsing history, activity behavior, loyalty status, case history, and email interactions. CONNECT. CDP pulls data from all touchpoints between the customer and the brand such as purchase history, buying preferences, loyalty data, service engagement, website, and app engagement, and more. HARMONIZE. Leveraging the customer’s unified profile, CDP derives intelligent Insights on new metrics such as “propensity score” to predict the customer’s likelihood to buy a particular product. These insights enable marketers to make faster, data-driven, decisions. CDP can drive tailored shopping experiences and promote those products. ENGAGE. Commerce Cloud leverages insights from Data Cloud to provide tailored shopping experiences to the customer on their brand’s online store or app. And with the help of the customer’s propensity score, data points such as reward points, recent purchases, and recommended products are automatically served up. CDP can automatically activate relevant and timely actions in the customer’s journey. Actions like clicks and cart abandonment can initiate a background process that anticipates the customer’s needs and encourages action.   EXPERIENCE. When a customer visits their favorite mobile accessories brand’s website or app, they get personalized product recommendations. And if they abandon the cart before checkout (for whatever reason), CDP can automatically fire a reminder email with a discount incentive to nudge them to complete the order. The Website Winner Improve conversion with personalized experiences. Benefits: Increased engagement, higher conversions KPIs: Bounce rate, browsing history, average time spent on a product, session duration. Data Involved: Purchase history, engagement data, loyalty status. CONNECT. CDP draws together customer data across marketing, commerce, sales, and service interactions. HARMONIZE. After unifying all the customer data into a single customer profile, CDP identifies a customer’s past purchase behavior, including their recent purchases. CDP then places the customer in the post-sale segment focused on helping them to derive immediate value from their latest purchase.  ENGAGE. Based on the customer’s recent purchase data, CDP fires a personalized text via the Salesforce messaging app, with a link to the brand’s website to prompt them to learn more about the product and its usage. And as soon as the customer lands on the website, the page is dynamically populated with relevant how-to articles, care instructions, and other relevant and personalized content. EXPERIENCE When the customer clicks on the link to the website, they land on a webpage populated with relevant content based on their recent activity. This includes product-related articles, videos, images, and additional offers. The Cross-Seller Intelligent predictions for your customers’ next purchase. Benefits: More upsell and cross-sell opportunities, higher conversions KPIs: Sales, Product popularity, Average cart size Data Involved: Purchase history, browsing history, engagement data, loyalty status. CONNECT. CDP connects sales, loyalty, and service data to generate unified customer profiles and offers intelligent insights to reveal opportunities for cross-selling and up-selling based on the data. It can also suggest customer lifetime value (CLV), propensity scores, engagement scores, and more. HARMONIZE. CDP-powered insights create a new metric called affinity score which predicts a customer’s affinity towards other products. CDP then leverages this data to define new customer segments based on the insights. ENGAGE. CDP then activates this customer segmentation data across multiple customer engagement platforms. Customers get personalized emails, texts, tailored web and app experiences, and personalized ads on their preferred channels. EXPERIENCE. As customers browse an online store or app, personalized product recommendations are automatically served up. Customers can view these items and complete the purchase. The Insight Viewer Analyze marketing performance. Benefits: Optimized performance, Deeper Insights, Improved average time for ROI. KPIs: Product Views, Sales, ROI. Data Involved: Purchase history, cross-channel activity, Engagement, and Campaign performance. CONNECT. CDP connects data from all touchpoints across marketing, sales, service, and commerce, to create unified customer profiles. Analytics tools such as Tableau and Marketing Cloud Intelligence leverage this data to augment audience discovery and measurement. HARMONIZE. Marketing Cloud Intelligence helps marketers optimize campaigns and customer journey performance. Tableau provides deep customer insights to help teams discover new customer segments and behaviors that drive adoption and increase their lifetime value.  ENGAGE. CDP drives the wheel of optimization. Marketing Cloud Intelligence uses data from CDP to refine campaigns. Tableau serves up intelligent audience insights, identifying high engagement areas. These insights then flow back to CDP to drive hyper-personalization in every moment. EXPERIENCE. As customers enjoy their purchases, brands stay connected with personalized offers on their preferred channels. As data is being gathered and analyzed on the go, brands can measure and optimize campaign performance, discover new segments, and act on high-value actions. The Service Solver Convert service cases into happy customers. Benefits: Customer Satisfaction KPIs: Service Cases Created, Duration of open cases, CSAT (Customer Satisfaction Score) Data Involved: Purchase history, Sales data, Service Data, Engagement data, Browsing activity. CONNECT. CDP pulls in comprehensive service data like service cases, customer service feedback, lifetime value, loyalty data, and more.   HARMONIZE. Service data in CDP augments the customer segmentation process. This helps marketers refine their engagement strategy based on customer service interactions. ENGAGE. In a scenario where a customer has an open service case, CDP gets notified and pauses all marketing activities tailored for that customer until the case is closed.  Additionally, because CDP is receiving all service data, the customer service team has access to the customer’s profile enabling them to be aware of their problem as soon as they reach out to a service rep, and then quickly resolve the issue. EXPERIENCE. Customers get their order related issues resolved in a matter of minutes. When a new case is logged, the service team quickly reaches out to the customer, being aware of their order and having access to their unified profile. Not only does the customer get the issue resolved quickly, but they automatically get a personalized email or text with a 10% discount voucher for their next purchase to make up for the mistake. The Loyalty Earner  Reward customers at every stage.            CONNECT. CDP connects data from a brand’s loyalty system into a customer’s unified profile, along with marketing, sales, and service data. HARMONIZE. Based on interactions with customers in a particular segment, CDP automatically places them into the relevant loyalty tier giving them access to tiered marketing offers and deals automatically. ENGAGE. CDP activates this segment across multiple engagement platforms and customers in this segment automatically start receiving personalized content. The content (which includes product recommendations and offers) is linked to their loyalty status and encourages them to aspire to be in the next loyalty tier for further exclusive benefits such as rewards, discounts, preorders, and more. EXPERIENCE. A customer’s latest purchase of mobile accessories automatically moves them to the next tier of loyalty status. This gives them access to exclusive discounts and offers. It’s time to build your own customer data strategy, and if you have one, you can always refine it. Our extensive experience in Salesforce consulting services can help. With a robust CDP, marketing teams can connect every interaction throughout the customer journey with a unified source of actionable, real-time data. They can truly understand their audience and deliver personalized engagement that drives revenue and builds lasting relationships. And that’s not where the value of CDP ends. In fact, it is just the beginning. Every department and team across sales, service, and commerce can also benefit from the power of a CDP. Powered by Customer 360, Marketing Data Cloud unifies all customer data across all channels and departments to create a single, unified customer profile that is updated in real-time with every interaction. With a unified view of your customer, Marketing Data Cloud empowers marketing, sales, service, and commerce teams to make every moment count. With a robust Customer Data Platform, your business can interact with your customers not as disparate departments, but as one brand with one voice. A brand that understands and engages with confidence, relevance, and trust. Whether it is prompt Salesforce support, hyper-personalized product recommendations or hyper-segmented targeted advertising, with Marketing Data Cloud you can make every customer interaction count and unlock the true power of real-time customer data. Want to learn more? Connect with our Marketing Data Cloud specialist today.

Salesforce Chatbot enables businesses to offer personalized and prompt service using AI-powered bots available natively in the CRM. Now you can supercharge customer case resolution with clicks not code by automating mundane, time-consuming tasks by linking AI with your CRM data. This empowers service teams to do more by leveraging AI-generated responses to customer queries. Before going into how AI chatbots can be pivotal in customer service, let’s educate ourselves on the basics. What is a chatbot? A chatbot (derived from “chat robot”) is a software program that can simulate human conversation (voice or text) and can solve a problem. Businesses typically use chatbots to augment customer service to complement traditional service channels such as phone and email. Just like software can be configured and customized in any way you want, chatbots can also be customized and used in ways that are aligned with your goals. We are already familiar with bots for customer service that are used with popular messaging platforms like SMS and WhatsApp. With AI chatbots, users can interact with a computer program to find answers quickly. Most notably, chatbots can enhance customer relationships by responding to queries faster at their convenience by being available round the clock. With 24/7 availability to serve up responses, chatbots free up time for service teams so that they can work on more complex issues that require a touch of empathy. How do chatbots work? Chatbot development has evolved leaps and bounds over the last decade or so, as developers have adopted sophisticated techniques and technological advancements in machine algorithms to enable chatbots to contextually understand user questions and offer more useful responses. While bots today still aren’t equipped to handle all user queries, they can easily respond to commonly asked questions or execute simple, repetitive tasks without any human intervention. One such example is when a chatbot parses customer input, identifies keywords or phrases, and then scans the organization's data to retrieve relevant articles based on those keywords or phrases. Chatbots typically follow a pre-defined decision tree, which is why they are often referred to as rule-based chatbots. Rule-based chatbots execute pre-defined actions based on user input. Rule-based chatbots are based on click actions, like a user responding with a binary input like a “yes” or “no,” or by recognizing specific keywords. You would have come across instances when you typed a question into a website’s pop-up box and got an answer that had no relevance to the question. That usually happens when although the chatbot recognized keywords in your input, it did not understand their context. This is where AI chatbots come in. What is an AI chatbot? The level of sophistication involved in chatbot technology cannot be overstated.  With inbuilt natural language processing (NLP) capability, chatbots can engage in human-like conversations with users effortlessly. Engineering teams are relying on NLP to build AI chatbots that can understand human speech and text better. With NLP, it is now possible to better recognize user intent and consequently provide better, more intelligent responses. With the latest disruptive tech of generative AI, chatbots can interpret context in written text, which allows it to work on its own. In simple terms, AI chatbots can understand language outside of pre-defined rules and offer responses by relying on existing data. This allows users to navigate the conversation and allows the bot to follow. By drawing on huge data sets and the processing power of the machine, AI- chatbots can leverage deep learning algorithms to significantly improve their quality of understanding questions and offer more accurate responses. When chatbots connect with technologies such as Large Language Models (LLMs) and NLP, they can train themselves to simulate human conversation better by: Maintaining the context of the interaction. Managing a personalized conversation. Refining responses based on the changing customer needs. AI chatbots get better with every interaction. They do this by connecting with deep learning algorithms and drawing on enormous amounts of conversational data stored in the CRM database. 3 Benefits of Using AI Chatbots in Salesforce: Businesses, irrespective of size and the domain they operate in, can derive the benefits of process automation, particularly a function that delivers direct value to their customers. With chatbots, you are available to your customers round the clock, giving them 24/7 access to your business. They are also able to get quick responses to common questions anytime, from any device. Reduce Human Intervention As a business leader, you would be aware that not every customer query needs you to dedicate human resources to respond to that query. Just like a knowledge base or a library of FAQs in Service Cloud can offer relevant and accurate information to customers whenever they need it, a chatbot can automate this process by understanding their queries and serving up the right answers. Chatbots can be very useful in increasing the deflection rate of customer support cases. Reduce Costs and Improve Productivity Leveraging chatbots to automate mundane, repetitive tasks and straightforward processes gives your internal teams more time to focus on more critical and creative tasks. This leads to a significant reduction in manpower especially in your customer service teams. The ROI of using a chatbot to free up agent time so that they can focus more on doing what’s most important- nurturing customer relationships, is a figure you cannot ignore. Your internal team performance will witness a significant improvement as well, since your service agents are focused on solving complex problems where human intervention is necessary, translating to higher-quality customer service. Time is a commodity that is available in limited quantity to every organization, and chatbots allow service teams to do more with less. If you wish to scale up your business without the associated costs of additional resources, you should look at AI-powered chatbots. Entrusting many of the repetitive, mundane tasks across departments to an AI chatbot and having the provision to escalate a case to a human agent as and when required will boost the morale of your teams, improve staff retention, and allow them to shine in their work. Customers Notice Innovation Customers often compare 2 or more brands that offer the same products or services that they are looking for. And if your business is completely human powered it means customers sometimes will have to wait for their turn for a human agent to be available to get their issue resolved. If your competitor is offering chatbot-powered customer service which allows customers to self-serve and find answers quickly, they will notice the difference in service availability which will compel them to choose the latter. Let’s look at an example. A visitor to your website asks the chatbot for pricing information and more details about a particular product or service. The chatbot can immediately dive into Salesforce data and serve up the information instantly to the website visitor.  Compare it with getting a message “Please wait a moment while we find an agent to talk to you.” Let’s look at another scenario. The website visitor wants to book a demo to see how your product actually works. All he needs to do is type – “I want to book a demo”. The chatbot can immediately open a calendar for him to select a convenient time and date and once the visitor has made a selection, the bot can immediately check rep availability by diving into the booking system which is also connected to Salesforce, and then confirm the appointment. All this without ever leaving the chat conversation. The use of chatbots in customer service has increased dramatically over the last 5 years and with the advancement in AI technology, it is going in only one direction. Why Should You Consider an AI Chatbot for Salesforce? Looking to invest in chatbot technology? Heard and read a lot about them and their benefits in the context of business but don’t know where to start? There are several ways of approaching this, with so many options available in the market. If you are starting out, the best way to do this is within your single source of truth – Salesforce. And the reason is very simple. A Salesforce native chatbot can leverage customer data, product and service data, and knowledge base, to engage customers and serve up relevant and accurate answers. A Salesforce native chatbot can also trigger automations at appropriate events within Salesforce making it very productive and tightly aligned with your business goals. Salesforce does come with AI-powered bots called Einstein Bots. Einstein Bots are powerful, and available out-of-the-box in Salesforce. They require a Service Cloud license along with a chat or messenger license with each license offering 25 bot conversations per user per month. Einstein Bots also come with an inbuilt Salesforce Messaging App allowing businesses to engage in text conversations with customers via SMS and WhatsApp. AI Chatbot from Salesforce is a powerful tool to re-imagine customer experiences, automate processes, and improve productivity. With round-the-clock availability and immediate responses, AI Chatbots from Salesforce transform the way businesses connect with their customers. To learn more about AI Chatbots for Salesforce, connect with an expert today.