In an earlier article, I wrote about service trends and automation. At my company, we're always asked if machines will eventually take away support jobs. Do computers substitute humans or, are they complementary to existing workers? In the last two decades, as globalization has come into the picture, we have started to compete more as humans. This often means that if there is a lower-cost resource that could do the same job as a higher-cost resource, we switch out those resources. This trend will only continue, as all humans have the same basic needs  —  food, shelter and luxury items. A machine does not need any of the above. Innovation is the key to customer support. 82% of those who are in charge of making decisions for their companies believe their business' support practices must evolve to remain competitive. What will your business do to stay relevant, and how will machines be a part of that change? What Does It Mean To Be Complementary? Let’s look at a simple example . In 2012, teams competed to develop the best machine learning algorithms to identify dog breeds in ImageNet's library of dog photos. We engineers marveled at what the technology here could do. Then, we paused and realized that a 2-year-old could easily point to any type of dog and verbalize a description without any training. This made us recognize that humans are a marvel; we have a long way to go to make machines the same. We, humans, excel at making plans and forming decisions in very complex situations. Computers aren't quite the same. They excel when there are loads of data to process, but they struggle when it comes to making simple judgments that humans are used to. While we can understand and make sense of multidimensional situations, computers can process multidimensional data. We are categorically different. We are complementary. We have used computers for these complementary scenarios in various parts of our lives for decades  —  fraud detection, network switching, efficient processing power, fast transactions, etc. As we reach optimal infrastructure levels (our phones are way more powerful than the massive computers of old), many hope to bring this processing power into enterprise decision making. Our human minds are also slowly being trained to understand the power of what it means to be "complementary." We use computers to narrow down our flight searches, find the fastest routes to a destination, discover efficient ways to find the lowest price for an item, correct our mistakes, find the words to finish our sentences and more. As millennial minds come into the enterprise world, they are questioning how we can use this technology to perform complex multidimensional data analysis and pattern recognition. The Handshake Between Man And Machine Let’s look at decision making in customer support and customer service. This support happens across industries and verticals. Whether the support for a physical product or a software product, it is essentially focused on solving problems in three dimensions: Solve today’s problem, something that a customer has already pointed out. Make sure the same problem doesn’t happen again by making changes to the product, employee training or organizational behavior. Predict trends and problems (more applicable to physical products) before they happen. Problem prevention and problem elimination are the core of customer support, whether it is solved by self-service, the community, an agent or field or auto-support. With smart physical machines and advanced software, the data that comes in from customers has increased considerably. Customers are also smart enough to know the nature of the problem they are facing and expect a quick response. Let’s drill into this to see how computers can help. In customer support, we often solve customers' problems with tiered approaches and/or swarming. In both cases, humans spend hours through patterns in community forums, FAQ pages, knowledge bases, product patches and release notes, dump and log files and running proprietary scripts to reproduce or gather information from customer scenarios. Essentially, what we are doing is looking at various patterns of previous incidents to see if we have seen a similar situation before. This level of multiple-dimensional data crunching is what computers do best. But while it is cool to have access to machine learning algorithms that can handle these tasks, computers alone will not solve all issues. Many companies are already looking at how computers can help humans solve hard problems. This process is very different from traditional service management. Businesses can search, using natural language processing and machine learning, for relevant data that can then be sent to agents. This helps make decisions across all three dimensions of problem-solving. Along with providing relevant data, businesses can also use feedback mechanisms, which shed light on what the machine predicts to be the root cause of the problem, as well as possible solutions that have occurred before. This feedback mechanism is the critical handshake between what the human interprets and what the machine predicts. Even still, customer support automation may not be the right choice for every business, even with its complementary nature. For a business to see some sort of return on investment with this approach, it needs to be ready to invest in the solution. This may include assigning a member of management to oversee the process. Also, if your support team is less than two people — or if you deal with little digitized data — it is hard to see value in this approach overall. The Future Of Customer Support We will never know what unknowns the future of computing will bring. Some people are a bit wary of the future, but if we use machines the right way, we will hit the cosmic lottery. If we use them incorrectly, we can expect Skynet to take over. Nevertheless, we are at least a century away from this. Until then, there is time for you to use the complementary aspects of machines to build a vastly better support organization — that is, if the costs are worth it for your business. Learn more, Knowledge Management To Improve Support Experience Do You Have Enough Data For Machine Learning?

An organization that sees its customer service department as a cost center is ignoring a significant opportunity to increase customer loyalty and lifetime value. Software-as-a-service (SaaS) is taking software that you pay a little bit less in the beginning but regularly. Monthly, yearly, sometimes longer depending on the contract. Customer support and customer success teams are the ones that interact much more closely with the customer after the final sale of the contract. “Service to sale” thinking needs to be cemented in customer support. Customer support is now the primary human touchpoint a brand has with buyers! End customers are trending towards self-service during the buying process. This reduces direct personal interaction with sales. When buyers are not able to fix simple customer service issues with self-service tools, customer support is often the first human contact they have with a brand. That makes interactions with support a critical and strategic advantage in building customer loyalty. ​ Every support interaction is an opportunity for a company to build a more personal relationship with a buyer. At the end of customer service interaction, a happy customer can be showcased in a marketing case study, events, G2, or Trustpilot review. Every unhappy customer can be called out for a follow-up to improve a business process, training, or product improvement. ​ Companies that don’t take a revenue-oriented approach to their customer services teams fail to unlock a lot of sales opportunities. Top Reasons why Customer Support is Revenue Customer retention is far less expensive than customer acquisition. Excellent customer support improves public persona and strengthens the brand. Existing customers are more likely to buy from you than new customers. Your customers stay with you longer. Word-of-mouth marketing is the best kind of marketing. Great customer support opens doors for organic partnerships and opportunities. Providing phenomenal product support results in a reduction of overall problems. Support is the Voice of the Customer that improves the product drastically. How AI can enable the pivot for Customer support into Sales ? Today, AI-based platforms show the current and historical sentiment of the customer based on current and historical interactions. They also show product issues that are open to the customer. All this can be used to gauge when the time is right for a support agent to transition into a sales role. A happy customer, a customer who is thrilled after an issue is resolved, a customer who expresses a Wow moment of using a software feature, all of this is factored in. ​ When the agent is ready, the AI platform also suggests cross-sell and up-sell opportunities available for the customer enabling the ease of transition and an ability to pull a salesperson in at any given time. This is especially true for B2B sales, where issues are rarely closed in a single call. ​ So the question is- “Should support leaders advocate customer support as a revenue generator?” ​ Here is where you might agree, or perhaps differ- and this is the conversation that Ascendo AI and Support Driven are trying to facilitate! Our speakers for the dialogue- Ahmad Shabazz and Mo McKibbin engage in an insightful conversation to bring to you their unique take on several topics related to ‘Growth Through Support’. Check it out in our Events section. ​ Learn more, Ways To Improve Customer Services With AI How to Scale Support to a Large Number of Customers?

Many of your customers, who are already in a stressful or complex situation and need help, may become agitated during an interaction. How do you bubble up the exact issues from their interaction to make meaningful changes? It can be scary, but when you understand where it’s coming from and why it’s happening, it can be easier to handle. For example- often, the customer is frustrated or facing an issue about the situation that led them to the interaction, rather than the interaction itself. Let's look at the stats! 35% of customers have become angry when talking to customer service. (American Express) 27% of Americans report that ineffective service is their number one customer service frustration. (Statista) 12% of Americans rate their number one service frustration as “lack of speed.” (Statista) 78% of customers have given up on a transaction because of a negative customer experience. (American Express) Product teams are always looking for ways to get the emerging trends and the top of mind issues affecting customer satisfaction. Ascendo's "Voice of the Customer" module has an enhanced workflow to allow the user to not only see the trending issues and look at possible opportunities but to develop the solution. Multiple AI models work in tandem to identify the issues, identify opportunities and solutions and provide human feedback to further adjust the issues that need to be addressed. These can be approved with a click of a button and they are automatically sent to AI Bot so they can quickly present the top issues and solutions. More issues are resolved before reaching the agents, higher customer satisfaction by the end customers. Following are what Customer and Product teams can do with Voice of the Customer: Identify areas of product that needs improvement. Identify Customers who have the most issues, lowest sentiment, highest effort and low satisfaction. Manage next steps to make Customer Experience top-notch for every customer. Reward experts and identify which agents need training. Bring out intelligence in knowledge - improvements, duplicates, expiration. Take your top issues and manage self service through self service channels. Voice of the customer provides insight into the support process, agent training, knowledge intelligence or product improvements. Everyone wins! Ascendo autonomous trending issue finder and workflow brings smiles to all!

During the pandemic, businesses have learned that managing key customers is essential to surviving difficult situations like economic downturns, supply shortages, and more. A business’ key customers are the clients that have long-standing relationships with and make up a large, consistent share of a company’s revenue. Many businesses rely on their key customers for recurring revenue and would be devastating to lose. Therefore, systems like Ascendo that can improve customer communications are vital to maintaining these important relationships. What Are Key Customers? Managing key customers can be incredibly difficult because just like any business, they are susceptible to market downturns and will walk away from deals if pricing and services are no longer worth the cost. An easy way to determine your key customers is by looking at the following: 1. The customer’s lifetime value 2. Level of influence and/or authority in the market 3. Additional revenue and referrals they contribute 4. Level of commitment to shared partnership goals Why Are Key Customers Important? Focusing on what products or services drive revenue with key customers allows the business to understand which activities are most profitable. Ultimately, this can determine a company’s mission, products and services, and overall market strategy. The best way to approach key customers is to view them as a separate segment of the market. A company’s key customers will likely have higher demands and lower growth than newer customers but are more important. Due to the prolonged relationship, many key customers will rely on a business like a support team rather than a supplier. A support team needs to be able to respond quickly to business communications and remain agile in order to properly manage these key customers. This type of relationship comes with major benefits when handled correctly. Key customers are great for pitching new ideas and testing new marketing strategies since they are more loyal than newer clients. However, key customers can also be demanding of a company’s time and sometimes boundaries need to be set. It can be common for key customers to demand freebies or contact account managers on the weekends, which is a bad practice to maintain. That is why using a communications platform like Ascendo can help bridge gaps in communication and strengthen feedback loops in order to improve relationships with your key customers. How to Communicate and Manage Key Customers? The relationships with key customers are often complicated with longstanding contracts, communication precedents, and big egos, it’s important to treat these relationships with care. Companies should be available to quickly respond to all sorts of issues like technical support, product questions, and more. Maintaining a constant feedback loop as the support team for your key customers is crucial for keeping the relationship in good standing. This can look like bi-weekly check-ins, email newsletters, or an occasional conference call to gauge emotions on both sides. The constant feedback loop can help identify issues with a client, or a larger problem with the products or services. Further, when working on a project or sales pitch, support teams should provide regular updates to make sure both parties are aligned on the progress and goals. Even if a client reaches out during a meeting or busy day, it’s important to send an email or quick message to acknowledge the issue and let them know you’re on it. Finally, another important area of communication support teams should be aware of is identifying broader customer requirements. Through Ascendo, support teams can quickly identify if issues are common amongst multiple clients, making it easier to identify larger technical issues. When done proactively, this will lead to improvements in products and services and a better relationship with the key customers. Gauging Client Satisfaction The best way to understand a problem is to analyze it with data points, which is where Ascendo comes in. Through Ascendo, support teams can quickly find common problems across multiple key customers in a fraction of the time it would normally take. Another method support teams can use are Client Satisfaction Surveys (CSAT Surveys). Most companies will send out a CSAT survey at least once a year to all clients and potentially more frequent or longer surveys to key customers. CSAT survey can help a company identify issues within their own reporting structure or other problems like communication, product/service issues, and more. Another important metric to look at is a company’s client turnover or churn. This measure shows how frequently a company retains or loses business. While high rates of churn are normal for certain industries, every company should understand what’s normal for their industry and own company to gauge past or present turnover rates. Finally, employees can be a great indicator of client satisfaction. Support teams should ask their own employees how the relationship is with their key customers. If key customers are being extremely demanding or difficult, it can cause high-performing employees to leave which will ultimately hurt the company and the key customer relationship. Management should always work to protect their employees and step in when the situation becomes unreasonable. Mitigating the Avoidable and Unavoidable Problems Support teams are generally going to tackle two types of issues, avoidable and unavoidable. No matter how much experience or planning a business does, there will always be both types of problems that need to be handled regularly. Unavoidable issues like client turnover and technical malfunctions should be prepared for as they are almost certain to happen. Having standardized practices in place to handle these issues will inform employees of their responsibilities and the appropriate actions to take place. Avoidable issues like missed meetings and general unpreparedness require a different approach. These types of issues can be mitigated by outlining best practices for your company so employees understand how business should be conducted. Different Business Models Offer a Variety of Solutions Another way companies have adapted to difficult situations is by implementing new business models. For instance, many B2B and B2C operations have adopted freemium models for customers who can’t afford the upfront cost of the product or service. This is most popular in mobile gaming and social media where companies make money by advertising to the customer rather than charging the customer for the product or service. By testing different business models, a company can segment different buyer groups and evaluate which strategies are most effective. This too can determine a company’s objectives and strategies moving forward. Educating your Team on Key Customer Management Understanding how to manage key customers is only half the battle. Making sure the entire support team understands how to manage and interact with key customers is a huge factor in achieving revenue goals. Since this is so important, management should never assume that employees already know how to manage key customers, even if employees are experienced and highly trained. Management should create a system of best practices and standards for key customers that should be reviewed with all support teams. Further, this should be done on an annual basis since overall company strategies and market sentiments can change how support teams should approach key customers. For instance, if a company has experienced downsizing, it might require stricter communication boundaries to be implemented for employees to stay efficient. Key Customers are the Key to Company Success The value of key customers cannot be understated. Key customers are the bread and butter of any operation and are generally what companies count on for revenue goals and financial outlook. By using Ascendo, support teams can close the feedback loop with their more important clients. Through Ascendo’s platform, support teams can analyze communications data and discover issues that can improve products and services in a fraction of the time. When managed properly, key customers can be incredibly useful beyond the revenue they contribute. These customers are more likely to refer others to use your products and services and can also help fine-tune and identify issues and opportunities for a company. As long as there is constant, transparent communication, your key customers will stay satisfied. Learn more, Great Customer Service and Products Create Market Leaders Role of Customer Support Team in Engagement and Churn

Companies that make great products distinguish themselves from the competition through even great service. What is Customer Service? Service means the given product works most of the time and when there is an issue or question, they get solved quickly. Customers demand support on their terms – any time – any channel/mode of interaction – any type of issue. They want expert help and their perception of the product comes through how they receive the service. Better service they receive better their perception and they stick to the brand longer and buy more from the company. Service Model Opportunities Companies strive to offer support on multiple channels but the core of their support model is around some kind of a ticketing system that inherently translates in all their service delivery models – be it chat, email, portal, web, phone, mobile, SMS, and other media. The service model is built around more “chat” and less problem resolution. Customers are forced to provide a lot more information and are involved in a lot of back and forth before the issue becomes clearer to the support agent at the company. Even a 24-hour chat service that is available to the customers lacks actual troubleshooting and resolutions and is more fine-tuned for simple questions or just chat (pun intended). For companies that extend customer service to include Field Engineers and/or Professional Services teams, the challenges are even higher. The troubleshooting and resolutions require one or more visits to the customer site in addition to spending time on live phone calls or conference calls. In today's world, customers are more interested in talking about their roadmap, value, and success instead of coordinating and spending time on investigation and troubleshooting. It is not that companies are not interested or want to solve issues quickly. The opposite is true. They want to increase self-service resolutions, they want to know customer issues before even their customers become aware of them, they are keenly interested in knowing silent “brewing issues” before they become a fire drill, they want fewer escalations, they want to spend more time in their customer roadmap, their engineering team wants to collaborate with the support team so they can improve the product in a way that drives better customer experience when they need to hire new engineers don’t want to spend months training them, they want to teach and transfer the know-how built over time by a handful of experts to the rest of the members, prioritize to work on important things that matter to their customers, and avoid spending hours on phone and conference calls on customer escalations. When their professional services and field engineers get involved, they want them armed with game plans and needed materials (in case a physical component is involved in the repair services) so they can avoid scheduling multiple visits to the customers to solve issues. Logistics and quality want to spend less time on RMAs and stocking parts and more time increasing the lifespan and optimizing their logistics operations. Simply, companies want to do less chat during support and more conversations on customer experience and success! Interestingly the goals of both the customers and companies are aligned – spend less time on unnecessary chat and more time on issue resolution and avoidance. Then why is this becoming a constant challenge and theme in customer service? The reasons are: Customer support and customers spend more time deciphering the symptoms to understand the root cause. Finding the right solution to the given problem. Finally, understanding and predicting proactively the potential issues that might come up so the companies can be better prepared with optimum solutions and materials, where they are applicable. Ascendo has been built and continuously enhanced to solve this challenge. We are making the technology built with Artificial Intelligence and ML for this specific purpose and making it work for the demands of customers and objectives of companies when it comes to customer service. Ascendo helps companies to: Do less “chat” and resolve fast. Serve more, fast, accurate, and reduce escalation. Replace less and repair quickly. Stock less and avoid downtime. Working with some of the wonderful brands in both Business to Business (B2B) and Business to Consumer (B2C), we are elevating the experience in every interaction by the customer and agents. Learn more, Tips To Stay In Continuous Touch With Customers 10 Ways to Improve Customer Services With AI

One of the most common issues that customer service teams have is maintaining communication with customers. Working with customer service teams we’ve found that mid-touch and high-touch customers tend to stop reaching out to customer service teams after onboarding. So what tips can we use to re-establish communication and avoid customer churn? In general, SaaS companies have two types of pricing models, freemium and tiered pricing. Regardless of the pricing model customers sign up for, SaaS companies aim to provide the best support experience for all their customers. However, ensuring that all customers receive high-quality service can be difficult, especially when there are differences in size and the level of service they pay for. To make sure that all customers receive top-notch service, customer service teams can take advantage of technology and processes that can be used for all types of customers. For instance, the number of unresponsive customers at the freemium level signifies that the customer has not retained interest or value from the product. Further, non-touch engagement levels with paid customers may signal issues with customer churn. Fortunately, we have created playbooks for customer service teams to use in these situations: Building Multiple Levels of Relationships One of the most effective ways to improve customer communication and the feedback loop is by fostering multiple relationships between the customer service team and the customer. However, some relationships are more important than others, and finding the right people is crucial to mitigating churn and improving customer satisfaction. These are the 3 relationships customer service teams should focus on fostering. 1. Customer Service Manager to Customer Service Manager Customer Service Managers are the people in charge of understanding and perfecting the user experience. As a Customer Service Manager, you should be reaching out to your counterpart on the client’s side. Opening this channel of communication will ensure that your client can feel comfortable reporting any issues or requests that may prevent the client from leaving in the future. You always want to build trust and transparent communication channels with the client. 2. Support Admins and Heavy Users Arguably the most important people to build relationships with are the Admins and Heavy Users of your software. These people will be your champions in client meetings and can ultimately decide whether your client stays or goes. If the people in charge of the budget or the people that use your software the most aren’t satisfied, there is little chance they will stay on. Not only does good communication with these stakeholders mitigate churn, but they also are the best people to ask for product improvements and feedback. As the main stakeholders, these clients generally have an in-depth understanding of your product and which areas need the most improvement. Remember, when you have good transparent communication with your clients, that can become an incredible resource. 3. Marketing to Marketing Another area that customer service teams should focus on creating relationships is with client marketing departments. Because marketing departments are in charge of outward communications, this is the best opportunity for customer service teams to collaborate on events, reviews, videos, and training. Marketing teams are also a great target for clients who are likely to become heavy users when managed correctly by the customer service team. Tips To Stay Continuous Touch With Customers Another great strategy to ensure consistent, transparent customer communication is to set up regular touchpoints with the customer. Regular touchpoints such as Quarterly Business Reviews (QBRs) are a value-add that most customers will usually agree to. Hosting QBRs and other recurring touchpoints with main stakeholders will provide customer service teams with plenty of opportunities to gain feedback, understand client usage, and review customer usage as a whole. When conducting QBRs or continuous touch with customers, here are a few items customer service teams can focus on. 1. Joint Goals Establishing joint goals is a great way to assess progress over time. While joint goals can be added or changed over time, they provide a foundation for what are the customer’s expectations. 2. Identify Open Items that Require Higher Visibility Every touchpoint should include a time when clients can identify and discuss items that have recently become important. This can include SLAs, new features, and other items that need to be addressed. Make sure you are transparent with items that did not go well or are not expected to go well. Transparency in features that cannot be fixed, reasons behind escalations, and missed SLAs do need to be summarized. Make sure to share mistakes, plans to fix or avoid in the future is shared with the team so the customer feels that you have their success behind their back. Be proactive whenever possible. 3. Open the Feedback Loop Your customers are your best R&D asset because they use your product in the real world compared to in-house developers. By asking for feedback, customer service teams can build trust with their clients while gaining valuable information that can improve the product overall. We look at the sentiment of each interaction and bubble up with excitement! Always remember to encourage your clients to share any feedback and thank them when they do! 4. Summary of Product Updates It’s always good practice to share with your customers any new features that may be coming down the pipeline. This reminds customers that there is more value to be added to your product and gives customer service teams a chance to gain initial feedback on the upcoming changes. This is also a great opportunity to test out any new marketing for the new product or features by sharing videos, photos, or even demos with the client. 5. Outline New Collaborative Opportunities Discussing collaboration opportunities with clients should be done at least on an annual basis. Joining forces in activities like marketing, sales, and more can be a great way to build relationships and create client dependency on your product. 6. Drive Actions for Next Touchpoint The last item on every touchpoint should be setting up the next touchpoint. Customer service teams should summarize action items and the agenda for the next touchpoint. Customer service teams should get clients to agree to the action items, so everyone is on the same page. Sending out a page memo that summarizes the highlights of the touchpoint and the agenda for the next touchpoint will ensure expectations are understood by all parties. Complete the Circle Bring in other representatives from the Product, Marketing, and Infrastructure teams. Be ready to show that customer that you are pulling in resources across your company to make them successful. At Ascendo, we aim to improve customer relationships and make constant, transparent communication easy for all parties. An AI-driven tool brings out all of the above collaborative touchpoints so customer teams can focus on what they do best – building relationships! Learn more, 10 Ways To Improve Customer Services With AI Use AI to Drive Service Improvements

Post sales service delivered 45% of companies’ gross profits on only 24% of their total revenues (Source: HBR) by the end of the first decade of this century, and since then subscription revenues have consistently grown nearly five times faster than S&P 500 Industry benchmarks over the last decade. The distinction between product and post-sales service sales is slowly blurring. To maximize revenue and profit, companies must focus on the customer experience, on how they can use and get value, and the experience they get from the customer support and success teams. Reacting to service requests is a huge expense for organizations. Service centers spend significant time just categorizing the reported symptom into a problem, and schedule more than 70% of the support engineers reactively because of a reported problem. Because of the stringent SLA, organizations are forced to find sub-optimal solutions for immediate recovery and are forced to come back again at least 30% of the time to fix the same problem. If the company has hard assets, the service organization stocks aftermarket parts inventory at multiple echelons just to support the response commitments to their end customers, but still, ends up facing stockouts and costly, last-minute shipments more than 10% of the time. These challenges have gone up even more with the recent supply chain constraints. Furthermore, if field service is involved, technician dispatch is based on a hierarchical model and unfortunately results in either deploying expensive resources for simpler problems or implementing sub-optimal fixes to the equipment. How Ascendo Helps? Ascendo provides a predictive Artificial Intelligence-based customer support solution to elevate the experience of customers and agents in every interaction. Ascendo applies advanced modeling to incoming customer questions and detects the context and intent behind the questions. Through that, it uses semantic inference to find the symptom, root cause, problem, and solution from across multiple solution articles. Ascendo also predicts customer sentiment (with sentimental analysis) and predicts customer-specific and broader problem trends to avoid future problems. Ascendo connects with the company’s service CRM, installed base, and internal knowledge base to provide prescriptive recommendations within the existing service workflows. For companies that make hard assets, Ascendo has additional models to help with the logistics and field service teams. By looking at the problem and failure trend, Ascendo also helps provide predictive part demand recommendations for the logistics team. For companies that include hard assets in the field, Ascendo provides the game plan in terms of fixed procedures and part recommendations before a technician visits the customer site. Support Agents/Engineers Support teams want quick mechanisms to have their customers get self-help first. With improved technology bandwidth, a good number of customers first perform either a search or ask a chatbot to get the answers. Ascendo through its contextualization and correlation engines, combined with its self-learning capabilities, immediately identifies the context and the intent behind the search queries and chatbot questions and finds solutions from the in-depth knowledge it has garnered from within the support organization. Because of this, the “self-help” customers inherently feel better about appropriate or relevant solutions being suggested. The solutions become more meaningful. Support teams want to seamlessly get agents to help their customers when self-service may not be preferred or sufficient. Ascendo has the knack to identify if end customers require actual live help with the Agents. Ascendo can automatically offer and transition the customer to get live help from one of the Agents. Support teams want to make sure Agents are getting the needed help to solve the issues. Ascendo helps the agents so they exactly know if the previously tried solutions did (or did not) work. Ascendo combines the “context” behind the customer questions and the tried solutions to further recommend better solutions to the Agent. In Agent Assist mode, Ascendo looks into prior cases of similar nature and additional knowledge sources that are more reserved for internal audiences within the company and provides recommendations to the Agents. Before the “remote” workforce model, many agents were collocated and had the luxury of “swinging” their chairs and talking to their colleagues to get help. There is an inherent challenge in that Agent is “supposed to know who to go to for help”. With an increased remote workforce that has become a bit harder. Also, knowing the expert has become a unique trait of Agents rather than corporate knowledge. Even in a colocation scenario, Agents tend to ask their neighbor “hey, do you know the answer for this?” and not necessarily the true expert that might know the answer in the back of their hand. This is where Ascendo comes into help. Ascendo has a way to automatically identify the “experts” based on how prior similar issues are solved, how many, and how effective they were. Ascendo uses its unique modeling technique to derive the expert by first understanding the context in which the question is being asked, knowing the intent, quickly mapping the issues that were similar to being asked, and detecting the experts based on how well they solved the issues. Ascendo knows the difference between quantity and quality. The modeling technique uses customer satisfaction on the prior solutions to improve the ability to determine the expert. Support Leaders If you ask Support Leaders what keeps them up at night, it would be delivering a fantastic support experience with the best customer services at an optimized cost structure. Depending on the type of company, onboarding a support engineer can take anywhere from 6 weeks to as much as 12 months. This does not even include initial shadow/review time spent on the new support engineers. Support Leaders not only about the cost of onboarding but also the opportunity cost of the time. Ascendo is proven to help in reducing the onboarding time due to its inherent nature of being an “experts in back pocket” model. Engineers can easily learn the solutions by querying within Ascendo and that reduces the time and the areas they need to look to provide solutions to customers. Another issue that Support Leaders grapple with is customer escalations. Once a customer escalates, they do all they can including involving the best resources, being available for the customers, potentially offering new concessions, and other benefits to keep the customers happy. They are being forced to become reactive and counterintuitive to them wanting to be in charge and lead. They can rely on Ascendo on two fronts. First: Ascendo predicts potential escalations before they occur and second: Ascendo provides proactive support by predicting the sentiment of the customer using hidden signals and communications from the customer users. Ascendo does this in real-time and alerts the support agents so they can pay even more close attention to the customer's problems. This type of model allows the customer leaders to switch their engagement with their customers from being reactive to proactive and they can regain their advantageous position of being in the drive to realize the outcome – delightful customers. Support leaders are seeking to understand hidden trending issues before they become serious. Given the nature of the Ascendo modeling techniques, it can group or cluster the incoming issues based on the context, intent, and symptoms. No manual effort is needed from the support team to involve multiple team members to comb through the tickets to identify the top issues. Ascendo knows the top issues could change over time and constantly looks at them and provides the support leaders early guidance on the top issues. Knowing top issues also allows the Support Leaders to develop appropriate solutions – do they need to make fundamental changes in the product? do they need to train their engineers more? or do they need to enrich their knowledge? The early alerts on top issues also allow the Support Leaders to focus their resources on important things. They can assign fewer resources to focus on issues that matter most to their customers. Support Leaders can also empower their support delivery teams to increase self-service and auto-resolution of many routines and/or high-volume customer questions. Instead of support agents needing to look at every issue, they can review Ascendo recommendations and use that to address their backlogs more effectively including auto-answering with possible solutions. The advantage is twofold: their customers get solutions quickly and their agents' productivity increases. Field Engineers Field engineers/Field Techs come into play when the company makes hardware/electromechanical type of products or makes complex products that require a field person or a professional engineer to work with them. Companies are always looking to reduce both the time and the number of trips the engineers spend to solve issues in the field. Customers also want a quick turnaround – they want the tech to come and complete the work quickly instead of needing to come multiple times. Ascendo can provide a game plan using its arsenal of solutions - it provides the optimum predictions on the root cause, the area of the fault, and recommendations on parts if such is needed. Field engineers can use this information and are much better prepared before they even visit the customer. They have a fair knowledge of what the problem might be and also can carry the parts. The diagnostics become simpler and no more need to come back again for a part. The entire resolution could be done in one visit and in less time. Such a saving in labor and travel is significant. Their customers are also much happier as they get their systems back up and running optimally in less time. This win/win is possible because of Ascendo’s exhaustive self-learning capabilities. Support Operations Support Operation teams are a glue to connect people, processes, and technology to the needs of the various support delivery teams. They are incentivized to think about the future and create practical paths to connect the dots. Given the complex nature of the global service teams, Support Operations is looking to use AI/ML-based solutions that work with their existing deployed systems and artifacts and elevate them to the next level. Support Operations are leveraging solutions like Ascendo because Ascendo automatically learns them from their existing data. Ascendo has the needed connectors to work with their CRM systems and other knowledge/help articles and further enriches them in a meaningful way. The Setup process within Ascendo being straightforward helps with the quick implementation. The Support Operations team is also looking to deploy value-based solutions, and they are wanting to move away from user-based models to value-driven models. Given the way, Ascendo can be easily consumed and deployed and the pricing model based on value realization, it makes it easier for the Support Operations team to try out and deploy Ascendo solutions. Logistics Support teams that need to have spare parts face the unique challenge of needing to stock spare parts in one or more locations (depots) to satisfy support contract commitments they have with their customers. Depending on the mission-critical nature of their products, they may be offering various service levels such as 4-hour replacement, 8-hour replacement, or Next Business Day (NBD). Given their customers are geographically dispersed, support teams may have to stock spare parts in more than one distribution center and depots. Global companies may also take into consideration specific country custom rules when deciding the location and quantity of their spare parts. Ascendo can use various information such as the field failure characteristics, customer install base growth trend, specific consumption pattern at the depot-part level, and type of support contracts, and recommend the spare parts stocking requirements. Using Ascendo, the logistics team can optimize their spare plan in a much more effective way. Ascendo works in conjunction with the support teams’ ERP system and the planners can use Ascendo's recommendation to determine their reorder point (ROP) at the spare part-location level. Ascendo uses the prediction logic and provides customer SLA risk and the logistics team leaders can use that to take proactive actions. Furthermore, Ascendo can detect the change in install base movement and the change in the company's third-party logistics team locations and provide proactive alerts for the logistics team to better plan their spare parts move as well as procurement. Summary Ascendo is razor-sharp and focused on the customer support experience. Using the fundamental semantic inference models combined with self-learning models, Ascendo addresses every step in the customer support lifecycle journey. Ascendo is providing multiple returns on investment for the customers and a few customers are now beginning to embed Ascendo in their new revenue models. The pact areas can be summarized into the following: Improve customer experience and Churn (Faster fixes, Less downtime, Higher Satisfaction) Service efficiency (Increase workforce productivity, Increase in incidents handled by a support member) Cost reduction (Fewer resources/Reduce multiple visits/Fewer dispatches/Less inventory) Improve Product Feedback Ascendo fundamentally turns companies to become proactive and predictive in the way they offer support services to their customers. Learn more, Escalation Management Guide For Proactive Support Ways To Improve Customer Services With AI

In today's scenario, most businesses are turning to artificial intelligence (AI) to provide the best customer service. AI technology can be used to provide a stellar customer experience. Businesses are looking to take advantage of these dynamic technologies to benefit their organization. The use of AI in customer experience will undoubtedly enhance the customer experience of your organization and take it to the next level. AI has enabled many complex processes to be automated. 10 Ways To Improve Customer Services With AI 1. Predictive Analytics AI can analyze large amounts of data in a short amount of time which contributes to helping customers in making more informed decisions. AI can make predictions about the resolution of customers' problems through predictive analytics. The process of making predictions using statistical modeling is known as predictive analytics. When and how to interact with each customer and accordingly suggest customer-related products and services, making the customer experience more relevant. Helps you predict outcomes with analysis, which can also help predict potential risks. All this information can be used to improve customer satisfaction and improve efficiency. 2. Personalized Customer Service Quick replies with real-time responses will take your organization's customer experience to the next level. Artificial intelligence (AI) chatbots play a vital role in resolving the issues of customer service representatives handling customer calls. AI Chatbot is designed to be at the forefront of the user. One can also remove the additional burden on human agents by resolving customer queries with the highest accuracy and human-like behavior. 3. 24×7 Customer Support Every customer expects round-the-clock service at their convenience and businesses that understand the responsiveness of their customers will enhance their potential customer experience by being always available to the customer. Customers want their queries resolved 24×7 without waiting for a long time. The AI ​​system enables us to provide continuous customer service and resolve issues with ease. It enhances customer satisfaction and contributes to enhancing the brand image. 4. Prevent Employee Workload AI has the potential to improve the employee experience by automating routine tasks. Automating repetitive processes can save your employees a lot of time and effort. Doing so will give them more time and opportunities to focus more on essential and complex tasks. Due to this, not only the development of the agents will happen, but as a result of the ideas and activities, the organization will also grow. 5. Monitor key online channels AI can effectively and quickly analyze data from any channel and provide predictions and insights to enhance the customer experience of existing customers. AI is increasingly helping to make accurate predictions about online customer preferences and marketing strategies. By analyzing data from online channels and predicting which leads will act, it can automatically target them with customized marketing messages. Presently, the customer base is increasing a lot for these channels and with the help of AI, you can improve customer services by giving this facility to your customers. 6. Collect Customer Feedback Feedback exercises enable you to gather insights into the positive points of your organization as well as identify gaps that need to be filled. It can be very challenging to handle and analyze all the feedback data manually or through traditional systems. With the help of AI, customers can give feedback through various support channels but they will all be analyzed for actionable insights and sentiment. Apart from acquiring new customers, it is equally important to nurture your existing customer base and strive to keep them happy. 7. Data-Driven Customer Insights When the organization can easily access historical and feedback interactions of customers systematically, the data derived from this can build a definitive 'view' of the customer. And this 'view' can help you get an idea of ​​what customers' experiences, interactions, behavior, etc. will be helpful for both customer support and business growth. Moreover, by sharing this 'view' of the customer across different departments of the company with this data, you will be able to target them more effectively with the right message at the right time. 8. Seamless coordination Customers look for the best customer service and want to get solutions to their problems in a quick manner with smooth coordination. AI chat bots are great for answering frequently asked customer questions. The best part is that they never lose their motivation. Chat bots can provide a precise solution to a specific problem. Thus, using Artificial Intelligence to improve the customer experience can be very useful for your company. 9. Automate Support Experience With this technology, some companies have made their customer system so strong that most people do not even realize that the companies they are doing business with are working to improve the customer experience. Using AI, automating repetitive processes can save your employees a lot of time and effort, from filling out forms to statistics. This will give them more time and opportunities to focus on essential and complex tasks. Leverage AI to enhance your customer experience, so you can drive growth for both your employees and your business. 10. Understand the location-based needs Last but not least, when a customer has some issue or query it's definitely directly related to the product or the services provided by the organization. But with these, there are other factors too which make a customer happy and let them feel a good experience with your customer service. Same as AI technology helps to understand the sentiments of the customers , it also has the power to provide solutions that are location-based, or which will fit a customer in the place where they are sitting at that moment. Conclusion Definitely, Artificial Intelligence can help you create memorable customer experiences and AI has the potential to improve the way you provide customer service at every stage of the buying process. It is up to you to discover new ways and means to take advantage of these dynamic technologies to benefit your organization. Not only do you benefit from the organization but its learning management system allows your service agents to be trained and updated with the latest skills and training prevalent in the customer service industry. By easily understanding your target audience, their interests, their preferences, etc., you will be able to strengthen your support team. Learn more, Innovative B2B Automated Self-Service Technologies Using AI to Drive Service Improvements

Customer Service and Support Experience is not a buzzword - it is the DNA of a company's success. With the trend in “outcome based pricing” and “Subscription based Selling”, service experience is right in the center of keeping and growing customers. Customers walking into a copy shop and paying for just the copies getting printed was just a start instead of buying a copier. Today, medical device companies are looking to charge hospitals based on a number of surgeries being performed using their machine. A new electric car company just announced in August that they are thinking of selling their cars for a lower price and charging the buyers a per month battery fee. Customer Service is New Product Post sales service segment delivered 45% of companies’ gross profits on only 24% of their total revenues (Source: HBR) by the end of the first decade in this century, and since then subscription revenues have consistently grown nearly five times faster than S&P 500 Industry benchmarks over the last decade. The distinction between product and post-sales service sale is slowly blurring. To maximize revenue and profit, companies must focus on the customer experience and the experience they get from the customer support and success teams. Customer Service Challenges Reacting to customer service requests is a huge expense for organizations. Service centers spend significant time just categorizing the reported symptom into a problem, and schedule more than 70% of the customer support engineers reactively because of a reported problem. Because of the stringent SLA, organizations are forced to find sub-optimal solutions for immediate recovery and are forced to come back again at least 30% of the time to fix the same problem. If the company has hard assets, the customer service organization stocks aftermarket parts inventory at multiple echelons just to support the response commitments to their end customers, but still ends up facing stock outs and costly, last-minute shipments more than 10% of the time. These challenges have gone up even more with the recent supply chain constraints. Furthermore, if field service is involved, technician dispatch is based on a hierarchical model and unfortunately results in either deploying expensive resources for simpler problems or implementing sub-optimal fixes to the equipment. Ascendo Game Plan for Service Teams Ascendo provides a predictive Artificial Intelligence based customer service solution to elevate the experience of customers and agents in every interaction. Ascendo applies advanced modeling in incoming customer questions and detects the context and intent behind the questions. Through that it uses semantic inference to find the symptom, root cause, problem and solution from across multiple solution articles. Ascendo also predicts customer sentiment and predicts customer-specific and broader problem trends to avoid future problems. Ascendo connects with the company’s service CRM, installed base, and internal knowledge base to provide prescriptive recommendations within the existing service workflows. For companies that make hard assets, Ascendo has additional models to help with the logistics and field service teams. By looking at the problem and failure trend, Ascendo also helps provide predictive part demand recommendations for the logistics team. For companies that include hard assets in the field, Ascendo provides the game plan in terms of fix procedure and part recommendations before a technician visits the customer site. Learn more, Knowledge Intelligence in Customer Service Innovative B2B Automated Self-Service Technologies

Knowledge Management (KM) is the methodical management of information, data, and knowledge assets held by an organization to add value and achieve strategic goals and objectives. In simple words, it is the process of capturing, sharing, and successfully utilizing knowledge. Knowledge management has a variety of use cases, including employee onboarding, customer onboarding, customer service and self-service. These processes can be expedited and run efficiently with the help of knowledge sources. Also, there are knowledge management applications that enable field technicians to leverage knowledge and insights for better productivity and cost savings. Today, artificial intelligence (AI) has transformed the way organizations handle their knowledge management processes. Knowledge intelligence, i.e. AI-powered knowledge management, is a popular trend that will only become more pertinent over time as businesses come to understand the advantages of integrating it into their operations. Why Knowledge Intelligence in Customer Service? Agents are swamped Teams representing a major corporation with millions of customers will manage a greater volume of interactions. Customer service representatives are flooded with help requests, follow-up calls, emails to respond to, reports to process, and other tasks. Apart from this, rigid operational methods, old KM methods and broken internal processes make it harder for agents to satisfy customers. Hence it is key to invest in a modern, adaptive software tool. Issues are getting complex Customer support personnel deal with a variety of problems every day. While some are simple to solve, others are more challenging. Support agents are the face of the company and the impression they leave on customers as they work through complex problems has a significant bearing on how that company is seen and whether or not those customers will return. Therefore, it's essential that agents have the right tools when tackling customer issues. Customers want resolution fast One of the most illuminating results from the survey conducted by Dimensional Research is that “customer service experiences are judged more on the timeliness of the interaction than on its final outcome.” Sadly, after providing all the details to the agent, customers are forced to repeat the information when talking to the next person in the support team. Need to improve customer experience Making customers work too hard to find answers to their queries leads to a bad customer experience. Telling agents to go above and beyond for customers is likely to result in confusion, lost time and effort, and expensive giveaways. On the contrary, companies can improve customer experience and thereby create loyal customers by helping them find solutions quickly and easily. Advantages of Knowledge Intelligence in Customer Service All Data At One Place The core of knowledge intelligence is an information repository that houses data on customers, products, services, and frequent problems or complaints. With its help, decisions can be made more quickly and problems can be solved effectively because all the information is in one location. The knowledge source is a cloud-based solution that makes it easier than ever before to manage customer service data. Analyze & Act On Data Faster Organizations can quickly identify trends and patterns using knowledge intelligence. Support leaders no longer have to manually find out problem areas, internal issues and so on. AI-powered knowledge management systems provide real-time insights into how customers interact with the company. Automate Workflows Automation will simplify the process of carrying out repetitive tasks. Each time, it takes a lot of time to perform it manually. Although it may not appear to be much now, it will build up over time. AI allows the automation of more processes than ordinary automation. It enables support leaders to build workflows based on their own rules. This will cut costs, save time and improve efficiency. Strengthen Self-Service Tools AI-powered knowledge base systems allow businesses to automate responses to customer inquiries. A proactive and personalized AI bot enhances customer experience and reduces agent workload. Static knowledge is never enough in the world of customer service. By adding knowledge to the system time to time, it stays updated and serves useful for agents and customers alike. Deliver Better Customer Experiences Knowledge intelligence is a highly integrated and innovative solution that opens the door for improved customer experience. It provides a comprehensive set of features designed to make sense of the data and take action based on insights gained from analyzing it. It will thereby accelerate issue resolution and reduce customer effort. Improve Productivity & Reduce Costs According to a study of 1000 companies: The average response time by the customer support team is 7 hours and 4 minutes, but the top 5% of organizations respond in just 16 minutes. While the issue resolution time is 3 days and 10 hours on average, the top 5% of companies can solve problems in just 17 hours. On average, each support agent can handle 21 tickets per day. With the use of artificial intelligence, organizations can boost output while keeping costs down. Knowledge intelligence helps support organizations to become the cream of the crop as it optimizes their operations and internal data-sharing procedures. Ascendo Offers Knowledge Intelligence Ascendo helps companies provide proactive customer support with the power of artificial intelligence. With Ascendo's no-code integrations, support teams can link to many CRMs and other data sources and see all of the solutions listed together in one location. Consider the unique tips and techniques established by an employee to complete a task faster or more efficiently. This is important information that is lost when an employee leaves. Organizations that overlook such information jeopardize their overall performance by risking the loss of knowledge that only a few people possess. With the Ascendo AI engine, it's easier to structure tribal data and convert it into valuable knowledge. In a world of limitless possibilities, knowledge bases should incorporate the latest developments as well. Using Ascendo, support teams can update and improve knowledge articles as needed. Ascendo also helps identify how issues evolve over time, which ones are prevalent, and which ones require solutions. Learn more, Innovative B2B Self-Service Technologies Ways To Improve Time To Resolution