Ascendo AI career oppurtunity for Angular Frontend DeveloperFull Time Position Angular Frontend Developer Location Remote, United States Employment Type Full Time Job Description Overall, you will be responsible for ensuring that these applications are performing, secure, and easy to use. In addition, you would be required to contribute to the development of new features and functionality of our software. We encourage creativity and innovation and are looking for candidates who wish to own the space provided and truly improve the product. Objectives of this Role Designing and developing user interfaces using angular best practices. Adapting interface for modern internet applications using the latest front-end technologies. Writing TypeScript, SCSS, and HTML. Developing product analysis tasks. Making complex technical and design decisions for Angular Modules. Developing application codes and unit tests in Angular, Python Technologies, and Rest Web Services. Conducting performance tests. Consulting with the design team. Ensuring high performance of applications and providing support. Skills and Qualifications Bachelor's degree in computer science, computer engineering, or similar. Previous work experience as an angular developer. Proficient in SCSS, HTML, and writing cross-browser-compatible code. Experience using JavaScript building tools like Gulp or Grunt. Knowledge of TypeScript MV-VM/MVC frameworks including Angular. Excellent project management skills. Proven experience implementing front-end and back-end JavaScript applications. If interested, Email your resume with LinkedIn profile to apply@ascendo.ai

Elevate Support Logistics Operations with Ascendo AI Enterprises invest significantly in supporting critical service level agreements (SLAs), stocking crucial parts, and collaborating with external contractors. After-sales service represents a significant portion of revenue and profit. Things break unexpectedly, and sometimes emergencies need to be attended to before scheduled jobs. How can an Enterprise Service logistics team become proactive? Ascendo's PredictGPT module is the answer to the questions related to all the missed SLAs by your team. Ascendo Cognitive Parts Planning is introduced as a solution involving proactive management of parts, tools, and locations to deliver spare parts efficiently. By analyzing enterprise service, install-base, and materials planning data, valuable insights can be gained to accurately predict demand and prepare the service organization accordingly. The application of machine learning principles helps implicitly learn failure patterns, enabling the development of prediction algorithms for component demand. Ascendo Cognitive Parts Planning is presented as a solution, leveraging modern technologies like AI (Artificial Intelligence) and machine learning to proactively manage spare parts. Ascendo’s PredictGPT module analyzes enterprise data to predict demand, allowing for more efficient and prescriptive service operations. Download whitepaper to read more on this: More White Papers Auto categorization 01 Ascendo brings to you one of its most utilized and successful components, Auto Categorization, that is built on state of the art Natural Language Processing techniques and Deep Learning algorithms. AI Based Modern Support Experience 02 Businesses these days receive hundreds and even thousands of customer queries daily. Get started to transform complicated client communications on Slack to smooth, AI assisted interactions 03 Should Companies use Slack or Teams with Their Customers? Escalation Management Guide for proactive support teams 04 The term escalation refers to the action where the issue and the details of a customer interaction is sent higher up the chain, sometimes to the CEO level. View All AI Agents in 2025: Redefining Technical Support with Precision and Partnership As we approach 2025, the conversation around AI’s transformative power is shifting from speculation to strategy. In his recent article,... The Evolution of Service: How AI Agents Are Shaping the Future of Support As the technology services sector embarks on what promises to be a transformative year, businesses are navigating a delicate recovery... Our Blog Here is your go-to guide on what's latest and greatest in delivering superior customer service with the power of artificial intelligence. Catch some invaluable industry insights, and take it forward on your social media channels! Read all Ready to learn more? Contact Us

Proactive customer service with Ascendo AI. Our smart backlog system offers proactive support, predictive solutions, and personalized responses based on ticket history and context. Boost agent efficiency & deliver exceptional service. Smart Backlog Provide your experts at all times and all channels with virtual agent. Watch Demo 5/5 Ratings SOC 2 certified No credit card required I I Top Call Drivers As the volume of data increases, the complexity of the issues also goes higher exponentially. This leads to the immediate need of not just tracking issues, but also keeping an eye on how issues are changing over time, which issues are causing continuous customer dissatisfaction, what latent factors are causing issues to go up/down and which ones are completely new or unseen. With Ascendo’s AI Engine, the above challenge, which takes almost 17.2 hours a week on an average for an agent, becomes a click of a button! Auto-triage Dealing with the continuous flurry of new issues in the form of tickets is always a challenge. Ascendo surmounts this by providing you a smart backlog for your tickets that entails not only actions to prioritize, sort and keep track of your tickets but also predictions to automatically group similar tickets together and solutions to resolve them, then and there. Ascendo performs contextual clustering on your tickets and groups them into similar buckets. From here, not only can you see the number of tickets for each type of issue, but also take actions on these tickets from within Ascendo itself. Ascendo also provides predictive solutions based on the history of your tickets, contextual information and hidden intent. This knowledge can then also be applied to existing tickets in the form of responses, that are generated by Ascendo using the predictive results. 01 Understanding the Problem While it is incredibly difficult to deal with the high volume, velocity and variety of data, Ascendo has created algorithms that can help you understand the data deeply. Utilizing the state of the art NLP and ML models, we are able to generate data insights and provide relevant solutions at the same time. 02 Recommendation Engine Ascendo uses its custom advanced ranking system to choose the most valuable and relevant solutions for the problem searched. To set the right relevance, our ranking system also keeps track of any human feedback and other features such as solution’s recency, expert technicians and the number of clicks. 03 Autonomous Along with understanding keyword importance, Ascendo AI Engine uses Advanced Transformers and Attention networks to depict the text in the vector space. With the Attention mechanism and Positional Encoding, Ascendo is able to find context for any position within the sentence. 04 Categories & Sub Categories Ascendo AI engine is able to inspect the incoming issues to find the related symptoms, problem categories and problem subcategories. This gives knowledge to the agents, which otherwise goes undetected. Consequently, the agents can take the right actions and result in fewer escalations. 05 A Guide for Agents Gone are the days when agents had to do everything by themselves. Ascendo provides an always available guide to agents that intelligently pilots the agents towards the right solutions, actions, and the right game plan. 06 Resolve with Minimal Bias No matter how careful you are, where your ticket ends up always involves a bias. With Ascendo’s AI, you need not worry any more, as it removes the undetected subjectivity that often comes into play when a ticket is being routed to the right assignee. Get started with Ascendo Today Contact Us

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From Manual to Seamless: Teradata's Support Evolution with Ascendo AI Teradata, a global leader in data and analytics solutions, faced inefficiencies in customer support due to manual processes and inconsistent service quality. Despite using multiple tools, support engineers struggled with slow knowledge retrieval and repetitive tasks, impacting First Contact Resolution (FCR) rates and customer satisfaction. By integrating Ascendo AI’s generative AI capabilities with their ServiceNow platform, Teradata transformed its support operations. AI-powered tools streamlined knowledge access, automated repetitive tasks, and predicted customer needs, enabling faster more accurate responses. The result was significantly improved FCR rates, reduced resolution times, and a more efficient support process. The partnership delivered substantial cost savings and elevated customer satisfaction. With plans to expand AI integration across more functions, Teradata is driving innovation in customer experience. Read more to explore the full case study and the impact of AI-powered support. Ready to learn more? Contact Us

Discover how to transform your customer service into a profit center. Learn about the CX Maturity Model and strategies for making support proactive and revenue-generating. Gain insights on tailoring your pitch to different decision-makers and measuring ROI. Turning Customer Service into Profit Centre | Transcription Previous Next Kay - Welcome to the experience dialogue. In these interactions. We pick a Hot Topic. That doesn't really have a straightforward answer. We then bring in speakers who have been there and seen this but approached it in very different ways. This is a space for healthy disagreements and discussions but in a respectful way. By the nature, of how we have conceived, this, you will see the passionate voice of opinions. Friends having a dialogue and thereby even interrupting each other or finishing each other's sentences. At the end of each dialogue, we want our audience to leave with valuable insights and approaches that you can try at your workplace and continue the discourse on social media channels. A little bit about Ascendo, it is addressing optimization of support to operations within enterprises so that they can serve their customers better. We enable enterprises to optimize workflow for the agents and provide dashboards for insights on risk, churn analysis, and visibility for senior managers. We are revolutionalizing support ops in the same way DevOps and RevOps have transformed other areas of the business. In the last three years, we have created a G2 category and are ranked #1 in user satisfaction. We are very proud to be loved by our users, and now with the topic Turning Customer Service to a Profit Center. For most companies, customer service is still viewed as a cost center and with the increasing and ever-changing customer demands, this perception is further strengthened. However, when utilized correctly, customer service could be one of the biggest revenue generators in your entire organization. Now it’s a pleasure to introduce the speaker, Jonathan Shroyer, Chief Customer Experience Innovation Officer at Arise Virtual Solutions Inc. Arise .has been following a customer experience maturity model that can help you turn your cost-center service team into a profit center. We will be talking about each phase of the maturity model and how to make a support center proactive and profit-oriented. Jonathan, a pleasure to chat with you. Thanks for the opportunity to come on the show. Jonathan - It's really great to be kind of in the catalog of great shows that you have and has the opportunity to share a little bit more about the views of turning customer service into a profit center, so I appreciate the opportunity, Kay. Kay - And, what is interesting about your background, Jonathan, is. You've done various types of companies, from security to, you know, office applications to Autodesk and Kabam fully in the gaming space and now you are in the gaming space. So, it's fabulous to see the entire customer success and how it has been, it's rare to see people who have had decades of customer success experience.so it's wonderful to have you at the show. Jonathan - Thank you. Thanks for the opportunity. Kay - So let's start right there. Actually, since having decades of experience, Jonathan, tell me a little bit about how you have seen customer service change over time. Jonathan - Well, I think it's interesting. So when we go back to the 1980s, there was this very kind of brick-and-mortar viewpoint to services. It was in the early times when we started to see the kind of technology morph to where contact centers or call centers, started to come about. Then you go into the nineties and that that infrastructure at the the kind of the boon of the internet at the end of the nineties enabled. That type of capability to be serviced outside of the local country, whatever the local country was, right? I was in the United States and they were fast, quickly. The 2010s in it and, and we went from, Hey, we can contact to, all of a sudden there's text, there's email, there's chat, there's Facebook, etc. I mean, there are all these different ways that customers can access brands, and what changed at that moment was this concept where brands now could hear from their customers more often, understand their customers more and the customers had a lot more information and data to make better choices, and they started to make different choices based of how brands started to treat them and then as we fast forward, you know, up through the 2010s into now, into the 2020s, we're noticing that customers are making choices based off of how brands treat them in their customer experience, and they're making their choices with their feet and with their money. So it's been an interesting transition of where, and how consumers and customers make their business and their brand choices based on how they're treated. Kay - it's fascinating that you brought in the data, and evolution along with the customer service evaluation when you answered this, Jonathan. So one of the things we say is metrics are good, but metrics don't say a story, data does. Do you actually see the way brands are relating to customers and the amount of data that they are using more and more and, how do you see the data transition also over the years? Jonathan - Well, I think what's interesting is, data is like super important to companies. I think consumers don't always think about it in as in that valuable sense, right? They think of, oh, I'm not a member. You know, I'm a person, treat me individually. Customize it for me. But the reality is, for companies to be able to deliver that optimum service, that best-in-class service that drives stickiness, loyalty, and so forth, they have to have the data to understand, what the customers are doing with their product inside their product and so forth. And so I think that over the years, one of the things, you see happen in the early 2010s, this idea of a unique identifier that could identify a customer across an entire company or entire product suite, and the reason why a unique identifier was created partially was for security reasons, to protect the customer, protect the client, the business and so forth. But the other component of it, which people didn't realize at the time, was and enable the company to be able to correlate. Data between different parts of the company. So for example, it allows this correlation between customer experience and profitability as an example, right? Or like adoption and usage and different product suites or different product features that come out. A company can now say, feature X, and based on what all these key clients are telling, Based on using it and loving it or not loving I, that tells us whether the product feature was a good product feature or not, in addition to, anecdotal feedback from the market or from the individual customer. So I think, the transition and maturation of going from very lean to data in the eighties to big data in the 2020s have been just as important in this framework of creating profitability through customer experience as it has. As, the actual activities or the processes that a customer experience team does to drive that profit. Kay - Arise has been actually following a CX maturity model and I would love to understand how you see that model will make support, proactive and how do you see that transition from cost center to profit Center. I know that's two different questions, if you wanna split it and answer, that's fine too. Jonathan - So to give a little context, I invented the maturity model called the Service Tech Maturity Model at the time and trademarked it, but the idea was when I started Officium Labs, I had been working in large enterprises in startups and gaming companies for some time and what I realized was that there wasn't like a simple, easy-to-use framework or model that you could go and join a company and all of a sudden look at like, based of this model and this framework, I have all the features necessary to create profit and to communicate profit, to the power cores of the company in a way, they understood it. And so what I thought I would do is, I said, what if we treated customer experiences if it's a product? So if you create a product, what you tend to do is, create a framework of what the product is going to be. And inside that product framework, you have pillars that we'll call major feature sets. For each of them in your feature sets, you have feature components that build that feature area, right? So for example, if you're building a Microsoft Office product? They have seven or eight different types of feature sets, and then they're like, well, we wanna add this, or we wanna add that, and the same thing with the video game, the same thing with any type of product, right? So I said, let's build a customer experience product or let's at least think that way, right? So change the mindset and say, what are the pillars that we need to have inside of this product? And then what are the features inside the pillars? So for example, workforce management, learning, and development, interactions, products, those types of things, right? Quality, operations, those types of kind of pillars. Okay, so those are the pillars. And then what are the features that need to exist? And, so we build them out and we said, okay, these are the basic feature sets if you wanna run the basic operation. So, when we use that word, basic was a, had a different meaning than it does today. Basic has a very different meaning, The urban definition of it and whatnot. But generally speaking, the next one was, what's the standard look like? What's the next feature set? And then what does best in class look like? And then, you know, what is the next generation look like? So we build it that way for the users, but the idea was that if you build a customer experience with the product mindset and you have these features, then you can help companies understand, where are they at in the maturity model or where are they at in the customer experience product to be able to mature to a state where they can deliver a profit? And the outcome is if you're in the best, if you have the best in class features or the next generation of features of the maturity model, we can 100% show you how to correlate the work you're doing in customer experience. Kay - I love it because suddenly when we treat it like a product, what happens is, it enables the entire company to become a customer-oriented, customer-obsessed, customer-focused company, right? So it's easy for all the teams within the company, within the organization to tune in to the customer very easily because then there is a framework that enables a company to tune to that and say, okay, marketing, this is what I need to do. Sales, this is what I need to do, product, this is what I need to do. So I love that. So, can you summarize the eight pillars, and then we can dive into at least a few of them? Jonathan - them? Yeah, for sure. I mean, so when we look at the pillars, You, you've got, uh, the interactions and interactions really include all of your technology, so it's the non-human facing interaction component, like everything that sits behind that makes the interaction possible, whether it's AI, technology, CRM and so forth, then you have kind of the operations piece, and this is really about all the different processes and how to Interact and engage, you know, with that human being on the other side. Do you use vendors? What are your frameworks of success, your methodologies, and those types of pieces? Then you have the quality piece, which really looks at the overall experience and what type of quality experience you're delivering, whether you look at quality from customer effort, customer satisfaction, NPS, whatever it is, you know, it has that piece. Then you're looking into the learning and development piece, which is how are you training, onboarding, and equipping your people to be able to talk to the customers, engage with the customers, and then be proficient. In that piece, the next one you have is, we call it content management, but it's really looking at your knowledge base, the knowledge that's out there, whether it's through self-service or you know, whether it's through using social channels like Discord or other components and pieces. The next one looks at the product itself, which is like we, we firmly believe that when you design an experience for a customer, you design it at the development table. You don’t. The product's launched service go, make the customers happy like that's old school thinking. So inside of it, we have this whole concept of product liaisons that need to sit as in the experience design piece, design it, and develop it and then you go to beta or alpha, then you go to beta, and then you launch it, right? So there are some key components overall. And then, and then we, then we kind of then look at, you know, what's the rest of, you know, the tech stack that looks that supports the organization, that doesn't really have to do with it. The interactions themselves, cuz there are a lot of techs inside of the experience side, right? And then you look at kind of the pillar with looks at the customer journey, looks at the journey mapping and all of those different components and pieces, so really kind of, it sets up these different overall pillars that which is a little bit more complex for someone that's trying to follow along to what I'm saying now. so we can share a visual of it later. But the most important thing is, what are the features that you have today? So how do you assess against that? And then what are the key features that you want to add over the next 12 months? And so every company's gonna be a little bit different in that, in that component. Some companies wanna invest in interactions or AI, some companies don't have a quality program or WFM program, and they're gonna wanna invest in those things first, right? And so it's gonna be different by company, but the goal is how do I create ROI? How do I create profit? And then once you have the unique identifier set up and you have the correlation capabilities. The maturity model is then doing A/B testing and proving out, what correlative values, and a correlative profit look like for your business, because it's gonna be different for gaming, which is the hat that I'm wearing, right? We have gaming clients, healthcare clients, finance clients, and clients all over the world. Tech clients, it's gonna be a little bit different, like how you drive profitability or correlation of profitability, in what tests you need to do and so forth, so that's doing the assessment, understanding the model, but then actually putting the model into the application and driving it as a business strategy. A business transformation is just as powerful and having the mathematical data to verify and validate the work that you're doing has an impact, that's kind of the soup to nuts. Yeah. Kay - So what is interesting for me is when if you look, you know the model that you're talking about, if you take the interactions, right? So the interactions are actual ones that is there in the system. The second one you talked about is the activity that is happening with the customer and if I tie in with the unique identifier, what are the existing regards with this unique identifier? I know. What are the interactions or the activity that are happening in any channel, that's happening with the customer? And then I can start correlating saying, how is this Piece of interaction that's happening right now with the customer, with quality, with learning and development, with the product and all of that and suddenly you have a nice flushed-out full interaction where you have the intelligence built-in and then you take, you know, thousands or 10 thousands of several of those interactions and then look at the patterns and the anomaly of those interactions, it becomes a beautiful, intelligent player that's more customer first. Did I give the same view of what you mentioned, but more from a data perspective, but does it? Jonathan - Yeah, I mean it totally does and I think the reason why I create the maturity model is cuz what I found is that there's a big disconnect between how people at companies that make funding decisions and the services team themselves and so it was a big frustration and a big tension between the services teams and the power cores as it were at a company that is making these investment decisions and so what I thought was important, how can we talk in a language that will help the power cores in the company understand the importance of investing in the customer experience side? Right? And that's where the money comes down to like that was the simple question. I'm a big believer that simple questions lead to the next generation of innovation. And so that was the simple question, asked me and then I was like, okay, well in order to do that, it's this, and it's the maturity model and the application of the transformation but the most important piece is, then how are you communicating back to the power cores of the company. The impact, and that's what, where one of the biggest things that the power cores have to get over is investing in the unique identifier, because most companies, they'd be like, we've been over for 30 years. A unique identifier across 45 databases is gonna be really hard. Yeah, it's gonna be really hard, but it could also drive 10 to 20 to 30 million of future revenue for you as well and so helping them understand and correlate is super powerful and then demonstrates the impact of like, hey, you gave us a million dollars. We protected, or we created 4 million or 5 million of revenue based on that a million funding that you gave us, and that conversation is just as powerful and important to the overall success of the services team, creating a profit center and communicating then the framework itself too and so I think that's important to note. Kay - I love, how you mentioned the power cores, who make the decisions, so let's talk a little bit about the various people who are making the decisions for this funding and the kind of roles and how it differs from your experience. Jonathan - Well, it's super interesting. So I think there's like four or five cores inside of a company and in any company, it's never the same group of people that have the actual power versus the perceived decision-making and authority and so you look at IT, you look at finance, you look at marketing, you look at sales, and then you kind of look at the executive team and product, so those are kind of the six-ish power cores and in some companies, product drives everything. Like product is the power core, right? And you see this a lot in startup companies. You see this in companies, that are more tech, you know, industrial companies, but then you go into other companies like financial or healthcare companies that have been around for 30 years and I find that oftentimes finance and legal are the power cores in the companies, which is super interesting to me cause it's different than, a product power core company or a finance power core company. I think the most important is to understand here, doing an analysis on who actually makes the decisions in your company, and then what's the decision process that they go through to make decisions, and then how can you speak in that language? And I think that's the most important thing to think about. Like, I was with a gaming client two years back and it was clear that finance was like a power core in their company and so the way that I pitched the maturity model and the value that it could provide was a little bit different than a gaming company where tech was the power core. Right. And so it was much easier to get tech to do the single identifier than finance, and so you had to talk in a different language. Like as example, tech was like, yeah, it makes sense, we should do it. Then we were ready to go and they're like, yeah, let's do BDI, Big Data, and let's do this and they were ready to invest much faster, whereas a finance company or finance power core was like, well actually, what's the ROI? Take me through these five presentations to convince me and prove to me, and then I wanna follow up every week afterward so in one way is not bad or, or right or wrong, but they're just different and so it's important that as you start to think about, how do I talk about profitability. In the customer experience area, you just have to know who your audience is and what's important to them, and then how you can frame the language to help them get value out of it. Kay - there are a lot of people watching this, who are from the support background, and one of the biggest things that they are asking is, how do I take this argument to the decision makers? It's changing a little bit with the chief customer offices themselves making those decisions, but they have to work with the rest of the company, so I think what would be wonderful for this audience is let's take it through these examples that you talked about. Let's talk about stories that are wonderful, Jonathan. For example, this finance, and how did you do it for the finance, with the CX maturity model? Jonathan - Well, I find the easiest way to start with any power core is to start with, its magical word, which I love, it's called a pilot and most power cores are willing to take risks on a pilot, but they might not be able to be willing to take risks enterprise-wide, right? or company-wide and so what I end to find is it's really important for the customer service team to identify a group of customers, whether it's a product, whether it's a delineation of customers inside of a product or, whatever it is. Find a group of customers, you believe, as you have a hypothesis like, Hey, this group of customers will definitely be able to demonstrate a profit. We have a hypothesis in video gaming as an example, a mobile game company that we worked with, the top 2% of their customers generated 80% of their revenue, right? And so for us, let’s focus on doing a pilot for the top 2% of these customers, let's identify, what we're going to change for this 2% of the customers versus the rest of the customer base. You can call that an offering, right? What's the pilot offering going to be? What are the pro processes, the methodologies, and the policies that we need to change for this pilot, and then what's the data that needs to be recorded or adjusted in order for us to be able to demonstrate whether the pilot was a success or not and then, what's the key success measures of that? So you build all that and then you take that presentational proposal to the power core. In this case, it was the finance team and then for the finance team, and it was really important for them to understand how this impacts the bottom line. So we built the entire presentation to do all of that, but then also talk about, like this is going to be an investment of X, but it's gonna deliver an ROI of Y and we're gonna be able to get it. Know that the ROI was delivered within eight weeks or 10 weeks, right? You give them a timeframe. And then you set up the meeting to talk about this, the success or the non, the findings of the pilot, and then from there, you know, the findings statistically significant enough to scale it, or do you need to elongate the pilot for another six weeks or eight weeks to get that statistic significant? We presented to them and so forth, and in this case, we were able to present it. For the pilot, we scaled it enterprise-wide based on the fact that they saw the ROI, they saw stickiness and retention numbers. They saw the stickiness and increased revenue attribution and so we were able to do it right, but that's the most important thing is to start with the pilot experiment, have a hypothesis, prove your hypothesis, and make sure you think through all of it, the processes, the policies, the methodologies, the data structures, the technologies, all that build up a bit, right? Put it together and then proposes that and then make sure you have your finance number of what you need for funding versus what the output is going to be and then you can attribute what the success of the pilot was or not. Kay - That's, you know, essentially, a full framework for the proof of concept, right? So that's essentially right from the planning all the way to the measurement, the proof of concept too, so in the end, there are no questions about, was this even successful? It is very clear what that success metric would be, so in the end, the decision-makers can participate in saying, yes, this made sense. Now how do I, we go and deploy and in what stages do we deploy? That's very good. Would you like to add anything else with respect to the framework, if it was a different decision-maker? Jonathan - Well, I mean, I think that like, if you're talking to like a technology or product power core, they're interested in the ROI, but they're also interested in what could we change in the product in addition to what you're doing in an experiment in the service? It's like, maybe like after the beta test, we like that, we'll just build it into the product, right? And maybe we'll just become part of the product and it could drive that attribution, so they just, they just have it. It's more of a like, Hey, how can we use this next? Yeah, give us data online, but then let's build in the product so we can scale it and it's not a manual process and then they tend to think, you're a creator as well. I know that you think this way too awesome, but how do we build the product so we don't need so much manual intervention? We retain the customers earlier in the cycle versus later in the cycle, right? So a product like something like that, somebody that's in, from a legal standpoint, but are we getting away? Is there any risk or, like, are we gonna lose all these other customers because we're doing this thing for this customer? or what about the data? Like, is this data, is it gonna be GDPR? Is it those types of things? Right. You have to go through all that for power core, but those are kind of the questions that they'll want to have the answers to. Right? If you talk to an executive, maybe an executive that's more high level, they'll be like, I don't even know about anything. All I wanna know about is what's the service metric, what's the ROI metric and gimme a weekly update. Right? So it will just depend on who the power core is and how invested or interested they are and how you make the sausage versus the sausage being made for lack of a better metaphor versus the sausage, how well it tastes, and how much customers love the sausage and all that jazz. Kay - Yeah. So, essentially in that group of concept, the ROI is the metric for the finance person, and that metric changes if it is a product person, marketing or sales person, or something else, that's kind of how the metrics tie back to the profitability of it, so at this point, you don't know anything about your customer experience of the product, but here it is, when you tie all of this together, you have real-time feedback on how customers view the product and what changes you need to make to the product and that is the driving force for turning it into a profit center. So, the CCO drives who the decision-maker is, and what is the metric that's going to resonate with that decision-maker? Jonathan - I think that as you do that, create that decision maker and help them become a sponsor and that will be the next powerful thing, you have these conversations cuz if you have a sponsor, you're good, that's outside of CS. If you can get an executive sponsor that has influence in the company, then we're not only gonna be able to try this first pilot, you're gonna be able to do other experiments. There's, a Nelson Mandela quote I love, “I never lose, I only win or learn.” that's a very iterative way of thinking, which is like, either I won or I learned something and now I'm gonna go try something new and I'm gonna win at that which tends to be more stereotypical of a product or, or a tech power core, but in essence, I think any company that wants to be successful, they have to try this. Long ago, the waterfall was the way that we did project management. Hopefully, that's gone because it doesn't allow for iteration. It assumes that you're having, this is the product and we're delivering the product. Let's see what customers think. You know, it's a very risky way to do it in my viewpoint, but it's an iterative way and I think that if you can get a sponsor and they'll be okay, what's the project that we're gonna do? what's the next experiment that we're gonna do to drive stickiness and retention? and then what you'll find is once you prove that pilot out, you'll get another PowerPoint. Be like, wait a second. Like how are you doing that? Oh, wait a minute. I wanna know how can you help me think about that for marketing. Or how can you help me think about that for sales? You know, how do we drive that same mentality? Maybe the framework is different, but in the customer journey, how do we drive a mentality of experience, design, and retention proactively rather than just reactively? so then you look, then you start to give this interest across the entire customer journey. Kay - Yeah. I know we are running out of time. I wanna squeeze just one little thing into the conversation. How do you create urgency? The easiest is to create that urgency to make this happen. Jonathan - You show the amount of money that is being lost because of it, like that's the other important piece is like you when you look at the industry data and you know, I have industry data, I could share that. Maybe each particular customer experience person has their own data, but essentially I always like to do an analysis, a simple analysis to do this is all open source, right? Give it away. So, but a simple analysis, what is the revenue generation of customers that never contact support versus the revenue generation of customers that do contact support, do that analysis and full stop. 99% of the time, what you'll find is that customer service or customers that contact support is stickier. They drive greater revenue, and they have more of an impact on your future and so that revenue difference is saying, hey, all these customers that never contact support, they just left. They don't have a good experience, they don't care about the brand, and they don't care about the product. That's money that's on the table, that's lost. That's how you create a sense of urgency. Usually, in large companies, that's millions of dollars. And that starts to speak. Kay - people. Yeah and then you can start showing urgency on what are the brief thoughts, right? So then you need to get to it now, to make it important and I like that metric. Anything else that you would like to add that add to it? Jonathan - I mean, I think that as you think about it from a high-level standpoint, I always think about two words. How are you protecting your customer, but how are you optimizing the experience? And so that's, that's those two words are kind of what helped us build the maturity model because different pillars in the maturity will protect the experience. Different features and other features will optimize the experience. I think as an example, like, protecting the experiences is really understanding who the customers are, and how they want to be engaged. Meeting them where they are, as an example versus where you want them to be, but optimizing is looking at, how does AI help my customer have a better experience versus human-to-human engagement? Encourage better experience. so those are just very simple examples of how you protect and optimize. But as we built out the framework and we built out the maturity model, that's how we thought. Kay - Excellent! Protecting the customer versus optimizing the customer's understanding, how to create the urgency around, how many you know, revenue generated with customers who reach out to support versus not, and then building out that, a framework for the proof concept to make it a reality and then driving from the proof of concept into the entire deployment to make this a customer-wide phenomenon, so thank you very, very, very much, Jonathan. I think you have given a full framework. It feels like there is a lot we covered in a short time and it feels like there's still more we will certainly bring you in for a further conversation, but I really appreciate the time that you took today. Thank you. Jonathan - No, thanks for the opportunity. If anyone has any questions about it, they can reach out to me on LinkedIn or you can find me. I'm a Chief CX Officer on TikTok on the instant, a variety of other places, and YouTube. So, thank you so much, Kay for the time, to share my thoughts and add to all the wisdom that you know, that your podcast and your life have. Thanks for the opportunity. .

Speaker: Jeb Dasteel The CCO Playbook Unlocking Customer Experience Leadership Speaker: Jeb Dasteel March 27, 2024 Previous Item Next Item Buckle up for a deep dive into Customer Experience (CX) leadership! This podcast explores the experiences of Jeb Dasteel, a former Chief Customer Officer (CCO) at Oracle, who now coaches other CCOs. This episode dives into the key challenges and insights for CCOs, aiming to improve customer experience (CX) and drive business growth. Why CCO Coaching Matters Jeb emphasizes the importance of knowledge sharing and mentorship for CCOs. A standardized playbook for CCOs is crucial, as the role often lacks consistent approaches. Balancing Customer and Employee Engagement Striking a balance between customer satisfaction and employee engagement is a major challenge for CCOs, especially in complex industries like healthcare. Optimizing Internal Handoffs CCOs play a critical role in ensuring smooth handoffs within organizations. This ensures a seamless customer experience, where transitions between departments are invisible to the customer. Strategic Planning vs. Day-to-Day Operations Finding a balance between daily tasks and strategic planning is a significant hurdle for CCOs. They must be proactive and focus on long-term goals while managing immediate demands. Key Takeaways for CCO Success CCO Playbook: Develop a standardized playbook to streamline the CCO role and empower new CCOs. Balancing Act: Prioritize both customer and employee engagement, acknowledging potential conflicts between these groups. Seamless Transitions: Ensure efficient handoffs within the organization for an invisible and positive customer experience. Strategic Focus: Balance day-to-day operations with strategic planning to be proactive and achieve long-term goals. Knowledge Sharing: Collaboration and knowledge sharing among CCOs is key to overcoming challenges, improving CX, and driving business success. By implementing these insights, CCOs can navigate the complexities of their role and become strategic drivers of customer experience and business growth.

Provide the best customer services to your end customers with the AI and ML-based technology of Ascendo AI. Welcome to the world of Ascendo AI resolution engine that works across data to give you the most relevant solutions based on customer interaction. AI Agents Conversational Intelligence from self help to agent assist creating consistency across channels. Sign up for free If you have been operating with a chat bot for website, a tool for each Slack, Teams, Whatsapp and other conversational support channels, you must be drowning in rules, process definitions and chat bot training. Welcome to the wold of Ascendo AI resolution engine that works across data to give you the most relevant solutions based on customer interaction. Measure every self service interaction to see resolution, solution effectiveness, Customer Effort Score or CSAT. No need to train or run multiple weeks of POC. Scale your team and measure ROI from within Ascendo. Ascendo AI Conversational Engine 01 Not your chat bot! Ascendo’s AI Agent consolidates knowledge from multiple data sources to provide your customers solutions with any interaction. Your customers need not create a ticket for all issues when a myriad of solutions probabilistically ranked are provided from multiple data sources all in one page. 02 Solve Complex Issues Our distinctive AI search model returns contextual solutions as it has been able to harness tribal knowledge specific to our clients. The uniqueness of Ascendo’s AI Search is embedded into your conversations to provide consistency across channels. 03 Cater to your Industry While Ascendo’s AI Agent can cater to your customer support needs irrespective of the industry, it can also be configured to gain specific knowledge. 04 Resolve not Prolong As a customer support agent, Ascendo’s AI Search allows you to view solutions based on which data sources and predicted root causes you want to explore. It also allows you to differentiate your solution search between different products. 05 Predict Customer Effort and Health Scores All interactions with customers are saved and used as a knowledge bank to understand the trends and patterns of customer concerns over time. One Platform for entire Customer Service Lifecycle Contact Us AI Agent with Intelligence Live Agent Handshake Your customers never have to repeat their bot interactions and what they tried so far EVER. When a agent handoff happens, agent not only knows what solutions the customer has tried before but also gets additional predictions from enhanced data access. Make every front-line agent a super hero!

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