In a 2023 Salesforce survey of Sales and Service users, half of all respondents indicate that they “don’t know how to get the most value out of AI,” while a 2024 survey from LinkedIn and Microsoft shows that 59% of survey respondents “worry about quantifying the productivity gains of AI” and 60% say their company “lacks a vision and plan to implement it.”
TruSummit Solutions is committed to helping you maximize Salesforce AI in your organization. In this session, TruSummit Solutions’ Danielle Nelson takes the nebulous statements around AI — “AI is going to help us transform our business” — and shows you how to turn them into something more concrete. Using customer support as a use case, we cut through the AI noise to help you determine your expected value from Salesforce AI, enabling you to move from vague generalizations to needle-moving results.
Watch the full recap below and follow us on LinkedIn for our next Salesforce AI LinkedIn Live session.
TRANSCRIPT:
Speaker 1 (00:07):
Think we are going live. Hang on one moment. We are live. We’re live. Hello. Well, hello. Hello. Welcome
(00:33):
To everyone that’s joining us for today’s presentation on mapping value from Salesforce AI. Please bear with me as I scroll through two different screens to monitor what’s actually happening on the LinkedIn live, as well as work through the platform that we’re using to produce the LinkedIn live. I’m Becky White. I’m with TruSummit Solutions, I’m the director of marketing. I’m joined by Danielle Nelson with Tru Summit Solutions. She is our solutions director, and this is the second in our series on Salesforce AI. We demystifying Salesforce AI, I should say. We first met back in June to talk about introducing Salesforce AI and laying out a roadmap for assessing your organization’s Salesforce AI readiness. And that session is available on our website. You can scan the QR code on your screen. It’ll be up for just another few seconds. You can scan that, you can access the first webinar if you’re looking for that foundation of what we began talking about earlier in the summer.
(01:45):
Today, we’re taking that conversation to the next level, and we are going to talk about how to estimate what value you can plan to extract from Salesforce AI within your organization. So we will do a little bit of foundational conversation. Again, just lay some groundwork and then we will advance into, okay, what can Salesforce AI really do for me? We are all talking about AI constantly. It’s on the tip of our tongues. Every email subject line has AI in it. How does it actually work for me for my org? How will I actually derive value from all of these tools at my fingertips? And that’s what Danielle’s going to walk us through today. Throughout the session, I will ask you to give us some grace. We’re doing this live. It’s always a little bit of a, you never know what’s going to happen when you’re live. So bear with us of course. And then as you see the ticker on your screen below, share your own use cases. We’ll be talking through some functional use cases today, but share your own in the LinkedIn live feed and we can surface use cases, questions, comments, anything throughout the presentation. We’d love for this to be as casual and conversational as possible when we are talking at you. And I think that’s it. I’m going to turn it over to Danielle and we’re going to go ahead and get started.
Speaker 2 (03:07):
Hey there. Mic check. Can you hear me okay?
Speaker 1 (03:14):
We can hear you. We can hear you. We are good. Yes.
Speaker 2 (03:17):
So this is me. So as Becky said, I’m the solutions director here at TruSummit. I’ve got about 20 plus years of experience in Salesforce, both on the in customer side and in the consulting and implementation side of the house. I work with TruSummit Solutions. Obviously we are a Salesforce partner. We’re based out of Pennsylvania, but I am streaming from Minnesota today. And really our differentiators and what you’ll see as we walk through this is really taking our strategic initiatives from a business perspective. What do we want to accomplish as an organization? What do our clients want to accomplish? And what is the value that they get from all of the capabilities within Salesforce? AI being one of the forefronts these days in terms of trying to understand how do I move from that nebulous AI will help me transform my business to AI will absolutely do this.
(04:16):
And these are the dollars and cents around it. So that’s really what’s on deck for today. When we think about the course of our conversation today, we’ll just do a little definition and stats, make sure everyone’s kind of on the same page on what we’re talking about. Talk a little bit about what we’ve seen and observed in the AI journey for our Salesforce customers. Talk about our readiness indicators, go through our value exercise and talk a little bit about next time. So that’s what it’s on deck for today. And as Becky said, feel free to comment as we’re going. If you have questions, if you have thoughts, very happy to make this interactive versus me just talking at you. So a couple of things. AI is not new. It really started with us. The human element, the data we provide, our actions, the context, our norms all compile AI capabilities, but AI is not new.
(05:11):
Many industries and tools have used the concepts of AI over the last number of decades. Capabilities provided by machine learning, predictive intelligence and generative models have catapulted over the last number of years. And the focus now is not on what are the capabilities, but more on the democratization of these capabilities through products and packaging, the commoditization of ai. When we think about Salesforce AI capabilities, we’re mostly talking about predictive generative. So just to give us a little guidance on predictive versus generative, we think about predictive. You’re leveraging historical data in order to make informed predictions about future, thinking about operations, value adds, managing risk, improving decision making. But again, AI is not new. So it’s starting in 1970s into the eighties around the early machine learning models. But right now really starting to harness that and think about those core capabilities and fitting it into our purpose-driven model around both industry and kind of just our capabilities from a top of funnel management all the way down to getting that cash.
(06:32):
When we think of Gent ai, we think about things like the creation of new content. That content might be in the form of graphics or just text-based content design-based content. It’s creating new data that’s mimicking patterns found in training data. And when we think about when that was introduced in the 1960s, it was in the form of chatbots. So Joseph Weisbaum created the chatbot, Eliza, demonstrating how AI could simulate natural language processes, natural language conversations. And when we think about the other AI capabilities that are less talked about, but also very important to be aware of is the diagnostic analytics that help organizations understand the underlying reasons. Really kind of trying to diagnose through identifying anomalies and patterns and historical data onto why things are happening and how you prevent future issues as you go forward. We also think about prescriptive analytics, going beyond just predicting the future, but then prescribing action and outcomes based on those predictions.
(07:49):
It’s really integrating that predictive model with optimization techniques to provide actionable insights and actions for more efficiency, for better decision making, for really kind of adoption of processes, thinking about what do I do next in this step? But in general, as we kind of talk about it, thinking about Salesforce ai, you’ll hear me reference a lot of predictive generative as we go through this deck. Couple interesting stats to be aware of. From an AI adoption perspective, 77% of companies today are either using or exploring the use of AI in their businesses. That’s a big stat. But then we start to think about are they actually using ai? Are there barriers to that? One of the top barriers identified 25% of respondents over a survey of enterprise companies is data is one of the top barriers. Really, it’s too much data complexity, not enough data of the right caliber in order to get the most from those results.
(09:07):
The other thing to think about is limited value. Right now, yes, 77% of companies are either using or exploring, but nine out of 10 businesses who have already invested in AI technologies, only 14.6% have deployed AI capabilities in their operations. That’s a low number. So now I’m paying for something, I’m investing in it, but I’m not yet seeing those returns on value. And then we start to think about AI and there’s kind of this notion of AI is going to take over my job. So when we think about it by 2025, we think AI might eliminate up to 85 million jobs, but create 97 million new ones resulting in a net gain of 12 million jobs. And the interesting part of this is it’s really kind of thinking about and evolving the different roles. So it’s not just about can AI help me, but also what are the skills that I need as an individual within our organization in order to support the AI capabilities that might look different than what we have today.
(10:20):
So when we think about the Salesforce AI journey, just a little fun graphic, it often starts with I want to use ai. Sure, absolutely. Right? Can I use ai? Yes. Yep, you can. It’s enabled in the org. Sure. Let’s do it. Let’s turn it on. Whoa, results look off. Yeah, that didn’t work. Write it off. We’ll tackle it later. It’s been wrought with a lot of fits and stops along the way. Another way to look at this is the different kind of phases of ai, the AI journey. We think about things like awareness, understanding what’s out there for Salesforce. I think everyone fundamentally understands the product mix available to them. It’s now connecting the dots. Can I connect what I’m doing today in my organization and where I want to be to how I could leverage the AI capabilities within Salesforce? You’re going to find a lot of people.
(11:24):
Yeah, absolutely. I can connect the dots. But then there’s the buy-in garnering funding and organizational support. It’s not all about getting money for it, but making sure that you understand why you’re using it, anchoring to the key performance indicators around it and getting that buy-in because ultimately you’re going to need that when it’s implemented and executed within your organization to get and drive the best results. And then from a readiness perspective, functional and technical planning, data management, change, alignment, and then utilization. So once you enable it and have it up and running, how do you evaluate the results? How do you fine tune and enhance and expand the usage as you’re going? And then value monitoring and assessing the AI process, learnings and achievements and anchoring that back to the initially defined KPIs. What we’re finding at True Summit is that there is a gap. There’s a gap between the, yes, I know I can use this to the buy-in organizationally from an executive level as well as from an overall kind of user audience level of why would we use this and how is it going to help me?
(12:33):
And so when we think about the Salesforce AI tools, I would be brave to not mention all of the capabilities. So when we think about all of the capabilities, we have a bit of an eye chart. You can certainly go on to Salesforce help and see all of the information. But as you can see, it straddles the entire capability set from top of funnel all the way to cash to really enhancing your platform capabilities. The idea is now how do I use these tools and why are we having this discussion today? So when we think about ai, it’s not just, can I turn it on? It’s the investment in time and energy, whether that be through a partner or through internal, a standard admin, a Salesforce team, most likely you have multiple priorities that you’re working on. How does this become one and how does this become the one that you work on?
(13:33):
And you might have a question from me of, well, Danielle, can I just turn this on? Sure, absolutely. You could turn it on, learn from it, continue to improve. But the question I would ask you back is what do you do with the results? Do you have the buy-in and trust of leadership and your end users to make it add value to the everyday or is it just noise on the screen and do you trust your data to provide the right learnings? And so when we think about AI readiness, we categorize it into three ways. Data preparedness, I think that’s a non-starter. Everyone’s aware data is going to be critical to the AI capability use case mapping, really understanding how you’re going to use the information and what you’re going to do with it. And then the executive buy-in. So moving your executives from acknowledgement, yeah, I know it’s out there, but I’m not sure what we would do with it to executive champions that would say, Hey, we’re doing this and this is what I expect to see as results.
(14:35):
And so when we think about readiness, we categorize it into today, preparedness, use case mapping and executive buy-in. You can certainly use readiness tools to support this. There’s the built-in Salesforce, Einstein readiness and estimated ROI capability, that’s in the setup menu for your instance. And then we also have the true summit solutions AI data readiness for standard and custom use cases, which is currently in beta. But what these don’t give you is they don’t personalize to your organization, what is the value? What is the dollars and cents we expect to receive as a result of this implementation as a result of this enablement? How do I get to that number?
(15:21):
So when we think about the value definitions, I like to think about things in terms of high value tasks versus low value tasks. Where am I spending my mental energy? A good example of this is I could either vacuum the living room or have the room do it. I’ll have the Roomba do it so I can do something else. I am kind of partitioning off my low value tasks to technology so that I can focus on high value tasks like making zucchini crisp. So there are some interesting things there in terms of how you define value, but to make it a little bit more real, let’s do an example exercise of the different phases I would see in terms of value add. So we think about the baseline. Baseline is your starting point. It’s a fixed reference point. It’s the most simple way that you could do things.
(16:26):
So when I think about our CRM journey, your baseline would be a Rolodex. Now, I don’t know if anyone uses Rolodexes anymore, probably not. Let’s say Excel or an Outlook contact list. That’s how I’m managing my prospects. And the way that I have to manage them is I have to go in, I have to add data, I have to track information. I have very limited time for the high value task, which is meeting with them, building relationships, really kind of thinking about what’s the next step? How do I become that trusted product, that trusted advisor. I don’t have a lot of time with that. But then we think about the next level up, standardizing, driving consistency. How do I drive consistency as it relates to customer data, prospect data, CRM. So I implemented CRM, I’m driving consistency, everything’s going into the same place. I’m able to report on that now I’m free up a little bit more of my mental energy to do other things, build those relationships, think about the next deal, think about how I’m positioning things, and then we go to the next level, right?
(17:39):
Fit and improve rationalize. So thinking not only about the CRM and entering information in, but how do I enter the most important information and am I prompted for that? How do I precisely capture data that’s ultimately going to help me build that relationship with my prospect better? So this is where we come in with configuration and precise data capture validation rules, and then we start to think about innovation. So how do I go beyond just the baseline, the standardization and rationalization of the data that I’m capturing to innovating with that data? This is where I might use automated workflows and quick actions. It helps me identify what’s the next step that I need to take in a matter fashion. Now I’m having to tell the system how to do all of that and what to expect, and I’m standardizing it and driving consistency, but I’m still having to program that in.
(18:39):
But then we think about that next layer, right? Challenging, disrupting, disrupting the current state of what I do and thinking about things differently. This is where AI capabilities come into our insights, our predictions, our prescriptive actions. It not only helps me with these low value tasks, it’s freeing me up to really start to disrupt my processes. Are my relationships built in the right way? Am I getting the most from those? Are there other things that I should be focusing on in those conversations beyond what I am today? It allows me to become a disruptor in the marketplace versus just someone who’s riding the tide. And so when we think about value definitions, we think about how do we start to have a specific and standard use case around it using this high value and low value task measurement.
(19:44):
So when we think about the AI tools and the value exercise, if you are with us in our last session, you might see that we did a starting point. So we did this with our emails. We had a starting point where it was emails, email templates, data-driven email templates, email automation and triggers, and then Einstein copilot, and then we did actions to dollars. So then we said, okay, an email, just a standard email takes me about $10 to write, takes a sales person about $10 to write 10 minutes. Email template is $7. So I’m saving $3 from the baseline data-driven email templates, $5, saving $5 from the baseline email automation triggers $2. Now I’m saving $8. Now I’m getting a lot of money here. And then Einstein copilot right now we’re down to pennies versus dollars. I’m saving $10 overall that same email. And if I aggregate that for one email per 100 people, salespeople, I’m at a thousand dollars.
(20:52):
This is taking what we just did with a value exercise and connecting dollars with it, but it’s not just about dollars, it’s also about the cost of inaction. We are in a time where if we stand still, we are already behind. And so we think about things like, if I don’t do this, if I don’t invest in email templates, what’s going to happen? Well, I’m not going to have the ability to grow if I don’t do data-driven email templates, what could happen? Well, I might have some turnover in terms of my employees because they’re trying to make it up as they go and they’re not getting that support that they’re expecting from the organization. If I don’t do email automation and triggers, what’s going to happen? Well, I might have an increased attrition by my customers because now I haven’t been able to personalize these emails and it feels very automated to me as the end user.
(21:54):
And then if I don’t use Einstein copilot, what’s going to happen? Well, I have, based on all of these, I have a decrease in the ability to get to net new expansion. Either that’s through expansion of my current product set or services that I’m offering or the ability to expand in new ways that I haven’t had the mental energy to think about because I’m stuck down here in this level. So not only do we think about dollars, but we think about the cost of inaction. But the question that you should ask me next is what does that all mean? How do I tie that together in an executive summary that gains buy-in from my leadership that this is what we need to work on and this is why.
(22:43):
So now we’re going to go into an exercise around support. And again, this is a generalized exercise. I’ve put some numbers and values here. This is something that you can take and do with your own numbers and values as you go in whatever metrics are most important and critical to you. But when we think about support, I think about institutional memory. I dunno how many times I’ve been with clients where I say, okay, well when you onboard a new agent, how do they know what to do next when a customer calls in about this? Well, they don’t. You hope they learn it and you hope the people that know it because of institutional memory never go away. What that results in is you have a one-to-one support and it feels like groundhog Day every day at information. I’m trying to find it every single day unless I have a really good memory.
(23:42):
Again, very, very low opportunity for any high value tasks at that point. Okay, well, my next level might be Word doc faq. So I’ve seen this go, let’s put everything in Word or SharePoint or some or other document library, and that’s better. You still have that one-on-one support. It’s consistent dish, right? It depends on the person to find the right information in the word doc and use it in the right way. But you’re freeing up a little bit because no longer hunting and pecking for information in multiple systems. I’m only doing it in one at this point. But then there’s the introduction of knowledge, right? Knowledge within Salesforce, it’s at this point, I could do one to many, right? Not just one-to-one support, but maybe I have knowledge in a customer portal that provides some case deflection or some self-service and I have consistent support with that knowledge.
(24:40):
Everything’s formatted nicely for me. I have most likely email templates that can draw that knowledge in, and I’m able to send that information out appropriately. So now I’m one to many consistent support. I have more mental energy to really focus on my customer support relationships, deliver that kind of best practice capability. All good to go. But what if you did recommend knowledge? So instead of an agent having to go in and say, I’m going to keyword search on my knowledge articles to get to the right place and use some time there, I’m able to recommend that. So I’m in a one to many situation. I have consistent support across multiple channels, and I’m initiating case deflection with that recommended knowledge. So again, freeing up our agents for more high value tests. And then when we go to that next layer, right? Einstein for service one plus to many, right? So you might have one agent that can manage multiple chats or the chat bots are managing that on their behalf and it’s only getting to them when needed. And it’s consistent and more intelligence support across multiple challenges channels. And you have advanced case deflection. And the beauty of this is the personalization of the support process, leveraging the same sentiments that you’re receiving from your support cases, understanding conversation insights, and really starting to reflect back to the customer what they’re wanting here versus what you want to tell them in terms of that support.
Speaker 1 (26:20):
And I really love the opportunity for the bi-directional data collection at that point and the building out of a more holistic customer profile because we’re now, when we think about everything from three down, four down, really it’s still a one way. It’s still, yes, here’s your question, let us give the answer to you or your need or whatever. I love the bi-directional. I love the ability to continue to capitalize on that profile building for further personalization, further conversation, further expansion, upselling throw your word in there. So I love that.
Speaker 2 (27:05):
That’s awesome. That’s exactly right. Getting to the point where you can have a personal relationship that feels authentic to your customers and not contrived, and that’s where the high value test having that ability really comes into play. So when we think about support, let’s put some dollars to it. Let’s do a dollars exercise. So I’m going to do parameters. My agent salary is for $2,000. I’ve estimated it to about 33 cents per minute and my CRC, my customer retention cost is $700 a year. Customer retention costs for those who might not be familiar with this is really about how much are the salaries and the benefits and the costs of tools and software, customer loyalty programs, all the things that you do to retain your customer versus how many customers are retained.
(28:03):
So let’s talk about it institutional memory. So if I’m using institutional memory, I’m spending about $10 per case. It’s taking me about 30 minutes on average. Maybe it’ll take me a little less time if I have a very good memory. So that’s our baseline, the word doc, FAQ. Let’s say I shave off about nine minutes because I know to go to the word doc, but I still need a search in it. I still need to format my response, personalize it. So I’m saving about $3, but still cost me about $7 per case. And then knowledge, now I’ve cut my down time by seven minutes, I’m saving about $5. I’m able to have it built into the system, right? I’m not reformatting the solution. I can actually just use it and send it. Then we think about things like recommended knowledge, okay? Now at this point, we’re using tools and technology and the constructs we’ve built into the system to recommend knowledge.
(29:03):
And now at this point, I’m able on average to close out a case in six minutes savings of $8. There are people on this call that are like, that’s ridiculous. That will never get to you. Or Hey, we can close out in one minute. There are going to be variances for your use case. This is really just more of a framework of how to get to that amount. And then when we think about Einstein for service, let’s assume two minutes per case at that point, that’s reviewing the information, validating that the response was correct and closing out the case 60 cents. Now we’re at a savings of $9 and 40 cents, which is an aggregate savings of a hundred cases of $940. Again, that’s for one case across 100 cases. That might be exponentially increased depending on the size of your organization and size of the support cases that are coming in.
(30:04):
A couple of things to be aware of as we’re thinking about these dollar values is not just the case support time, right? Time to resolution, it’s things like other savings, case deflection costs. What does that look like? The ability to serve your customer in multi-channels. What does that cost efficiency, the customer satisfaction and retention? Are you able to increase your overall retention and your customer satisfaction? Those might be things that are more qualitative versus quantitative, but I would argue you can absolutely put those to dollars as well. First time resolution and then agent capacity. So if I’m able to get my cases down to two minutes on average, what does that do for my agents in terms of the capacity that they can take on? What would I need to do in terms of continued growth? If I were to grow as an organization, continue to expand my number of cases, but not do anything to make my case handling more efficient, how many more individuals would I need to add in from a staffing line perspective in order to manage to that? And so while you’re seeing just a TTR dollar figure right here, there’s so many more ways that you can slice and cut this data for that additional dollar value that you’re looking for.
Speaker 1 (31:37):
I would argue too, and it’s not an argument, I would add as well, but I think that there’s this softer intangible value, which you mentioned on the previous slide of being an organization that is a thought leader at more of a bleeding edge of adoption of the AI tools. There’s an employee morale benefit to what I’m working smarter, not harder. I think that there’s some of these intangibles externally and internally that also, while they are harder to put that dollar amount to, they are extraordinarily beneficial to an organization. So I think you’ve got to think about that as well.
Speaker 2 (32:16):
100%. I think absolutely. There’s the intangibles, there’s, if you’re a technology company specifically, and you’re still in the institutional memory and word doc, FAQ, stage of life for customer support, that’s going to say something to your organization. And so you have to start to think about how do I, to your point, Becky, enable products and solutions that are of that cutting edge so that my team feels like, Hey, we are set up for success as the time proceeds forward because the speed of change at this point is so dramatic. We want to make sure that you’re not standing still. And that is actually a really good segue into my cost of inaction. So we’re not only looking at this as dollars and hours, but we’re also thinking about the cost of inaction. So when we think about if I were to not move from institutional memory to Word doc FAQs, I’m probably going to have an increase in team turnover.
(33:19):
People who join my organization and are like, no thank you in terms of trying to remember things, knowledge, if I’m not implementing knowledge, am I increasing our, decreasing my case handling efficiency, I’m decreasing it, recommended knowledge, I have a decrease in customer retention potential. And then Einstein for service by not doing any of that. If you’re not doing Einstein at this point, your per case cost is incrementally increasing every time. If you stand still in this world, you are going to be continuing to be left behind and get further and further behind. And so that’s something that we talk about a lot with our prospects and our clients and our customers and our team is it’s hard to always be on that bleeding edge. Of course it is, right? There’s a lot of organizations that are behemoths and are still on legacy applications, tools, and software, a hundred percent understood.
(34:26):
But if you are using Salesforce as a platform and you have the capability of enabling this, you are already behind if you’re not doing it. And so when we think about, Hey, we’ve done the value exercise, we’ve got the dollars, we’ve got the cost of an action, how do I compile this in a way that is compelling and something that is palatable and within reach for my executive team to really understand? And so what we put together is an executive summary snapshot. So taking those figures and knowing that, of course you’ll want to do that exercise multiple times over depending on the different capabilities that you plan on implementing. It could be any of these capabilities for support for Einstein. But if we think about the current KPIs as an executive, I would want to know where’s my starting point? What are we talking about here?
(35:24):
This is where we start to put in those parameters, our agent’s salary, our customer retention costs, our current TTR, our total cases last year, case deflection, currently percent case, first time resolution, 57%. That gives me some insight into what’s my starting point, where are we today? And then we want to go into future year projections. So tying back to your growth initiatives and your strategic objectives as an organization, what are we expecting in terms of year over year growth? And it might be, I have customer here, but it might be something else for you in terms of those future year projections. And then with my customer year over year growth of 10%, I anticipate that we will have a year over year growth of 20% case increase. And then we go into the dollars. And again, this is going to change for your particular use case, but what we wanted to surface up are these are the critical things to think about in terms of dollars or costs and what you would think from a projected savings perspective or what you would anticipate from a projected savings perspective.
(36:37):
So there might be some software class depending on what you’re trying to enable or implement, there might be an implementation cost if you’re using a partner or what your internal team might need to do in order to enable and set this up. There’s the internal rollout cost. So this isn’t just your admin team turning it on and then saying, okay, it’s on now it’s the change management, it’s the communications, it’s the measuring, right? So thinking about how am I rolling this out that is effective and also is advisory and saying, okay, we need our managers and our leaders to make sure that our teams are using this information in the right way, and that it’s not just noise on a screen. And then what does that ongoing support look like for you, whether that be external or internal to you. Thinking about these numbers helps set the stage of, Hey, I’ve thought about this.
(37:33):
I’ve thought about what this might take from an organizational perspective, but here’s what we expect to see a negative TTR, right? I’m going to go down from 30 minutes to case to six minutes case deflection. This is what I want to increase. Case deflection by 10% is what we expect. And the case first time resolution from 57% to 63%, or maybe 80% depending on where you are making those details available and front facing, based on the exercise that you did, you should be able to get there based on what we just went through in terms of what’s anticipated. And then you want to do a projected savings. And what I’ve got here is a three year projected savings. Again, with all technology, there’s going to be learning curves, there’s going to be right sizing, ongoing support, and not seeing that big, big bang initially, but year two and year three.
(38:38):
So that’s one way to cut the data and provide that information. The other way to cut that data is if we did none of this, right? So if we spent none of this, what would we expect to see in TTR? Would TTR go up? Would it go down? Would it maintain the same thing for case deflection and case FTR? And then projected savings year one, two, and three, and this will go into negative numbers. So if these continue to go up, there’s cost associated with it. So it’s either you spend the money doing this and save or you do nothing and your costs increase year over year. Either way, you slice it at some point there’s going to be a reckoning of that investment. So when we think, oh, go ahead, Peggy.
Speaker 1 (39:30):
Oh, I was just going to, and you keep going, I’ll interrupt in a second. You’re good. Continue.
Speaker 2 (39:34):
So back to where we started. And so when we think about our starting point, what is it that we’re trying to accomplish? What are the actions to dollars and what’s the cost of inaction? And then the result is the executive summary. What do I expect to see? And then you use this as your blueprint for implementation and well as the ability to measure and continue to measure it as you go. So I’ll pause there. Becky, is there anything? Yep, go ahead.
Speaker 1 (40:04):
No, we don’t have any questions or comments yet in the chat on LinkedIn, but I do encourage anyone that has something to add, please do so. I am monitoring that. I also wanted to call attention to the lower third of the screen. If you’d like the frameworks to the executive summary framework or the value exercise framework, we can send those to you directly. Feel free to drop me an email. My full email is on the lower third of the screen, and I can get you those framework templates that you can use for your own organization, customize and modify, so those are available to you as well. That’s all I wanted to say.
Speaker 2 (40:46):
Well, thanks so much as we went through. That’s the end of our show today. Just to recap, definition of stance, talked about the AI journey readiness indicators and went through the value exercise next time, because this is a three part series, we’ll talk about activating Salesforce ai. So we’ll do a demo, a tale of two instances, and is it working? So let’s say, let’s fast forward. We did all the upfront work, we’ve enabled it, we’ve got it up and running. How do we tell is it working?
Speaker 1 (41:21):
I love that. And then of course too, I have the QR code up on the screen for beta access to our AI readiness tool. So if you are interested in getting access to the beta version of that tool, you can scan that QR code and give me, I think just your name and email and we will make sure that you are in that beta cohort. And then we also have an AI adoption playbook, which I am putting that QR code on the screen right now. And again, you can download directly from that QR code. Instant access, no gating on that content because who likes to have gated content these days? Really nobody. So it’s a whole other webinar though. This was fantastic. If you have any questions or comments, you can find us via choose summit solutions.com and stay tuned for the next session. We’ll do that in a couple of weeks. Thanks so much. Thanks, Danielle. Take care. Bye-Bye.
Ready to tackle Salesforce AI? Our team is here for you! You know where to find TruSummit Solutions.
Featured Articles
Getting to Know Salesforce AI: Mapping Value from Salesforce AI
In a 2023 Salesforce survey of Sales and Service users, half of all respondents indicate that they “don’t know how…
The AI Adoption Playbook
There is no avoiding the rise of AI, but the rapid arrival of all things AI-enhanced or AI-driven has left…
Getting to Know Salesforce AI: Assessing Your Readiness
2024 is the year AI at work gets real. According to LinkedIn‘s Work Trend Index on the State of AI,…