00:00:00Can Customers Trust AI Answers
00:01:23The Trust Gap And New Data
00:02:30When AI Agents Replace Service Calls
00:03:37Authenticity Means Disclosing AI Use
00:06:37Three Trust Questions To Audit Now
00:11:10Planning For 2027 And Next Steps
ABOUT THIS EPISODE
Your AI just answered a customer. Now ask the uncomfortable question: do they trust it, and do they trust you more or less because of it? We dig into why trust is becoming the defining customer experience metric as automation spreads across chat, contact centers, and self-service. The data is sobering: many leaders believe customers highly trust their brand, while far fewer consumers agree, and that gap is poised to grow as AI gets embedded into everyday service.
We unpack what’s driving the trust slide, including why customers feel more loyal when real people stay visible in the journey and why authenticity matters more than ever. We talk through a practical approach to AI disclosure: when you can treat AI as an internal assist for human agents, and when transparency is non-negotiable because it could feel like impersonation. We also broaden the lens beyond chatbots to AI avatars and video, where the line between real and synthetic can get blurry fast.
Then we get tactical with three questions you can apply to your CX and 2027 planning. Subscribe, share with your team, and leave a review so more CX leaders can build trust before it turns into a crisis.
Resources Mentioned:
Order your copy of Experience Is Everything -- http://experienceiseverythingbook.com
Learn more about CXI Membership™ and apply -- http://CXIMembership.com
Get more resources -- https://experienceinvestigators.com
Want to ask a question? Visit askjeannie.vip to leave Jeannie a voicemail! (And don't forget to follow Jeannie Walters, CCXP, CSP on LinkedIn!)
English
United States
SHOW NOTES 🔗
TRANSCRIPT 🔗
WEBVTT
00:00:00.320 --> 00:00:02.399
Your AI just answered a customer.
00:00:02.399 --> 00:00:05.200
Do you know if they did it correctly?
00:00:05.200 --> 00:00:08.400
Do you know if they made a mistake?
00:00:08.400 --> 00:00:13.599
And more importantly, how does your customer know to trust it?
00:00:13.599 --> 00:00:25.039
If it's wrong, will your customer trust your brand in the future?
00:00:25.039 --> 00:00:31.519
In this world that we're living in, we need to build and earn trust across the board.
00:00:31.519 --> 00:00:36.079
But it's not as easy as just being accurate and consistent.
00:00:36.079 --> 00:00:45.840
We need to make sure that we're living up to it in our messaging, in the way that we interact with customers, in the way that we're building our processes for the future.
00:00:45.840 --> 00:00:55.439
We've talked about the leadership gap before when we discover how many executives and leaders believe they're delivering great customer experiences.
00:00:55.439 --> 00:00:58.960
But when you ask their customers, they don't all think that way.
00:00:58.960 --> 00:01:02.320
Well, we have the same thing happening with trust.
00:01:02.320 --> 00:01:13.280
90% of executives believe that their customers highly trust their brands, but only 30% of consumers actually agree with that.
00:01:13.280 --> 00:01:18.480
Now, that is a gap, and it's one that's going to expand.
00:01:18.480 --> 00:01:23.439
We are in a world where we can't always trust what we see or what we understand.
00:01:23.439 --> 00:01:29.760
Answer Connect recently released an AI Customer Service Attitudes report.
00:01:29.760 --> 00:01:34.000
And 57% of consumers now trust brands less.
00:01:34.000 --> 00:01:36.000
Now, this is a big jump.
00:01:36.000 --> 00:01:39.599
It's up from 53% a year earlier.
00:01:39.599 --> 00:01:42.640
I believe that number will keep growing.
00:01:42.640 --> 00:01:51.040
73% of consumers say they feel more loyalty toward companies that use real people in service interactions, up from 69%.
00:01:51.040 --> 00:01:54.799
Now, does this mean we're going to stop using AI?
00:01:54.799 --> 00:01:55.760
Absolutely not.
00:01:55.760 --> 00:02:03.439
We're going to live in a world where customers have AI agents who are dealing directly with the brands that they interact with.
00:02:03.439 --> 00:02:18.319
In just a few years, the predictions are saying that traditional customer service calls, the ones that we know, the ones that mean customers are calling in to get some information or resolve an issue, those are going to go away.
00:02:18.319 --> 00:02:25.199
There's no reason an agent will have to call on the telephone to get another agent.
00:02:25.199 --> 00:02:29.599
That will all be happening behind the scenes almost constantly.
00:02:29.599 --> 00:02:41.840
So if we are building trust today for the future, we have to make sure that our brands are representing that level of trust every step of the journey.
00:02:41.840 --> 00:02:49.360
If 70% of our customers are saying, we're not sure if we trust you, that's a big wake-up call.
00:02:49.360 --> 00:02:55.280
We have to make sure that we are reassuring customers along the way.
00:02:55.280 --> 00:03:08.080
Now that switch between humans picking up the phone and calling versus AI agents really handling all parts of the transaction, it's not here today, but it's coming pretty quickly.
00:03:08.080 --> 00:03:19.680
In the meantime, we can leverage this data to tell us that we need some real people involved to reassure customers, even when things are automated.
00:03:19.680 --> 00:03:34.479
Once we build that trust that yes, this automation works, that yes, you're going to get the right information, that yes, you can actually trust our brand, then we won't need as much reassurance for our customers.
00:03:34.479 --> 00:03:37.039
But it's an important question to think about right now.
00:03:37.039 --> 00:03:40.960
Where in the journey should we be reassuring our customers?
00:03:40.960 --> 00:03:43.280
So, right now, today, what can you do?
00:03:43.280 --> 00:03:48.240
Well, the number one thing people talk about is that they want brands to be authentic.
00:03:48.240 --> 00:03:52.159
They want to know when they're actually dealing with AI.
00:03:52.159 --> 00:04:00.560
If you are not disclosing that information to your customers today, you are missing an opportunity to actually build trust.
00:04:00.560 --> 00:04:09.840
More than half of consumers say they'd stop buying from a brand entirely after one inauthentic experience.
00:04:09.840 --> 00:04:12.400
A third would leave a negative review.
00:04:12.400 --> 00:04:17.519
That's from Emplifi and Alchemer from April of this year, 2026.
00:04:17.519 --> 00:04:31.439
If we know that people are on the lookout for how they don't trust us, we have to really over-index on being proactive about how they can.
00:04:31.439 --> 00:04:35.279
And that includes disclosing when AI is involved.
00:04:35.279 --> 00:04:38.160
So when and how should you disclose?
00:04:38.160 --> 00:05:09.360
Well, one way to think about it is that if you are using AI to support your team and they're interacting with real people in your contact center through your customer service, uh chats, things like that, I think it's perfectly fine for those conversations to not necessarily have a label about disclosure because there's still that person using critical thought, understanding, okay, even if AI serves up the information to use, they might second guess it.
00:05:09.360 --> 00:05:16.079
They have the agency to say, you know what, we're not going to do it this way, we're going to do it this other way.
00:05:16.079 --> 00:05:22.000
So if that's the case, it doesn't mean disclosing every minute of every day.
00:05:22.000 --> 00:05:30.720
But if you are using AI in a way that could be interpreted as impersonation, I would highly recommend you disclose that.
00:05:30.720 --> 00:05:46.800
Now, most people are getting used to these ideas of the named chatbots that we have, the named agents that we use maybe in our personal life through ChatGPT or Gemini or Copilot or Claude, all those things.
00:05:46.800 --> 00:05:54.000
People are getting more experience with this, which means they're getting savvier about identifying when it's used and when it's not.
00:05:54.000 --> 00:06:00.480
But we know that we are really on the precipice of a possible trust crisis.
00:06:00.480 --> 00:06:07.600
And so if you want to be proactive about that, get authentic right now, today.
00:06:07.600 --> 00:06:20.160
That also means training your people to understand when and how they should disclose and how to best use AI along with their own critical thought.
00:06:20.160 --> 00:06:30.240
And that sometimes means making sure the people that we're empowering to use it have different training, different guardrails, different governance around it.
00:06:30.240 --> 00:06:36.560
All of that will help us continue to build trust with our customers, our employees, and our brand.
00:06:36.560 --> 00:06:38.879
So a quick three questions for you.
00:06:38.879 --> 00:06:43.680
Number one, does your customer know who they're talking to?
00:06:43.680 --> 00:06:44.959
This is the big one.
00:06:44.959 --> 00:06:48.160
This is what people say breaks trust very quickly.
00:06:48.160 --> 00:06:57.680
If they believe they're talking to a live person, but they're actually talking to an AI agent, that can feel very deceptive.
00:06:57.680 --> 00:07:02.000
That's a great way to break trust quickly.
00:07:02.000 --> 00:07:14.800
So audit all of your touch points, your AI touch points, and consider could this be really interpreted in a way that is inauthentic or is even feeling like impersonation.
00:07:14.800 --> 00:07:18.879
We want to make sure that people know exactly who they're talking to.
00:07:18.879 --> 00:07:21.439
Now, this is true with video as well these days.
00:07:21.439 --> 00:07:24.639
There are some amazing AI avatars out there.
00:07:24.639 --> 00:07:29.519
They do a great job of scaling information and training.
00:07:29.519 --> 00:07:36.959
But if people are watching something that they think is a real person and it's actually an AI avatar, it's important to disclose that as well.
00:07:36.959 --> 00:07:41.439
Number two, what happens when the AI agent gets it wrong?
00:07:41.439 --> 00:07:42.959
Do you have guardrails?
00:07:42.959 --> 00:07:44.240
Are you auditing?
00:07:44.240 --> 00:07:54.319
Are there practical steps in place to make sure that you are not just looking at something like resolution rate as the end all?
00:07:54.319 --> 00:08:00.480
We have to make sure that we are looking at the quality and not just the quantity of resolutions.
00:08:00.480 --> 00:08:08.720
That requires human oversight, human in the loop, all of those things because AI is not going to be right 100% of the time.
00:08:08.720 --> 00:08:10.480
We know that well by now.
00:08:10.480 --> 00:08:12.720
Not only that, but things change.
00:08:12.720 --> 00:08:20.079
And if we don't have the right data going into these models, then the right data won't be coming out.
00:08:20.079 --> 00:08:22.000
We have to stay on top of that.
00:08:22.000 --> 00:08:30.160
Also, are we training and empowering the people who hear about those mistakes, who discover when things aren't as accurate as they should be?
00:08:30.160 --> 00:08:36.480
Do they have a way to communicate within the organization to say this is not working the way we think it is?
00:08:36.480 --> 00:08:47.759
I've seen a lot of frontline folks, people like cashiers, salespeople, contact center agents, who have no way of sharing when they discover something like that.
00:08:47.759 --> 00:08:59.120
If nothing else, ask yourself where in the customer's journey would a frontline customer-facing person get some information about what's working.
00:08:59.120 --> 00:09:01.039
What should they do about it?
00:09:01.039 --> 00:09:02.639
Where can they report that?
00:09:02.639 --> 00:09:05.200
How can they make sure actions are being taken?
00:09:05.200 --> 00:09:11.440
How can we close the loop, not only with the customer, but also with the person who's sharing those issues?
00:09:11.440 --> 00:09:15.360
And this final one is tricky, but I would ask: are you measuring trust?
00:09:15.360 --> 00:09:18.000
Are you really looking for ways to build trust?
00:09:18.000 --> 00:09:23.840
Trust shows up in a lot of different behaviors based on your organization and your industry.
00:09:23.840 --> 00:09:30.799
It can show up in renewal rates, it can show up in repeat visits, it can show up in user reviews.
00:09:30.799 --> 00:09:37.600
So we need to look at the behaviors that are also attached to customer trust.
00:09:37.600 --> 00:09:42.559
And if we see things changing, we need to address why they're changing.
00:09:42.559 --> 00:09:44.559
Why is trust decreasing?
00:09:44.559 --> 00:09:56.240
Is something going awry within the journey that maybe we've said it and forget it and we aren't doing our due diligence around audits and making sure that things are working the way we think they are.
00:09:56.240 --> 00:09:57.600
Trust is a big one.
00:09:57.600 --> 00:10:01.679
I think we're in an age where trust has a big capital T.
00:10:01.679 --> 00:10:04.960
We need to build it with every step along the journey.
00:10:04.960 --> 00:10:10.000
That's with our actions, our behaviors, our words, everything.
00:10:10.000 --> 00:10:20.480
And that means we have to make sure that the AI and automations that we're releasing into the journey have guardrails around them so that we continue to build trust.
00:10:20.480 --> 00:10:26.320
If nothing else, ask yourself: is this authentic to the customer?
00:10:26.320 --> 00:10:30.399
And authentic simply means I know who I'm talking to.
00:10:30.399 --> 00:10:36.320
I can trust that my issue will be resolved in a way that I'm expecting from your brand.
00:10:36.320 --> 00:10:43.279
So go out there, look around, make sure that you're showing up as you want your brand represented.
00:10:43.279 --> 00:10:48.320
Because right now, customers are looking for ways not to trust you.
00:10:48.320 --> 00:10:54.240
And it's very easy on the inside of organizations to assume, well, we're doing just fine.
00:10:54.240 --> 00:10:55.919
Everybody trusts us.
00:10:55.919 --> 00:10:57.840
But this is a big one, folks.
00:10:57.840 --> 00:11:09.200
I encourage you to really think about it, apply it to your 2027 planning, apply it to how you measure success, and keep fighting the good fight on behalf of your customers.
00:11:09.200 --> 00:11:10.480
Thanks for being here.
00:11:10.480 --> 00:11:14.000
Don't forget, you can always leave me a message, askjeannie.vip, with either comments or questions.
00:11:14.000 --> 00:11:28.799
And if you love this podcast or this particular episode struck a chord with you, please share it with the people that you think need to hear it. And we love your ratings and reviews.
00:11:28.799 --> 00:11:33.440
That helps other people find this podcast because experience is everything.
00:11:33.440 --> 00:11:34.799
And we're glad you're here.
00:11:34.799 --> 00:11:35.440
Thanks.
00:11:35.440 --> 00:11:36.480
See you next time.
00:11:36.480 --> 00:11:46.879
If you're ready to turn insights into action, join CXI Membership, our community for customer experience investigators just like you.
00:11:46.879 --> 00:11:53.519
Get the tools, support, and inspiration to move from ideas to true impact.
00:11:53.519 --> 00:12:00.879
And don't miss my book, Experience is Everything: Making Every Moment Count in the Age of Customer Expectations.
00:12:00.879 --> 00:12:03.039
A USA Today bestseller.
00:12:03.039 --> 00:12:09.840
And if you enjoyed the show, please subscribe, share with your team, and leave a quick review to help others find us.
00:12:09.840 --> 00:12:16.080
Until next time, keep asking questions, keep improving, and keep leading with experience.
00:00:00.320 --> 00:00:02.399
Your AI just answered a customer.
00:00:02.399 --> 00:00:05.200
Do you know if they did it correctly?
00:00:05.200 --> 00:00:08.400
Do you know if they made a mistake?
00:00:08.400 --> 00:00:13.599
And more importantly, how does your customer know to trust it?
00:00:13.599 --> 00:00:25.039
If it's wrong, will your customer trust your brand in the future?
00:00:25.039 --> 00:00:31.519
In this world that we're living in, we need to build and earn trust across the board.
00:00:31.519 --> 00:00:36.079
But it's not as easy as just being accurate and consistent.
00:00:36.079 --> 00:00:45.840
We need to make sure that we're living up to it in our messaging, in the way that we interact with customers, in the way that we're building our processes for the future.
00:00:45.840 --> 00:00:55.439
We've talked about the leadership gap before when we discover how many executives and leaders believe they're delivering great customer experiences.
00:00:55.439 --> 00:00:58.960
But when you ask their customers, they don't all think that way.
00:00:58.960 --> 00:01:02.320
Well, we have the same thing happening with trust.
00:01:02.320 --> 00:01:13.280
90% of executives believe that their customers highly trust their brands, but only 30% of consumers actually agree with that.
00:01:13.280 --> 00:01:18.480
Now, that is a gap, and it's one that's going to expand.
00:01:18.480 --> 00:01:23.439
We are in a world where we can't always trust what we see or what we understand.
00:01:23.439 --> 00:01:29.760
Answer Connect recently released an AI Customer Service Attitudes report.
00:01:29.760 --> 00:01:34.000
And 57% of consumers now trust brands less.
00:01:34.000 --> 00:01:36.000
Now, this is a big jump.
00:01:36.000 --> 00:01:39.599
It's up from 53% a year earlier.
00:01:39.599 --> 00:01:42.640
I believe that number will keep growing.
00:01:42.640 --> 00:01:51.040
73% of consumers say they feel more loyalty toward companies that use real people in service interactions, up from 69%.
00:01:51.040 --> 00:01:54.799
Now, does this mean we're going to stop using AI?
00:01:54.799 --> 00:01:55.760
Absolutely not.
00:01:55.760 --> 00:02:03.439
We're going to live in a world where customers have AI agents who are dealing directly with the brands that they interact with.
00:02:03.439 --> 00:02:18.319
In just a few years, the predictions are saying that traditional customer service calls, the ones that we know, the ones that mean customers are calling in to get some information or resolve an issue, those are going to go away.
00:02:18.319 --> 00:02:25.199
There's no reason an agent will have to call on the telephone to get another agent.
00:02:25.199 --> 00:02:29.599
That will all be happening behind the scenes almost constantly.
00:02:29.599 --> 00:02:41.840
So if we are building trust today for the future, we have to make sure that our brands are representing that level of trust every step of the journey.
00:02:41.840 --> 00:02:49.360
If 70% of our customers are saying, we're not sure if we trust you, that's a big wake-up call.
00:02:49.360 --> 00:02:55.280
We have to make sure that we are reassuring customers along the way.
00:02:55.280 --> 00:03:08.080
Now that switch between humans picking up the phone and calling versus AI agents really handling all parts of the transaction, it's not here today, but it's coming pretty quickly.
00:03:08.080 --> 00:03:19.680
In the meantime, we can leverage this data to tell us that we need some real people involved to reassure customers, even when things are automated.
00:03:19.680 --> 00:03:34.479
Once we build that trust that yes, this automation works, that yes, you're going to get the right information, that yes, you can actually trust our brand, then we won't need as much reassurance for our customers.
00:03:34.479 --> 00:03:37.039
But it's an important question to think about right now.
00:03:37.039 --> 00:03:40.960
Where in the journey should we be reassuring our customers?
00:03:40.960 --> 00:03:43.280
So, right now, today, what can you do?
00:03:43.280 --> 00:03:48.240
Well, the number one thing people talk about is that they want brands to be authentic.
00:03:48.240 --> 00:03:52.159
They want to know when they're actually dealing with AI.
00:03:52.159 --> 00:04:00.560
If you are not disclosing that information to your customers today, you are missing an opportunity to actually build trust.
00:04:00.560 --> 00:04:09.840
More than half of consumers say they'd stop buying from a brand entirely after one inauthentic experience.
00:04:09.840 --> 00:04:12.400
A third would leave a negative review.
00:04:12.400 --> 00:04:17.519
That's from Emplifi and Alchemer from April of this year, 2026.
00:04:17.519 --> 00:04:31.439
If we know that people are on the lookout for how they don't trust us, we have to really over-index on being proactive about how they can.
00:04:31.439 --> 00:04:35.279
And that includes disclosing when AI is involved.
00:04:35.279 --> 00:04:38.160
So when and how should you disclose?
00:04:38.160 --> 00:05:09.360
Well, one way to think about it is that if you are using AI to support your team and they're interacting with real people in your contact center through your customer service, uh chats, things like that, I think it's perfectly fine for those conversations to not necessarily have a label about disclosure because there's still that person using critical thought, understanding, okay, even if AI serves up the information to use, they might second guess it.
00:05:09.360 --> 00:05:16.079
They have the agency to say, you know what, we're not going to do it this way, we're going to do it this other way.
00:05:16.079 --> 00:05:22.000
So if that's the case, it doesn't mean disclosing every minute of every day.
00:05:22.000 --> 00:05:30.720
But if you are using AI in a way that could be interpreted as impersonation, I would highly recommend you disclose that.
00:05:30.720 --> 00:05:46.800
Now, most people are getting used to these ideas of the named chatbots that we have, the named agents that we use maybe in our personal life through ChatGPT or Gemini or Copilot or Claude, all those things.
00:05:46.800 --> 00:05:54.000
People are getting more experience with this, which means they're getting savvier about identifying when it's used and when it's not.
00:05:54.000 --> 00:06:00.480
But we know that we are really on the precipice of a possible trust crisis.
00:06:00.480 --> 00:06:07.600
And so if you want to be proactive about that, get authentic right now, today.
00:06:07.600 --> 00:06:20.160
That also means training your people to understand when and how they should disclose and how to best use AI along with their own critical thought.
00:06:20.160 --> 00:06:30.240
And that sometimes means making sure the people that we're empowering to use it have different training, different guardrails, different governance around it.
00:06:30.240 --> 00:06:36.560
All of that will help us continue to build trust with our customers, our employees, and our brand.
00:06:36.560 --> 00:06:38.879
So a quick three questions for you.
00:06:38.879 --> 00:06:43.680
Number one, does your customer know who they're talking to?
00:06:43.680 --> 00:06:44.959
This is the big one.
00:06:44.959 --> 00:06:48.160
This is what people say breaks trust very quickly.
00:06:48.160 --> 00:06:57.680
If they believe they're talking to a live person, but they're actually talking to an AI agent, that can feel very deceptive.
00:06:57.680 --> 00:07:02.000
That's a great way to break trust quickly.
00:07:02.000 --> 00:07:14.800
So audit all of your touch points, your AI touch points, and consider could this be really interpreted in a way that is inauthentic or is even feeling like impersonation.
00:07:14.800 --> 00:07:18.879
We want to make sure that people know exactly who they're talking to.
00:07:18.879 --> 00:07:21.439
Now, this is true with video as well these days.
00:07:21.439 --> 00:07:24.639
There are some amazing AI avatars out there.
00:07:24.639 --> 00:07:29.519
They do a great job of scaling information and training.
00:07:29.519 --> 00:07:36.959
But if people are watching something that they think is a real person and it's actually an AI avatar, it's important to disclose that as well.
00:07:36.959 --> 00:07:41.439
Number two, what happens when the AI agent gets it wrong?
00:07:41.439 --> 00:07:42.959
Do you have guardrails?
00:07:42.959 --> 00:07:44.240
Are you auditing?
00:07:44.240 --> 00:07:54.319
Are there practical steps in place to make sure that you are not just looking at something like resolution rate as the end all?
00:07:54.319 --> 00:08:00.480
We have to make sure that we are looking at the quality and not just the quantity of resolutions.
00:08:00.480 --> 00:08:08.720
That requires human oversight, human in the loop, all of those things because AI is not going to be right 100% of the time.
00:08:08.720 --> 00:08:10.480
We know that well by now.
00:08:10.480 --> 00:08:12.720
Not only that, but things change.
00:08:12.720 --> 00:08:20.079
And if we don't have the right data going into these models, then the right data won't be coming out.
00:08:20.079 --> 00:08:22.000
We have to stay on top of that.
00:08:22.000 --> 00:08:30.160
Also, are we training and empowering the people who hear about those mistakes, who discover when things aren't as accurate as they should be?
00:08:30.160 --> 00:08:36.480
Do they have a way to communicate within the organization to say this is not working the way we think it is?
00:08:36.480 --> 00:08:47.759
I've seen a lot of frontline folks, people like cashiers, salespeople, contact center agents, who have no way of sharing when they discover something like that.
00:08:47.759 --> 00:08:59.120
If nothing else, ask yourself where in the customer's journey would a frontline customer-facing person get some information about what's working.
00:08:59.120 --> 00:09:01.039
What should they do about it?
00:09:01.039 --> 00:09:02.639
Where can they report that?
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How can they make sure actions are being taken?
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How can we close the loop, not only with the customer, but also with the person who's sharing those issues?
00:09:11.440 --> 00:09:15.360
And this final one is tricky, but I would ask: are you measuring trust?
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Are you really looking for ways to build trust?
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Trust shows up in a lot of different behaviors based on your organization and your industry.
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It can show up in renewal rates, it can show up in repeat visits, it can show up in user reviews.
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So we need to look at the behaviors that are also attached to customer trust.
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And if we see things changing, we need to address why they're changing.
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Why is trust decreasing?
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Is something going awry within the journey that maybe we've said it and forget it and we aren't doing our due diligence around audits and making sure that things are working the way we think they are.
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Trust is a big one.
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I think we're in an age where trust has a big capital T.
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We need to build it with every step along the journey.
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That's with our actions, our behaviors, our words, everything.
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And that means we have to make sure that the AI and automations that we're releasing into the journey have guardrails around them so that we continue to build trust.
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If nothing else, ask yourself: is this authentic to the customer?
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And authentic simply means I know who I'm talking to.
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I can trust that my issue will be resolved in a way that I'm expecting from your brand.
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So go out there, look around, make sure that you're showing up as you want your brand represented.
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Because right now, customers are looking for ways not to trust you.
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And it's very easy on the inside of organizations to assume, well, we're doing just fine.
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Everybody trusts us.
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But this is a big one, folks.
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I encourage you to really think about it, apply it to your 2027 planning, apply it to how you measure success, and keep fighting the good fight on behalf of your customers.
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Thanks for being here.
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Don't forget, you can always leave me a message, askjeannie.vip, with either comments or questions.
00:11:14.000 --> 00:11:28.799
And if you love this podcast or this particular episode struck a chord with you, please share it with the people that you think need to hear it. And we love your ratings and reviews.
00:11:28.799 --> 00:11:33.440
That helps other people find this podcast because experience is everything.
00:11:33.440 --> 00:11:34.799
And we're glad you're here.
00:11:34.799 --> 00:11:35.440
Thanks.
00:11:35.440 --> 00:11:36.480
See you next time.
00:11:36.480 --> 00:11:46.879
If you're ready to turn insights into action, join CXI Membership, our community for customer experience investigators just like you.
00:11:46.879 --> 00:11:53.519
Get the tools, support, and inspiration to move from ideas to true impact.
00:11:53.519 --> 00:12:00.879
And don't miss my book, Experience is Everything: Making Every Moment Count in the Age of Customer Expectations.
00:12:00.879 --> 00:12:03.039
A USA Today bestseller.
00:12:03.039 --> 00:12:09.840
And if you enjoyed the show, please subscribe, share with your team, and leave a quick review to help others find us.
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Until next time, keep asking questions, keep improving, and keep leading with experience.
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