Advanced Dashboard: ​Purpose-built AI tools that makes your job easier​

0:04
Hey, Ryan, thanks for joining today.

0:06
No problem.

0:06
Thanks, Rosie.

0:08
Yeah, so we’re here to we have a webinar today about Advanced Dashboard.

0:13
I do want to give folks, you know, a few minutes to settle in, join.

0:17
I know that first meeting, first minute of a webinar, you’re trying to do a million things.

0:22
So we’ll give everyone just a few seconds to hop on.

0:26
In the meantime, I know you and I are both here in Colorado.

0:31
We’re we have this webinar during, you know, winter and it has not felt like winter, has it?

0:37
Have you been skiing been up to the mountains a few times?

0:41
It’s obviously it’s a little bit of a light snow year.

0:43
So it’s been challenged, but you know, that’s nature’s some years you get dumped on some nights, some years you dump.

0:51
So I know it’s felt a little spring like in in recent weeks here.

0:56
So we’ll see.

0:57
Hopefully we get a few more storms and skiers.

1:01
Everybody coming to Colorado can go hit the mountains.

1:05
OK, Well, I think I think we’ve given everyone a few seconds to hop on, get settled in.

1:12
So let’s kick off again.

1:14
I want to thank you Ryan for joining and letting me pick your brain about Advanced Dashboard today.

1:20
Really, really fun conversation I think we’re going to have.

1:23
I do want to ask you to introduce yourself for folks who aren’t familiar with your role here.

1:30
Yeah.

1:30
So my name is Ryan Tamaga.

1:32
I run product and customer success here at Alchemer.

1:35
I’ve been here for about 7 years, coming up on seven years.

1:38
And through that time, as we’ve, you know, continue to grow our business and, and bring a, a full CX solution to our customers, it’s been a really exciting journey.

1:46
And and you know, what we’re starting to deliver in terms of these advanced capabilities to leveraging AI is that next generation of those capabilities.

1:54
And we’re really excited about them and what what they’re going to do in terms of the way you can approach the problems that you’re facing within your organization’s to bring more speed to value and, and make the insights that come out of the data that you collect with our platform much more actionable on a daily basis.

2:11
Yeah, Thank you.

2:13
And I’ll just do a quick intro.

2:14
I’m Rosie Davenport, the Director of Product Marketing here at Alcamer.

2:17
I do not have your tenure.

2:18
I think I’m a year and a half in, but I work really closely with everyone on your team, Ryan, thinking a lot about how customers use our products, you know, making sure they have all information they need and are getting the most out of them.

2:32
So with that, let’s get started.

2:35
I will move us forward here if I can on the slides.

2:39
OK.

2:40
So today’s agenda, you know, we for those listening who might not know this, Alcamer somewhat recently launched a dashboard product that’s available to all of our customers.

2:54
We have a separate webinar on that topic.

2:57
If you’re interested in the core dashboard product, drop us a note in the Q&A, we can send you a link to that webinar.

3:03
We’re not talking about the core dashboard product today.

3:06
We’re talking about something more advanced.

3:09
We have some really, really incredible AI tools that are only available if you upgrade to Advanced Dashboard from that core dashboard product.

3:18
So we’re going to talk about that the what those tools bring.

3:23
Ryan, you’ve agreed to give us a live demo, which is exciting.

3:26
Thank you for doing that.

3:27
And then hopefully we’ll have some time for Q&A at the end here today.

3:31
So introducing Alchemer, our advanced dashboard tool here.

3:36
You know, we, I’m guessing a lot of folks listening to our, our webinar today oversee feedback programs or work on a feedback program.

3:45
They obviously need to analyze their data really thoroughly.

3:47
I think, you know, we know a lot of folks use a traditional BI tool.

3:51
They might export their feedback data into an Excel, but we also know that those kinds of tools can take a lot of time to set up or they take a long time to analyse data.

4:06
So it’s a lot easier when you have a feedback platform that actually comes with a robust dashboard.

4:10
A lot of vendors in our space I know have a dashboard tool, but I think what makes ours really special, and I think what we’re going to get into today is it’s not only incredibly powerful, it’s also easy to use.

4:21
And I think that’s a rare combination.

4:24
Ryan, I’m going to put up a slide here from a real customer kind of touching on that pain point of using other tools to try and get value from from your dashboard.

4:34
I think, I’m guessing there might be folks on today who need to analyze their data but aren’t data analysts.

4:41
Can you tell us a little bit more about why we built advanced dashboard?

4:45
Yeah, what’s funny is like I keep thinking about this word advanced like it means you have to be better, right?

4:51
Or more expert or more complicated.

4:54
And I think when we deployed the dashboard capability a couple of months ago, what was great about the way we built that product is I know we’ve got, you know, people who are just getting into data analytics as a team, people who are doing it as a part of their job, but it’s not necessarily their job.

5:11
And then we’ve got folks that are like full on data scientists who are in the data all day long.

5:16
And we built a product that we, we generally made available to all of our enterprise customers that spans all of those needs.

5:24
And so that our, our kind of our core dashboard product is, is unbelievably robust and deep if you want to get really, really into the data that you go collect.

5:34
So the when we talk about advanced, what it really means is putting more powerful technology that’s AI driven into the product to accelerate your analytics, your research, accelerate the way you’re building out the reporting and dashboarding, how you’re sharing that data, and generally just understanding data at a different scale than you could before.

5:57
So again, I think that the concept of being advanced is more like, let me put more power behind what I’m going to go do to make it easier for us to go faster and go deeper.

6:07
I, I love hearing that.

6:09
I also can relate to that.

6:12
I will admit, you know, I’m not a highly technical user.

6:16
I’m not a data, you know, a data scientist.

6:20
I’m on our marketing team here.

6:21
But, but it’s really, really important to get the insights quickly.

6:24
I’ve been able to use this product over the last few months here.

6:27
I love the core dashboard product.

6:29
It’s incredible.

6:30
But having access to these AI tools totally speeds up what I’m able to do.

6:35
I think the the depth of analysis I’ve been able to get to really quickly and I mean, as we’ll see in seconds is special.

6:44
And I think it’s made my job easier.

6:45
So I’m definitely an advocate.

6:48
Can you talk about a little bit, tell us a little bit about, you know, in this slide here we have a kind of this list of how how some feedback analytics tools don’t help team speed up, you know, they can actually slow you down a bit.

7:01
How can folks get to that new depth of analysis using advanced dashboard without spending hours, you know, trying to extrapolate the right data?

7:09
Yeah, well, I think the problem, the problem statement we’ve heard for years is that, you know, traditional BI platforms don’t understand survey data, right?

7:20
Like surveys capture data in an unstructured way and, and it takes a lot of energy and work to transform that data into a, a format that those traditional tools can, can, can, basically can read and you can manipulate with.

7:34
And so I think the first thing that makes our product different is just the fact that this is purpose built for feedback data, right?

7:40
Like our dashboard product, advanced dashboard, it is built to listen to direct and indirect feedback in the context of how we all collect feedback through survey, through forms, through ratings and reviews, through social media information, right?

7:55
Like all of this unstructured data, it’s hard to manage unless you’ve structured it in a way that these tools can really like drive value on it.

8:02
We’ve spent a lot of time building our data, data lakes and data sets in order for these tool.

8:07
So our tool can leverage it in a way that makes it really easy for our teams to just get into it.

8:12
They don’t have to worry about reformatting.

8:14
They don’t have to worry about transposing.

8:16
It just shows up and you can start using it, which I think is a huge value add.

8:21
So it sounds like customers are excited about this.

8:23
This has been a, this has been a long time and advanced dashboard in particular, it sounds like is kind of takes it a step further and helps them, you know, do that analysis in, in I don’t even want to say half the time I don’t even know.

8:36
And I think the other piece of it too is, and this kind of ties into the second one is, you know, the depth and the 10 year of data that our customers have collected in our product is deep.

8:47
And it’s, it’s years and years and years and millions and millions of responses across hundreds of surveys that are all very different.

8:55
And, and being able to start thinking bigger about how I access all of my insights over time in this same fashion in a single place makes it really, really valuable.

9:06
Right.

9:06
So now I’ve got everything organized.

9:08
I’ve got the ability to go look at depth.

9:10
And then I think the second thing that makes this really valuable is, you know, these dashboards are shaped around your teams.

9:15
So all the data and the user teams and roles access that you provided to your teams.

9:20
That’s all inherited as a as a way of looking at your data.

9:23
So you don’t have to worry about who is looking at what.

9:26
It’s all controlled within the context of your platform.

9:29
And so now I’ve got the depth of all of my data.

9:31
I’ve got it organized in the way that I’ve set my teams up and my users up to, to access the information they’ve collected.

9:38
And now I’ve really empowered the team to go for it right, and go, go look for the things that they’re looking to go do.

9:45
And then I think the third thing is, you know, we built, we, we deployed the AI capabilities inside of the inside of the product in a very easy to consume and understand way.

9:55
So when you want to ask a question, the prompt is already inside the dashboard.

9:59
If you want to do some AI analytics on it, it will show you soon.

10:03
It’s just a click through directly within a chart.

10:05
You don’t have to go to a different tab or go look at different places.

10:07
It’s all built very, very user friendly way inside of the way the product is being used so that it’s not a how do I use it, but it’s where should I use it and when should I use it more?

10:18
Yeah, I mean, oh, sorry, I didn’t mean to cut you off.

10:21
I was going to say I I just think this is, I don’t know anybody who doesn’t want to do their job more efficiently and and more quickly.

10:28
I know I’ve been that person in other roles where, you know, I’ve been doing V look UPS across like various spreadsheets trying to figure out where the insights live.

10:36
And I love that idea that, you know, we’ve built this tool to make people’s jobs easier, which, you know, is this advanced dashboard tool.

10:44
It brings the AI directly into the analytics experience.

10:49
And I think you started talking about this.

10:51
So I kind of want you to keep riffing if you have anything else to say on this topic, You know, what makes the product different here?

10:58
We kind of have these buzzwords on the screen around purpose built and but, but you know, keep going if you have anything else to add and I’ll kind of just combine the last two there with the the human judgment and faster answers.

11:08
So, so one AI is you are in control of what you wanted to go do, right?

11:15
Like it’s, it’s there to be your assistant and how you want to go look at the data and it’s there to support the questions you want to have answered in a really easy to use way.

11:24
It’s not out there like doing things on its own.

11:26
It’s not interpreting other data and making decisions.

11:29
It’s literally you asked it a question and it’s going to answer what you want to know.

11:32
And then you can keep probing deeper, but you’re always in the way that you’re interpreting the data.

11:38
So that again, I think a lot of people are worried about is what I’m getting out of these tools accurate?

11:45
And it absolutely is because you’re in control of how you ask the question, get the response, do the analysis and then be able to interpret what’s happening.

11:52
The thing that it does do is again, provides faster action with faster answers with less friction, right?

11:59
So I can go faster, ask questions.

12:02
And I think the thing that is really apparent to me when I talk to our customers who are using this product today is it helps people overcome what we all face, right?

12:11
We’re all human.

12:12
We all can categorize things as far as we can, but there’s always the anecdotal story that everybody tells.

12:18
There’s always the top three things that people know we need to go fix to improve our customer experience, but may or may not be on the agenda for the year because they’re big or they’re expensive.

12:26
It’s not a priority.

12:27
The depth at which you can get to different answers with this tool so fast provides you so much more optionality in the way you think about approaching customer problems.

12:37
You know, you can go now deep on specific customer journeys.

12:41
You can go deep on specific geographies.

12:43
You could go deep on specific product lines.

12:45
I mean, like the world’s your oyster in this case because it allows you to go so much deeper, faster by surfacing up these insights to allow you to go make the decisions on where you want to go.

12:55
Focus.

12:56
Yeah.

12:56
You know, I’m thinking what comes to mind is like our customers know they have the context of their, of their brand, their organization so well, so deeply, but we are human.

13:08
We go to sleep at night.

13:10
We don’t have 24 hours a day to process data and information like these AI tools do.

13:15
And I love that combination of like the context, the human bringing the context to the situation and then using an AI tool to help you get to the, to the heart of the matter, you know, find something troublesome in that’s happening in Australia really, really quickly or being alerted to that automatically.

13:32
I, I think that’s incredibly valuable.

13:35
So one of the more interesting things that I’m starting to see is that, you know, for so long we had to control when we asked questions inside of the customer journey because we wanted to not dictate what we wanted the customer to tell us.

13:49
But we’re like, Hey, it’s, you’re more likely to tell me about a post return experience after you’ve made the return.

13:55
So I should ask you that question then or hey, I want to know about your in store sales experience, like directly after you’ve left the store.

14:03
We had to be very targeted because you had you couldn’t look at data so deep that you can now.

14:09
And all of these tools and and dashboards allows you to go do is go help me understand where people are talking about product returns, right?

14:15
Because people talk about what they want to talk about when they want to talk about it.

14:18
And what this allows us to do is provide more freedom and flexibility to how our customers want to engage with us and then leverage the technology to eliminate a lot of the complexity of sorting through multiple surveys and multiple years of data just to get to the insights and the questions that we want answered.

14:34
Yeah.

14:35
You know, I’m that That’s so true.

14:36
I, I just had that experience.

14:39
I went on a trip trip recently.

14:41
I bought a new piece of luggage prior to the trip, but I didn’t use the luggage until like, you know, a month after buying it or something.

14:47
And I had feedback, it was a piece of it broke.

14:50
And I just remember thinking that, you know, is this still relevant?

14:55
Does the brand still care?

14:56
Like, what are they going to do this much?

14:57
You know, it’s not immediate, right?

14:59
And so I think I did not post an online review, but if I had or done something, you know, they could have showed up where they, they might have, you know, filled, I might have filled out an MPs survey and, and dropped it in there.

15:11
So I think, I think that’s, I think you’re, you’re shaping this up to be really exciting product demo, which is what we’re going to do next.

15:19
We’re going to hop into the live demo in a few minutes.

15:24
Before we do, you’ve kind of teased some of the features that this product has and, and what we’re going to see today.

15:32
I want to give folks like a bit of a, a deeper dive before we hop into the live demo so they know what they’re looking at.

15:38
As you start to use these terms, AI highlights, the first thing we’re going to look at here, it encompasses a whole suite of AI tools.

15:45
I know.

15:46
And the way I’ve been thinking about this AI highlights, you know, summarizing what you were saying earlier, it really helps you discover what you didn’t know to look for.

15:56
And I think, you know, like I said, I’m an Alkimer’s marketing team.

16:00
We collect a lot of customer insights, say around like NPS CSAT and we might get like a positive NPS review score, you know, but but maybe in the open text or somewhere else, we’re getting some different context clues and we’re not matching those up across the board.

16:15
And I think, you know, on mass, on scale, that’s hard to see.

16:20
And that’s where maybe these tools come in.

16:22
So with this suite of tools, AI highlights that we’re going to look at.

16:26
Ryan, what I’m assuming it helps teams get to insights quicker.

16:30
You kind of mentioned this already.

16:31
It also helped uncover things we didn’t know.

16:33
Is that right?

16:34
Yeah, because I mean, I we’ll see in the demo.

16:37
But you know, a lot of times when you’re looking at like a CSAT or an MPs survey, you’re going what, why is it going down?

16:44
And, and sometimes you’ll go, well, maybe it’s by channel of where people are providing the feedback, but that’s actually not what really matters, right.

16:52
It’s that next two or three levels deeper where you may have a geographical problem or a product line problem and you need to start making those joins faster.

17:01
And what the tool allows us to go do and they start to ask it to go do that work for us.

17:04
So instead of either having to build the jazz for it, it tells us something we put in Excel, do a lot of work on the back end, go back in, build some new charts that illustrates the the results we’ve had.

17:14
You know, we can ask the tool to go do that outlier analysis or correlation analysis or even even predictive.

17:20
We’ll show an example of of how we’re doing predictive analysis in this as well.

17:24
And again, what it’s doing is it’s doing what I think is the the most amazing part of this product, which is sparking curiosity, right?

17:32
It’s sparking curiosity in a way of going, well, why is it that way?

17:35
Well, why is it that region?

17:36
Why is it, you know, why is this correlated with this?

17:39
And, and having the tool build those connections for you just allows you to be more curious to ask the next best question to get to the answers that you’re looking for without having to be bogged down with the spreadsheet work or having to outsource the word to a different team of, of analysts or to a data scientist to go do it.

17:56
It’s doing that heavy lift for you.

17:57
So you can just keep thinking through the problem set that that you’re facing and get to a solution for your customers.

18:03
So what I’m hearing is if I use advanced dashboard, I can call myself a data scientist.

18:07
Is that right?

18:10
I mean, I think you’ll look like 1.

18:12
I don’t know if the, you know, it might be run around saying I’m a PhD.

18:16
What it does is it does make you feel like it.

18:18
I’ll say, OK, I won’t add it to my signature.

18:21
And again, it’s all about, it’s all about using resources appropriately, right?

18:25
So, So what this allows you to do is really focus on what you can control.

18:29
And then when you need help, right, that’s when you’re actually at that depth where that data scientist can come in and really provide a lot of value because you’ve kind of done the heavy lift for them.

18:37
And then they can go take it to the to take it into their expertise to get where you want to go.

18:41
So it actually makes teamwork way more easier because it’s putting people in positions to really empower them to be successful and then be successful as a group.

18:51
Yeah, I like being that person.

18:52
I like being the person to find things and then go take it to the person who can help me figure it out.

18:57
So I think that makes sense.

18:59
The other thing I wanted to talk about before we hop into the demo is this incredible tool Spark.

19:04
I think this tool is so cool.

19:07
I think most folks watching have probably used a tool like ChatGPT.

19:11
It lets you ask a question in plain language and get some kind of in depth response.

19:15
I just used it to plan that trip I was talking about for my family.

19:20
But you know, as we know, ChatGPT is not purpose built as you were talking about previously for managing your feedback and handling your feedback data.

19:32
And this is purpose built for data analysis, right?

19:34
No, no sequel, no formulas needed.

19:36
And it can just build things from a single prompt.

19:39
Is that, is that right, Ryan?

19:41
Yeah.

19:41
I mean, I think what’s so amazing about this is when we talk in our teams or when I talk to our customers, we talk about survey context or we talk about ratings and review context.

19:51
If you talk to Spark and say, and I’ll show you an example where it just says, tell me about this survey.

19:55
It knows what a survey is and it knows what the purpose of the survey is supposed to do.

19:59
And so it’s bringing the context of what we do every day into the data and relating it back to you.

20:05
So it’s almost like it’s talking to one of your peers.

20:08
I.

20:09
I started using just core dashboard when we first launched it and then I started using Spark to help me build tables and visualizations and I was blown away.

20:17
So anyways, I’m gonna let you, I’m gonna stop sharing and let you take over the screen share here.

20:24
And I am excited.

20:26
Live demos are always exciting to.

20:30
So thanks for volunteering for this.

20:31
It’s all good.

20:34
If I can do it, anyone can, right?

20:35
OK, so I think the first thing I’ll show I’ll start with is this is the dashboard product inside of Alchemer Clarity.

20:43
We’re in the dashboards tab and specifically a I’m, I’m I’ve built a dashboard to help us improve CSAT scores.

20:50
What is behind the dashboard are a couple of different data sets.

20:54
There’s ACSAT score or CSAT survey.

20:57
We’ve got an MPs survey.

20:58
We’ve got some of our data from our digital product on the net fan score there.

21:02
So now I’ve got multiple surveys worth of information sitting behind this dashboard and and this stand alone is super important, right?

21:09
It’s super valuable because now I can start seeing what’s happening, you know, monthly in terms of my change on CSAT.

21:14
You know, I’ve got my global satisfaction, I’ve got the sentiment breakdown by month.

21:20
You know, I’ve got channel breakdown, I’ve got all the power the dashboard brings you.

21:25
And there is an incredible amount of depth that can come out of this.

21:29
The challenge with that is the incredible amount of depth can sometimes be hard to get at.

21:34
So what I’m going to demonstrate here with our advanced dashboards or how do we deploy these AI capabilities to make getting at answers easier?

21:41
So the first thing I want to show is, you know, again, sometimes dashboards don’t move very fast, right?

21:48
Like they don’t move every minute, they don’t move every hour.

21:50
Sometimes they’re moving on a weekly or monthly or quarterly basis.

21:53
And So what we want to be able to do is give you the power of control without having to have the paranoia of having to check this every day.

22:00
So the first thing we can go do is start to set alerts based on KPI updates or attributes that change limits so that when something happens, it will bring it your attention and you can come take a look at it again.

22:12
And again when we set these up, you can set it up based on changes by percentage.

22:16
You can do a whole bunch of different formulaic views of of when you would want to care about something.

22:21
Because again, if your score stays the same everyday, not that interesting.

22:26
But if you start to see a 5% increase or decrease, you probably want to go take a look at that data.

22:30
So the alerting because a core component of how the dashboard starts to tell you when something important is happening based on what matters to you.

22:39
Yeah.

22:39
I mean, I’d love that alert to show up.

22:40
And as I start my day and tell me where I need to focus 100%, the next I’m going to do is go.

22:47
So let’s say Rosie built this dashboard for me and I have no idea what’s in it.

22:50
She’s just like, hey, Ryan, you should go take a look at this dashboard.

22:53
It’s super interesting.

22:54
And I like open it up.

22:54
And now I’ve got like data over.

22:57
I’m overwhelmed by the amount of information on this data.

23:00
I can click this AI highlights button and what this is going to produce for me in seconds is an overview of what’s happening in this dashboard.

23:11
So instead of having to comb through every single chart and try to understand why somebody built it and organized it the way it did, I can just go, oh, I’m going to go look at this expected change and I’m going to go, our monthly CSAT score has dropped 13%.

23:24
If I click on that, what it automatically tells me through the analysis is I’ve got a challenge by country, I’ve got a challenge by role, and then I’ve got a I’ve got a couple other things around feedback channel and membership level.

23:38
So what I’ve quickly gotten to now is the things that I should go take a look at within this dashboard based on the delta change that somebody is experiencing within your customer experience.

23:49
So I have within 30 seconds now, I’ve got the context of a dashboard that somebody built for me without somebody sharing that context with me directly, which I think is unbelievably powerful.

23:59
I have to comment on that because you press that one button at the top.

24:02
I missed that.

24:03
Looked at all of the data available on this dashboard, which we saw was quite extensive.

24:07
And I, I don’t even think it was 2 seconds.

24:09
Was it for that, for all of this to show up.

24:11
I mean, that’s incredible.

24:12
It’s so fast.

24:13
Yeah, it’s pretty amazing.

24:15
So let’s say I want to go take a look at something a little bit deeper.

24:18
We noticed that there was a channel challenge in terms of where the feedback is coming in, and that Channel is driving down our CSAT.

24:24
So if I go to my channel CSAT chart here, I noticed that in our website channel, I do have a pretty good drop from 86 to 77.

24:32
So let’s go explore that.

24:35
I could click in this and go drill in and try to go figure this out myself.

24:40
But using our AI highlights, what I can do is right click, go to my AI highlights, analyse.

24:45
It gives me a couple of different options of analysis that the tool performed for me.

24:49
And let’s say I want to do an outlier analysis, I quickly make sure that the things that matter to me are collected.

24:58
I click analyse and in the background the tool is going and performing all of that outlier analysis on my behalf and producing new charts for me that I could you, I could go do more analysis on.

25:15
I could go pin them back to my dashboard.

25:17
I don’t have to go create these charts.

25:18
It’s done it for me.

25:19
But if I take a look at this website, what it’s showing is that I’ve actually have a problem with a couple of countries on the downside here with their providing feedback from these geographies by website.

25:30
And that’s my challenge.

25:31
So what it’s done for me now is that I’ve got a problem.

25:34
I’ve got a negative experience that’s impacting my CSAT score.

25:37
I found that it’s relatively through my website channel.

25:41
And now I know and literally in the two minutes we’ve been talking that it’s related to probably Canada and the Japanese geography.

25:48
So I’m now I know where I need to go double click even further and I can keep going down on this chart to go deeper if I needed to.

25:55
But I’ll stop here in this one is I want to show that, you know, I think a lot of people are are concerned that there’s a black box behind all of this and I don’t understand how it’s doing its work.

26:05
If I go to my analysis details here, it’s showing me how it did the calculation of producing what the outliers are, right.

26:12
It’s got the mean, it’s got the standard deviation it used as well as the multiplier.

26:16
So you know how the calculations in the background are working to produce the the set and where it’s lining people up against the set.

26:24
So again, 2 minutes we have now gone from I know I’ve got a problem.

26:28
I I’ve got a dashboard someone sent me.

26:29
I understand the dashboard.

26:31
I’m I’ve got a problem with probably a geographic issue by this one channel.

26:35
I went to my channel.

26:37
I did had the tool do the outlier analysis for me.

26:39
And now I know that I need to go take a look at my Canadian and my my Japanese geographies.

26:44
All relatively straightforward and easy yeah and I know look I know a human can do that right we can get to that analysis by downloading and and looking at all that data but not in three seconds.

26:55
I think that is a is really outstanding yeah.

26:59
All right, so let’s get to the problem everybody always wants to talk about, which is like, what is my future going to look like?

27:04
What if I don’t do anything?

27:05
What if I do something?

27:07
How do I know where something is going to lead to?

27:10
So let’s get to that predictive analytics concept.

27:13
So if I look at my monthly CSAT here and I want to go, what is going to happen to my C set in the future?

27:18
If I click on this button here and I go back to my AI highlights, I can click on my forecasting analysis type and I’m going to click next.

27:27
I’m going to make sure I have the right things selected, got my channels.

27:32
And when I click on this, what it’s going to do is it’s going to produce a predictive model that’s going to show me what’s going to happen, most likely going to happen.

27:42
And then where are the ups and downs on if I improve it or don’t improve it?

27:45
So here’s my line that’s actuals.

27:48
So my actuals today.

27:50
And then I look at the dotted line here and what this is representing is the most the the most likely path of if nothing changes, this is what your score is going to do over time, which is pretty crazy.

28:03
Like literally in seconds.

28:04
Now I’ve got an idea of if I do nothing, this is where I’m going to go.

28:09
And then it’s going to say, it could get worse, it might get better, right?

28:14
So now it’s kind of giving me some weight on what I want to go put in terms of like, should I go improve this or is it something I should really care about?

28:20
And clearly here, there’s some trending happening on the back end here that’s saying like, you need to start looking at this because if you don’t do anything, you’re right and most likely will be here.

28:29
But there is a better than that chance that something bad is going to happen.

28:32
And so now what I’ve done with this chart is I can start taking this one deeper and deeper and deeper to understand specifically like again, what channel, what geography, what product line, what experience matters to people.

28:44
And I can get hyper focused and, and I can start to set these as benchmarks so that I can start looking, as I start to approve, apply new experience improvements in the way I engage my customers and they’re providing more and more feedback.

28:57
How are those things improving against my predicted model and, and are the things that I’m doing really making a difference?

29:04
Yeah.

29:05
The ability to be proactive here, to prep your teams to know what your business might be encountering in the next, you know, weeks or months.

29:12
You know, it would take it.

29:14
Look, obviously nothing’s guaranteed, but it’s taking the guesswork out of helping you prepare for for what you whatever is whatever’s coming based on all of the days.

29:22
It’s the question we all get asked for.

29:24
I got asked for about CPO.

29:25
And where do you think NPS is going to be in August?

29:28
And now I’ve got an idea of how I can start to apply it.

29:31
And then, and not only that, but then the conversation goes deeper because it’s like in here are the five things we’re going to go do that are most likely to impact that score based on our detailed analysis of the scenario.

29:40
And again, it’s me, it’s my team, it’s all of us working in this tool, providing that information back up to our leadership team.

29:48
Yeah, that’s incredible.

29:49
What a cool tool.

29:50
I love.

29:50
So that’s, that’s how AI can actually be deployed within the context of you use the dashboards that you’ve already built.

29:59
You highlighted Spark a little bit.

30:01
So let’s go to kind of the the really cool thing and we’ll go to Spark and we’ll start about like, what if I haven’t built my dashboard yet?

30:07
And what if I just got a data set?

30:08
What do I start to do?

30:10
So if I go back to my overview tab, here’s my Spark engagement prompt.

30:16
I’ve got my C set demo data set associated with my prompt.

30:19
So what I’m going to do is I’m going to ask Spark to help me understand what’s going on in a data set.

30:25
So I am, let’s assume I have no idea what I’ve collected is a, you know, the project’s just closed or the survey is just come to a new.

30:33
I want to go and analyze and now I want to go figure out what’s going on behind the scenes.

30:38
So I mentioned earlier that again, the tool is built for the data that we collect and it understands our language.

30:46
So the first thing I want to ask it is something simple as tell me about this survey.

30:55
And what Sparks doing is it’s going in there in almost real time.

31:00
It’s producing context of all of that data in the context of the language we speak.

31:06
So it’s it’s telling me what the CSAT survey is supposed to do.

31:10
It’s giving me my key use cases.

31:12
It’s looking at all of the relevant columns that are associated with the data that’s been collected.

31:16
So it’s giving me an overview of the structure of the data.

31:19
And this is when it gets really, really cool.

31:22
It starts giving me ideas of what I should go ask.

31:25
So it’s assuming that maybe I don’t know what I should know.

31:29
And it’s saying, here’s some more questions you might ask in the context of the specific data behind it.

31:34
So obviously if it’s asking, saying, hey, you should ask what’s going on in March for Canada, it knows there’s something going on with Canada in the month of March.

31:42
And so you can start to like understand how to start to deploy this capability and ask the right targeted question.

31:50
But let’s assume I, I kind of know what’s going on.

31:53
So I’m going to add a couple more prompts here.

31:56
So the first one is, you know, what is the trend of CSAT scores over time?

32:01
What it’s doing now is it’s going to go produce all of the analysis to show that trending over time and produce the chart for me.

32:08
So it’s literally starting to build my dashboard for me.

32:12
And what I can do with this chart now is I can go pin it to any of my existing dashboards, or I can go create a new one.

32:19
And so as I’m having this conversation with my data set, I’m starting to build the next dashboard or I’m starting to enhance my existing dashboards with the things that are most relevant to me today.

32:29
And not only that, but let’s say like, I don’t really want this to be a line chart.

32:33
I want it to be more of a KPI chart.

32:35
So I can just ask for it, make this a KPI chart and voila, it’s going to produce AKPI chart for me.

32:42
So then again, it’s got the right charting element that that illustrates what I’m trying to provide to the people who I’m I’m sharing this info with.

32:52
But maybe let’s give it a little bit of a harder test because that was pretty straightforward.

32:55
So let’s say again, we talked a little bit about Spark told me that there might be a geographic problem with the way that the data is coming in.

33:03
If I change my prompt and say, how does my CSAT score for February of last year vary by country?

33:10
Now I’ve got a targeted time frame and I know that I’ve got maybe a geographic problem and I wanted to show me this in, in a map view.

33:18
So I want the, I want the charting element to look like a map.

33:20
It’s going to go produce that analysis for me and it’s going to go produce that visualization as I’ve asked it to go do.

33:30
So there is my CSAT score for February by country in my map view, which that I can quickly go pin, save, download.

33:36
I can edit it further in seconds, right?

33:40
So now I’ve already built three charts in 45 seconds here to build my next one.

33:46
Now let’s give it a problem to solve.

33:49
So let’s say I want to understand, OK, this is great to know, but have I seen a change by geography month over month in that same time period?

33:57
So I add my next prompt, which is show me and calculate the difference by country between January and February and then display it.

34:09
And as it’s thinking through this, what it’s doing is it’s looking at every single geographical geographical score in those two months.

34:16
And it’s putting together the categories and it’s doing the analysis to tell me where I’ve got my deltas.

34:20
And what’s been so amazing about asking this problem now.

34:23
Now what it’s done is it’s actually gone in and it’s done the comparison by country and it’s producing an easy to understand list and delta.

34:32
So you can see here I’ve got my countries, I’ve got my CSAT score by month, I’ve got the difference in the CSAT score here articulated.

34:39
And then I’ve got some summary view of what those tables look like.

34:43
But now I’ve quickly gone from I have no idea what’s in my data set to here’s what this survey is telling you.

34:49
Here’s some questions you might want to ask because I understand there might be some challenges here to here’s what I want to understand for my CSAT score over time.

34:57
I’ve charted it.

34:58
I’ve changed it to the chart type that I want.

35:00
I’ve created a map view by geography.

35:02
I’ve asked it to do some comparisons of time over time and let’s say I just, you know, Rosie, you got a quick question for me and you’re like, hey, Ryan, I really need to know just you know, what country had the biggest drop in CSAT during this time frame.

35:15
I can go ask it that specific question and it’s going to go tell me in near real time that we have, we need to have a conversation about Australia.

35:28
So it looks like Australia has had the the, the biggest drop in in CSAT month over month.

35:32
So we should go continue to double click into it.

35:34
So again, when I say like the best thing about this capability is the speed at which you get to insights and start to build those dashboards and those capabilities for analysis.

35:43
But it just continues to spark curiosity, right?

35:46
That’s why I think Spark such a great name for this.

35:49
It’s like, well, now what do I want to know about Australia?

35:50
I’m going to go ask questions about Australia and then I’m going to ask about specific channels in Australia.

35:54
Then I’m going to start asking about product lines or experiences in Australia, right?

35:57
And you can quickly see how fast you can get to, you know that that 5th, 6th, 7, eighth level of depth that you know would have taken hours or days to get to before you can get to in a matter of minutes.

36:08
And then set direction and start to prioritize where you want to focus all your time and energy, right.

36:13
It feels to me like you’ve added a very experienced team member here.

36:18
You know, all the questions you’re asking, the, the answers you’re getting.

36:21
I mean, they’re, they’re really rapid.

36:22
But if, you know, it feels like this could be somebody’s whole job and, and you’ve just added that capability here in, in seconds.

36:29
I’m, I’m sure a lot of people on the call and, and a lot of our customers have heard me make this, this analogy before.

36:34
But I think when I think about deploying AI in our products, it’s, it’s really about giving Tony Stark the Iron Man suit, right?

36:42
Like Tony Stark’s great and he’s not, he’s, you know, he is Iron Man, but he’s not Iron Man without his suit.

36:48
And so, you know, by giving you tools like this, it makes you so much more powerful.

36:53
And again, the speed of the then the curiosity of sparks really makes all of your team members so much more extensible because they have all of this control and power at their fingertips and are really easy to use and easy to consume Way.

37:06
Yeah.

37:07
Thank you so much for sharing this.

37:08
Really blown away by everything this tool can do.

37:13
I love the the depths and how you just keep getting you’re able to go deeper and deeper into that data set.

37:21
Looking at the time I’m going to I’m going to keep us rolling along.

37:23
So thank you for letting me take back over the screen share.

37:26
But I appreciate the demo.

37:27
Like I said, you know, and I just want to share this is kind of a just just kind of recapping some things we’ve talked about today and, and what you just showed us.

37:36
We saw first hand what a big difference these advanced dashboard AI tools can make, you know, and without without the AI tools, I think dashboard is still an incredible tool.

37:45
Like it is incredible, so easy to use.

37:48
It’s, it’s really made my life a lot easier.

37:51
But the addition of the AI tools, it becomes even more powerful.

37:55
It’s like this really, really powerful BI tool that is as easy as typing in, you know, a question of your data set.

38:02
And I, yeah, I’m really, I’m really excited to watch our customers start to use that and engage with that even more.

38:11
Ryan, is there any, you know, as we think about kind of takeaways here, the future of our feedback programs, any takeaways you want to share anything about how you’d sum up kind of the advantages of dashboard of advanced dashboard?

38:24
Excuse me.

38:25
Like I said, I think, I think the thing that this enables all of us to do is think bigger, right, Bigger data sets, more time, think about it from the lens of of how your customers are interpreting their experiences and how they want to share that information with you, right.

38:39
We don’t have to be so tight anymore in terms of trying to control everything we can, we can let our customers dictate where they want to talk about things and we just need to ask about what we need to go do differently to make their experience better and continue to drive the experiences that we all design and, and, and want our customers to have from us.

38:57
And so again, I think the, the theme that all of this and I keep saying is curiosity, right?

39:02
Like it just keeps making us more curious because it gives us the tools to be so.

39:06
And so I’m, I’m really excited about it.

39:08
We’re going to keep iterating on this and providing more and more capabilities.

39:12
We’ve got a feature coming down the pipe where instead of just building 1 chart, it’s going to build an entire dashboard for you.

39:17
So again, it’s just you’re, you’re only limited by your own curiosity and the questions you want to know.

39:23
Yeah, I, I share that sentiment.

39:26
I have talked to so many customers or heard or listened to customers saying there it’s never a problem of like we don’t have enough data.

39:34
It’s being able to take action on the data, action it quickly and take the next step and get to outcomes.

39:39
And I think what you just said sums that up so beautifully.

39:42
I know we’re kind of running short on time here.

39:45
So let me try and pop up a quick poll here for folks watching and then I think we’ll have time to answer a few questions.

39:53
If you, you know, viewers can take our poll quickly, that would be super.

39:59
We are short on time, so I, I think we’re gonna have time for like one or two questions.

40:03
That being said, if you put a question in the Q&A and we didn’t get to it, we do have a short post event survey.

40:11
If you fill that out and let us know what your question is, we’ll get back to you.

40:14
I promise.

40:16
OK, Ryan, let me see what questions are popping up most.

40:21
This one looks pretty relevant.

40:23
OK.

40:23
In the demo you mentioned multiple surveys showing up in a dashboard or you were kind of showing that, I guess how does that scale across the organization’s entire history of feedback collection With Alchemer, every survey and every response you’ve ever collected is available in dashboard.

40:39
And again, I and, and the reason why we’re confident in in releasing data that way is because, again, this is built based on your user teams enroll permissions.

40:48
And so only the people who have access to your data can leverage that data within their dashboard context, but it shouldn’t be limiting to the folks who have access to all of it.

40:56
And so we want to make sure you have the depth of your entire history of data collection at your fingertips so that you can drive that curiosity everywhere.

41:04
Yeah, I appreciate that.

41:05
OK, one more, I think this one is relevant as well.

41:09
You were starting to talk or sharing a little bit about, you know, your vantage point on AI and how Alchemer approaches AI.

41:17
So this one is how does Alchemer think about AI in the world of data privacy and security?

41:24
Well, I think first and foremost, we’re really proud of our security stance, right?

41:27
We’re sock 2, Type 2 GDPR.

41:29
We’re compliant wherever our customers need us to be compliant and that’s for all of our products.

41:36
You know, when you apply things like AI, it’s no different.

41:39
We are going to continue to be leading the pack in our industry in terms of our security stance and we apply all of that.

41:47
When it comes to AI data privacy, we know that there’s a lot of concern out there around what people are doing with their data.

41:54
We’re very transparent with that.

41:55
And again, it’s all we comply with all regulations, whether it’s governmental, industry specific.

42:03
And you know, we’re here to make it easy for you to understand so that you can go talk to your teams about these tools and make it really easy for your teams to adopt them.

42:11
So again, we’re never going to waver on on that stance here because it’s super important to us.

42:16
And so you can always be confident that what you’re using within the outcomer environment is safe and secure.

42:22
Yeah, I know that’s something we pride ourselves on.

42:25
Ryan, thank you so much for joining me today.

42:29
Loved your live demo, loved all the points you brought.

42:33
So again, thank you for all the insights you shared.

42:37
We have, you know, as we wrap up here, we have a if, if folks can scan this QR code to take that post event survey.

42:45
Obviously it’s very helpful to to let us know if there’s anything else you want to learn about Advanced Dashboard.

42:50
If your question didn’t get answered, if there are other topics in future webinars you want us to cover, we’ll put Ryan on the hook for those.

42:57
Right?

42:57
Cool.

42:59
OK.

42:59
Thanks, Ryan.

43:00
Talk to you soon.

43:00
Bye.