Cliff Kim, Director of Insights and Analytics at Fender Musical Instruments, shares how his team transforms raw analytics into customer stories that drive action across the organization. Using examples from Fender Play, the company's online guitar learning platform, he presents four practical techniques for helping stakeholders see the real people behind the data. The talk is grounded in the challenge of instilling a genuinely data-driven culture, rather than one where data is used to validate decisions already made.
Key Takeaways
- Convert percentages to whole numbers when the raw count makes the scale of a problem more visceral for stakeholders. Sixty-three percent is abstract; 61,000 customers who quit at a sign-up screen is a decision trigger.
- Surface buried insights explicitly. A finding that appears third on a list and sits behind another percentage will be ignored, even if it is the one thing your team can actually act on today.
- Suppress assumptions before reaching conclusions. Sending a survey to 300,000 inactive users revealed a mix of player types, health barriers, and missing equipment, not duplicate accounts or product hate, and opened several distinct intervention strategies.
- Analyze both sides of the bar chart. Building look-alike models from your most successful users is sound practice, but understanding why users fail is equally necessary if you aim to serve a wide audience rather than a narrow high-value segment.
- Get cross-functional buy-in before the analysis is complete, not after. Involving stakeholders early gives them skin in the game and makes findings harder to dismiss.
- Frame every number as customer feedback. Helping colleagues understand that each data point represents a real person telling the company something is the most reliable way to build a culture where data leads strategy rather than validates instinct.
Questions & Answers
- How were the suggestions to improve the app experience generated? Were they from a list or open-ended, and how did you help colleagues understand where to focus?
- Kim uses a combination of structured lists and open-ended fields depending on how well-defined the themes are. For that specific question, the team used an open field because hearing unfiltered user language felt important. On getting buy-in: he brings stakeholders into the survey design process before results come in, not after. He compared it to inviting a sound engineer to review a construction project at an early stage so they have skin in the game when results come back. When people are involved from the start, they are much less likely to dismiss the findings.
- Have you tried to gauge the brand equity value of signing up, even when people remain inactive?
- Yes. Fender tracks the value of an email subscriber or platform sign-up regardless of activity level, because the company spends paid media to acquire some of these users. The team analyzes users across different entry points to determine whether the economics of acquisition still work even for inactive accounts.
- How much or how often do you include the market research department in this type of research?
- Always. Kim tries to involve every relevant group as early as possible. He noted that people at Fender are deeply passionate about the product's mission, which makes cross-functional collaboration easier to initiate than it might be elsewhere.
- How much of your data was from internal sources versus external sources such as panels or secondary data, and does believability change by source?
- Yes, believability does change by source. Stakeholders tend to trust first-party analytics data most readily because it covers everyone, not a sample. Research data requires more education, particularly qualitative research where the sample is smaller. Kim spends significant time explaining why a smaller sample can still be representative and why qualitative findings do not need the same scale as quantitative surveys to be valid. He described education as a larger share of the job than he initially expected.
Session Notes
About Fender and Fender Play
Fender Musical Instruments has operated for over 70 years. In recent years the company expanded beyond hardware into digital learning with Fender Play, an online guitar instruction platform built around short, bite-sized lessons designed to get new players playing songs quickly. The curriculum was developed by professional guitar instructors. As of the talk, Fender Play had surpassed 2 million users, and the platform is free to access for a seven-day trial with no payment required.
A partnership with Mattel and Netflix around the film Barbie: Big City, Big Dreams added a branded song-lesson collection to Fender Play, with three free months of access bundled with select Barbie doll purchases, illustrating how the platform serves as both a standalone product and a marketing channel.
The Core Problem: Data That Does Not Drive Decisions
Kim opened by distinguishing data-driven from instinct-driven organizations. In a truly data-driven organization, data leads strategy and initiatives. In practice, many organizations use data to confirm decisions already made, bury analysis in inboxes, or treat reports as boxes to check. He argued that the root cause is rarely malice or resistance to change. It is that stakeholders see numbers as numbers rather than as customer voices.
Every report you are building and every number that they see on your decks and your spreadsheets represents a person, an actual person, an actual customer.
The analyst's job, in his framing, is to be the customer's representative in every meeting, making it impossible for colleagues to separate a metric from the human behavior it reflects.
Four Tips for Helping Stakeholders See the Customer Behind the Data
1. Convert Percentages to Whole Numbers When the Scale Matters
Fender Play's acquisition funnel showed that 63 percent of users made it from the sign-up screen to the plan selection screen. Presented as a percentage, this generated little stakeholder reaction. A single negative app-store comment, by contrast, sparked immediate discussion about fixing the problem. Kim's explanation: percentages invite argument about whether a number is good or bad based on individual baselines, the same way two people disagree about a 63 percent Rotten Tomatoes score. A raw count does not.
When Kim reframed the funnel drop-off as 61,000 customers who quit because they saw email sign-up as a barrier, the conversation changed. The recommendation is to present percentages alongside whole numbers, or to lead with the whole number, whenever scale is the real story.
2. Do Not Bury the Actionable Insight
During the COVID-19 pandemic, Fender offered three free months of Fender Play in late March 2020, bringing in 1.4 million new learners. Increased learner volume drove record guitar sales. However, analysis of purchasing behavior uncovered that 20 percent of users had planned to buy a guitar but did not.
Digging into that group revealed the top reasons for not purchasing. The first two correlated with pandemic-era job loss. The third was that users did not feel they had made enough progress to deserve a new guitar yet. This finding was easy to overlook because it sat behind a percentage within a percentage and ranked third on the list. But it was, in Kim's assessment, the single item the team could most directly influence.
When expressed as a volume, roughly 31,000 people gave this response, and it became the leading actionable signal. The implication for product and marketing: building benchmarks and progress encouragement into the Fender Play experience could shift users' self-perception and move them toward purchase. The lesson for analysts is to evaluate findings by what can be acted on, not by where they rank on a list.
3. Squash Assumptions by Investigating Before Concluding
Fender Play found that 33 percent of users who signed up during the free offer, more than 300,000 people, did not use the product at all during the first seven weeks. Internal theories ranged from duplicate accounts and spam sign-ups to COVID impact, product dislike, and login failures. Kim cautioned that reaching conclusions without evidence leads teams to build things that will not actually help the customer.
The team surveyed the inactive cohort. Key findings from that survey:
- The group was evenly split across beginner, intermediate, and advanced players. This was striking because the platform was built primarily for beginners, who typically represent over 70 percent of sign-ups.
- Motivations differed sharply by skill level. Beginners wanted to finally learn; intermediate players wanted a refresher; advanced players were evaluating whether the platform could enhance existing skills.
- None of these users had watched a single lesson in the seven-week window.
- For absolute beginners, not yet owning an instrument was the second most common reason for inactivity, creating a clear marketing and commerce intervention point.
- The most common reason across all groups was lack of time, though Kim acknowledged this needed further investigation.
- Health conditions emerged as a meaningful barrier, a reminder that the same pandemic conditions that drove sign-ups also created real obstacles to engagement.
These findings opened distinct strategic paths for product, marketing, and CRM that would have been missed if the team had acted on any of the early assumptions.
4. Both Sides of the Bar Chart Have Customers
More than 90 percent of new guitar players quit before developing lasting skills. Fender's data showed that lesson completion in the first week of use strongly correlated with long-term retention and lifetime value. A user who progresses from casual learner to committed player represents a potential lifetime spend of around $10,000, compared to a single entry-level purchase.
The temptation is to focus analysis on what makes successful users succeed and build look-alike acquisition models from that group. Kim said that is a sound strategy but an incomplete one. Users who abandon represent a separate set of learnable signals, and dismissing them as low-value from the start forecloses the opportunity to understand what additional support might have moved them across the threshold.
We're not here to fill the world with one type of angel. We're here to fill the world with all different kinds of angels.
Findings from lapsed-user analysis are feeding future product sprints, marketing initiatives, paid campaigns, and CRM flows at Fender.
Closing Argument: Storytelling Requires Human Characters
Kim closed by framing the analyst role as storytelling. A story made entirely of inanimate objects has no impact. Numbers treated only as numbers have the same problem. When every metric is presented as a customer communicating something to the business, the data becomes part of a narrative that stakeholders can connect with and act on. That shift, from number to voice, is what makes a data-driven culture actually function.
Transcript
Read the full transcript
one and others of our speakers of everyone pretty much and then please use this opportunity if you're on zoom here with us um to ask questions chat in the chat feature if you're youtubing we'll try to keep online of those comments as well and all that so it is my pleasure to introduce cliff kim our director of insights and analytics at fender and he's going to talk to us about some uh customer information which is frankly my my love consumer behavior so plan i will pass it over to you all right and you can go ahead and get started i will disappear while you're talking okie dokie let's see let's play this slideshow and share it all right can you see that we can all right well then let's jump right into it um so if you guys have any questions just throw it into the chat i think we'll get to it kind of at the end um that way it's a little more i guess flow of the session but um yeah a little intro about myself um you know my name's cliff i'm the director of insights and analytics at fender musical instruments company and you know i've kind of been using data to tell stories all my life um professionally now for about 10 plus years my career has led me to some really iconic companies such as yahoo espn live nation ticketmaster and now fender i built multiple analytics organizations have been a part of really large data teams even been a department of one that i'm sure some of you might be um but the one thing that i've done was use insights and data to add millions of incremental revenue but the real question is how do you do something like that and the way you do it is you instill data data-driven culture into the workplace through powerful and actionable stories and the most important aspect is helping the end user understand that every report you are building and every number that they see on your decks and your spreadsheets represents a person an actual person an actual customer so the first thing i want to do is just start with fender fender iconic guitar brand that's been around for over 70 years and while the iconic look has maintained its legacy over the years the current crop of master builders are innovating every single day to modernize that perfect piece of history so fender has since launched this hybrid model called acoustasonic half acoustic half electric and everything in between innovation to service the need of every type of player and you know the quote on there leo's vision was that artists are angels and it's our job to give them wings to fly and that kind of will always be fenders mission but moving on to today we wanted to continue that vision but multiplying it filling the world with angels by putting wings on beginner angels fill the world with angels amazing and we decided to build an accessible guitar learning school for everyone that can teach them how to play at their pace at their leisure on their time and now we're really proud to say over 2 million users have learned on fender play and you know we're just getting started because one of the things that we've done is we've opened up the platform to everyone on app on web we're not limiting it to credit card access so for anyone on this call that's wanted to pick it back up and just try it for seven days for free no strings attached learn for the first time go check out fender play uh helps my numbers too but so fender play a little bit a little bit deeper was designed to teach anyone how to learn how to play their favorite songs and our focus is quick bite-sized lessons that are designed to get you playing in minutes and the entire curriculum was built by real guitar instructors some with phds in the stuff and we dedicated ourselves to ensuring this program would be the absolute best way to become a guitar pick player quickly and most importantly with sustained skills that kind of last a lifetime so we have an array of content that resonates with all different types of players and the fender team has been dedicated to fostering the development of the next generation of angels so speaking of which uh fender guitars and mattel are marking the release of netflix new movie barbie big city big dreams with a new signature barbie collection of song lessons on its online learning app so this was created to inspire future musicians and the lessons show young guitarists how to play songs from the movie while building guitar skills at the same time and playing techniques so this fall anyone who purchases barbie dolls it's in the stores now inspired by these guitar playing characters will also get three months of play for free so again you know we're dedicated to inspiring this generation and the next generation and the generation after that one so pretty inspiring exciting stuff that's in a nutshell that's the vision and vision is imperative and marching towards that requires focus but how do we ensure the initiatives follow suit and i think everyone on this call probably knows it's through data it's through insights that's how you steer the ship towards vision towards your goals that's how you grow you look at the map and you steer the ship and while most professionals will say that is the case but that doesn't always happen reports are often used to prove a case numbers are used just to check a box and sometimes analysis just gets buried in an inbox and never sees the light of day but why why does that happen it just might be a sign that your team or your boss or your peers or possibly even your company is not data-driven and it's your job it's your job to help change and instill that culture as analysts so what does it mean to be data-driven it means that the data leads the strategy and initiatives not measuring the validity of an instinct because that's instinct driven which sometimes is validated by data quite often spun to make the story work in your favor it's you know i like to think of it as when choosing a restaurant you look up yelp ratings read reviews check out the menu before you make a choice versus walking into a restaurant with a nice sign that you think would satiate your cravings and sometimes end up arguing with your friends that the restaurant you picked was actually good even when you don't believe it because there's a lot of pressure there's a lot of pressure to validating why you did something especially when it fails or assumingly fails so being data driven is letting the data drive the decision that top bar you have questions you build reports you make a decision have action so you might be asking yourself all this all this sounds reasonable oh this sounds really reasonable why wouldn't anyone agree to this and i think it's because sometimes people see numbers just as numbers because they have their own assumptions and they have their own baselines and i had to realize this it wasn't because teams didn't want to change for the customer because that was what was frustrating me it's because they didn't understand that those numbers represented customers i mean that's simple logic but sometimes it's really hard to separate and distinguish and see behind all those numbers but what's critical as an analyst is to bring to life is that you have that duty to represent the customer every single number you report is the customer giving you feedback that you take back to the stakeholder they're telling you where they're looking how much they like something how much they hate something and how often they're willing to use something when you can help others realize the customer behind the data that's when you start realizing how prudent becoming data driven actually is and i'm going to give you four tips on helping stakeholders see the customer behind the data so first sometimes percentages just aren't strong enough so one of the major initiatives for any subscription business is to build a leakage map of your current acquisition funnel step one step two step three step four where are the drop-off points where can we improve so when we built ours it showed that 63 made it from the sign up screen to the plan screen and when this information was brought up to the stakeholders it was met with a lack of enthusiasm however months we later a comment like this on the right and it gets teams it gets the teams to start brainstorming how to solve this issue gets them excited gets them problem solving so my question is why does the left have less impact or why does the right have more impact because for me as an analyst i see the right as a blip it's an outlier a single comment versus an app that currently has a 4.8 star rating with 45 000 reviews and then we perseverate on this but how does one comment spark more discussion about change than the percentage on the left i mean i think it's because people have preconceived notions about what good percentages are just ask any two friends that disagree on a movie based on a rotten tomato score one person will say it got 63 let's go watch it and another friend can say it only got 63 both are saying the same thing but their preconceived notions the the content behind why they're saying it is different so with this analysis there's no context so people see this as an arbitrary benchmark as opposed to the comment on the right as a displeased customer so one of the things that i did is when i flipped this percentage to the actual whole number which is actually 61 000 customers quit because they saw email sign up as a barrier that caused a little bit of stir in a good way so make sure that your percentages are telling the story or use the whole numbers to back up your story sometimes that helps second point second tip is don't bury the actionable insight it's all these are a lot of stuff that i'm making mistakes on so a little a little tidbit so anticipating the a little bit more backstory anticipating the growing need for individual and healthy and positive hobbies during um the pandemic and the time of isolation uh at the end of march 2020 fender offered three complementary months of fender play and we never did that before no catch we kind of just wanted to do our part and since that point we've taught 1.4 million new learners and that have come into fender play to learn guitar and an incredible amount of users hungry to learn hungry to consume during a time when all of us were home you know if you're stuck at home might as well make a little bit of noise so the good part of that is that led to soaring guitar sales because if you flood the market with new learners you flood the market with new guitar buyers so increasing guitar sales to record record counts was amazing but we did uncover something very interesting based on purchasing behavior as we started diving deeper into this audience the gray part is uh they intended to buy or they didn't intend to buy they did exactly as we expected but it gets interesting when you hit the green because 20 of our users planned to buy but didn't end up buying which is a bit concerning so we dove deeper into those users broke it down a little further to figure out if it's something we did or something else that happened and the top two reasons for not making that purchase seem to correlate with the unprecedented times we're living in with the number one reason likely derived from losing their job the the third reason was the most interesting as these users didn't feel they deserved a new guitar until they've made some sort of progress and this was another one of those items that was buried because it was a percentage behind a percentage and it was also ignored because it was third on a list but it is actually the number one item that we can make a difference in today for anyone that's ever learned a skill particularly an instrument they know that there's someone better does anyone ever feel like they're good enough uh at an instrument does anyone feel good no because you look at john mayer and you're like wow that's that's good you know what we can do to make a difference is setting benchmarks you know encouraging their progress could further enhance these users self-conscious perceptions of getting a new guitar because they deserve it if you have the funds if you want to learn it's actually easier to learn on a new electric guitar than it is on an old acoustic guitar that's action is crazy when you realize there's 31 000 people that said this and it's also the number one item to influence it kind of tells a different story so make sure you give proper context to the percentages again whether it's through volume or even just in the presentation of data and what we can affect and what we can use to impact our customers third don't leave things to assumptions so we may have added you know a ton of users we have ton of new learners but one of the most fascinating and frustrating things was that 33 of users that signed up didn't touch the product for seven weeks didn't touch it at all that's over 300 000 users that didn't do that and there were many conspiracy theories going around why what is going on why are they like this like they might be duplicate users people that are just spamming sign ups just to get it done maybe could it be covet impact uh you know is this just a function of covet they sign up and [Music] you know things happen maybe do people hate our product uh probably not but maybe is there something wrong with our platform is there can they not log in you know ideating is healthy but reaching conclusions without digging can be dangerous uh it can lead you just to the wrong path it can you can stray in in ways and develop things that won't impact the customer so this huge cohort of users needs to be dug into so we sent them a survey to break down who they were why they signed up and all these things and here's kind of some of the things that we found you know we asked them what their proficiency was and the results of that became fascinating this group evenly split beginners former players active players beginners intermediate advanced they weren't just one type of player and the reason why this is fascinating is prototypically users that come in are over 70 beginner 70 we've built the we built the product uh to help beginners learn and get over that initial home so again i think that alone tells a lot of the story but i think it's important to split out their answers of why their motivation and their excuses based on the proficiency because we're going to be able to find different things that are that are telling a story so their motivations for starting ended up being as you might imagine vastly different so the beginners had aspirations for learning right this was their chance to do it and while intermediate players they just wanted a refresher to kind of pick up where they left off and advanced learners just wanted to see what play was about potentially to see if this platform could enhance their skills but the common denominator between all of them was that none of these users actually watched one lesson in that first seven week span none of them actually started playing but why why sign up without using it still infuriates me the absolute beginners they cited not having an instrument as the second main reason they didn't start which is a great opportunity to reach out get them the purchase gear up front so it enhances our marketing strategy the number one excuse across all users was time they didn't have enough time you know that's probably not enough information that we need to dig further into but i think something else that did come up with many of these users was health conditions as reason they didn't use the product and i think thinking into that while the pandemic might have boomed the signups it was also a unique roadblock to users getting started um and i think that's where you know sometimes it's easy for us to look at the positive of that but not look at the effect on the other side uh now there's a customer behind each item you find each of these percentages and the behavior tells us so much about a consumer and also the current time period so when you address and you squash assumptions you can really begin to start attacking the key takeaways to kind of enhance the next strategic development and advancement in both you know marketing initiatives product initiatives commerce all of that to be able to better service uh the consumer all right and fourth uh it's easy to focus on the wins but both sides have customers so you know we're focusing on developing new players every day and you know our instructors have been focusing on a pedagogy that relies on habit building little habits you know studies have shown that it takes 66 days to be for a habit to become automatic and we're trying to build up those tiny habits that create lasting lasting change and while it's worked to a certain degree we still know that guitar has an incredibly high barrier over 90 of new guitar players will give up playing the instrument they'll stop progressing even though they were filled with desire to start they leave they abandon and it's because guitar is like going to the gym on january 1st you think about the gym january 1st everyone is dedicated to going to the gym i'm going to make this happen and then a week goes by and you're like i'll go next week a month goes by i'll go next month and seven months go by and you think um how did i get swindled into this membership and i think that's because the idea of going to the gym and also the idea of learning guitar is much more romantic than the actual practice of it because the actual practice takes sweat equity it's hard it's tough it's a journey it's long it's not easy it's not like watching a youtube video and then you consume it it's not like neo getting plugged into the matrix now i know everything it takes the time to build it up and it's hard work that sometimes it's you question whether it's worth it and so sometimes it's something that users don't have and will need us as the company to help encourage them give them give them that outside motivation to keep going and why pour so much sweat and to get all of these users going it's because the benefit for us at fender is for a user that does make guitar more than just a hobby you know using it and turning it into a habit and then turning that into a lifetime skill becomes infinitely more valuable they go from owning a single guitar which most of the time is your dad's relic found in a storage unit somewhere during a marie condo moment to a potential ltv of ten thousand dollars per customer upgrading from your dad's guitar to a mocha burst fender american ultra stratocaster with noiseless pickups and humbucker she's got the goosebumps uh they find the value in relation to their skill so guiding them through that path of success on the learning side yields tremendous results for us on the hardware side but you know so what can we do to influence them and we found that the importance of adoption in that first week really leads to a stronger potential for lifetime conversion as you can see in the blue each lesson that you take the further you go the higher propensity you have to becoming a lifetime player so it's easy to be proud of the impact of the tool to say we've created something that the more you use it the better it is wonderful and you see the happy faces of the customer we have a facebook community where i say it's the most positive place on the internet you won't find a comment section on facebook like that that doesn't evolve into something else you know i think one of the things that we've been trained to do is lean into the commonalities of successful customers that yield higher results and we build look-alike models for that success very sound strategy and i'm not saying don't do that but on the other side it's easy to say that they weren't high value customers in the first place the users that abandoned but we're not here to fill the world with one type of angel we're here to fill the world with all different kinds of angels and for every player that cranks through the finger pain goes through frustration sometimes supplementing with in person instructors having the resources to do that on the other side there's another that just needs a little bit more help before they frustratingly give up on playing again and again and again because it's their dream and we we want to really figure out how we can help them figure out that dream so just remember what users look like on both sides of the bar chart so i think while we are leaning into the things that make a user successful we also need to counterbalance that by taking the time to analyze what could help these failed users cross over into success and we're taking these and using them to inform the next wave of sprints epics market initiatives paid campaigns crm flows that's that's the thing that gets me going helping these users uh get a little bit further so kind of just sum up this whole thing i think it's easy for us as analysts and research professionals to sometimes be consumed by the numbers you know we're constantly parsing constantly building queries that lead us down rabbit hole after rabbit hole after rabbit hole and we're discovering those minor nuances every day and during these sessions we often lose sight of why we're digging in the first place so the key is to remember behind every session number behind every conversion is a consumer that's telling us something you know it's incredibly easy to look at numbers just as numbers but storytelling is all about the characters and the subjects and the journey they take across a movie and how utterly impactful would it be if all the characters and subjects were inanimate objects the story of the rock and the bench that just stood there but that's same with these numbers when they're only seen as numbers it's incredibly hollow and empty but when you humanize them all these numbers by reminding all your stakeholders that this represents customers telling you something that's when every number becomes powerful from the small to the big and it becomes a part of a story and a journey and when you can master that that's when you let the consumer's voice be heard and it can turn into things like this okay and we have a strong malfunction okay i think today has been a very good day better that's sounding better okay nice [Music] that's that's it so um i think that's all i got all right thank you so much cliff i enjoyed that um if there's any questions you can either post them in the chat or in the q a um just let us know we'll take a little bit of time here to see if anybody has some questions if that's okay cliff yeah yeah yeah i'd love to answer anything for you guys uh but i'm also learning as much as you guys are do you actually play guitar cliff i do i do it was a kind of a coming home moment uh when i started 20 years ago in my church band and uh you know trying to buy a fender at that time was you know so difficult as a high school kid it's just as expensive than as it is now and so it's uh yeah i understand the want and desire and how feeling good enough you know kind of um comes into play uh because i think that can be applied to so many different products because i'm not musically inclined at all so i do not play guitar or any instrument for the sake of everyone involved um but for products i do use i find myself you know even saying that like i'm not good enough golf for instance i'm not good enough for that set of clubs i'll just stick with the cheap clubs until i get good enough yeah yeah i we were we were challenged um by uh some members of our board to find the point in which it becomes fun you know to and i think that probably applies to a lot of skill based you know hobbies like like golf is uh when when is the point where you want to do it where you're not just slogging through the you know you know hitting the ball so poorly not getting your putts in but when it becomes like oh oh there's something here that's that's where they challenge us to find and yeah and to get people to that point and keep them engaged all right so we do have a couple questions sure um first um this is from an anonymous attendee otherwise i would say their name but how were the suggestions to improve the app experience generated it was shown on one of your last slides did respondents select from a list was it open-ended and how did you help your colleagues understand that process and where to focus uh so we collaborated so let me answer the first last one first so one of the things that i like to do is um get buy-in from our teams beforehand before because i feel as though once i show the metrics on the back like after it's all done the analysis i find that they are much more hesitant to agree i feel like they're they're inclined to disagree at first uh this this might be too much detail but i once uh lived in a condo where i was trying to pass a sound test um barrier and i hired my own sound test engineers but uh it never passed and the president actually gave me a recommendation he says why don't you invite a sound engineer twice once when the first panel gets down and he tells you this will pass and then secondarily after all of the panels have been placed then sound test it again then he has much more skin in the game to be able to say oh yes this actually will pass because he was a part of the process from the beginning similarly with these surveys and developments we kind of bring up all the things we want to talk about at the beginning we do we both do a list and also have open-ended fields when it's we feel it's very important to otherwise we really like to kind of keep it simple to the main themes that we're seeing and then how we can break those out but for that specific question we had an open field because we thought it was really important to see what the users are saying and we're going to dive deeper into it also with qualitative studies as well excellent and then calvin asks have you tried to gauge the brand equity value of signing up um even when people remain inactive yeah we do a lifetime value of uh or what is the value of an email subscriber someone that comes into the ecosystem so we do analysis of users whether they use it or not what whichever location they sign up from because we have multiple entryways and we try to figure out the value of that because we're spending paid dollars to acquire some of these users so is it worth that bridge and as long as the numbers work out um you know it's still worth it excellent and then nick asks how much have you closed my screen because you know i'm old now uh how much or how often do you include the market research department for this type of research uh always always uh i i always try to get everyone as involved um that needs to be uh as often as we can um i i i think collaboration is so critical for something that's so [Music] people are so passionate about uh people are really passionate about fender play and people are really passionate about its success um both the customers and the employees like we i mean how much what good of a feeling it is to build more musicians and bring more music into the world and because of that people are really they feel really close to it and so i think people are willing to put in that extra effort so i think luckily for me it's easy to get involvement at the beginning and so i i try to involve as many groups as i can that makes sense especially now when everything is so interdepartmental yeah um i understand and then jennifer asks how much of your data was from internal sources versus external um so panel secondary data etc and do you find believe believability of the data changes by source yes absolutely um when it when people are more inclined to believe the analytics data from our own sources uh and and they are less inclined to believe uh research just because i think sometimes so with analytics data it's everybody right you're analyzing everyone and there it is but with research data it's a sample size that is a it it's too uh i'm lapsing on the word but it represents there we go it represents everybody right and because not everyone is going to respond so the as you as you can probably tell from from that one example that i gave of someone speaking up that one it's like are we missing that guy that that is going to say that thing you know are we capturing everybody uh and so it's a lot of education that has to continue to happen because especially something like qual right which they're going to gravitate towards with a lot of a lot of um actual user feedback but the sample size is smaller but with qual it's it it doesn't require as big of a sample size as something like a quant survey and it doesn't require analytics and so i think it's just in terms of education uh that's kind of the largest part of making sure people respect and uh take the data for what the data says yes yeah i found in my career too that that education portion is a much larger percentage of the job than i had expected yeah that's how i wanted to do this presentation because i think in a lot of ways um at least when at least when i start and i started i i thought everyone especially that was above me believed everything that david said you know i was like it's the data how can it's not personal it's it has nothing to do with that this is just what it says but i find the further along i go in my career um people like everyone here on this call are the rarity uh where we are not um we we take the data for what it says and then try to move off of that whereas a lot of people will find a reason not to believe it you know and so that's why i i always like to frame it as the cut there's a customer here they're telling us this it's not just these numbers that i'm creating out of a database out of thin air that i'm trying to push my agenda i have no agenda i just want what's best for the customer that's my only agenda and so that's that's why i like to like this this presentation and this idea is so important to me is because i've used that um method to really help other people see how powerful and how useful data is excellent uh that is all the questions cliff i thank you so much that was um i enjoyed it immensely um okay good obviously you're not data driven um yes i i appreciate that and i think even you know us here at accelerant working for a uh you know on the supplier side yeah definitely applicable as well so thank you so much again yeah thanks everyone for listening in i really appreciate everyone coming in and i hope all of us can continue as data nerds to bring the truth to the world it is always good to get together with fellow data nerds okay thank you again cliff all right guys we're going to
