How AI is supercharging market research and innovation

Welcome to Mintel's little conversation. Real conversations with actionable insights into what consumers want and why. My name is Andrew Medugo and I'm Director of Beauty and Personal Care Research at Mintel and I'm excited to bring you our latest installment chatting with more of our lovely experts. Today we're going to be taking a look at one of the hot topics right now that we get asked so much about and that we're definitely looking into a lot, diving into this world of artificial intelligence but also its implications for businesses like ourselves but also for our clients as well. So with this I need to have some bright brains to have this conversation with and I'm delighted to be joined by two of my esteemed colleagues and experts in this area. First up we have our very own Senior Vice President of Mintel Futures, Jason Thompson. I've been on the podcast before but welcome back Jason. Hi Andy, good to be back. It's great to have you back and I'm also excited as well to be joined by our Senior Vice President of Data Science and Analytics Ben Arnold. This is my first time speaking to you on the pod Ben but again I know you've done stuff in the past so yeah definitely happy to have you. So hello Ben. Hi Andy. Happy to be here. It's great to have you both here today and I actually have so many questions I want to ask but I do have a vague structure that I should probably stick to as much as possible. But kicking us off there seems to be this kind of growing interest and also at prevention about the capabilities of AI and how it will help us in the workplace as I say here at Intel but also business in general. This kind of should I play or should I go now it's kind of what can I be doing with it as it were. So with this I've also heard some terms been thrown out about AI which I've not heard anywhere else and one of these is Fobo. I don't know if the two of you have heard of Fobo. This fear of being obsolete. So my first question to kick us off is really looking at when it comes to AI and what we know about it. How does this kind of Fobo impact businesses and why do market research companies and businesses in general need to be proactive in learning about new technologies? Okay I'll start off and then Ben jumping at any time. It's something we're hearing from chief execs and investment companies that the senior stakeholders in every organisation have been really pushing people to look at AI and in particular generative AI and it's all blown up as I'm sure everyone knows in the last couple of years and I think the reason is that it feels like there's something magical when they release chat GPT and it could do all these amazing things. It felt like there was it was a real pivotal point and that the world was going to change and so I think everyone got really excited about it. Someone I was talking to who runs a generative AI company, he liked to describe it as if before computers could calculate they could add up and they could do sums and they could do analysis, now computers can read and write and if you think about what opportunities that gives you, a lot of business activity is about reading and understanding and then about creating content and so that's why I think people are so excited about it but no one knows what it means yet, everyone, everywhere is still trying to figure out what it means and so that's where I think people are kind of scared of getting left behind. I know that when we released our first generative AI product and it was in development, we felt like we were in a race, we released Mintle Leap, we pre-released it last December and it very much felt as we were developing it, that there was a race to get it into production. So that's kind of my take on it, that's why I think it's so prominent at the moment. Yeah, it's interesting just, I mean I take, I think I agree with everything you say but I think there's something that's worth highlighting with this technology and others that have come up in the past and I think this is where the term Fogo comes out, the sphere becoming obsolete. I think that when a new technology that seems like it could have a big impact comes on to the scene and I think generative AI and what OpenAI has done and what chat TV has shown is one of those that has just hit us by storm. I think sometimes businesses overreact to a specific technology because they're afraid of that technology forcing them into obsolescence, right? Just something's going to happen, they don't know what it is but the way they're doing business isn't the way that they're going to do business anymore and so they just dump everything into, we have to figure out how to use this tech and everyone has to use this tech. There's another research company, Gardner, they have their hype cycle and I think very much this gen AI, you can just see this hype cycle play out time and time again where there's this huge peak, a new technology hits the market, everyone goes crazy, hey we have to figure out what this is but I think there's something critical that a lot of companies do that I want to highlight that causes this hype cycle to fall into what they call the trough of disillusionment where they've invested a ton into it, it doesn't do what they thought it would do and so then they just think this tech was stupid, it wasn't there, it's not going to do what I wanted to and then there's a few companies that actually identify real value, we'll use cases for it and over time that becomes better known and so I think we're at this point where some people are just saying hey do something with the gen AI, other people are saying this is scary, I don't know how this is going to impact us, let's control this. The thing I would say and I think what we're doing and I think what's really important here is with any tech but especially this one, it's identifying what it is that you are trying to do as a business, what are those things that you have and then if a new technology can actually help on those business objectives, on those use cases then yeah invest it, so I think companies should always be looking at what new tech is coming but I think they have to be really careful to make sure they're mapping it to their specific use cases, think about how it can disrupt them but I think they overinducks on that side of it and they end up missing the clickability of the things. I think you're right, I think it's going to take some time to play out but it does feel like this is a bit different, you know like the smartphone was, there was a hype cycle but it was a fairly shallow trough of disillusionment there, it didn't take long until the applications were found and I think that there are so much happening so quickly now, it feels faster than before as well actually and I think that is a bit disorienting but I know for us we've got a massive long list of things we want to try and applications we can see and I, okay it's my job but I think that this is going to be really really impactful. I think you're right that this could have a shallow trough, I think that for some industries it might be shallower than others right, there's some use cases that are really obvious and that we have to go after and that other companies probably are taking advantage of this pretty quick as well as us but like this use case that we have which is we have loads of contents and insights and research that's all in written form that is immensely valuable but there's so much of it, it actually is, it's valuable because there's so much of it and because it's so rich but it's actually a lot of work to go through it because there's so much of it right, that use case is perfect for this Gen AI, help me find what I'm actually looking for very quickly, that's a perfect use case and I think it's where we've raced to use this as quickly as possible, I think that's what other market researchers really should be doing is what are those use cases that this actually is going to impact and go in on that, not just hey you have to use this technology, you have to just use this wherever and whenever you're using it, yeah, well there's a lot of thought that it will change customer service, we've had chat box, customer service chat box around for almost 10 years and the horrible interactive voice response systems where you get through and end up shouting down the phone because they don't understand you, well they will get better but there's been some really interesting examples of people messed that up, there was DPD in the UK, they released a chat box or upgraded their existing chat box and gave it generative AI capabilities and it ended up swearing at their customers and writing a hi-coo about how terrible DPD was except it didn't get the hi-coo right either and there was an AI-coo- didn't get the meter right at all but and there was an AI Canada instance where they got taken to small claims court because their AI chat box had made up a policy about bereavement flights saying you could claim the money back rather than get the flight rather than that you needed to agree the price in advance and so someone claimed about 90% of their airfare for a bereavement flight because they were given bad advice by a chat box so that's examples of perhaps where FOBO has led people to do stuff a bit too quickly but you're absolutely right I think for us that first application is perfect. It's interesting what you both say because it's almost it's this idea that yes we want to get on top of this exciting technology and use it to the you know there are these uses that are going to be brilliant for us but it's also you kind of have to be using it and going through those processes to figure out like you say there's not one size fits all approach it you have to kind of be using it to understand what the capabilities what the limitations are right now also what the you know if you speak to experts like yourself you'll know what the capabilities are but what we can actually do right now are probably very different with it so it's kind of it sounds like it's trying to figure out the best case or the best use for it right now I don't know there's been so many examples I when you were talking earlier both of you about sort of this new technology and not knowing about it it reminds me of when social media was all well not social media in general but when Facebook and Twitter and all these came on board there was so much clamor for businesses to get into social media and there was so much focus on okay well how do we get ROI's out of this and it was kind of no no you have to use social media completely differently now it's not just it's not just get you know an intern in to just run your social media account you need to have departments on this and I think sustainability as well CSR roles have gone down that route so AI seems like it's down there where it's you need to have the dedicated teams to figure out what is what is the best case what is the best use out of this going forward I mean do you do you either if you have any kind of specific examples Jason you mentioned obviously we and Mintel had this race to get leap launched and obviously that has evolved even over the last sort of six months sort of we have new implementations over which are great but you have any specific examples where FOBO has driven other businesses to adopt new technologies maybe a bit earlier than they planned and then also how that has worked out for them I mean actually I confess I use chat GPT to look up this this answer because I couldn't think of any at the beginning and I knew some of the stuff you're going to be asking me one of the the chat GPT's answer it came up with it gave the example of the Boeing 737 max where and that's kind of related to their needing to adopt technology Airbus had come out with the a 320 neo which was killing it on the on all the fuel efficiency things and so Boeing 737 rushed out their max and I think we all know some of the challenges they had to do with safety issues and software issues and training issues so technology and technology advances do and competition and actually at the end of the day it's the competition that drives you to do it is not not the technology itself is the fear that everyone else is doing it so you have to do it and I think I think that you've got to be careful and you've got to make sure that you know to Ben's point I think part of what he was getting is make sure you know where the value is for you and concentrate on the value not the not the not the technology what would what would your advice be on that though then would it be get out there and troubleshoot as you go or is it the safer option to make sure before I think you need depends on the specific application and the risk and and your your specific environment but the interesting thing is with chat GPT and technologies like it they're kind of like a general purpose technology and so they can be applied in so many different places and I don't think it's possible to do that centrally you can't you know you need to empower people to experiment with it safely and find their own applications in their own ways of getting value out of it and that's one of the things we're trying to do at Mintel is to is to make it more accessible within the right guard guard rails and encourage people to find value from it but there's a danger there because you can you can spend a lot of time missing around and actually kind of go backwards a Boston consulting group did a study last year where and it was with Harvard and water and some some other universities where they looked at how you that they had two cohorts one was using chat GPT and one wasn't using chat GPT and they tested performance of their consultants on a range of tasks and they found that it improved performance dramatically on creative tasks you could use it as an assistant to help you be creative and creative ideation and innovation they found that it reduced performance somewhat on tasks where you needed you were needing to make business decisions and the reason for that was people were trusting the AI so they were using the AI trusting what came back and kind of abdicating their responsibility to think and so you need to be careful about where you do roll it out and whatever you do needs needs to have that that consideration I guess it's just think a bit right my head's going somewhere slightly slightly different based on this question and this conversation and I I agree with you on this path there's all about being mindful of how you're going after something the 737 max and the race to imperfections and that sort of thing is a great analogy of what can happen when you're sacrificing quality and completeness for you know a race to a destination but I think at the core of what we're talking about is trying to disrupt yourself before something else does it's it's trying to about disrupt your own business through the use and stay ahead of where you need to be and I I I generally get this sons that yes the gen AI is amazing and there's so many things that can be done with it and we and others need to think about how it can be used but there's the movie money ball we all love the movie and we think it's about analytics and we think it's about data and we think oh they money ball baseball for those of you don't know watch the movie it's the best way I can explain it but effectively you know Brad Pitt comes in these manager of the angels and Los Angeles I know nothing about baseball is on the data scientist and he entered into a world of professional professional baseball in the US where everyone was trying to optimize their team based on buying the best players and so they had all these stats about the players and they were trying to best by the best players because the best players would create the best team would create you know championship wins would would get you the the world series win logical and it made sense but the whole idea of money ball was that it was the wrong problem they were they were trying to buy players but they should have been trying to buy runs because buying runs is what wins games and wins games is what gets you a world series so same same idea and there's like two different solutions to get to the same end result but people can get lost and over optimization on one metric it's just being the general idea of like any any KPI ceases to become a good KPI once you've over you know once you publish it once you over go after one KPI it ceases to be a good KPI the same thing happens I feel like with technology an innovative solution can can stop you from being innovative if you're over focused on one thing and over focus on that one solution so I think I think when you're thinking about AI and thinking about technology and how it can help you do what you need to do this is obviously impacting this world and obviously needs to be considered as a capability that can help you and ourselves do a lot of new things but if you focus on that technology and not on this is what we need to achieve this is what our clients want this is what our users want this is what our users need how can we help them get there instead say how can gen AI help them get there you'll have the gen AI answer and maybe not the truly innovative answer I mean this is the blackberry the blackberry was great but then it just took you know the iPhone to come out and then take it to bed so this sort of thing I love I love the stories you've used to relate to there because I'm immediately now thinking yeah we're thinking about gen AI or thinking about how can AI help us with all of these big problems when actually to use your money ball example we just need AI to get us on first we just need to load those bases like they're doing those little steps first to get there so I kind of I love the idea because again I know from what we're doing I mean tell there's a whole host of and Jason you will probably sort of scoff at me when I sort of say they're all the different all the different things we're thinking about with AI because you know a lot more than I do but it's amazing just to think of there's so many different implementations we could have of this and there's so many different ways it can help our clients and help us as a business and help us functionally but it's all about okay let's how do we get how do we do those little things here and there just to tick off rather than thinking that has to be this one big solution that it must solve with everything it's almost looking at okay how does how do we how can we sort of have that implemented application of AI to help us to free up more time for our employees for our experts how does it help them and and give them sort of turbo charge them and sort of add more value in the market research is helping the human side as well I think you're absolutely right is it our experts one of the things are really differentiator and empowering those people is really important but actually the focus shouldn't be on the AI the focus should be on what those experts can do to help our clients grow their businesses and and how they can join the dots and put things together and and make recommendations that actually make a difference for people and I think we we are aware of that this is this is something that where we are keeping very much in focus and I do think that AI has the power to do some of that stuff and I think it really does I think it can help save people a lot of time but only only if it's a implement executed well only if it's implemented well but I think that's some of the stuff we're going off to with our big long list of things 100% and I mean I'm not to plug ourselves right I think that's why we're working so well together is because I'm a data scientist which basically just means I'm a data skeptic and I approach everything with what's wrong with this and if I can prove everything not to be wrong then it's right and you can't just have that you also have to have the the optimist of everything you know this is all the things all the great things that this could do but if you have just one you know 100% yeah I am that unrealistic optimist and I'm the overly pessimistic pragmatist right and but together we meet in the middle somewhere you have to go after it but you have to be realistic as well and and the other thing I want to say in relation to AI is I think we all have different ideas in our heads of what that could mean but artificial intelligence this term is not is not new because of conversational AI because it's generative you generative AI isn't new like it's it's just a new application that is more obvious than it's in the immediate use of implications it's got an excitement but artificial intelligence is just programming of computers to do something that looks like something a human could have done right and that can be that can be as tactical and explicit as just explicitly programming a chatbot to say hello when someone says hi to it right or or manually mapping words in English towards in French like it can be as basic as that it would still you know you could you could force it to look intelligence if you put enough time in it what we have now is much much better than that and I think that's what's what's powerful about it but what I'm trying to get to is there are other applications of AI that I fear some people are just totally forgetting like the linear regression as an example is something that's still used all over the place and is really powerful to just understand correlations of two points next to each other basic it doesn't solve everything it's not great at everything but don't don't try and solve a problem that could be solved as linear regression with this massive large language model right I mean there's you have to have both sides of this and and I think this is this is on the same point of you have to be looking at the problem that you're trying to solve the aware of the of the technologies they're available to solve it but don't over force on one tech use them appropriately to solve the problems that you have yeah 100% I love I also love the image of having one of you on each one of my shoulders so one being the positive one being the negative there's I but that's so that's a balance that I'm happy with and very comfortable with as well and I also think it's fascinating as well you mentioned there about it because that is with I guess with any technology in AI is the technology of the time right now but you do rush to think right any to implement this technology but actually what you've said there is it's kind of actually what the most important thing is what you actually want to do with it and then find your best solution rather than thinking I must use this solution to yeah I think that's right but the thing to bear in mind is that the advances in technology just over the last couple of years have made things possible that were not possible 12 months ago even six months ago and more than that some of those things they've made possible with an order of magnitude less effort than you would have had to do something similar you're on the nose Jason rush to understand the implications rush to understand the technology don't rush to to shove it out into the market without understanding it well but I think I think and that's what I'm trying to say yeah hundred percent well and if you do you see stuff go wrong if you if you you know you still need to think you still need to make good decisions about things but there are opportunities here and that's what I'm excited about and it's happening so fast and it's happening faster faster so you definitely need to be investing in thinking about this and and spending time on it as an individual if you're in the space you need to be doing it and understanding the implications it has within in any industry right and I don't think that there is a person in the world who couldn't use this this technology in some way shape reform if it was accessible for them you're right but there's there's still and this is the other thing if you think if you're listening here today and you're thinking oh well late we've got to rush at it we're to you know the sky is falling in you got to remember that I think there's been a survey there was a survey done maybe by the Wall Street Journal recently where they said or someone did it reputable and they said that still only 54% of adults in the US have heard of chat GPT and then a smaller percentage were were using it at all and then a smaller still percentage were using it regularly and it and it it's like low it's low tens of percent are using these technologies regularly so there's still a long long way to go to adoption and to your point about companies needing to find the best applications chat GPT is great for a certain sort of things those kinds of technologies are great for a certain set of things but I don't think yet there's the killer app I think that's I think that's still to come yeah we still we still seem to have I mean with it's interesting you say there those figures from that study that we think is Wall Street Journal about the sort of the the use of it because there are so many skeptics out there as well as much as there are so many pro people who are using it and and trying to promote as heavily as possible and finding great ways to use generative AI specifically it is interesting there is still this skepticism there and there is still there's still a lot to learn as I say it's this evolving beast if you like and so I guess from from our point of view how how would both of you say how can we use AI to get better data or to create better models and analysis in our it's sort of in our business specifically how do we get the best out of it how do we ensure that there is this balance between the human and the AI this notion that the best insights come from human intuition interacting with that sort of artificial intelligence and vice versa what would you say is the best way to go about this I think we have answered this question based on what we know of the technology right now so I mean I want to just put that out there in two months time there could be you know a new model that's that's going even better and further than what we're at but I think the first thing that comes in mind is this idea of the well Jayce you can speak to the closed loop architecture that we have with how we're using it with with our lead mayi which I think is ultimately important because we have insights and reports and content that our experts are doing research into and creating that content and I think application of AI in that East case is being able to do deeper and richer research right so as as AI assistants are coming out in different fields are as our own is being created you're able to spend less time finding proper information now some of that needs to be replaced with more time validating it you have to be careful there right and I think that's that's an important call out there's some there's some use in these technologies of helping helping your just natural creativity and as you're as a researcher you're you're asking questions to yourself and you're digging through and it's helpful sometimes to be able to talk to it's the rubber duck as software developers we we call it a rubber duck you know you you want to talk through your code to a rubber duck just so that you're having to vocalize it and think through it I think that these aIs can be that rubber duck to researchers and people that are generating content and generating research and creating insight and can be powerful in that way so long as they're validating where those things are coming from and that's in the creation side of it there's the user side of it then which is the same thing but in reverse which is using these aIs to find human generated insight and much more easily much more quicker and so it just it just explodes it's it's information transfer right this is like this is like a step in how we communicate information between humans like the written word was it was you know it can go so much faster and so much more quickly in this with this technology that's the interest I've never thought of it like that that's an interesting way of doing it it transforms information from one format to a more useful format that's that's kind of interesting but to but I think some of what you're saying is that you've got to find the right applications so you know if how's it going to help how's it going to transform things you've got to find the right applications and and is really good at reading and summarizing and transforming information one of the other things that you can use it for and we're starting to do this is if you've got a huge amount of data to process text data and there are a lot of companies doing this kind of thing one of the things it can do is it can understand data at scale and extract not insights but facts or key key terms or key concepts from that information and it can do that so there are applications where you can use it to do that kind of stuff and you can analyze data sets that would that you wouldn't do by hand because it would take you too long so analyzing verbatim from surveys that that's kind of a fairly obvious thing that you can get it to do and helping you find the themes in those things and as Ben says you don't just then trust it you then verify it and and and review it but that's one way that it can help unlock the power in in existing content and data is to is to help you analyze the meaning of content that you've got at scale that you just wouldn't do by hand so that that's that's one thing yeah translations yeah transcriptions along the same thing as well transcriptions you can you the multi multimodal AI's or the the voice models now are getting really good at listening and understanding what you're saying but AI generally and we use this and your team's done a lot on this Ben is it helps you find patterns in data that you wouldn't otherwise have been able to find and that massively transforms and elevates the value of that data and that I mean that's kind of more traditional AI if you like but the value that should not be underestimated it's fascinating all the two of you so both of you in this by in this brief conversation we've had have mentioned so many different applications already so again there's not like a one all we must do this so we must do them all but it's just finding what works right for you I know from speaking with a number of ingredients supplies for example and people working in regulation around ingredients in the beauty sector for example a lot of them are saying to me I couldn't do my job without AI now because it we've we've trained and we've we've coded in a certain way that it again it finds the information it gets that it does everything quicker for as it saves us that time it's really fascinating because it's that idea that we do have to be flexible sort of with this with this technology and sort of have your target find the right application for yourself and I love what you said earlier actually Benazoe about try to disrupt yourself before someone else or something else does it I love that kind of idea behind that is there unfortunately I think we're probably coming to the towards the end of our conversation we can definitely talk about this and I probably will try and pressure you both to come on the podcast again and just continue this conversation to the Philippines this half hour is absolutely flown by but just to end is there anything you predict or how do you predict the role of gen AI specifically because mainly what we're talking about at the moment how do you predict that will evolve in market research over the next decade and do you think I would you want to put your neck on the line and say what the next big thing is going to be big question to end their boys but there we go for my part how is gen AI going to affect things I think as the technology gets better and companies get better applying it for their specific applications and individuals get better at using it I think it is going to transform people's productivity right I mean and that's what I hope happens is that everyone has more time and if productivity grows in our business and anyone's business then growth follows and kind of that tide lifts everyone in individuals and companies so that's what I hope is going to happen and I think there's every chance it will in terms of what the next big thing is that's almost impossible to say I don't I don't think I don't think that gen AI as it stands is the solution for artificial general intelligence you know super intelligence is but I do think it's probably part of it and that will either come up with new things or new ways of putting AI components together and when that happens I mean it's possible that everything will change but but again there'll be an adoption curve and it will take years and years for that to happen it won't happen immediately now for the pessimist view I know I was going to say that we need to balance that we have to balance and this is going to be more of a warning I think in market research in particular and other fields that are generating content and insights we have to be we have to be careful to not allow computer generated insight and summarization to force us into this average because that's what can happen right yeah this is going to allow us that what's going to happen is we're going to have one way more written communication than ever before because chat GPT these generative AI is going to make written conversation much more efficient and so as a result more data more written conversation is going to come out of all of this and if we rely too heavily on and on the AI's as they currently exist to generate all of that content eventually us as humans are going to start to recognize what GPT created versus what a human created there's going to just be this uncanny valley of it seems too perfect or it seems too on the nose or it seems too just like what a normal average person would say and doesn't have any unique characteristics or personality in itself and maybe there's some things that can be created to combat that but over time there really could be a fear of just you can start to see you know this was an AI personality versus a real personality and we could lose creativity we could lose real thinking and we could just end up having information that we have today in our world be this status quo in terms of market research I think other industry sciences and stuff that connect different impacts but in ours more more content is going to be created and I think in order to stand out you're going to have to have unique and meaningful content or at the very least that's that's my pessimist view and it's more of a warning and might not actually happen I mean let me follow up on that because I think you're right but it doesn't have to be that way right you don't you don't have to use it to create more less helpful information but here's a risk I agree there's going to be two types of companies there's going to be the ones that over index on efficiency and end up creating just land contest that we're just not not newsworthy not innovative not really critical and then and then I think there's the path which I am which you and I both are pushing mental to be on which is this is about empowering our human expertise to to be more human and to to to spend less time on the mundane and more time on that critical and that's what that's what's really critical but there may be a section of our industry that goes to conformity what I think is going to happen in the future and you sorry we're going over has nothing to do about AI and I know nothing about this field it's just my gut but as we as humans use this and rely on this tech more often and it becomes more applicable in more places something is going to have to happen with regards to our technology around how we extract and store energy and how we do compute these models are massive and they consume tons of energy in tons of space and if it's truly going to be as powerful as we're thinking it's going to be and it's going to have the impact everyone that that we think it's going to have something has to happen on that side I know nothing about that that's just my my philosophy for you. No but I love that I love that I say you heard it here first now that's and again you may well have you may well have hammered your master in there to when when this topic does come up in future so we're right we're going to have to go speak to Ben about it now but no I thank you so much both for your your rap on there is almost perfect because you say it was an optimist and pessimist but I think we can probably all agree on the fact that it is going to be this balance of whether whether you are an optimist or a pessimist the the good thing for humans is that the future is going to be this balance of this artificial intelligence and human roles working together and how we how we navigate that for the future is going to be the challenge but it's also going to be hopefully quite rewarding as well so thank you both very much thank you Jason thank you Ben I know your time is very very precious so thank you both for being here today and having this conversation as I say I will try and push and get you back again but thank you both anyway for your insights thanks Andy thank you and thank you very much for listening as well but the conversation doesn't end here if you head over to mincelles linkedin and instagram page you can let us know what you think we'd love to hear your thoughts on AI and how your business is using it or how you see the future looking in this space as well whether positive or negative they're all welcome views here if you want to know more about mincelles then visit mincelles.com and sign up to become a member of the free mincelles spotlight community and make sure you never miss an episode of mincelles little conversation by subscribing on iTunes Spotify or wherever you get your podcasts so all that's left for me to say is again a huge big thank you to Jason and Ben both for joining me today again thank you very much for listening goodbye for now and we'll catch you next time on the new episode of little conversation