Comprehensive Category Study: Meal Delivery Services During COVID-19

there are any issues if we're having any difficulty hearing or seeing me guys my name is Bill McGowan CEO of accelerant research and I'm gonna walk us through a neat case study that that that we did just hot off the presses during this quarantine and kovat time period and it's in in relation to the meal delivery service category which you know as I'm sure you can all match and has been just off the charts in terms of its an emergence and and its its usage right and you know that's in many cases because we have to be not necessarily because we want to be so it really interesting a category to sort of dive into if you're just joining us I'm gonna go through very quickly our quarantine virtual insights conference ground rules you know here we are at the mercy of the technology that we're all living with day to day so you know if my audio goes out if I have any issues I'm gonna apologize ahead of time but we will be able to record and capture all all presentations today not just the one that's happening right now but but everyone and we'll get those back on on as archived versions after the fact I'd like for you to remind everybody to be respectful to one another don't troll or or you know get to insensitive in the comments section you know do ask pointed questions do feel free to push back challenge there's nothing wrong with that but you know keep it kind does it work right and last thing is you know we're doing a virtual conference here we want to make sure that we are to the extent possible engaging with one another networking with one another we can't shake hands obviously but we can chat with one another so you if you're logged in in the zoom conference definitely feel free to get on board with the the QA and the chat if you are logged in elsewhere get on Twitter get on LinkedIn use the hashtag QV I see 20/20 talk about the content that you're singing about you know feel free to reach out to other participants engage with one another as you would if this were you know run-of-the-mill conference I will say the one thing differing this then your run-of-the-mill conference is it's being hosted by a research company so you know you'll definitely notice some some clunky or transitions from you know one presentation to the next apologies for that we are a research company we are not an event planning company bear with us as it were but you know we're all kind of in this together what we do have is some really great content and what I'd like to do is share some of that content that the team here at accelerant thought would be a worthwhile kind of case study as it were I'm gonna jump right in so we wanted to be able to and you know I'm going to try my best as we're going through this to keep an eye on the QA to keep an eye on any chat that's going on but apologies I have a tendency to get into tommy-boy mode and I may be overlooking definitely as I start to wind down I'll try to you know to get back to that piece of it but if I know if you have a question if I don't see you right away I'll certainly try to get to get back to you trying to get my chat windows viewable here okay so what we're gonna be going over is a nifty little methodology that we've come up with at accelerant and we like to call it a comprehensive category study and the best way that I can describe this is is the old attitudes and usage research study meats ethnography that's big-time right Clash of the Titans we're talking like Mothra meets Godzilla we're talking you know Globetrotters and scooby-doo gang Run DMC and Aerosmith big deal type stuff right I'm gonna apologize ahead of time because those aren't gonna be my only lame pop-culture references throughout this presentation it is what it is I'm gonna go ahead and hit you with another pop-culture reference Adam Sandler from the wedding singer and I believe his quote was I have the microphone so you will listen to every day I'm worried I have to say this is this is where we are right no so a bit more kind of concrete about this methodology and how it works and what it's all about so the a and you piece of attitudes in usage what we do is in this comprehensive category study we approach the you by getting it actual usage not necessarily just your stated from from survey metrics no we are looking for ways to get into database analytics behavioral analytics things that are essentially true reads of what people are doing right what the consumers in a given category that we're studying are up to we also when we're doing this type of category assessment we get into quantum quantitative research base so you know the behavioral we're gonna be getting from from the these analytics the sort of attitudinal coming from the quantitative you know marrying the two together as it were and then also qualitative research and in many cases in the case that we're gonna go over here this is done in the form of what we call Show and Tell ethnographies obviously you know and especially right now when everyone is dispersed and while some focus group facilities are beginning the reopen process it's certainly a you know a clunky process right so a lot of folks are on remote we are big proponents even prior to quarantine of this this what we call Show and Tell ethnography so it's your rather than sending the team to a given participants home we are basically engaging via webcam we get to get into all kinds of different you know screen sharing and you know asking people to toggle back and forth from from you know stationary webcam to to phone screen sharing screens on both devices and you know being able to walk us around their homes going on shopping exercises all kinds of different you know neat techniques that are available to us in this show-and-tell ethnography as it were I've got my screen covered up apologies so you know in this case for this case study and kind of in general so these comprehensive category studies that we do they can be very custom in nature what I'm describing to you is kind of you know an example and a fairly common example of how we we tend to approach so we're talking when we get into the quantitative phase of research you know 1200 category consumers who are also sharing with us you know some types of behavioral analytic feeds and are also not all 1,200 going through qualitative at least not the in-depth you know graphic interviews you know you start doing the math on incentives for for you know in-depth half-hour 60 minute multiple our interviews among consumers and it can get incredibly expensive incredibly fast in this case what we did was 60 minute show-and-tell ethnographies and we did so among I believe it was 20 20 category consumers but again you know these are folks that are a subset of the ones that we talk to for the quantitative research and the ones that we were assessing their their their behaviors okay next slide so we've got this this deck that I'm gonna be going through today and it's it's broken into three types of slides so we're color coding isn't that fun we're looking at blue methodology slides gray finding sides and the gold kind of implication slides and we're gonna kind of hop back and forth and and swirl around as it were as we're sharing this you know the thing that I can say about the study that we're we're gonna get into here is that this was a self funded study so we have you know a fake client as it were that we we did this for but what that means is this is proprietary research that accelerant conducted we this is not a joint presentation with with one of our client organizations this is a study that we did independently and as a result we're able to name names were able to share actual data and results and hopefully you know it's a very interesting data and I think you'll be able to take a lot away from it what we really like for you to be able to do is you know some of what we're gonna share is is gonna be relevant to your particular industry some of it is not but we're really trying to get into some you know just inspiration mention these three phases of research you know the analytics the quant and the qual anytime we're approaching a study like this it's you know the order in which we do those it can vary quite a bit the objectives that we're looking at or getting into they can vary quite a bit so you know we try to customize as best we can you know while staying true to these sort of three legs of the stool as it were right and again you know the idea being that we're getting at sort of that comprehensive picture of whatever category we are studying so accelerant has a panel you know an online insights community the name of it is Agora you know this is our proprietary panel in addition to conducting research you know just administering surveys doing qualitative recruiting and you know doing qualitative full-service research studies with folks we also ask our participants to opt in to certain feeds of behavioral or usage you know data feeds essentially and these you know can be kind of all over the map some are ongoing some are just point in time usage Diaries for example you know it may be a certain study that that folks are asked to engage in and it's something that is this finite but what we're starting to you know realize and recognize is this sort of you know Big Data picture that is taking shape and how we can on a case-by-case basis tap into these different feeds and when we're talking about data feeds among our panel members I'm certainly not referencing like a Cambridge analytical type of you know unbeknownst to them you know scraping and capturing and then selling off personal data in fact this is very banal to them this is all opt-in this is all paying participants for whatever information it is their share I think that is a huge sort of you know looking forward to the future of insights and of you know our value as researchers you know I think blockchain was you know it's been a buzzword in recent years and you know every time I hear someone talking about you know its application to the insights world it's this kind of appeal that we can allow consumers ownership of their data and when is it appropriate to share such data with with the research companies with end-users with you know the world in general when we did our conference last month in April we had a representative from SMR talking about data privacy you know all of the not just within you know the the kovat environment but just in general you know we're getting better and better at being able to target and to grab information from consumers we just have to be very careful about how we do it what we do with it I'm a huge proponent of fair compensation you know a consumer or a panel member is sharing information with us we want to make sure that we are making it worth their while this is what keeps them coming back this is what keeps them longitudinal and this is you know from a research standpoint which keep what keeps them high-quality and what allows us to be able to tap into their information over and over again okay so you know that's the the behavioral piece of it right we've got these these myriad different types of data feeds that we can be tapping it and you know what is our approach with the these types of data it's really trying to fill in blanks when we embark on one of these types of category assessments we're not looking to reinvent the wheel or you know encroach on you know there's a ton of secondary data feeds that are already in place secondary research you know scanner data all kinds of information that that is available what we're looking to do is you know formulate a plan that's going to help to sort of address some of the blind spots that may exist in these types of data feeds right and we're doing so on a very you know case-by-case custom basis okay we're looking at this category of consumers let's figure out what we know about them what we don't know about them you know you think of you know loyalty program members for example or customer database obviously those are very inward looking and we don't necessarily know in addition to what's happening you know in the organization's customer data it's what are these folks doing in addition and that you know you can get into all kinds of loyalty implications there you know MPs for example we know what our shoppers our customers say or or think from a likelihood recommended standpoint from an advocacy standpoint but we don't necessarily know how immune they are to do to others in the marketplace to competitors you know these types of data feeds help to sort of unearth some of that so great you know you're you're an advocate you're super likely to recommend me but you know from a Sheriff while at standpoint you're running around town with every other provider that that's available you know is that truly a loyal customer and then what we're also really looking to do is rely less on self-reported survey responses you know we need surveys and quant research to answer attitudinal and you know to the extent possible for people to tell us what they're feeling why they're feeling it but when we ask questions you know about purchase habits or dollar spent or you know things that someone may have done that's where a lot of recall bias can come into play so to the extent that we can have these data feeds that help us validate and understand you know truly okay did this person buy Oreos in the past three months or you know is it more like you know six eight months ago you know are they not recalling it quite as accurately as you know they may think they are we use this method a lot for you know as a side bar not even getting into like a broader kind of foundational category assessment we use this a lot for just qualitative research recruiting for example you know we need to in a focus group sit you know eight people who have engaged with or shock to certain in the past three or four months using a data feed like this we can actually you know get at that truly we don't have to rely on self-report we you know in some cases people they do try to you know why their way into a research study in order to get the incentive and if they can talk to talk oftentimes they can make it through with you know a data feed they can validate them that's you know it's always a good thing and we get into true share of wild assessments right okay so I'm gonna start going into some actual results here so I've kind of at least tried to get at I know it's a bit of a squishy topic and it's kind of broad but you know keeping in mind sees it's these three pillars these three legs of the stool right we've got the analytics we've got the quant research we've got the qual research and what we're doing is looking at a particular category and you know it's important to I guess when you embark on analysis like this you can't just walk the world in terms of I want you know to know every single thing about every single person no you have to to set objectives just as if you know you're embarking on any type of research study you know what is it that you're looking to learn who in the organization is going to be the end user or recipient of this information you know what is it all about and that helps you shape your game plan your learning objectives and help to answer you know okay which of these different types of data feeds should be we'd be implementing for this type of stuff alright so you know I'm going to take us back in time to start off with back to January remember January so long ago we were you know kicking off a new year a new decade we were so you know excited we were so doe eyed and and innocent before you know the world started to really smack us down we've just met baby Oda like things were looking great right and thence than happen along the way we had a lead day yeah he is so exciting you know the some bad things happen we had you know we lost Kobe we had Australia wildfires but you know from a consumer standpoint we were sort of just plugging along and then we weren't you know and this is the assessment that we're doing this is all in context of you know consumer usage consumer behavior trying to avoid a lot of health implications or you know all that is you know crowding the headlines with regard to code this is really about okay I mean we're all researchers were all you know serving organizations so we want to know what is it that consumers are doing right all right so here we go first week of March that's when the hoarding started that started to set in right and then we got into bunch of shutdowns and so you know I've got I've got a timeline laid out here right so as part of our and I first of all I'm gonna get into these in detail so don't you buy worry about the fact that there's a lot of jumbled mess right now on this page but as far as our first step in in you know the the assessment of the category we set out to assess you know we we first you know looked at essentially expenditures so you know weekly budget of US consumers right so week to week what are people spending and what share of that is going to a bunch of different categories that we look at a bunch of different types of purchases as you can imagine you know the share of you know for example clothing purchases is obviously gonna be much smaller on a weekly basis then you know your share of grocery purchases or you know what you've been spending on mortgage and rent is obviously gonna be far in a way more than your spending at coffee shops what we did is we basically to try to sort of normalize bring everything into you know comparability we started with okay so to what we're looking week by week here right so to what extent does that category that we're looking at represent the share of that week's outgoing expenditures for for a consumer and then we essentially between the beginning of January and the end of April we index to these so you know if I'm looking at you know a perfectly stable category where it represents the same share of purchasing from week to week throughout the first third of the year you know I'd be looking at in this jumbled line graph that you're looking at I'd be looking ahead just a you know a flat line in the middle of the screen right so that would be you know going going in that regard well instead what we see is a lot of volatility and that's what we're gonna get into and you know what was happening so you know winners and losers during the age of code so we looked at you know the the hoarding that was beginning to take place you know the lock downs that were going into effect you know there were certain categories as you can imagine as I'm sure you've been reading about they have done really well versus others not so much you know so we've got the you know the meet Drake meme one to represent the losers drag me into to represent the winners okay grocery that's the first category we're gonna look into you know for the first part of the year kind of bopping along no no biggie everything is staying relatively normal then it got to be you know March and hording time and you'll see you know a pretty big jump in the share of one's outgoing Hill weekly expenditures that's going to grocery and it coincides with everybody stocking up on the toilet paper and the disinfect and then everything else right and what you've seen you know since then as we've kind of embarked on and gotten deeper into shutdown well it keeps going up you know and we've got this dip here after the first couple of weeks of shutdown quite possibly this was when people were realizing that you know the world is not completely over I am going to be able to go back to the store so I can start you know actually using some of this stockpile that I've gathered and I will say you know the hoarding mentality we had a great presentation during last month's conference by Mona Patel she did a very interesting did a research on the whole mindset of the the toilet paper hoarding why people did it and what that was all about so who recommended you check that out if you haven't seen the archived presentations for for last month's conference ok so we look at Walmart and a very similar trajectory right you know starting off the year normal and then just you know kind of up you know a big spike around hoarding time and you know it's interesting that Walmart is you know among the the flatter of the the lines that we're gonna look at and I mean if you think about that they're you know one of the sole retailers or establishments nationwide that's been sort of you know open the whole time right they you know and relatively crowded Amazon you know similar and interesting results so we look at you know kind of ahead of the curve as it were for hoarding we saw a lot of people flooding flooding Amazon presumably for these stock of materials but then you know since shutdowns have been in place more and more Amazon share of purchasing happening right this one is is fascinating and this is this is ATM withdrawals okay so and I will say that you know the left-hand side of our chart here we're looking at you know the first week of January that actually begins at January 5th so you see a spike on ATM withdrawals that under normal circumstances and we don't see it for January because we're missing in first few days but under normal circumstances you see a bump every you know beginning of every month right and that has coincided with you know payday and people withdrawing you see you know and that's normal for for February for you know earliest March and then you know you see a much closer peak as people are stocking up and you know going through the the hoarding right but then what you see is just an immense drop-off as people are shut down staying at home so you know if you're in the financial services industry you know consumer banking those ATM fees that you know are normal though part of the business model have been you know all but drying up in recent weeks interesting that we see this kind of bump in the middle of April as well wondered what that was all about and guess what it coincides with people receiving their first round of stimulus right so they they get their direct deposit and they're getting hitting the ATM rideshare services the ubers and lyft's the world Wow huge drop for those guys which you know it definitely makes sense right you know we saw a bit of a bump leading up to the the new hoarding fest and then just off the map in terms of the claw pick hair category you know followed similar trajectory to grocery and a little bit of an unfair assessment here because the pet care this doesn't necessarily represent just you know I mean you can definitely see the folks were out you know buying up big bags of Alpo I'm sure during you know the other hoarding that was going on but you know picture also represents grooming it also represents you know veterinary services which you know in large part unless emergency have you know dwindled quite a bit apparel another big drop you know we saw in middle January it looks like presumably people you know hitting the malls cashing and gift cards and then you know steady until stay-at-home started to kick in and then wow just a huge drop and I mean if you've been looking at the headlines you you've seen what's been going on a flight you've got you know the JC Penney's of the world you've got the the j-cruise Neiman Marcus a lot of very visible struggles being seen by by apparel retailers coffee shops I thought was it was an interesting because you saw a really big bump in advance of stay at home you know get out stock up on your on your Joe I guess predictably a decline as people were staying at home but then you know a bump around in the same time people were getting those stimulus payments hey who knows maybe they they hit the ATM they hit the coffee shop for a recharge while they were out fast-food is another one and we're starting what we're starting to get into an arrow into here is the subject matter of this case study that we're doing but we couldn't help ourselves there just so many interesting you know it kind of and and the way we like to approach this this type of study or the analogy that we'd like to provide is you know so we talked about the three stool or three legs of the stool right the analytic the quant the Paul a lot of times we we kind of liken those to you know think of Google Maps for example you know you've got the you know very broad global view you've got the more narrow you know a city block view and then you've got you know and we'll you know liken this to the qualitative but you've got that like the street view where we're looking at one individual you know one individuals viewpoint and the neat thing about this type of category assessment is you know everyone that we're looking at they are all kind of the same people so those you know those folks that we're looking at on the Google Street View there are also among that population that we looked at from an analytic standpoint so so you know very powerful to be able to zoom in and out as it works okay so we were talking about fast food you know you saw a pretty pretty decent drop-off as the the shutdowns began and that doesn't necessarily that mean that fast food wasn't being consumed this is your engagement with actual fast food providers and that's something that we'll get into in just a minute as well restaurants kind of similar story big drop-off as the shutdown's went into place a bit of a peak after the first few weeks though and presumably this is when you know restaurants started to get their act together for from a you know a carryout and delivery standpoint perhaps but what we looked at and you know the the subject we couldn't help ourselves to dig into deeper for this case study was nil delivery services so these guys are the beneficiaries of that you know that drop-off in in you know fast food in in restaurant dining it's you know the door - has GrubHub ubereats post mates of the world Wow I mean it's just insanity how you know steep this curve has been growing and it's it's such a fascinating category because you know we're kind of as consumers we're sort of forced into our usage of these right so to what extent you know if I am a door - or GrubHub you know am i sitting back and just you know enjoy it while it comes or am I really digging in and trying to assess you know okay I've got these folks yeah I didn't have them before but here they are they're captive audience what am i doing to try to keep them once this is all over right and we can see that some are doing it well and some not so much so let's see we okay you know that was the the broad kind of kind of narrowing still within this you know we we can look at not just you know their share of you know how they're using a given category we can also zero in and in this case we did own which providers they're using you know and provide a true share of wallet this isn't self-reported this is based on actual transactions that people are actually making and it's it's fascinating you look at you know and this is the the big for postmates scrub ubereats door - then make up the vast majority of purchasing in this category so that's that's who we we looked at for this assessment but if you you know I think all are benefiting from this this wave of you know new purchases that are happening but you you can see you know and we broke this up to looking at you know a collapse to January in February versus March into April grow up digging at the demo and ubereats is really you know from a share stealing standpoint able to kind of take advantage of that it's fascinating you know and you know possibly the impetus behind you know what a lot of us have probably seen in the headlines plate that uber is is making a plight for effort for group hug you know and we actually so you know we'll get into a little bit of this as well so you know we hop back and forth we're looking at you know these these more macro issues and taking a step back you know the approach that we took with with this research the the kind of viewpoint that we decided to take was that of you know if we're in one of these organizations if we are the the consumer research or insights team you know to what extent can we you know help inform the organization for opportunity areas helped to describe what's going on there's a lot of talk out there and assessment of you know even the long-term viability of this whole meal de leur delivery app service model right you know there's ton of VC money going into these guys there's a lot of question as to whether long-term this can even make it as an idea you know can this even achieve profitability one day that's really not what we're getting into with our assessment you know ours is just as its it's the research angle of this right you know how can we help a lot of those lines if we were you know in this organization right so you know we did our macro with the analytics we did our you know narrowing with the quantitative survey we did you are super focused with the qualitative and we did these via what we call these show-and-tell ethnographies these webcam based here's just a quick clip from one of ours this was Carmen and she was talking about GrubHub in specific you know very quick quick clip from her and forgive the yeah we tried to you know do a funky blurring technique from from PowerPoint it reminds me of the take on me video from aha if you remember back in the eighties I'm definitely dating myself I'm just gonna get out of the way and get started on this my name is Carmen and I am calling in from Los Angeles I live in the valley it's like 20 minutes from Hollywood and it's actually raining today it never rains so it's pretty nice I think my most used and favorite meal delivery services GrubHub but it might be changing a little bit during during this pandemic well interesting we'll definitely be talking about that some more okay and we will be talking about that so the voice that you heard was was that of Erica our moderator for the study carmen was was the participant on her web cam talking with us in detail about about work you know the subject matter and you know just to describe it a little bit more this is very interesting the qual piece of this what we did is we call them show-and-tell at ethnographies in this case we did at mealtime a one-hour interview with with consumers so we you know from you know I'm hungry I'm trying to decide what I want to eat where I want to get that food from all the way through the ordering process all the way through the waiting and the delivery and the communication and then even the you know post delivery you know unbagging and usage there aren't a ton of categories where you can spend an hour and do you know a full-blown you know purchase cycle assessments but you know this is one of them and it's just kind of a fascinating way to be able to over-the-shoulder and to again be able to marry that with you know these these clot and and analytics results that were capturing okay so you know they're you kind of come to a crossroads with a study like this and i think i alluded to this earlier but you know I'll definitely underscore that you have to set objectives if you were trying to embark on a have a massive category assessment like this you need to know what it is that you want to to be learning at the end of the day now there's nothing wrong with you know taking a bit of an exploratory tone to it you know the whole point of doing research is to learn right but you have to at least know or have hypotheses and plans about what you want to do with this information so what we did was we came up with you know basically no fake client right so we are a research company serving a door - or whomever and you know put ourselves in their shoes made up kind of fake research objectives in this case we really wanted to kind of narrow in so you know different avenues that we could be taking we could be looking at this from a marketing research standpoint like a consumer research standpoint usability research standpoint innovation standpoint you know a lot of different directions we could be taking this and it's not as if you know you do this research and it must you know answer questions only with regard to one of these buckets but you do have to you know prioritize and and set plans otherwise you get into this you know kind of big data dilemma where you're just inundated and you never get out of the sifting process right so you set objectives in our case we were we're serving marketing so our fake can't client wanted us to look at category consumer personas right so we're gonna do a segmentation study and we're really looking to just understand and personify those those different segments in terms of you know what makes them tick how can I target them how can I you better get in touch with them essentially segmentation study that you know I'm sure many of us have had a lot of experience with right so who we targeted from you know just how we defined our our category users this is anyone who has used one of these delivery services in the past 30 days and this research was done over the course of - what month is it now May this was mid April so right smack dab in the middle of lockdown that we conducted the the quant and qual research assessments so definitely not something that can be you know obviously all things to all people we do have to set those objectives and we do have to narrow our focus a little bit all right and I am rambling quite a bit I've spent the vast majority of our talk on the first leg of the stool but it's exciting there was some really good stuff to talk about and you know the the pieces that I'm getting to into now are a little bit more familiar I definitely you know maybe we don't spend a ton of time on you know the actual results from from each of these definitely not from you know each of our segments go I mean there's an immense amount of detail you can go into to each so I'll kind of hit the highlights yeah did a segmentation we're talking an old-fashioned attitudinal segmentation survey instrument and you know we followed the the pillars of a you know a good attitude with attitudinal segmentation start with summarization and reduction principal components factor analysis getting into k-means clustering analysis goodness to fit through discriminant function analysis and then ultimately okay we've got our segments now it's into profiling them and the old school way of doing that is based on other pieces of the questionnaire right all the self-reported information the demographics the you know profiling the media usage habits the everything that we collect in heart you know massive survey well in this case a ton of that information is not collected via the survey instrument but via these data feeds that we've already established and you know what this allows us to do is not again not rely on the self-report necessarily but rely on actual usage so when we're getting into profiling of these personas and these segments we are able to you know literally size them from from from a dollar value standpoint you know what do they represent how do they act what makes them tick the powerful stuff so we came up with four distinct segments to that we're gonna focus in on the other two it's not as if they're not important but you know this is like the Julia Child's you know cooking show we're not gonna sit here and watch her you know peel the potatoes for 20 minutes know these you know highly-targeted will really good great information if you were the incline on this you would be all over the the results that are coming from it but we're focusing in on just two of the seconds and we're a little crunched for time so I'm going to zoom a little bit through these we've got segment one trapped with children and any excuse for me to use you know my hero Al Bundy is is definitely one that I'm going to take full advantage of you know this segment I'm just gonna read off some of my my notes about them you know these folks they tended to be millennial they tended to have children living at home they tended to have no real strong preference for meal services they are kind of out there using all of them and this is a really interesting thing about this this this whole category is the you know the non loyalty that comes into play a lot of you know one's choice when it comes to to a meal delivery service has to do with guess what distribution channel just like any any type of marketing or delivery what restaurants are you know providing this in many cases folks are using multiple providers and same provide our same restaurant offering different menu items and offerings for different items so I mean you know from this assessment it's just you see tons of opportunity for someone sitting in these shoes okay you know I am this provider I'm getting this influx of traffic what do I do to keep them here I've you know I'm doing this research I'm understanding the pain points and what makes these people tick now how can I shake my messaging what can I do this trapped with children one of the you know really big takeaways among them is substantially higher dollar share based on their so we looked at the behavioral we looked at the dollar share that's going to mil service delivery these folks the trapped with children they represented 27 percent of the meal delivery service audience but and I don't have that in front of me I'm scrambling on my notes but a much higher proportion of or share of the dollars that are being spent that's huge right another segment that we looked at is the we'd rather be dining out these are very reluctant folks right they are they yes the name would imply they are wanting to be dining out there's sort of forced into this you know presumably they would be the ones who are very likely to jump ship whenever you know we get on the back end of this but will some of them stick around you know they've they've used these services or are there opportunities to you know to team up with with local restaurants as a service provider you know offer things that you know and maybe a dessert promotional you know okay I'm I want to go to the restaurant hang out but my belly is full so head back home and have dessert waiting for me I don't know just all types of potential possibilities for all right they don't want to be here they are here how can we you know try to hang on to as much of that that chair as possible these guys weigh over index so and this is again not self-report this is based on you know actual usage metrics that we have way over index on Hulu subscription so you know if I am media buyer for door - and I am trying to figure out messaging you know based on this segmentation that I'm finding out what makes them tick and what appeals to them well guess what Hulu is you know an avenue that I would be very likely to to want to spend on how am i doing for time oh let me zoom in okay so we also did the show-and-tell ethnographies are not kind of described those earlier these were you know the hour-long kind of take us through the entire meal process just the the really cool and rich information that we can get from this is you know we get into screen sharing we get into you know unboxing or unbagging you know getting into reactions and things that are happening right right there in the moment right and I told you we'd come back to Carmen by the way and and we did so you know she said she's trying to describe why she was not so much into the grub hub in pandemic so host mates charges a lot more services and fees like you you think you're getting a free delivery or you think you're getting it just kind of delivery and then you look and there's like $12 in services and fees and I I have felt like in the past that GrubHub didn't charge that many services and fees but I have been noticing I have been checking it out a little bit more through this pandemic and I think they think they're starting to charge a little bit more for services and fees and it if you click on the question it's like this is helping us cover our operating costs so that's why I'm exploring other options like like this uber eats yeah and a couple of really cool things here okay so number one thing that kept coming up over and over again you're not just in the Koala but in the Qantas well with with regard to grub hub you know the frustration that folks are experiencing with them and the you know reason presumably that they're not you know spiking like that like the others is logistics you know a a struggle to sort of keep up it sounds like some some pricing issues that have come into play as well and just from a model standpoint I think grub hub actually you know they rely in large part on orders being delivered by restaurants whereas you know new breeds they've got their network of drivers who as we saw earlier they're not you know the rideshare isn't happening right now so you know they're gonna be on the ball from from a delivery from the timing from the customer experience and customer service standpoint right and maybe this explains why some of the growth was happening so you know sidebar as well so Carmen as she was sharing this with us you know we're watching her screen you know as the clock counts down as she's waiting for her uber eats order to arrive you just think about all the you know usability or you know over-the-shoulder shopping kinds of implications that can happen here couple other really interesting things that we found from from the qualitative is the I guess change in behavior that we've been seeing from folks even those that you know we're using meal service delivery in the past it ain't the same as it used to be go through thank you so much have a good day all right yeah good example of okay you're not meeting the person at the door anymore it's social distance they drop it off and then get out of Dodge the handwashing that kept coming up over and over so many of our participants wash hands before they receive their delivery washing hands after you know in many cases grabbing the Clorox wipes and wiping down every item here's a really good one from Daphne who is one of our participants you know sharing what she does but this case putting it into something else because there's a fear of you know the contamination and dealing with you know these these containers so get it out of that you know get it all in the garbage as quickly as possible come back wash my hands and then sit excuse me sit down and eat all right on shake so running out of time I spend a lot more time on this but here we are research you know research industry and I'm gonna use the you know cliche that's appearing and I'm sorry I'm picking on Budweiser a little bit but you know every ad that you're seeing of light as essentially the same thing that now more than ever in these uncertain times you know I don't mean to make light because it is you know crazy situation and marketers are trying to figure out what to do but you know this this isn't going away as fast as maybe any of us thought at the beginning and from a research standpoint we got to kind of figure this out we've got to start to assess these these categories and understand what our consumers are going to look like you know today's version of your category consumer doesn't necessarily and in fact I mean we looked at all those crazy line charts earlier they definitely don't look like they looked you know a few months ago and you know a few months from now they probably won't look exactly like they do right now but what's certain is that they're changing to some extent and the only way to truly get out that is to do research to assess to try to understand and try to help your organization make the decisions whether you know regardless of which side of the equation you were on you know which of the versions of the Drake mean you are right are you the winner are you the loser at this point everybody stands to gain from understanding you know who their people are and you know kind of the going forward the you know we looked at the the learning objectives crossroads before you know thinking about all the different implications of something like this you know how can it be applied to market research well we talked about that kind of with the segmentation how can be applied to customer experience I think we alluded to this a little bit earlier this you know like in PS going beyond the the customer database you know all kinds of potential opportunities and applications Fran's presentation this morning was great you know with regard to innovation research and test marketing you know can you take you know sort of this snapshot assessment in a an individual test market versus the broader landscape and really get at not just you know do week over week sales increase for this thing that we've got out there but you know what else for these people doing you know is this thing truly disrupted and changing the way that they you know behave all together even volumetric forecasting right you know getting into looking at what happens after this this test marketing right even usability think about you know we we looked at some of the examples here but you know take like ecommerce commerce cart abandoned right trying to narrow in and zero in on that on that audience and and what you know what they're all about what makes them tick all right and I have totally just rambled on for almost the entire hour and it looks like there are questions guys I am going to I'm gonna put my email in to the chat you definitely feel free to reach out to me with questions I will definitely do my best to answer them yes Ari like I said I tend to ramble at times I'll definitely do my best to engage but it looks like we're we're bumping up against an expert presentation and I don't want to step on the margarita stone