Ep 294 – Dispensaries Are Re-Engaging Old Customers Thanks to This New Platform

andrew watson happy cabbage

A big problem for cannabis retailers is how to re-engage once enthusiastic customers.

CEO of Happy Cabbage Andrew Watson tells us how dispensaries are using his platform to rekindle customer relationships.

Learn more at https://www.happycabbage.io 

Key Takeaways:

  • Andrew’s background in cannabis and how he came to start Happy Cabbage
  • An inside look at Happy Cabbage, a data analytics and insights platform for the cannabis industry
  • Ways Happy Cabbage re-engages previous dispensary customers with highly targeted, personalized messaging
  • Analytic tools Happy Cabbage provides dispensaries that enable them to measure the success of their campaigns
  • Generating customer excitement through experiential events
  • Similarities between stripper economics and the economics of dispensary product placement
  • Dispensaries currently working with Happy Cabbage and how they’re using the platform to re-engage their customer base
  • Andrew’s experience with CanopyBoulder, a business accelerator and venture capital fund for the cannabis industry
Read Full Transcript

Matthew Kind: Hi, I'm Matthew Kind. Every Monday look for a fresh new episode where I'll take you behind the scenes and interview the insiders that are shaping the rapidly evolving cannabis industry. Learn more at cannainsider.com. That's C-A-N-N-A-insider dot com. Now here's your program.

A big problem for cannabis retailers is how to reengage once enthusiastic customers. Andrew Watson, CEO of Happy Cabbage is today's guest and he's going to tell us how dispensaries are using his platform to rekindle customer relationships. Andrew, welcome to Canna Insider.

Andrew Watson: Hi, Matt. Thanks for having me.

Matthew: Give us a sense of geography. Where are you in the world today?

Andrew: Right now I am in Boulder, Colorado, but Happy Cabbage Analytics is based out of San Francisco, California.

Matthew: Okay. What is Happy Cabbage on a high level?

Andrew: On a high-level, Happy Cabbage Analytics is a integrated data platform that is really empowering cannabis business owners, particularly small cannabis business owners, with how to target their customers and revolutionize the insights that they're able to garner from their point of sale data.

Matthew: Andrew, how did you get into this crazy world? What's your background and journey like and how did you come to start Happy Cabbage?

Andrew: I come from a background of actually corporate finance, data science. I spent many years at Salesforce. I spent a few years at One Medical and I actually started getting involved in cannabis in about mid-2017 in which I started doing analytics consulting for a small delivery service out of Oakland that was doing maybe 30 orders a day. Started to do some very basic prelim analysis like said, "Hey, you know, you have these opportunities with your customers. Hey, you have these opportunities with your pricing." By implementing those insights, that customer was able to take his business from doing about 30 orders a day to about 110 orders a day, in a six-month time-frame.

It was a really wild ride, a really exciting time, and with that, we managed to see and my co-founders got involved in that process, and we managed to see how successful a cannabis business can be even a small cannabis business, who doesn't necessarily have a very technically adept business owner can be empowered by analytics and can be empowered by data if it's given to them in a very simple way. We took the software and the stuff that we started built with that owner, and we packaged it together into Happy Cabbage Analytics about a year ago and I've been going to market with it ever since.

Matthew: Okay, let's dig into this a little bit here and set the stage. How often do customers visit dispensaries right now based on your data, what's the average?

Andrew: A regular customer and that's someone we define as having ordered three or more times, orders on average every 20 days is what it looks like.

Matthew: In the intro, I mentioned rekindling customers who are once enthusiastic but have not been back to the dispensary lately. That's a really frustrating thing for a retail owner because it's like you have this relationship that's like what happened? What went wrong? Why did the enthusiasm fade? How do you reengage them and make them excited about the dispensary again?

Andrew: That's a core opportunity that we see a lot in our data is how cannabis business owners will have cannabis consumers, cannabis customers, who had been engaged, had been enthusiastic, hadn't come back in a long time, right? First, what we do is we empower with that business owner with being able to even know who those people are, and then we empower them with the ability to segment and target those customers with very personalized messaging, right? If I purchase edibles, right? I'm a regular edibles consumer, and I haven't come back to the store in many days and I get a text blast of advertising like we have discount ounces of flower, that's not going to be relevant for me. I'm going to feel as if, "Oh, this is just a robot texting me. I don't vibe with this. This doesn't mean anything important to me."

If that message says, "Hey, I miss you. I know you used to come in. I know you prefer edibles and because of that, I'm launching a really great new brand on my shelves that I think you'll like." That's a lot more personal and that'll resonate with me as a consumer in a much bigger way, and that's the kind of messaging that we out of the box empower these cannabis business owners with.

Matthew: Okay, so you mentioned this can really easily turn people off as well as turn them on depending how customized it is and understanding what the most important top of mind thing is for the person that's getting that text message. Everybody's gotten some of those and it's like, "Oh, man." In fact, I'm on somebody's list for the person that the cell phone number before me seven years ago, and I still get text message. That's very top of mind for me, how off-putting that is. It can be a really two-edged sword here if you use the wrong way, so you got to respect it like the force, dark side and the light.

Andrew: Now, I would say that makes a lot of sense. A key thing about us is that we see customers who start like that, they're like blast, blast, blast, blast. What we found is that we can drive a lot of ROI for our customers like tens of thousands of dollars of return on investment in a month. The average consumer in their customer base will receive a single text message that month, just one per month. It can be really impactful if you're doing it in a really targeted impactful way.

Matthew: Okay, so if you were looking over the shoulder of one of your dispensary customers who are using Happy Cabbage, how will they actually see how successfully an SMS campaign or text message campaign was, how is that measured? How does that look to them after it's sent out? Let's say it was sent out two days ago, and we want to take a look at what happened. How is that actually measured, it's like a conversion and see how successful that was?

Andrew: We surface it back up as a very simple UI, a very simple table where you can see hey, here's my messages that I sent. Here's how many customers I sent per campaign, what the opt-out rate, what the delivery rate was basic SMS numbers everyone's used to seeing. Then we have the actual impactful numbers which are 24 hour ROI, seven day ROI, 30 day ROI, and then we then service up the sum of all the ROI that they've gotten within the month.

The mechanism we use is the same thing that Google uses. When you see how much your paid Google searches drive last touch attribution. What we do is we see whether or not somebody went into the store after receiving a message. Did they go into the store? Or did they go online and order delivery within 24 hours, 36 hours, seven days, 30 days, et cetera?

Matthew: That's interesting, keep going.

Andrew: Well, in particular, then what we're also able to do is then if you talk about, okay, what segment did we go after? If we went after a segment that hasn't ordered in 90 days and then we see, "Oh, wow, we were able to generate thousands of dollars from that in 24 hours." That is a very impactful, very clear ROI to the end-user, and those are the ones that we try to focus them in on in terms of articulating our value prop.

Matthew: Even when you get an SMS message and it's the exact fit for your needs, the first time you might be like, "Yes, I'm coming in, and this is a exact fit, I'm going to buy some flowers, some edible, some infused products, some vape cartridges." Then there's this really fine line where it's, even though you know my psychographic profile, it's one message too many. How do you get right up to that where you're delightful and don't cross the line to pain in the ass?

Andrew: Yes, that's a great question. Making sure that we're not really texting more than one a month per consumer, I think is really important. Making sure that the messaging is actually powerful and impactful. Everyone has the right to opt-out, right? It's all based on opt-in opt-out behaviors. If they've joined the list, and they've said I'm willing to be on the list, I'm willing to receive this information, it generally means that they're more inclined to want to receive messaging.

That being said, we're a data-first company. We're constantly learning from what our customers are doing with our platform, and with that, we can start to actually build predictive models around these customers and say, "Hey, customers who have these attributes need only this amount of engagement in order to come back. Customers who receive too much engagement are likely going to drop off. Let's predict that utilizing our machine learning that we have the ability to embed into the platform."

Matthew: What kind of customer data do you wish you could get that maybe it's not accessible now. Would you like political preference? Maybe you probably already have age but I'm just thinking for a political campaign the day after the presidential election, if you know someone wanted a liberal candidate and that candidate won, you could say, "Let's celebrate." If you knew someone who was a conservative candidate, then you could say, "Let's lick our wounds with this discount on a pre-roll." Is that getting too personal? Where's the line and what kind of data do you really want to get to complete that profile?

Andrew: Yes, that's a great question. I come from I mentioned a background doing data at health care companies. In a healthcare company I worked at, we had the same issue when it came down to thinking about what data do you need to understand whether or not somebody is going to go into the doctor. You gather so much information in healthcare.

You gather so much information about people's healthcare conditions, age, demographics, diagnoses and still it's not enough. What I find is that demographics, although they are the known knowns, although we can say like age does this, gender does this and although they are predictive most of the time, you can find out a lot about what you need to know based on just observing the behavior of what they're doing.

Going back to the healthcare standpoint, we didn't really need to know a lot of that extraneous information if you were able to just describe a model that really understood some of the causal factors that you're able to observe that lead to healthcare behavior, same thing in cannabis. Cannabis usage cuts across income, it cuts across demographics, it cuts across political preference based on the surveys that we've been doing.

What we can really start to see is let's describe people who are purchasing edibles on Friday at 12 and let's observe their pathway through their purchase and let's start describe them as a group, let's start to try to predict their behavior as a group. Ignoring necessarily, maybe inserting any other demographic information or other sort of things that we think are causal but focusing on the actual outputs of what they're doing if that makes sense.

Matthew: Yes.

Andrew: I think that's where really impactful, really good models come from is not throwing too many variables in, focusing just on the outcomes and similarities amongst people that are producing the outcome you're focused on.

Matthew: I feel like we're kind of reaching peak concern in privacy or people want a transition to something else and we're right now even talking about data points for customers, it's because we don't have specific examples that we can say, "Jane Doe or John Doe." I feel like sometimes data is like this impersonal thing and if there's some way to make it, treat the person like a person, how do you have that discernment to figure out how to treat the person like an actual person while still having a mass message?

That seems like a really tricky thing but are you really looking at what the headlines and the text message should be and the content of the message like is it fun? Is it playful? Are you relating as a human? Or is it more just get right to the point like "Hey, this much off, you come in today for this product."

Andrew: What it comes down to is a lot of understanding the business context from the business owners about what a certain group of customers, how that business owner believes that they behave, believes what they want, believes what they are. I can come in as the data person and I can say, "Here's a segment of people who order in eight every 14 days who are probably likely to purchase another eight at this point in time."

To that business owner, they go, "I've interacted with the people who purchase an eighth every 14 days. I know that resonates with me as people. I know because I've been in the store every day and I think that they would like this kind of messaging." Let's implement that messaging and let's see how it works. Okay, that messaging really worked, let's replicate that for other people that look like they would also like that same messaging.

That messaging didn't work? Now that we know that, let's test and let's figure out what messaging will work.

All basically using really the business brain of a small business owner, a dispensary owner who knows their customers the best. We do not know their customers better than them. We just have the ability to describe and segment the customer base in a way that makes it resonate with them as opposed to just having a list of 10,000 people you're texting every day.

That's I think how we can inform really personalization of messaging as opposed to just making it seem like a robot is sending you messages.

Matthew: You told me earlier there are creative ways you can make in-person events based on customer preferences. Right now we've been talking about sending text messages to get people into the dispensary just to purchase product but there is ways to generate excitement, an experiential event around a brand, can you talk a little bit about that?

Andrew: Yes, that's great. We have a retailer in San Francisco who-- One thing that he does is bring brands in for promotional events, set up a booth. I'm sure you've seen them if you've been into the dispensary. They set up a booth, offer to demo the product and everything like that but if that's between 4:00 and 7:00 PM on a Thursday, who's to know who's going to show up in the store?

What we're able to do is we're actually to take our platform, identify people who are likely to let's say that it's Canndescent in the store. Identify people who are likely to purchase Canndescent or people who really love Canndescent say, "Hey, look, we know that you really like Canndescent or we think that you're probably going to like Canndescent. In order to help you through your consumer cannabis journey, we're bringing them into the store so you can go to them and talk to them and ask them specific questions about the Canndescent products so that you can observe and learn more about CCanndescent."

With that, we're able to drive meaningful results of-- It's not going after a lot of people, it's maybe only going after a few hundred at a time bringing them into the store and actually having them engaged and then both the brand and the dispensary then make an ROI on the investment of having someone in the store for a few hours promoting the brand.

Matthew: That's really helpful. Now, let's talk about delivery. We already talked about people coming into the store and you mentioned delivery but how is delivery different in ways that are important for listeners to understand and what you can do in creating a campaign for delivery?

Andrew: California is a really interesting market when it comes to delivery. Most if not all of the four walls of recreational licenses also give you the ability to do delivery. Every dispensary, brick and mortar, technically also has a delivery business that they can run out of the back of the business. It's good for those businesses because as long as they make a margin on each individual delivery, it helps increase their profit because it helps get them more sales out of the same fixed costs of the store.

One thing we found that's very impactful a lot again with the tool is our geographic capabilities. We can say, "Hey, we know our competitor is opening up a brick and mortar store in the west side of the city." I live in San Francisco, I'm thinking like out by the ocean but we have customers who live on the west side of the city, out by the ocean. Now, they, because of the convenience, might get brought into that competitor store.

It would be really awesome if we could engage those customers with our delivery offering so we can actually compete in convenience against that competing store that's opening out. What we do is we find the geographic segments, say to those customers "Hey, what's it like living out by Ocean Beach? We know it's a hike for you to get downtown and purchase at our store, did you know we offer delivery? For you, we're offering 20% off, et cetera, et cetera, et cetera."

With that, you can actually seed an entire delivery business from your existing customer base and get a really great revenue stream without having to pay $5,000, $10,000, $20,000 a month to get on weed maps, to try to acquire new customers. We've seen that be very, very impactful and a very, very good thing for businesses in California to do if they're trying to get that extra amount of profit at the end of the month to keep their business afloat.

Matthew: What's the price points for people that are listening that might be interested in being a Happy Cabbage customer?

Andrew: We price competitively to other SMS products on the market right now. I like to say that we're not an SMS product full and through, we are a data product and we incorporate an SMS feature in order to action upon the data. That results in us being more affordable and we try to price it therefore more affordably than some other usage-based products.

In particular, we have no hidden fees, no upfront fees, no over [unintelligible 00:19:26] It's just fixed flat month to month. We price it at about $1500, gets you about 50,000 customer engagements.

Matthew: You often compare the economics of dispensary placement of products and brands to stripper economics. Can you talk what that means?

Andrew: [laughs] Yes. For the listeners who are not aware so strip club economics, the stripper economics as I like to call it refers to the fact that in a strip club because there really aren't a lot of labor protections around the strippers, they're contract laborers and they're forced to rent the stage they perform on. Then after they're done performing, they pay the rent and then they also have to pay the bouncer, pay the DJ, and essentially, it's a big pay to play market.

Shelving space in a dispensary is basically the exact same model. If a brand wants to be prominent and get a really good time slot or really good placement on a premium shelving spot, they have to or more and more dispensaries are asking them to pay to get into the store. That's hard.

It's good for the dispensaries because they are saying, hey, look, our shelving space is valuable. It's limited. It's good for the brands because if they believe that they'll get more traction they can pay, but both of them are going to feel a little bit like, okay, how much ROI am I really getting from this? The dispensary is going to say what if I had given that to a different brand and the brand's going to say I'm paying a few grand a month to be able to do this. Am I seeing results?

What we're able to do is bridge the information asymmetry and bridge the gap, and basically say to the dispensary owner, hey, if you want to prove out to that brand that their investment on your premium shelving unit was worth it, let's start driving that brand campaigns to people who we know via our recommendation engine or via just like they're purchasing these products a lot, people who would like to purchase that premium.

We say to the owner, hey, you can even go back to the brand, and we would love to be able to work with more brands with this and basically say, hey, I can guarantee your investment. I'm still going to need it but I can guarantee return on it because I have a tool and I have the capability to drive customers to that shelf. That's a big thing that we work on with our dispensary clients.

Matthew: Happy Cabbage is a pretty young company at this point, but you're already in some dispensaries in California as you mentioned. Can you talk about who you're working with and how they're using the software right now?

Andrew: Yes. Actually, most of our clients are now actually our delivery businesses, and then we have a dispensary in San Francisco. Each client is very different. The dispensary in San Francisco is catering to a more affluent client base. Generally speaking, more premium products, we can see that they're really big on how to do different brand promotions, how to do in-store traffic, bounce their delivery business. We also have a delivery client out of Oakland who actually has a geography that spans all of Sacramento, Tracy Stockton, lot of Central Valley, much more lower-income, but actually higher engaged population. They are really keen on making sure that they are making sure they're going geographies that may have lower retention, and they're re-engaging those geographies. They're really keen on making sure their VIP customers are constantly getting discounts.

When they do bring on name brands, they're also keen on making sure that those name brands get traction by promoting them through a tool before they invest necessarily in more upfront inventory for that brand.

We see it's clients of all shapes and sizes of populations that are all shapes and sizes. That's a really key interesting thing we see is just how different demographics across the Bay Area behave associated with cannabis.

Matthew: You’ve an interesting way to visualize cannabis flower on a cost per gram basis between markets in California. Can you talk a little bit about that and maybe where the price points are at right now?

Andrew: That's a really great point. One thing we do as a data company, we are always out there collecting information, collecting data. One thing we do is we mimic how Google collects information about what pages to search. We use that to collect pricing information available on different menus basically of dispensaries. We target some dispensaries and we monitor what they're advertising, so we can monitor price changes across the whole state and really, we have thousands of them across the country that we're looking at.

With that, we've been able to observe this really fascinating trend with flower in California, which is commodity pricing. Effectively, a unit of flower, an ounce of flower, a gram of flower, an eight of flower is all priced pretty much the same in a price per gram ratio. This is not true when you get to like vapes, concentrates, edibles. Basically brands there are able to ink a margin and they’re basically able to price a premium for smaller quantities. In flower, it doesn't matter. Basically an eighth is 3.5 times more than a gram and a ounce is eight times more than an eight. What that means is it's becoming a commodity. What that means is it's getting priced down to the way apples are priced and potatoes are priced.

It means that it's really great for consumers because they're getting some of the best prices we've ever seen in the open market. It must be much harder for brands and wholesalers because it means that it's very difficult to ink a margin on flower, and particularly if you think of like the vapor crisis and stuff, there's not a lot of other avenues for them to go to, to make sure that they're inking a margin and that they're actually getting a premium, as opposed to like I mentioned flower where pretty much they must be selling it at cost, given these price dynamics that we're observing.

Matthew: I'm not sure if you're in CanopyBoulder now or you are alum. For people that aren't familiar, CanopyBoulder is a seed-stage cannabis accelerator focused on ancillary cannabis startups. Can you talk a little bit about your experience there, Andrew?

Andrew: We are currently in the winter 2020 cohort, about halfway through it, which is why I'm out here in Boulder, Colorado. It has been an amazing experience. For us as a smaller company, we were able to gain revenue, gain traction before we took the investment from Canopy, which made us feel as if we are actually really well set up for a program like Canopy because we're able to go into it and really have intentions about what we're trying to achieve. Where before maybe it would have taken us time to maybe iterate and market test an idea with advisors, mentors, major players in the industry. Now we're able to talk to folks across brands, across retailers, across investors, and very quickly gain feedback, gain understanding and get some rapid iteration on our product and our sales cycle that is really helping supercharge our business.

It's been fascinating. It's also really fascinating to see how cannabis out here in Colorado is performing how different than it is in California. The ability to branch out and see how different markets are working are very valuable as well.

Matthew: What is your perspective being from California and Colorado right now? How do you compare and contrast the two markets just from being a visitor?

Andrew: I like this. I always like to put this point about how we really need to put the size of California into context. Colorado, I agree. It has become a more "mature" market. It is more vertically integrated. You have multi-franchise things. You have more corporate operations in place. The entire state of Colorado has fewer people than the San Francisco Bay Area, and the San Francisco Bay Area is less than half the size of Southern California. California is the sixth-largest economy on the planet.

It is so large, so vast, and so wealthy really in a lot of ways economically that it's really difficult to make equivalencies across smaller markets like Oregon, Washington, Colorado, with the entire state of California. I think that there's a mentality that California is a little bit more of the Wild West, that things are a little bit more nascent, things are a little bit more hectic, things are a little bit more mature and calmed down and stabler here in Colorado. There's truth to that. Again, because of the size, let's say San Francisco managed to be a solid consolidated market like Colorado, and the rest of the state is Wild West.

We would still think of the whole thing as Wild West simply because of the relative sizes. Because of that, I do think that there's a huge opportunity in California for people who are willing to go for the ride, but there's a lot of learnings in Colorado about what this business is able to achieve that we need to take back there, but really do them at scale.

Matthew: I also read that I think it's Los Angeles County consumes more cannabis than all of Colorado. Colorado is such a big state but not densely populated that sometimes it's hard to visualize how the different populations are. There is a California vibe in Boulder, and also now in Bozeman, Montana, which feels like it's becoming like Boulder-like. Interesting things happening there. Where are you in the capital raising process? You mentioned you took investment to be part of Canopy Boulder, do you have other investors? Where are you at right now?

Andrew: CanopyBoulder was our first outside investment outside of our founding team. We are actively in the program seeking to raise our next round. If there are any investors listening and they would like to get in contact with me, please do, but we're pulling that together. Our hope is to be able to raise some capital by the end of June.

Matthew: We'll get your contact information out there for listeners at the end. Let's go to some personal development questions here to help listeners get a better sense of who you are personally, Andrew. Is there a book that's had a big impact on your life or your way of thinking that you'd like to share?

Andrew: Yes, I went to Reed College, studied economics there. One thing at Reed is that you have to write a year-long thesis to graduate, which is the most intense and rewarding experience I've ever had, I guess outside of founding a company. [chuckles] One book that was published that was relevant to my thesis at the time was Thomas Piketty's Capital in the Twenty-First Century, which actually was published the second semester of my senior year. It was relevant because I was writing a thesis on income inequality in the United States and that book fundamentally changed my view and understanding of how one can take a very data-driven approach, a really thorough look at historical data, a really thorough look at even sparse data sets, things that we didn't really have. He goes back to the early 1800s, early mid-1700s to pull together and weave a strong story about data, but then also to lead it to easy- not easy, but powerful conclusions, I would say, an understandable conclusion about society.

That book was really impactful for me because it taught me how one can use data and information to describe society. Then one can go one step further and also use that data information to advise and how we can improve society. That was really impactful.

Matthew: Now, what kind of results does Piketty promote? I'm trying to remember, is it more of like socialism or what is his endgame in his mind?

Andrew: He's a prominent economist at the Paris School of Economics. What he points out is if the return rate on capital, the rent that people make on capital is higher than the GDP growth rate, so if you make 5% interest rate on a loan, but GDP growth is 3%. That means that that extra 2% you have to be taking from somewhere.

What he points out is that the majority of human history that was society. He said that look, feudalism has lasted a lot longer than the Industrial Revolution, and based on the data, feudalism is probably returning. The conclusions he makes is we've seen in a few times if you basically just make sure that your GDP growth, you stimulate growth, and you do it in such a way that you make sure that the capital is flowing throughout all parts of society, then it can increase and so to that aim, I think in America we have probably labeled a few of those policies probably like "socialists." It's capital taxes. It's making sure that we're redistributing wealth appropriately, but what he points out and what he correlates to other studies that have been done is that if you don't do that your overall growth of a society, overall growth of a country is probably going to lag and stutter as a result. It's very data-driven and I would encourage it for anybody who wants a really good understanding of just how modern economic analysis and modern economics, macroeconomics is working.

Matthew: What is the most interesting thing going on in your field besides what you're doing at Happy Cabbage?

Andrew: I would describe my field as the intersection between cannabis and data science. One interesting thing that's going on in data science is the concept of machine learning fairness, which is a concept pioneered really by the Google AI folks, and I recently sat through a keynote talk at a Data Science Conference with them and it's really fascinating. What machine learning fairness comes down to is if you have a machine learning model that's trying to predict something like probability of repayment on a loan, and that machine learning model has the ability to observe certain factors of people. For example, it can observe race, it can observe income, it can observe gender.

That machine learning model is likely to inherit the biases that we as human society have into its own model in its ability to predict the outcome because the majority of people who get loans and have been able to repay back loans come from a certain segment of society, and the machine learning model is probably going to say that qualities of people from that segment of society are more likely to repay back loans and therefore that machine learning model's going to recommend if you have a bank, that only people of a certain race and class receive loans.

This is a concept of fairness. Basically, what it comes down to is if the society has biases and racism, the machine learning model will also have it. There's entire departments at Google who are responsible for making other models to check whether or not the models that they're making are racist at the end of the day. In cannabis, we have all of this great data and there's all of this movement into saying, okay, let's like start applying ML. Let's start applying AI to cannabis data. One thing I'm very conscious of with that is hey, wait a second, where are the majority of all the cannabis data? If we talk about all the major market research providers, where are they getting their data from? It's not from the smaller kind of gray market retailers who are serving maybe lower-income communities. It's from the nice stores in San Francisco that are serving higher-income communities, which means that if you start building models around people's cannabis preferences and predictions about their cannabis usage and stuff like that, you'll start going to actually do the same thing, you're going to inherit the bias of the society of the data that you're selecting from and start to use that to predict certain things and start to use that to serve that community.

That's something I'm very conscious of. It's something I'm already starting to see in our own data when we look at different cuts I mentioned in the city of San Francisco versus the Central Valley. Just I think it needs to be more upfront and talked about the fact that hey, this industry is inherently political. What we're doing here is inherently comes on the heels of years and years and years of a relatively messed up society. As we're producing data, and as we're producing insights, and as we're empowering people with data and insights, we need to be really careful that we're not propagating biases in society because data can do that.

Matthew: Good point. Here's a peer review question for you. What is one thought you have that most people would disagree with you on?

Andrew: As it relates to cannabis, I would say the one thought that I have a lot of people disagree with me on is the power of the black market in California. I think that the concerns about the black market are valid. I think that they're a little bit overblown. I think it's blame every problem with the fact that the black market or the legacy market still exists. Just say that that's the reason why things aren't successful. I think that when you look at the pricing behavior I just described, if you had a legacy business who survived for years off of the fact that a gram of flower cost $20 to the cannabis end user, and all of a sudden, everybody can go online and search cannabis prices and they can see that oh, I can get a gram for 15. I can get a gram for 10, I can get a gram for five because of the legal market bringing on that amount of information, that's going to compete prices downward.

Unless your legacy organization can survive and thrive despite the falling price, your legacy organization is going to go under. In Oregon, the price of an ounce went from a few hundred dollars to $50 because of the supply. There's no way that that didn't impact these long stronger legacy businesses, particularly those ones that basically need to price a risk premia if they're operating in the black, or I guess in the illicit market price a risk premia at every step of the way. It'd be very difficult to compete against delivery that can give me an ounce for, I guess like $50 in an hour.

I think that there's a lot to be said about how to price economics can really turn an entire market around in that maybe the gray market is still a large problem where people are taking it out of the legal market at the last step of the way, but I think that the black market is definitely struggling due to the competition for the legal market in California.

Matthew: Now, final question. You mentioned you went to Reed College, and that's where Steve Jobs went before he dropped out I believe.

Andrew: Yes.

Matthew: In his Stanford commencement address, he talked about how you can't see how the puzzle pieces fit while they're going on, but he took a calligraphy course there and just because he had an interest in it, not because it was requirement or anything and that was directly responsible for the ability to change fonts and personal computers and most listeners may not remember, there was only one font in early PCs. Did you take anything at Reed that just for the love of it to calligraphy or otherwise that you felt, hey, this was just for fun, but it really enhanced my life?

Andrew: Yes, I was a very serious theater kid at Reed. I study economics, data science, and theater. Theater changed my life. I cannot stress it enough. If you've ever wanted to do an acting course, you ever wanted to try theater out, you got to try it. I think what I enjoy about it is the parallelisms between putting on a play and founding a company. Where what it comes down to is this notion of you create something from nothing. When you make a play, when you put on a Shakespeare production, you're taking a blank stage, and you're pulling together a whole bunch of people and you're pulling together a script, which is just a few pieces of paper, really, and you're building something and you're training people and you're creating life, really and then you're getting people to cry and laugh at it and then you tear it down at the end of the day.

That experience of creation and that joy from creation is something that I feel passionately about, and something that I always wanted in founding a company and then led me to entrepreneurship because it's a lot of the same ways. You start with just an idea and you really build it into something, something that can add a lot of value to people's lives. You go from there.

Matthew: Andrew, as we close, how can people that are interested or dispensary entrepreneurs that are interested in using Happy Cabbage reach out to you and also how could accredited investors reach out to you that if they're interested in investing?

Andrew: We have a website, happycabbage.io which you can go to to check out some of the information and then I encourage you to email me directly. I'm Andrew, A-N-D-R-E-W @happycabbage.io if you have any questions, accredited investors, potential customers, let me know and I'm happy to answer them.

Matthew: Andrew, thanks so much for coming on the show. We really appreciate it. You've got great traction, you're still in the accelerator, and you've got traction. That's awesome. Congratulations, and we look forward to hearing more.

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Andrew: Thank you so much.

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