Nik Samoylov is a Russian who moved to Australia and is the founder of Conjoint.ly, an online service for product and pricing research. He is a former consultant of Bain & Company. Nik was an outstanding student when he received First Class Honours with University Medal in Marketing from the Australian National University.
Catch Nik and find out more about his love for market research, that paved the way to put up his online service company called Conjoint.ly. Learn from him as he details how the process of product and pricing research using conjoint analysis. Also, Nik reveals how conjoint can be useful for all kinds of mass-produced goods and the compelling reason why you need to price up.
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Why you have to check out today’s podcast:
- Discover how they do market research in Conjointly
- How product and market research affect pricing decisions?
- How is Conjoint also used for claim selection of consumer goods?
“Sometimes, people are really afraid of pricing up, and a lot of the time, pricing up is a very good idea. People question the results of market research when the recommendation is to price up more than when it’s the price down. I think sometimes it’s useful to follow what the numbers say and price up if that’s what the numbers say.”
– Nik Samoylov
Get Accelerate Your Subscription Business: Your Blueprint to Packaging & Pricing for Growth Course at https://www.championsofvalue.com
Topics Covered:
00:47 – Three things to know about Nik
01:47 – How he got the idea of building his company called Conjoint
02:30 – Narrating how they do market research at Conjoint
03:51 – Asking 12 questions to several people to identify segments within the market
04:57 – Number of attributes they recommend in a product
06:08 – How the market studies made affect pricing decisions in Conjoint
10:21 – Nik details how Conjoint is also used for claim selection of consumer goods
11:26 – Using Conjoint in building customized products
13:42 – Conjoint is valid for B2B products
15:50 – Automated projects as their primary offering and no consulting work
15:59 – Price range of Conjoint
17:45 – Training program to teach people how to do Conjoint
19:02 – A piece of pricing advice to listeners
19:46 – Where and how to connect with Nik
Key Takeaways:
“Individual-level predictions are not as robust as maybe potentially they used to be, but it’s still pretty good at predicting what the market overall once. And it’s good at identifying segments within the markets by looking at clusters of people who have similar preferences. – Nik Samoylov
“When you want to make a decision for a price, you typically put in your product, competitive products, and then, you want to understand the elasticity of the month and use that information to make your pricing decision.” – Nik Samoylov
“Selecting what to say on the product is quite important, especially because it’s not just for marketing, it’s also for building that product, setting up the factory. Big decisions can be made on the facts about whether people are tuned to one statement or another statement.” – Nik Samoylov
“Conjoint is not only used for consumer goods, but it’s also used for all sorts of goods basically. As long as you have something mass-produced, something where you need to make an investment before you decide what kind of things you’re putting together, that’s when the Conjoint can be quite useful.” – Nik Samoylov
Connect with Nik Samoylov:
Connect with Mark Stiving:
Full Interview Transcript
(Note: This transcript was created using Temi, an AI transcription service. Please forgive any transcription or grammatical errors. We probably sounded better in real life.)
Nik Samoylov: Sometimes people are really afraid of pricing up and a lot of the time pricing up is a very good idea. People question results of market research when the, the recommendation is to price up more than when it’s the price down. I think sometimes it’s, it’s useful to just follow what the numbers say and price up if, if that’s what the numbers say.
[Intro]
Mark Stiving: Welcome to Impact Pricing, the podcast where we discuss pricing value and the mathematical relationship between them. I’m Mark Stiving today. Our guest is Nik Samoylov. Here are three things you want to know about Nik before we start. He is the founder at Conjoint.ly and that’s the reason we’re talking to him today. He’s been a consultant at Bain, so he must be pretty bright and he’s a Russian that moved to Australia, wouldn’t we all like to move to Australia? Welcome Nik.
Nik Samoylov: Hi Mark. Thank you. Thank you for having me.
Mark Stiving: Hey, it’s summer there now, isn’t it? It’s winter here.
Nik Samoylov: Yeah, there’s some, but it’s a bushfire season that started early, so it’s probably not the most enviable summer this time.
Mark Stiving: Oh, well, okay. We’ll just enjoy our snow. How’s that? I really want to talk to you a little bit about Conjoint. I heard of the company Conjointly. I know it was probably a year, two years ago. Someone sent me a note that said, Hey, have you seen this company? And I looked it up and it was an inexpensive way to do Conjoint. I thought, wow, that’s really cool. And uh, and then when I saw you on LinkedIn, I said, Oh, I’ve got to have him on the podcast. We’ll, we’ll invite him up. How did you get into this whole Conjoint thing?
Nik Samoylov: Well, I did Marketing at university and uh, because I went to Australia National University, it’s very academic heavy, very such heavy university. Um, even though I did marketing, it’s sometimes felt I did stats, um, as my major. Um, and I really liked that. I really wanted to make use of it. After I graduated. I applied to every single company, every single market research firm in Australia, uh, after graduating got rejected, had to go work into consulting, but then had to, had to, had to really start doing what I always wanted to do, which is market research and yeah, we started about three and a half years ago.
Mark Stiving: Oh, so you started the company about three and a half years ago. Nice. Tell my listeners what is Conjoint analysis and we’re going to try not to geeky. Okay.
Nik Samoylov: Yeah, it’s a, it’s a very old technique of market research. Um, I think it’s from the sixties and seventies of the last century and it has evolved quite a bit since then. And these days when people talk about Conjoint, they basically mean about a survey that’s a few questions long. Each question is multiple between several options. Each option is, um, is a product idea represented by seven combinations of features, price points. And that can be like flavors, packaging, um, if it’s consumer goods, price and your discount and then they choose between several of them, they make this choice several times. And what we do on the back end after we’ve collected all the responses, we look at them and see it. So it looks like people attending the choose the options that are of color red. So, therefore, the color red is the preferred color for this audience. So that’s international what it is. Yeah, it’s a market research technique that allows you to uh, to understand what people want and what kind of trade-offs they make.
Mark Stiving: Yeah. So one of the things I love about Conjoint is we ask one person several questions. I tend to think it’s 20 to 30, but you can correct me if that’s wrong, then we can pretty accurately predict any choice that one person would make, uh, given us all the features.
Nik Samoylov: Yeah. If you do ask 20 or 30 questions, then yes, you can make a prediction for that one person quite well. Usually these days because of, well I guess reduced attention span. Uh, you can’t ask any more than 14 questions, at least to a broad audience if it’s consumer goods. So maybe individual-level predictions are not as robust as maybe potentially they used to be, but it’s still pretty good at predicting what the market overall once. And it’s good at identifying segments within the markets, uh, by looking at clusters of people who have similar preferences.
Mark Stiving: Oh, that’s pretty bright. So instead of saying, I’m going to get one person to do this for 20 or 30 questions, I’m going to ask five questions of 10 people and I could still get similar type answers. I just can’t say this one person.
Nik Samoylov: Yeah, yeah, exactly. Yeah. Um, yeah, usually so we recommend about 12 questions and that sometimes it’s about, well, most of the time it’s about five minutes for the survey.
Mark Stiving: Nice. Nice. How many attributes or product features do you put when you recommend it?
Nik SamoylovYeah. Yeah. So, so when we talk about conjoint, uh, we tend to talk about attributes and levels. So, um, attributes are characteristics of a product. For example, let’s say yogurts. So yogurts has characteristics such as taste, sugar, contents, uh, type of packaging, price discount. So I mentioned five of them. And then each attribute has levels. For example, sugar content can be no sugar, no added sugar. And then one more can be, for example, no mention of sugar. Usually you can have about 10, up to 10 attributes. So characteristics of a product and then within each attribute tier sometimes have quite a lot of levels. It’s not unthinkable to go even with a hundred levels, but then your sample size becomes a lot larger. Uh, most of the time when people do a Conjoint now platform, it’s um, it’s about five or six attributes. Uh, each one has about five levels and the sample size would be about 300, uh, also for this kind of setup.
Mark Stiving: Oh, nice. Nice. One of the things I love about Conjoint is as long as we have price as one of the characteristics or attributes that we’re going to use, then we can actually say, if I were to change this other attribute by this amount, I would have to change the price by this amount in order to get the same result. So now I can put a dollar value on individual attributes.
Nik SamoylovThat’s what you described, the scope, marginal willingness to pay. So that’s the amount of money that’s equivalent to an upgrade in the future. So what you’re saying is that you can either offer a basic product for $5 or a more advanced product for $7, and the difference of $2 represents the equivalence of upgrade from basic to advance, assuming that people like option A same as option B on average. Uh, so yeah, this is marginal willingness to pay. It’s useful as a, as a guideline definitely. When people do actual pricing work with conjoint, most of the time, um, this measure can be a little bit hard to interpret. So when you want to make a decision for the price, you typically put in your product, competitive products and then, uh, you want to understand the elasticity of the month and use that information, to make your pricing decision.
Um, so that’s, that’s kind of the other way of using Conjoint for pricing that requires that you put your product in a competitive context. Um, so not just your brand but other brands. Um, and that sometimes means that the price points that you can go for another price points that your competitors can go for it. And so you need to also take into account the difference in applicability of features and price points. But in the end, you would get a simulator. So something that’s allows you to do what-if scenarios. So what if we offer it at five dollars? What if we offer it to six dollars? What’s the drop off between $5 and $6? How many customers do we lose to competitors? And then you couldn’t do it for five, six, and $8 and then find the price points that will maximize your either preferences like basically market share or revenue or profitability if you take into account direct costs of selling a product. And that’s, that’s the other, and that’s the other way of pricing in Conjoint.
Mark Stiving: Yeah. So we’re essentially doing a price elasticity type study and we’re either holding the competitor’s price constant or even if we fluctuate it, we can still say, Oh, we can get a dollar more than their price. And we would end up with this much market share.
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Mark Stiving: What types of projects other than just trying to figure out price is Conjoint commonly used for?
Nik SamoylovOther than price?
Mark Stiving: Yeah, other than setting a price.
Nik Samoylov A lot of what we do is about claim selection. So, uh, especially for consumer goods, somewhat I mentioned, no sugar, no added sugar, same for fat, no fat, no added fat, all these kinds of things are a big topic for companies. Selecting what to say on the product is quite important, especially because it’s not just for marketing, it’s also for building that product, setting up the factory, big decisions can be made on the facts, whether people, um, are tune to one statement or another statement. And you know, so that’s, that’s uh, one important aspect of the application of Conjoint.
Mark Stiving: Yeah. So you said claims selection and I just wanna make sure the audience heard that cause I had to struggle to understand what you said. And I think what you were saying was if I’m going to, I only have so much room on the package to claim something. What am I gonna claim? Am I gonna claim low fat, low sugar, great taste, something like that?
Nik Samoylov Yeah, exactly.
Mark Stiving: Yeah. I also heard the Conjoint was used and I was not involved in any of these, but the contract was used a long time ago. Cars used to be sold where you would buy individual options and then they use Conjoint to figure out what are the features that you would put together into those different packages and what seemed to fit well together. Have you heard that? Did you know that? Does that make sense?
Nik SamoylovYeah. So Conjoint is not only used for consumer goods, it’s used for all sorts of goods basically. As long as you have something that’s mass-produced, something where you need to make an investment before you decide what kind of things you’re putting together, that’s when the Conjoint can be quite useful. So cars, I’m not surprised so we don’t work a lot in that industry, but I can definitely see how uh, can, can be used. Another thing though is that sometimes if you are doing a conjoint on a, on one person with 30 questions, if they’re not too tired of that, you can build a profile of preferences for that person. And that profile of preferences is sometimes better than asking them what do you want, what features do you want? Because they might not be thinking in terms of the whole thing and with concern to ask them to make trade-offs between these things.
And if you are building your customized products, it is, it is sometimes the case that people would ask to do people, clients are controlling the exercise to understand what is it they want and then build it to that specification. It can be used for one individual. If the client is a company, you can ask the buyer team to do it and then that gets you to understand what, what is it that they want. So that’s kind of the other application of Conjoint. There is a sister technique called the analytical hierarchy process. There are a few of them that are kind of similar to Conjoint but use not for market research but for group decision making and decision making for an individual. Yeah, that’s an area we don’t really focus on but some people use Conjoint for.
Mark Stiving: I’d never thought of the fact that you could use Conjoint for one customer and use that to build a custom product for that customer because the customer doesn’t know how to explain this is what I really want. And when you do Conjoint, then you could tease out what they want without them having to explain it to you. That’s really good. And so I get asked this question a lot. I just want to hear your answer. Is Conjoint equally valid for B2C and B2B type products?
Nik SamoylovAh, very good question. I think, um, when you have a product where the pricing is, uh, a quote, so when you have to talk to a salesperson to get a quote for you, then the salesperson is probably the better, the better person to know how much to charge. And then there is negotiation then something that you can do in advance. That’s our market research. So in those cases, pricing decisions, probably better left out to a salesperson rather than Conjoint. If it’s a, if it’s a once-off product, maybe again, talk to the customer because of the customer’s right in front of you. And most of these cases when it’s a mass-produced product, Conjoint is essentially a way to talk to a bunch of people and use that to inform what the market wants. So I think, uh, in that case, yes. Uh, so that’s the distinction that’s at some B to B products are really mass-produced, software, for example, subscription, subscription-based B2B product variant. The vendor decides how much to charge and doesn’t really vary the price by, uh, by who the client is. So that’s when it’s really still optical, even though it’s bitterly.
Mark Stiving: Nice. So tell me about conjointly. You guys are obviously a SASS or at least an online type of software product. Do you do the work or do you just offer consulting work or do you just offer the software?
Nik Samoylov: So, we call it custom and automate, sorry. Yeah, custom and automated projects. So automated projects is our main offering, which means that you can look into our, our platform, set up a study, done the correspondence, get us to source respondents, and then you get a report us automatically produced. Sometimes though Conjoint can get complicated and we do a few other things other than Conjoint and you want us to do it, so we’ll execute it. But as, as a, as a custom project, we don’t do consulting though. So, uh, we will not go so deeper into the business objectives. we basically receive, brief, execute.
Mark Stiving: Excellent. Excellent. This has just been totally fascinating, I’ve loved this. One of the things I always used to say about Conjoint when I was teaching it was very expensive and I would use numbers like 50,000 to $200,000 for a project. And inevitably I end up with people in my classrooms once a while I would say, have you ever done one? And they go, yeah, and they would give me a number and it’s always in that range. 50 to $200,000 now this was before I ran into you guys, so I got to ask the question, what’s the price range? What’s the lowest price I could do a Conjoint for?
Nik Samoylov: So if you have a license, you can and if you have your own respondents, well then the cost of your own respondents or if you saw straws, maybe under $300 um, plus license. So the license is 2000 so if, if you’re doing it for consumer goods, usually it’s simple. You can set it up pretty quickly. You can like they have this thing as actually finding images that you would put into the country and then you get the results pretty quickly as well. And that said, sometimes for some industries, you have to go and do it. The really laborious, expensive way. For example, industries such as Telco’s because there are a million plans on the markets. Every, every company has literally dozens hundred plans. You kind of want to take into account all that complexity. And uh, for some industries, some applications you can’t avoid but spends let’s say 50 or hundred thousand dollars on that. If it’s a simple product like consumer goods, like durable goods, like fridges, if it’s phones, if it’s even insurance or banking products, it doesn’t need to be expensive anymore.
Mark Stiving: Nice. So I love the fact that it’s not that expensive. I think one of the things that makes it less expensive is we’re expecting people to be able to do it themselves. And yet most people I talk to don’t know how to do Conjoint. Do you have a training program to teach people how to do this?
Nik Samoylov: Yeah. So we are building tools for insights managers, product managers, marketing managers, notes to their stations. We try to take away all of the complexity of that. A lot of the people who sign up and play with it actually get it very quickly. We too have very strong support. So it’s something that we have to do like literally every day where we handle a few inquiries. So sometimes more than a few inquiries about how to use the platform, how to set it up, how to interpret results and things like that. What I found so far in this area is that it’s not possible to do it fully automated for clients because inevitably if you’re making big decisions based on a survey, you want to talk to someone, you want to be sure that interpreting and tried to assert its upright. And that’s, that’s why we have now a team who, who help with that.
Mark Stiving: Nik, I’ve got to say this has just been a blast, but we’re going to have to wrap this up. Um, I’m going to ask you the question, even though we haven’t been talking about pricing per se, what’s one piece of pricing advice that you would give our listeners that you think would have a big impact on their business?
Nik Samoylov: Very unique, what I’m going to say, but sometimes people are really afraid of pricing up and a lot of the time pricing up is a very good idea. People question the results of market research when they, the recommendation is to price up more than when it’s the price down. I think sometimes it’s, it’s useful to just follow what the numbers say and price up if that’s what numbers say.
Mark Stiving: I absolutely love that. I tell people to raise prices all the time, so that was awesome. Nik, thank you so much for your time today. If somebody wants to reach you, how can they do that
Nik Samoylov: On cojoint.ly website. We have all sorts of ways to get in touch with us so they chat, email, phone, everything.
Mark Stiving: Ok we’ll soon have a link to that in the show notes, but for everybody who wants to know, it’s conjoint dot L .Y. So conjointly website. Excellent. Episode 49 all done. Thank you. That was awesome. I love that. Thank you, Nik. If you have any questions or comments about the podcast or about pricing in general, feel free to email me,[email protected].
Now, go make an impact!
**Note: Mark Stiving has an active LinkedIn community, where he participates in conversations and answers questions. Each week, he creates a blog post for the top question. If you have a question, head over to LinkedIn to communicate directly with Mark.
Tags: Accelerate Your Subscription Business, ask a pricing expert, pricing strategy
