In this video, Richard Schreuer, CEO of Echo Cove Research and Consulting talks about best practices for pricing research and a new way to value brands.

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Check out our recent pricing webinar with Topline Consulting partner Richard Schreuer: B2B TECHNOLOGY PRICING OPTIMIZATION


Video Transcription

[00:00:00] Topline Strategy: If you want to figure out how much your prospects are willing to pay for a product or feature, all you need to do is ask, right? Well, actually, prospects aren’t always the best judge of their own buying habits. Even when they’re trying to be truthful, the way that you ask the question, and the way that the prospect buys your product, can affect the answers in unexpected ways.

And that doesn’t even consider the times that the prospect is outright lying, because they don’t want anyone to know exactly how much they’re willing to pay for something. Today. I’m speaking with Richard Schreuer, CEO of Echo Cove Research and a partner of Topline Strategy, the sponsor of this video.

We’ll discuss the state of the art for determining the maximum price that a prospect is willing to pay, how to use that intelligence to maximize revenues or profits, and [00:01:00] some of the big problems that can throw off pricing research, particularly brand. Finally, Richard will discuss a way to reverse engineer a stronger measure of brand equity than anything that’s currently being used by brand consultancies.

Thanks for joining us today, Richard. Tell me who you are, where do you work, and what do you do.

[00:01:25] Richard Schreuer: Hi. My name is Rich Schreuer and I run a consulting firm, market research firm called Echo Cove Research and Consulting. And I specialize in quantitative research and particularly with lot of work around pricing.

[00:01:40] Topline Strategy: I’ve encountered other consulting firms that do pricing research, and it’s a lot of qualitative questions about what people are willing to pay for things. Is that, how you approach it? [00:02:00]

[00:02:00] Richard Schreuer: No, indeed. That is a very old way of doing pricing research and it’s been demonstrated to be…. Well beyond not useful, actually misleading and inaccurate. And the reason is because asking about pricing is one of the hardest questions to do in market research because well… a couple of reasons. One is because many people will underestimate how much they’re going to pay, partly because they know that research is going on and they want to say a low price.

So, when you’re asking people directly, they’ll often underestimate it. A bigger problem is that pricing needs to be framed. Folks will often pay a very different amount than they originally anticipated based on what competition is spending based upon the combination of products and services that are combined.

And when you ask people just upfront, how much will you pay, again, [00:03:00] it’s not only inaccurate, but you often get misleading numbers that dramatically underestimate what people would actually pay in the market.

[00:03:06] Topline Strategy: So there are perhaps more nuanced approaches to asking about price like a van Westendorp and getting a range or going to multiple people with multiple prices and determining a bracket.

Do those things solve some of the problems that you just…

[00:03:29] Richard Schreuer: No, it really doesn’t. You mentioned the Van Westendorp technique. All that really is, is kind of a fancy way of, again, asking people what they would pay. And the Van Westerndorp technique, you ask what’s the least you would pay before you question quality what’s the most you would ever pay.

And what do you think is a fair price? And sometimes another question. So you’re getting multiple price points, but at the end of the day, you’re still asking people what they would pay. And it is again… Folks just really can’t give you an [00:04:00] accurate answer, what they will actually doing the decision-making process when in the market.

Um, the other thing you mentioned is something called split samples. You basically have a big sample and you cut it up into equal pieces and you describe a product. And for each one of these little pieces, you put a different price in, so you can see how people respond as prices go up or down based upon their likelihood to purchase.

This is a really blunt instrument because technically it should be reasonable, but you need really big samples that get expensive because once you cut them into small samples, you get a lot of margin of error. And the other thing is, is that you can’t get very nuanced about what you would include or not include in a package because what you’re doing is you’re simply reading or have somebody read a description of a product and then say, “The likelihood of buying it for this price.”

So, yes, but it’s a really blunt instrument that can be very expensive for the lack of depth of information it provides. [00:05:00]

[00:05:00] Topline Strategy: Now you’re talking about taking different features from a potential package and then asking what people would be willing to pay for each feature. Is that, did I get that correct?

[00:05:15] Richard Schreuer: No, that’s not really… that’s not really it. What developed a number of years ago is… actually it’s been around for over 25 years, is an approach called conjoint analysis. And the newest version choice-based conjoint. And what it does is, or what we do in that, in that technique we put together the list of features or services that could be included.

And we make a list of them. A list of, obviously, our client brand, but then other competitor brands and a range of price points. And what we then do is we vary all of those in combination. So people are seeing different brands, offering different feature or service combinations at different [00:06:00] price points, and folks go through probably 16 questions like that, and we’re very carefully varying everything.

So at the end of the day, what people are doing is they’re looking at a description of products and services at a brand and a price, and they’re comparing it to a couple of others. And they’re saying is “which of these would you prefer, and would you actually buy it?”

And then behind the scenes from the raw data, because we’re varying everything, we can then sort out a price-demand curves, how much demand there are for particular features and products. So it’s much more robust. The other benefit to it is that it simulates the decision-making process much more than an older technique.

For example, you know, here’s his service A, how much would you pay? Here’s service B how much would you pay? And then so on, and now let’s kind of add them up and see how many to be willing to pay for a package that contains all of them. People don’t think in that way, they think more in [00:07:00] terms of, of reviewing a holistic package for a price offered by a brand, and then deciding whether or not they would be inclined to purchase it based on the base, based against the competition.

And then thinking more fully would they actually do it.

[00:07:15] Topline Strategy: Right, right. You don’t get to set your price for each feature and then put the features together in a package. It’s not the way that most products are offered, but the context can lead to a lot of unusual and sometimes irrational decisions, right?

Like I’m, I’m thinking of the example of where people would be willing to pay more for terrorism flight insurance after 9/11 than they were for flight insurance that covered any eventuality. Knowing what the context is relative to the feature will change the price you’re willing to

[00:07:52] Richard Schreuer: pay for the feature.

Right. Oh, totally. And, in fact, one of the newest fields in [00:08:00] economics it’s called behavioral economics. And one of the founders of that recently won a Nobel prize. But what behavioral economics does is talks about the decision-making process. And, in fact, when people make decisions they’re not purely trying to maximize their “utility” there’s emotional factors they’re making trade-offs.

But one of the things they found in this is that when you’re trying to understand what people will do, you need to ask them about it in a context that is as close as possible to the actual decision-making process. And one of the beauties of conjoint is that it does simulate that in some way, much more closely than asking people a list of features on a zero to 10 scale and saying, how important are they to you?

And now when you actually buy it…  we don’t think that way. People don’t think that way. And so the choice-based conjoint approach is much more powerful in terms of disaggregating what goes into people’s purchasing decisions, [00:09:00] but then putting it back together again. So we can look at what is driving purchase and even plot price, demand, curves so we can see how demand shifts as price goes up or down.

[00:09:13] Topline Strategy: Keeping it in the context of buying, it makes a lot more intuitive sense, given that we’re human beings (and they are) irrational creatures, present company excluded, obviously. So how do you manage to get a clear picture on what people are willing to pay for given packages without getting into very large population sizes. Or do you, do you need a very large population?

[00:09:51] Richard Schreuer: No. No, you don’t. And in fact the technique I’ve been talking about choice-based conjoint has been the gold standard [00:10:00] in consumer research, around pricing and product development for a very long time.

So, consumer companies have used that approach, both to set prices, but also to sort out which particular product features are the most compelling and highlighting those in advertising, and so on. In, in the past, those have required pretty large stamps. And very specialized programs to actually do it, so they’ve been very expensive.

Recent developments in software and analysis has allowed us now to do this exactly the same approach, but with the smaller samples. And typically in B2B (business-to-business) research unlike consumer research, the samples are smaller and often the research budgets are tighter.

And so really in the past five years, we’ve taken some big steps towards applying this gold standard that’s been used in consumer research and making it available in the B2B world.

[00:10:59] Topline Strategy: Just [00:11:00] curious is the fact that B2B was… that group was a late adopter of this type of analysis. Was that a function of cost, or was it something else?

[00:11:14] Richard Schreuer: No, I’m not sure that they were necessarily a late adopter in terms of, in terms of technology, because a lot of the same market for market research firms that are doing consumer research with clients are using this technique, but they weren’t necessarily doing it with B2B clients.

I think it was more a function of this approach evolving software that allows it to be executed more efficiently and quickly, and more work to allow us to be comfortable with smaller sample sizes. So I think it really is a function of it becoming more accessible and consequently, the price for doing a well-executed study has dropped to the point where we can now use smaller samples and often B2B companies, not always, certainly, but often, will have smaller research budgets and some of the larger [00:12:00] consumer company.

[00:12:02] Topline Strategy: Early in my career, I saw a company that had launched a new product that was pretty much identical to the incumbent leader in the space and was being offered at a competitive price. They thought that they had a blockbuster on their hands, but when they eventually took it to market their prospects told them, eh, pretty much does the same thing, and it’s a little bit cheaper, but we really like what we’ve got.

So obviously brand is a pretty significant factor. How does your pricing research anticipate that type of response?

[00:12:42] Richard Schreuer: Well, it goes back to that notion of one of the benefits of this conjoint (analysis) is that it begins to simulate an actual purchase process.

Now, if you go in and you have blinders on and you run a study using [00:13:00] state-of-the-art choice-based conjoint, but all you put in is your company with the products and features and would you buy it and so on. You’re, you’re going to get a set of answers. But in this particular marketplace was dominated by an existing brand and what you would have learned if you had had the wherewithal to actually put in the competitive set is that this particular brand had so much let’s call it brand equity, right?

The brand name itself had so much power that it would have told you how far you had to cut your price to begin to erode market share. But it probably would have told you if this was a high-risk business and folks trusted this leading brand, and this brand had huge market share. It probably would have told you, “don’t challenge them in the short-run.”

Or if you’re going to challenge them, it has to be so inexpensive. You’re going to lose money. So there are examples where they’re technically better products that [00:14:00] are out there, but they never get adopted because of inertia. Because of the dominance of existing brands. And so the research has to be designed carefully so that you’re taking the competitive setting into account.

Otherwise you’re going to get really misleading and generally, really over-optimistic numbers.

[00:14:17] Topline Strategy: Hmm. Very interesting. So I know this isn’t your primary line of work, or maybe it’s not something you do at all, but it sounds like you could reverse engineer conjoint analysis to see what the specific premium a customer was willing to pay for a particular brand name and from there, extrapolate a much clearer view of brand equity than I’ve ever seen. Is that correct?

[00:14:47] Richard Schreuer: Yeah. That, yeah, that’s totally correct. I mean, brand equity, the term is kind of funny. There’s 50 different definitions on it by 50 different consultants, and it means everything from, at one [00:15:00] extreme high equity is a strong brand, right?

At the other extreme, which has really… I think how the term was derived and what it should mean, is how much more people willing to pay because of this brand name? Right. That’s the brand equity. And so yeah, this approach can be used, and indeed it has been used, is to assign the value to a brand and the way you do it is somewhat straightforward.

You build into your model, the products and features, you build into competitors. And sometimes we’ll put in just a brand that nobody has really heard. You may even make up a brand, a generic brand, right? And then you run simulations and you save for the brand that you’re interested in with the exact same feature set.

How much more are they willing to pay to get to the same market share? So you basically raise the price, raise the price, raise the price, and you get to the point where the lines cross for market share that versus another brand or that versus [00:16:00] the generic brand. And that’s, that’s, that’s a very clear indication of brand equity.

That is what the brand name is worth in the consumer’s minds. Right? Not in the minds of the stock market, not in valuations, which can go up and down, but in the consumer’s mind. That’s how much more they’re willing to pay.

[00:16:19] Topline Strategy: Well, that’s really cool. I know a lot of branding agencies were wrestling with this and it seemed like the best that they could come up with most of the time was just looking at the premium over book value for listed companies or other blunt tools that were clearly correlations and not causation… or had other confounding factors built in. So that that’s a very, very interesting approach.

Maybe you should start thinking about rolling out a brand equity agency in [00:17:00] addition to offering pricing research.

Thanks. I’m Dave Zweifler. Today, I’ve been speaking with Richard Schreuer, CEO of Echo Cove Research, a partner of Topline Strategy. Today we discussed pricing research, best-practices, and the inherent problems of traditional pricing research. We also discussed how brand plays an important part in the price that a prospect is willing to pay, how to quantify it, and a more precise measure of brand equity that can be reverse-engineered from a pricing exercise.

If you’d like a more detailed look at the pricing strategies that Richard discussed, including a deep dive on a simulator that takes the perceived value of individual product features and defines them into your maximum price, click the link below.

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