As the marketing industry – and the world at large – continues to experience its own digital transformation, marketers have seen an explosion of channels, platforms, and of course, data. To better understand the reality of today’s marketing landscape, and the tools at our disposal, we present our Tools of the Trade series.
In this episode, we sit down with Per Sjofors, Founder of Atenga Insights – a data-driven, predictive pricing service that combines market research with proprietary, AI-enabled analysis to measure and determine the prices customers are willing to pay.
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Can you share some background about your history in the pricing industry?
Per: Well, the story is that I had the chance to run a couple of companies in Europe and then when I moved here to the US, I've also been running a few companies. And because pricing has been a bit of an interest area for me, we did experiments. Some of those experiments were hugely successful, next quarter revenues were up 25%. Others were real disasters. And what I had learned in business school and what we could read about pricing at the time was so academic that it was really useless. So about a dozen years ago, I decided to figure out the process that would make pricing practical and applicable, if you want me to tell you that, in the everyday business and in short, just like you alluded to, it consists of price specific market research where you measure willingness to pay and then you correlate that measurement with variables such as we call them decision drivers or value drivers that could be marketing messages or features, positioning statements and so forth and also buyer demographics and customer profiles.
Per: And the result of that is that you get to know what features to focus on, which drives a higher willingness to pay, what marketing messages and so forth that drives a higher willingness to pay, what the most desirable profile of your customers are. Obviously, the profile that has the highest willingness to pay.
"Predictive Pricing” – what does that entail?
Reid: Yeah. Well, I mean, it's so interesting because the thing that everyone is always trying to get to is how do you connect the marketing spend with the dollars that you're going to get? And this is obviously a far more direct connection because it is literally the dollars you're going to collect and it identifies not just here's the price, but here's the people, the groups and it helps you identify targets who are going to pay more for the things that you're going to offer. So, I mean, there's so much more to just setting the price in this context. It's who you're going to reach, who's going to pay for it, the feature. So, the highlights there are fantastic. And then you get into the idea of then predictive pricing. So, what exactly does predictive pricing entail? I mean, what's the role of predictive analytics and then obviously Atenga within this, within the industry?
Per: Well, the predictive portion of this comes to that we can predict the exact price point that generates the highest sales volume and exact price point that generate the highest revenue. And those are not the same price. And just actually yesterday I got an email from a client from 10 years ago who said that, "Your prediction was dead on. And now it's time to do it again." You know?
How does Atenga's Predictive Demand Analysis (PDA) methodology unfold?
Reid: Right. I mean, that is kind of the best compliment you can possibly get given what you're trying to do here. I mean, it's so difficult for anybody to really predict seemingly anything at this point in time. So, predict people's willingness to pay and what are going to be the driving factors is pretty exciting. I mean, can you talk about then how you get there? Maybe give us some of the background on Atenga's methodology. How does predictive demand analysis process unfold?
Per: Well, the process is, it's a typical sort of, it's a process where we define together with our clients, these various attributes around the product or service that influenced willingness to pay. And then we use that in an online survey. We go out to the marketplace. And that could be a B2B marketplace or a consumer marketplace. And we target the respondents to this online survey according to the wishes of the client. So, this could be industries, or it could be certain locations, or it could be certain demographics. And in the actual survey, we make sure that we qualify people very stringently, both with a number of qualification questions and with technical qualification.
Per: So just as an example, people who are not spending enough time on a particular question, we assess that being that they didn't read it. So, they got kicked off. And when it comes to the actual questions, and there's a whole series of questions to assess willingness to pay and what we're asking people to do is to create certain price points with the value that they perceive in that product or service. And we allow them to fill in those price points themselves. So, it's unaided.
Reid: Yeah. So, one of the little kind of nuances there or things that you had talked about is the idea of then consumer or B2B. I mean, what are maybe some of the key differences between those things? Because I would imagine, well I mean, I would imagine they're different, right? A way for particular types of products or something like that. What are kind of the major differences? If you got one of our listeners and they're saying, "Well, I am a B2B company." Or "I have a really complicated sale. I mean, there's no way this is going to work for me." What would you tell them?
Per: Well, if there is a very complicated sale, if there is a sale that is done by individual negotiation, this particular method doesn't work to be honest. But if it is a product or a service that is definable, then it works just as well in B2B as it does in consumer goods. I mean, imagine us doing ... This is so narrow that I like to do this story, we did a project for a company that has a little light, it looks like a little flashlight. And you use this light and shine it on a gemstone, and it will tell you whether the gemstone is fake or real. I mean, what is the market size for something like that? And then we did it in the US, we did it in two or three countries in Europe and in India. You know?
Reid: Yeah. So that's interesting that you say there. I mean, the differences by country by country I would imagine indicating prioritizing different features, different value propositions and obviously then thereby different price points. So, it's different country to country and that's fascinating.
Per: It's one of the most common mistakes that we see is that companies that are successful with their product in a country go to market with the same messages, the same marketing, the same sales strategy and the same price as in their home market. And it rarely works.
Reid: And I mean, it seems obvious, but it happens all the time and it's so interesting.
Per: It happens absolutely all the time.
Reid: So, one of the other things though that I'm curious about as it relates to establishing pricing. Well, I guess I know, and I've seen it now in working with you is the idea that sometimes you can increase price without changing much of anything and actually have more sales as a result.
Per: Yes, absolutely. Absolutely.
Reid: And who wouldn't want that? Right? You can increase prices, you get more sales. So, there's a net positive effect and really, you don't have to change much of anything else.
Per: Let me ... So, as we talked a little about B2B, let me give you an example. We worked for a Los Angeles based telephone company, a business to business telephone company that has a telephone service in the cloud. We told them that they could quadruple their price, which they did, not overnight, but over a period of about nine months. And the result at quadrupling prices was a 25% increase in sales.
Can you share a few examples of Atenga's work in practice?
Reid: Yeah, I mean, it's totally fascinating. And again, go back to the kind of opening of product, price, place, promotion. Price being such a major part of it. And now there is a way that wasn't exactly the same in the past but where we are today, now there's a way to kind of predict what the effect will be and Atenga is able to do that. And maybe, Per, maybe you can tell us actually a few more case studies. I mean, because it is so fascinating and give us a couple more that you found particularly interesting.
Per: Well, so the method that we developed leverages something called behavioral economics. And in behavioral economics there is something called expectation bias. And that means that the price itself sets an expectation of the benefit of a product or a service. And that's been proven again and again. For example, a 5-cent aspirin is not nearly as effective to cure your headache as a 50-cent aspirin. So not only does pricing set an expectation of the benefit, but it also affects customer satisfaction. And just again, to give you another example, we did a project for a large trade show in Vegas. So, the entrance fee for that trade show. And we could tell our client that they could more than double their prices. And the interesting thing is that what happened was that people stopped complaining about the high price. So, you doubled the prices and people stop complaining about the price because then suddenly that expectation of value that the price generated matched with the expectation of value that the buyers had.
Reid: Yeah. So that's interesting. I mean, now I imagine there's some listeners who sit down and go, "Well, I'm just going to double my price now", or something like that. But there's a ton of strategy that will come into that because it can also really backfire. One if you probably, if you do it wrong and two, obviously, if you don't have the data to support a decision like that.
Per: Absolutely. Let me give you another example. A company selling training programs. So, they sell these programs to gyms and they have 10 different programs. You can buy a single program, a bundle of 3, a bundle of 6, and all 10. And what we found in that particular project was that the single program was too expensive. The bundle of 3 was too expensive, the bundle of 6 was too cheap and the bundle of 10 was too expensive. So, we recommended 3 price decreases and 1 price increase. And the result of all of that was that this company had been flat for years in revenue, no growth at all. And they started to grow at 5% a month.
Reid: Yeah. Well, and that's I mean, obviously that makes them a pretty loyal customer to what you're doing there. I mean, is there a required volume you feel like needs to be there for an existing product or can you do this for something totally new?
Per: No, we can do this for something totally new. What you do when ... In all these projects, what you want to do is to measure the willingness to pay and benefits, perceived benefits are being ... How benefits affects the willingness to pay. And you can obviously do that with a product or a service that doesn't exist. And in fact, if you're a real early startup, you may want to do this to find out even if there is a market for your product at a price where you can sell this profitably.
Reid: Yeah. Which could be in a different country. It can be a different target. It can be in all sorts of different things. I think one of the interesting things that I'd seen also, which I thought was kind of odd, which is the people who kind of say, "Well, I mean, everyone in my category pretty much prices at about the same anyway, so I don't see a lot of reason for me to kind of mess with it because the expectations have been set for something like that." Which I would say, to me it would seem that's a perfect opportunity to consider what role price would play in maybe establishing a premium position or something different. What do you think about that?
Per: Absolutely. And it goes to back to what I said that if you price high and focus on the people that are willing to pay that relatively high price, they will be much more satisfied customers than if you try to under-price and so forth because your price sensitive customers are rarely those that are loyal. So, a price sensitive customer doesn't have a high lifetime value, whereas a customer with a higher willingness to pay is much more likely to have a high lifetime value.
Reid: Yeah. I mean, this stuff is so fascinating. I mean, obviously I always loved the behavioral aspect of this stuff. We are weird but fairly predictable beings out there. So, I think it's so fascinating what you're doing and there is so much more that we could dialogue about this, which is why I would encourage anybody who wants to talk to you and the listeners who do to follow up with us and we'll make sure to get you connected. Per, it's always a pleasure connecting with you. I'm so grateful to be working with you and look forward to reconnecting at some point soon. So, thanks for joining us.
Per: Well, thank you very much, Reid. And you have a good day.
Reid: Absolutely. And for our listeners, be sure to subscribe to our podcast and leave us a review on Apple Podcasts. We'll see you next time.