Today Greg Bender, Director of Product Management at Survey Analytics, and I held a webinar to demonstrate our awesome mobile data visualization and analytics app, SecondPrism.
We talked about the importance of making sense of the proliferation of marketing data, the rise (and fall?) of data dashboards, the growing ubiquity of mobile, the limitations of PowerPoint, the power of touch, the importance of data visualization, and how to push through with innovative concepts. Then there was a comprehensive demonstration of SecondPrism.
If you missed the webinar, the video and slides are below.
Survey Analytics conducted a webinar on January 3rd, 2013 entitled, “How to Conduct Your Own Retail Audit.” A do-it-yourself retail audit gives you real-time intelligence on the retail environment. What follows is the text of the session up to the Q&A portion. At the end of this post you can find the webinar video and slides.
This webinar is how to conduct a retail audit. My name’s Andrew Jeavons. I’m the president of Survey Analytics, and I’m going to be trying to give you some insights into the procedures for retail audits and the technology involved.
First of all, we’re going to go through a little bit of the principles of a retail audit of what it’s supposed to be. Then, we’re going to do a technology demonstration showing you what kind of technology we’ve got. And then, we will be happy to answer any questions that you have.
What is a retail audit? A retail audit, as the name implies, is the study of a selected sample of retail outlets. You may do this continuously, there’s good reason to do this. You might do this discretely. Really, you’re looking at your retail environment and trying to work out, what’s going on? And if you’re trying to improve that environment, if you’re trying to catch where there are some problems, if you’re trying to look at how the retailing environment fix those problems, you need to be doing the study continuously.
Of course, there are lots of issues with a continued study. Not least, the costs of it and that’s something that for each company has to be sorted out very carefully, obviously. But the point is, unless you carry them out, you’re not going to really be able to see your environment improve.
If you want rapid improvement within the environment, the name implies that you should do the audits relatively frequently. Now, if you want to see improvement over a two-month period, you should probably be doing an audit at least once, or indeed, twice a month just to monitor the fact that things are improving. Asking for improvements over a short time scale and not monitoring them, just really leaving it to chance Unless you can track the progress of the improvements you want, you’re just simply not going to be able to see them.
A discrete audit, which implies that you do a set of stores every now and again, has its uses but again, the point I think of retail audits is to continually monitor the retail environment, catch problems, and try to push through or enhance improvement in that environment.
What’s the goal of a retail audit? The goal is to monitor products in the environment. Now, they can be your products, they can be your competitors products, which are often very much as equally important. It’s also to monitor compliance with agreed procedures and standards.
You might well, as is very common in a lot of the fast-moving consumer goods environments, have certain standards of shelf placement of the product, placement of promotional materials, of the availability of ancillary materials, or maybe there’s some equipment that needs to be placed in your retail environment. All those kinds of things need to be monitored.
While the retail environments may state that they’re doing these things with the best intentions in the world, lots of problems can occur whilst things get translated into the field, into the individual stores. And this is very often a huge motivator for performing retail audits– that is, that you won’t be able to see that those agreements that you’ve made, those standards that you’ve agreed upon are, in fact, being upheld, and implemented in the real world.
A retail audit is, after all, a survey. As with any survey, you really don’t want to make it too complicated. There is a trend or habit within surveys to make them long and complicated to capture a lot of data. The truth of the matter is, if you have a long complicated survey, you are compromising the data quality.
Even if you have people who are very motivated to fill out your retail audit survey. They could be your sales managers or some other sort of management. Even they will make errors or have a reduction in data quality if the survey is too long and complicated. And when we had paper surveys that really wasn’t an issue, because there was only a certain amount of paper that people could carry around. There was only a certain amount of skip logic that a person could actually administer themselves.
Now that we’ve become electronically based, all those issues go away. You could easily have a 300 question survey. On a paper, that would just be beyond believe. It’s too difficult, but you can easily do that with the technology. But that doesn’t mean that you should. There is an argument that says having a short survey that’s easily administered that will collect accurate information, is a lot better than the longest survey. That while you might think you’re getting more information, the accuracy is compromised because of the length of the survey.
Quality of data is critical in any survey, and particularly, in retail audits where you’re going to be making business decisions directly based on that data. And there is a question as to whether mystery shopping, that is sending unknown people into retail environments and asking them to fill out a questionnaire about the environment is best.
And I think it’s a good argument that says, we really need somebody who’s in your business environment who understands what they’re looking for, to pick up on things that an anonymous mystery shopper may simply not see. And again, we go back to the motivational aspect. Somebody who is in the business, who has a vested interest in the business, has a much higher motivation to fill out the survey correctly than somebody who’s being paid in dollars per store, and really just sees it as a job to get through at the end of the day.
That then, again, comes back to the economics of the retail audit, can you tie up your management staff in doing the audit. That’s just a question that companies have to answer on an individual basis. But mystery shopping, while it allows you to relatively easy cover a lot of locations, which may be very helpful to you, does have the problem that you’re getting what you pay for. You may have people relatively low in motivation giving you what you regard as critical information and that can be a problem.
Now, as technology has advanced, we now have a lot of smartphones, we now have tablets, we have some new data types. We have images, we have video. All have the potential for sound and these give us a lot more potential these days to capture real world data, which is actually what a retail audit [INAUDIBLE]. I’ll talk about those in a little bit.
The critical factor is what devices will be used to conduct a retail audit? Now, connectivity is also something that you need to address when you’re thinking about it. How do you get the data back? How do you get the data back to the servers where it can be analyzed? There are two ways, tablets and smartphones. You can use a Wi-Fi network.
Now, it’s true that most retail environments, somewhere, have a Wi-Fi network. But the process of getting hooked up to it would be fairly arduous. And you don’t really want to have somebody spending a lot of time dealing with technology issues when they are in the store to carry out a survey of the store.
One alternative is to collect the data, as we say, offline. That is you can collect it on the tablet or the smartphone. And then, you can return to a known location where you know the Wi-Fi connectivity works and upload the data from there.
And this can work very well, because the cost of devices that connect to the cellular networks– and you may well have 20, 30, 50, 100, 200, maybe hundreds of devices– is significantly more than devices that aren’ cellular-enabled, in particular when you look at iPads and Android tablets. An iPad that has cellular connectivity costs a chunk more than one that doesn’t. And you’re going to be saving many 10s of thousands of dollars, perhaps, not having that cellular connection.
The other alternative, obviously, if you have got those kinds of devices, just use the data networks. This can work very well. There are locations where you will hit dead spots, and again, you need to think about that. If you can’t get the cellular network going, you need to have some way of getting to a Wi-Fi network or a cellular network that works.
In the main, from what we’ve seen, in many ways, the safer way is to have Wi-Fi enabled devices where you can connect the data in an offline mode in a retail environment, and then get to a known environment with a known Wi-Fi environment, and then upload the data. This isn’t to say it isn’t possible using the data networks, but you still, even when you are using the data network, you may have the issue of no connectivity and that just complicates matters.
So what exactly are you going to use? Tablets. Well, we’ve got the new small form tablets, the 7-inch tablets. We’ve got the standard form ones, like the iPad. They have a good screen size. They’re easy to see. They might feel heavy after a while. If you’re going around and spending time carrying a standard iPad around from store to store and spending several hours doing that, it might be something that gets a bit unwieldy, but there are cases and holders that can help you do that. It really comes into that environment of ergonomic usability.
The small tablet is slightly smaller screen size, much easier to handle, and, of course, they’re a lower cost, and particularly, that’s the case when you move to Androis, tablets like the Nexus, which is a very good little machine and costs a lot less than an iPad. And again, when you’ve got hundreds or maybe thousands of these machines, that’s a significant factor.
Smartphones. Well, they’re a small screen size, and that is an issue because you can’t have complicated questions. You really shouldn’t have them anyway, but certainly with a smartphone, you’ve got a restriction on the screen real estate. The advantage is perhaps, that a lot of your staff or people who you want to execute the survey, already have them. The penetration of smartphones in the US is very high. Most people will have an Android or an iOS device, so you don’t have that cost factor of having to provide them. You do then have to work out all the issues of data connectivity and those types of things.
The big disadvantage is really, again, it’s a small screen size. And, that again, is a problem when you want people to use these machines for hours and hours on end. And this comes back to making sure the survey fits the device. If you are designing a survey that’s going to be used on a smartphone and tablet, it has to go to the lowest common denominator, which is the smartphones. And smartphones and not tablet. Just because it looks real good on your iPad, doesn’t mean it’s going to look good on an iPhone. The screen is just so much smaller. And again, in both these environments, the more concise the better, long preambles and questions, do not use. That can affect your data quality.
We talked a bit about new data types. We have images, very easy to collect. Now, you can take some great pictures, very useful to document any aspect of the retail environment. You can accurately assess store placements of products, you can go back later on and score how well products are placed and what you think about the displays. It doesn’t have to be something that’s done in the moment when you’re in the store.
It does allow an objective measurement in the improvements and degradation. It’s not just a weighting scale of how well thing are placed and how nicely things look. It is something where you can look over time and see changes by comparing images. But, the issues with images, of course, is scoring an assessment after you’ve collected the image takes time. It takes administration. But it does give you much more accurate data. You really can have a metric that you can look over time and see how things have changed in the environment.
Video, all the properties as images, but you can capture a lot richer information. You can perhaps, monitor how people interact with the displays, which you can’t really do with the static image. It gives you that kind of snapshot of customer behavior, traffic if you stand there for a couple of minutes, some video of the aisle and see what’s going on. That data could be very valuable.
Again, the issue is that you have to analyze the data. Analyzing a couple hundred videos is a significant task, which you will get significant data out of that. And I do think that investment in analytics, it always pays off. We’ve gone from an environment where it was hard to get these kinds of objective measurements, say 10 years ago, now, you can get them using new technology. And I think more time spent on analyzing these objective measurements of images and video is really well spent.
We can also record just the sound. You may want to, for various reasons, check out what the acoustic environment of the store is. You can listen for announcements, the noise, those types of things. You could even be asking customers what they think of the store and you get a snapshot there. And again, that kind of information can be very useful. It’s my experience that senior management will often be very interesting to hear the snapshots of what people think, and it really does enhance the kind of data that you collect.
Now, obviously, in a retail environment, one big data item is bar codes. And technology now allows us to scan bar codes. And obviously, this is very useful in having an accurate data point of what items are on the shelves rather than somebody taking a picture and it being hard to discern exactly what package size there is or what types there is, you can go through and scan the bar codes.
The actual bar code can either be resolved in real time, that is when you’re in the store, if you have connectivity the system can go ahead and collect that bar code information from a variety of different sources. You can even have your own source, if you so desire, or you can have that resolved later on. It does give you definitive information about the product quickly. It gives you exact information. It gives you consistent information. It’s not really dependent on how well someone can fill in a survey of saying what color package size is placed in what point of the shelf, you can scan the items with a bar code, you’ve got the information.
Let’s talk a little bit now about all the possible sorts of data you can to collect in the survey. You can look at the coupons and promotions that are available. You can look at the merchandising and presentation of the products, the conditions of the store, inside and outside, often an important issue with consumers.
You can gather metrics about staff and the training of the staff, availability and display of the products. You can assess service, the speed and quality of how long it takes you to check out, how quickly it takes you to get a price check, how many people are around to answer your questions about possible product, all those things can be part of a retail audit.
You can look at the inventory that’s available, any specialized equipment in the environment, if it’s an environment where there’s a drive-through, you can also do assessments of traffic on that there, taking pictures or video, seeing the kind of traffic you’re getting. You can make an assessment in the kind of customer that are in your retail environment. And for some products, it’s important to look at what kind of safety standards are being enforced within that retail environment.
And the most important thing that you can do, particularly when you’re conducting continuous studies is to standardize on the data. If you do not standardized on the data that you are collecting, you will not be able to do meaningful, longtime comparisons.
There’s always a temptation with any sort of continuous studies to add certain questions at certain points in certain instances of the study. While that can be done, it’s important to remember that the data you get the standard from you can call perhaps, wave on wave of these audits, is the same. If you are not standardizing on what data you’re collecting, you’re really not using your resources and revenue effectively when you’re conducting this audit.
We talked about earlier, that a retail audit being a kind of survey, and of course, then there are sampling issues. What kind of stores are you going to sample? You could do by territory and sales regions, which is very often the kind of sample that people carry out. That they are wishing to monitor their own retail environment.
You can do by vertical, by types of stores. Liquor stores, you go and look at all the different liquor stores. You might go around and look at all the different supermarkets, not just your own stores. And as I said, you’re looking at competitors stores, seeing what differences there are between your stores and your competitors store about the product placement and about the retail environment.
Random, as the name implies, is any store. You pick them on a random basis. That may be possible with some product lines, with others, possibly not. Again, if the audit is done on a continuous basis, the form of sample that you use should be the same. Otherwise, you’re not comparing apples with apples.
If you’re comparing different samples between different phases of the continuous study, you’re not going to get meaningful data. And that’s just the general principles of any survey. When doing surveys, you want to compare them, which is essentially what’s going on in a retail audit. You have to have the same stuff.
I just spoke about, a bit before, who collects it? Is it an expert? Someone who understands the business space environment? Expensive, but data quality may be higher. Somebody like this may have intrinsic biases. They may have a habit or something in their training or their experience is going to make them look at certain aspects more critically than others. That’s something very hard to avoid, all surveys are biased.
Or you could just basically hired out help, someone hired to carry out the survey, along the mystery shopper line, perhaps, or somebody that you hire and train up. Cheap, lack of quality of data may be variable depending on the training. You’ve got to monitor that very carefully.
And lack of knowledge may inhibit data quality, that’s the reverse effect of somebody who’s an expert. If they really aren’t trained in that kind of retail environmental or the kind of products that you have, they may not be able to pick up on some things that are pretty important. It could be really important to you, it may not be viable to train them in all those things they need to know. Again, you’ve got to be consistent.
The effects that people gathering data have on the data are real. Interviewer effects are real. This is a good example. If we have an expert versus somebody just hired to do the job. Being inconsistent with collection methods, again, can compromise your data.
If you do one set of studies using internal highly-trained resources, such as somebody who’s an expert, and then the next retail audit you carry it out using people who are essentially you’ve hired or are mystery shoppers, you’re compromising the data of the audit. You’re really degrading how useful it’s going to be for you. You have to make a careful decision about how you collect the data.
Now, if we go and think about what kinds of questions you’re going to ask on the audit, most usually, you’re looking at the kind of scoring or rating style question. A one to five scale. You could say, floors are clean, rate this on a scale of one to five, one being the worst, five being the highest. And then the scores, your one to five scale, they are very often summed up and set a percentage score for pass/fail audit.
So you might want to say, well, I want people to get 80% at the highest level, so if you’ve got 5 questions or 10 questions and they all score five, you want a score of 40% or higher as the sum of the questions to say that you’ve passed. That’s in the criteria, the set of criteria, that it’s up to you to decide. But it’s usually a good idea to set some sort of metric like that. You want to have an aggregate score. It makes it easier with reporting. It makes it easy to summarize the data.
Yes/no questions, again, you set a level for how many are fail and score accordingly. In general, the retail audit will want to score the environment on an aggregate score. At the end of it, you say, OK, this environment’s got an 80% or a 60%. And then that implies actions that needs to be taken to bring those scores up.
Obviously, the whole point of doing any sort of survey like this is reporting and analytics. You have to think about your audiences that you’re going to address. It might be store region managers. We might want certain regions to see the scores of their regional stores, very common in this sort of research. Higher up executives might want to see things on a national or a higher level of granularity. They want aggregation of the scores. And again, when you’re looking at that executive environment, they’re going to want to drill down on the data where they can. And we have some solutions that are available to enable all those audiences to be addressed.
Thanks everybody for their time. As I say, if you do have any questions, please feel free to contact us, and everybody have a great day.
Survey Analytics conducted a webinar on December 13th, 2012 entitled, “How to Set Pricing Using the Van Westendorp Price Sensitivity Meter.” What follows is the full text of that session. At the end of this post you can find the webinar video and slides.
Welcome everyone. I’m Dana Stanley, and I’m the Vice President of Marketing at Survey Analytics. And I’m very pleased for you all to be here for this webinar called How to Set Pricing Using the van Westendorp Price Sensitivity Meter. I’ve had a good time preparing for this webinar, and I look forward to a good session and some good questions at the end. By the way, if you do have questions, go ahead and submit them through the question interface on the GoToWebinar control panel, which should have appeared when you logged in.
OK, first before we dive in, a quick word about Survey Analytics. We are a company that provides DIY or do it yourself software for data collection, analysis, and visualization. Our core product is Survey Analytics Enterprise Research Platform. And we allow people to do their own surveys, but we have advanced functionalities including the van Westendorp Price Sensitivity Meter, conjoint, TURF analysis, things like that that you wouldn’t get in a standard package, but it’s at a good price point.
We also SurveyPocket, which is a tablet and smartphone app for doing field data collection. SurveySwipe is a mobile smartphone and panel app. LifeMetrix is for mobile data collection– mobile passive data collection that is– and Second Prism is a revolutionary system for visualizing and interacting with data on touch screen devices, such as iPads, Android tablets, and also smartphones of those two operating systems.
So enough about us. Let me go ahead and get started in talking about pricing research. There are so many products out there, and I think we all know that products have been proliferating and services have been proliferating. You have your standard grocery products, of course. You have your technology products, innumerable numbers of different types of gadgets, smartphones, tablets, and the like. Another kind of whole domain of product is pharmaceuticals. All these things need pricing, and all of them should be doing research on their pricing.
But it’s not just limited to products. It’s also services. So whether you run a massage service or you have an accounting service, you also need to determine pricing and not just in a haphazard way, in a smart way. Even pizza delivery– there’s another service that needs to know its pricing for the service of delivering pizzas.
Existing products, one example being Coca-Cola, are always introducing new products, and they need to determine the pricing for their new products. Coca-Cola has its classic Coke product, and Coke Zero is one important iteration that they introduced. And they have lots of different variations. And of course, they have to do research on all of the different pricing for those different products.
And even for a completely new product– here I found something funny– a goldfish carrier. No matter where you are in the market, pricing research is critical. You have to know what your market is and where your positioning is and what kind of pricing makes sense for where you are in the market.
Also things change over time. There’s seasonality, and the market is constantly changing. So pricing research is not just a one off consideration, but it’s also an ongoing consideration. You need to be checking in on your pricing on a regular basis, and you need to have your finger on the pulse of where the market is. And so that takes a methodical approach. And I’m sure everyone on this call would agree that a market research approach rather than a haphazard approach is what makes sense.
So as you’re determining your research priorities, you need to make sure that you’re not neglecting research on your pricing. It’s arguably the most important thing that you’re going to research, because you can have the best product in the world, but if it’s improperly priced you’re not going to be happy with the results.
So how to determine price. But first, how are prices usually set? There are a number of different ways. And number one is really guessing. There’s a lot of guesswork that goes on. Let’s just put a price out there, see what happens, and see what happens to our sales. Is it going to work? But I certainly wouldn’t recommend guessing. Putting your finger in the wind, going on intuition, again not recommended, yet all too common.
A lot of times prices are determined through negotiation. You suggest a price to your client. Your client comes back to you and counters. And its a back and forth, a tug of war, if you will. I don’t know about you, but negotiation is not one of my favorite things. A lot of these guys actually look happy, but I’m more like this guy. His facial expression captures the feeling I have when I negotiate. And so, not only is it unpleasant, but it’s also not recommended in terms of the way to optimize your pricing.
There’s the trial and error method. Put a price out. See what happens. Try something else. This is probably how most pricing is determined, not done through market research. Unfortunately many products are not researched, but the pricing is done by trial and error. Well people who are pricing by trial and error are certainly not optimizing their price, and most importantly, their profitability. And of course fear is a big driver. This may be one of the things that keeps prices down unnecessarily is fear of not selling– fear of offending people by charging too much. We need to get over the fear and we need to look at things rationally.
So you should be conducting surveys on your pricing. And I’m excited to talk about the van Westendorp method. The most common, I would say, way of asking about pricing in a survey for inexperienced researchers is simply to ask, what price would you be willing to pay for– and whatever your product or service is. And this is called the willingness to pay question. The problem with the willingness to pay question is really two major things are wrong with it.
One is that it’s too blunt an instrument. It gives you a point estimate of what price, but it doesn’t give you a rang. The second is that you’re really encouraging people to low ball you, to say a lower price in the course of the survey. So that’s not a recommended method. It is not sophisticated enough. You really want to determine a range for your pricing and not just have a point estimate, as I mentioned.
Why do you need a range? Well you don’t want to charge too much, and you don’t want to charge too little. One example is this bag of Gummi Bears. Would you charge $20 for it? Well the retail price is $2.79, so clearly $20 would be too high. What happens when you charge too high a price? When your product or service is priced too high, you lose sales.
Now how about this Movado watch? Would you charge $100 for it? Well the retail price is $1,200. So what happens if you charge too little? If you charge too little, your product or service is priced to low, and you lose profits. You’re underwater, if you will. And that’s no good either. you really need to figure out what is the acceptable price range.
So summarizing, if your price is too high, you’ll have lost sales. If your price is too low, you lost profits. So you need to find the acceptable price range. Even this is not quite sophisticated enough for most market researchers, and the van Westendorp method was a significant advancement over this better than basic but not quite good enough method of just asking for a high and a low price range.
The key idea for the van Westendorp method was created by Peter van Westendorp, who is a Dutch psychologist, in 1976. He traveled from the Netherlands, where he was from, to Vienna where he presented at the ESOMAR Congress in 1976. And this paper got a lot of attention, and this method really took off. But this is the original source. It has subsequently been modified, and there have been some improvements on the method from the original paper. But the original paper was in 1976 called and “NSS Price Sensitivity Meter– A new approach to consumer perception of price.” And that’s from the proceedings of the ESOMAR Congress in 1976.
So going back to the prior model, let’s look at what the van Westendorp model did to improve on that model. It recognized that there are two elements of high pricing and two elements of low pricing. You can have a price that’s too expensive and on the low end a price that’s too cheap. So on the high end, it’s too expensive for someone to buy, and on the low end it’s too cheap. Because not that people can’t afford it, but rather they infer that it is not a high quality product, or that is not a sufficient quality product.
On the high end, there’s also the consideration that the product is getting to be expensive, but not so expensive that you wouldn’t consider it. Why do you consider that in your equation? Well, as we know, and you’ll know in your personal life that sometimes a higher price connotes higher quality. And so you asked the question whether it’s getting expensive versus whether it’s too expensive to tease out that distinction.
On the low end, a product or service can be too cheap, which connotes low quality, but then at a higher price it can be considered a bargain. And you want to be above that bargain level, but not at the too cheap level. Likewise you want to be at the maximum at the expensive level but not the too expensive level.
Now this is a bit esoteric as I’m explaining it here conceptually. I’m going to go right into showing you the exact questions and going into some examples. The idea here is that price signals quality. And that is the key innovation that van Westendorp added into the pricing model.
I like to think of the four questions as a meter because of the term the price sensitivity meter. But you really can think about it as a warning system of where are you on these four constructs, as it were, in your pricing for different segments of the population at different times and for different products.
So here’s the too expensive question. Now I will tell you that there’s disagreement and there are different versions of the specific wording. This is the wording that we use here at Survey Analytics. For the too expensive question, the wording is, at what price would you consider blank to be so expensive that you would not consider buying it?
Now here’s the expensive question, and look at the difference here. At what price would you consider blank starting to get expensive so that it is not out of the question, but you would have to give some thought to buying it? So one is too expensive, and then the other is getting expensive but not too expensive.
The third question is what’s referred to sometimes as the bargain question and the opposite of the not too expensive question. At what price would you consider blank to be a bargain, a great buy for the money? And finally the too cheap question is, at what price would you consider blank to be priced so low that you would feel the quality couldn’t be very good?
So one important distinction here is that the van Westendorp Price Sensitivity Meter assumes a rational approach to pricing. Their are more inferential approaches to pricing, including discrete choice conjoint. But this method assumes that there’s a certain level of rationality among respondents to the pricing. And the conclusion from this is that it may be applicable more in some instances than others. So you really need to think as a researcher about your own market and whether you can reasonably say that your audience knows enough and is rational enough about the market in order to set this pricing within these questions.
So this question has become an arrow in the quiver of many pricing researchers. Again one of many methods, but one that’s proven to be quite effective and quite a regularly used tactic across lots of different industries. It has been validated across different industries for products and services and for expensive items and for low priced items. So it is quite robust in that sense.
So let me give you an example. Let me pick one product and give you a sample of how you would use the van Westendorp Price Sensitivity Meter to research that product. I’m a guitar fan, and you may know this product. This is a Flying V guitar by Gibson. It’s quite of high-priced item, but it is quite cool. Some of the best known guitarists in the world have used the Flying V, so it is a premium item. It’s not just your run of the mill guitar.
So let’s take a look at how you would do research on how to price the Flying V if you were the Gibson Corporation. By the way, it retails for $1,799. So this is a product that’s really a specialty product. Impulse purchases not withstanding, this is not a product that you would market to the entire population in a market. You would really be looking at people that know something about guitars. And again that goes back to that assumption of rationality. People in the market that are guitar collectors or have multiple guitars, they know a lot about the market and they have definite thoughts about the guitar market. So instead of going to the full market, we would be going to guitar enthusiasts. So we may be doing this research among a panel of guitar enthusiasts.
So let’s look at how that would work. In Survey Analytics we have a panels function. And I’ve made up this fictional panel called the guitar collectors panel. I’ve collected respondents and paneled them into our guitar collectors panel. And this is what it looks like. I’ve got a nice guitar players header. And this is my page within the panel. So we’ve got our guitar collectors panel. And then we want to do a survey.
So we go into Survey Analytics. We create a survey and we add a question. So first we click Edit Survey, and then we click Add New Question. We click Add-On Modules, which is the group of questions that the van Westendorp question is within, and then you see down for the bottom there’s a pre-programmed version of the van Westendorp price sensitivity question right there within Survey Analytics. So you can have the question in your survey within minutes. You also can customize it, but it does come in a standard format, which you’ll see in a moment.
So here’s how the question looks. We have a nice picture of the product. And the question says, at what price would you consider the Gibson Flying V electric guitar, A, to be so expensive that you would not consider buying it, B, to be priced so low that you would feel the quality couldn’t be very good, starting to get expensive so that it is not out of the question but you would have to give some thought to buying it, and to be a great bargain for the money.
There are some variations that you can do with this question. For example, the ranges certainly are customizable. And you do not have to do ranges. You can have open-ended input. There’s debate about which is better. When you analyze it, it does have to be in categories, however. You can vary the order of the questions and the specific wording of the questions. And you can change the slider to an open-ended input if you like. You can also have just end points on the slider instead of having the categories along the way.
So the other thing to keep in mind is that you want to make sure that the responses are validated. Obviously the question– the response for any particular respondent for the price at which the product is too expensive is going to be higher than their response for what price is too cheap. So you need to do a check. You can do programmatic validation with bounding logic, or you can do post hoc data cleaning. It’s really up to which way you do it.
This is a simple check to make sure that respondents understood the question correctly. The four questions need to be in an order logically, that the too expensive is highest. Expensive, or sometimes called getting expensive question, is second highest. Bargain is the third highest, and the too cheap is the lowest.
So the way you analyze the data is that you plot each of these questions for the population of interest. At first we’re going to be just looking at it among the total population surveyed. For that population, you want to plot the four questions. The trick is that you need to invert two of them. Now let me explain what I mean by that.
For each of the questions, you’re going to be plotting the cumulative percentage of respondents that thought that that descriptor describes the pricing for the product. And I’ll show you an example on the next page. For the expensive and bargain questions, you want to invert those questions. And then for the too cheap question you want to do the normal cumulative.
Let me show you what that yields in the results. But first let me explain how the axes work. The x-axis is going to be the– sorry I have these reversed. The x-axis is price, and the y-axis is the cumulative proportion.
And this is the result. So you see the red line represents too cheap. The green represents expensive inverted, and that’s not expensive. The purple line represents the bargain question inverted, so not a bargain. And the blue represents the too expensive. You see that it’s the proportion for each price plotted against the proportion of people that agreed with that for each price.
So how do we analyze this data? It doesn’t always come out as pretty as this with four intersecting lines, but it usually does. So how do we interpret the data? Well this intersection is called the point of marginal cheapness. It is essentially the place on the price line that is the cheapest that you can go while maximizing all of the other factors.
On the other end is the point of marginal expensiveness. Again that’s as expensive as you can get while balancing the different pricing factors. And that range represents the range of acceptable prices. So again this is not exact, but it gives you a good sense of the range of where theoretically your pricing should be in. Some people look at the place where the too cheap and the too expensive intersect as the optimal price point.
So what else can you do to enhance your analysis with the van Westendorp Price Meter? Well you can measure purchase intent. In fact, that’s recommended. You can take the output of the van Westendorp method and you can measure purchase intent at those different levels. And so you have some validation for the estimates that you’ve come up with.
You can also, of course, layer in profitability data. You know at what price levels what profits you’re going to have. So you can combine that with the van Westendorp data to determine the optimal revenue point. That’s the point at which you’re going to have the most profitability along the price line.
You also can do a box plot of each of the four questions to visualize the data in a different way. That gives you the 25 and 75 percentile for each of the four questions. And that’s just another way of understanding the data. But the aforementioned four-line chart is the standard way of analyzing van Westendorp data.
So when you have many different products– and my daughter is a fan of the American Girl dolls– so theoretically the American Girl company could do iterations of this pricing research for all of their different dolls. So you can see how it gets to be quite useful to distinguish among the different products and the different versions of your product. And so they would in theory have a nice little chart for each of the different products, for each of the different target groups, regions of the country, et cetera.
Well what are some of the criticisms and limitations of this method? Well, as I mentioned before, there’s an assumption of rationality. So you have to be comfortable with that– that that’s applicable in your market. One big criticism is that it within the survey does not account for competition. It looks at a price of a product in isolation.
If you’re looking at a competitive situation, if you want to focus on that, or if you’re not comfortable with looking at a price in isolation from the competition, then you may want to consider discrete choice conjoint or other methods.
Someone said that the pricing in the van Westendorp method tends to be lower because it encourages low balling. I’m not sure I agree with that, but that criticism is out there. It also can be limiting. And this is true of any market research method– that when it’s not used in conjunction with other techniques, it can provide a limited window onto the phenomenon you’re trying to study. You always want to, as a researcher, triangulate in on something using multiple methods if possible. That’s why we do qualitative and quantitative– to have different views on the same phenomena.
And because there are so many nice little charts and numbers that come out of the van Westendorp method, the analysis chart can make it appear that the method is more precise than it really is. Of course, this method is subject to the same survey error, the same measurement error, that all surveys are. So don’t take the ranges too literally. Take them as a guideline. And, of course, you want to replicate the results, do it more than once, and you want to look at different methods in conjunction with the van Westendorp method.
So that’s my presentation. If you want to go ahead and submit some questions into the GoToWebinar control panel, I will do my best to answer them. And I do thank you for your time. And my contact information is here. There’s my email address. And at surveyanalytics.com you can check out our software. You can sign up for a free trial if you’d like to check it out. And, of course, we’d be happy to talk to you.
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