" And the survey says...
The survey results are in, and they are interesting. You thought your product was very reasonably priced... your customers disagree.
Upsert Offices – Early Monday Morning
The price is too damn high
You just started in a job at Upsert, a software as a service tool that helps ecommerce businesses automatically upsell their products on their blog. You wanted to find a quick win, so as any responsible B2B marketer would do, you conducted a survey of users of your free plan. These are people actively using your product and maybe there's some easy fix to get them to upgrade. The CMO was very supportive of this initiative, and everyone on the executive team eagerly awaited the results. Much to everyone's surprise, the biggest factor anyone mentioned was price! Over 25% of respondents mentioned it in answer to the question \"What's stopping you from purchasing a pro plan?\". Now the results have been fed back to the board, there's talks of running yet another survey, this time specifically focused on pricing. That's not an area you've covered before, but you joined this company to learn, and this is a great opportunity to do so.
The moment you make a mistake in pricing, you're eating into your reputation or your profits.
There's certainly a lot of excitement about the results of the survey.\nPricing isn't an easy fix, but it's always a good thing to identify a way to improve.\nI've talked to the CEO, and I'm recommending we run another survey.\nThis time focused on pricing.\nI have some experience with Van Westendorp pricing analysis – it was very insightful at my last company.\nI'm afraid that I don't actually know the details of how to run one, we outsourced it at the time.\nCould you do some research and figure it out?\nShe wants the survey sent out by the end of the week.
Van Westendorp Pricing Analysis
The Price Sensitivity Meter (PSM) is a widely used pricing technique which uses survey data to determine the willingness to pay of your potential consumers. By asking a series of four questions, it's possible to determine where consumer demand starts to drop off because too many people perceive the price as too expensive or too cheap (i.e. too good to be true, or a sign of quality issues). The questions are:\n1. At what price would you consider the product to be priced so low that you would feel the quality couldn’t be very good?\n2. At what price would you consider the product to be a bargain—a great buy for the money?\n3. At what price would you consider the product starting to get expensive, so that it is not out of the question, but you would have to give some thought to buying it?\n4. At what price would you consider the product to be so expensive that you would not consider buying it?\nBy asking this series of questions you're able to derive the customer's willingness to pay indirectly, rather than specifically asking \"how much are you willing to pay?\" (a question they might not know how to answer).\nAs a result of the analysis you're able to determine a range of acceptable prices, including the Optimum Price Point (OPP) where an equal number of people see the price as too cheap or too expensive, and the Indifference Price Point (IDP) where an equal number of people see the product as cheap or expensive (usually slightly higher). Van Westendorp is commonly used by Marketers because it's simple to execute, asks questions that are easy for respondents to answer, and is relatively easy to understand.
One common error with surveys is scope creep: you set out to test pricing but add multiple other elements you care about. Suddenly the survey becomes too long and your engagement rate drops. This can also bias your survey results to the people who have the most time to do a long survey: i.e. not always the most valuable customers!
After reading about Van Westendorp, you realize the survey is the easiest part: you just need to ask 4 standardized questions. You send the survey and wait for the results.
Who's willing to pay more?
You have the pricing survey data back, what does it tell you? Are some customers willing to pay more than others?
Upsert Offices – The Following Week
Hey I'm not sure if you saw, we got the data back\nCan you take a look and do some analysis?\nIn particular we wanted to know quickly if there were some attributes of the survey takers that stood out as having a higher willingness to pay\nLet me know what you find
In our pricing survey we have asked a couple of qualifying questions: not too many to put off the respondents, but enough to answer a few important questions. Primarily we want to know if the customers we attracted from different marketing channels were willing to pay more or less, if one of our integration partners (Shopify and Woocommerce) was better than the other, and if there's a change in willingness to pay based on the amount of traffic they have on their blog (as our product helps them monetize that traffic). We should be able to answer these questions with a simple pivot table, and look at the average of the answers to question 2 Cheap and 3 Expensive.
Hey, let me show you how to make a pivot table in order to do some analysis here. \nSo we have a questions and we have a number of respondents. I'm going to kind of set them up and see the prices they're willing to pay based on the questions that they answered. \nSay, I'm just going to select all of this control shift down.\nAnd then we're going to go to insert and then pivot. I'm going to create that into a new sheet. \nAnd we're going to put in the row is the question that we want to analyze. \nSo in this case, let's just say. The platform so they are chop fire or commerce and then for values when they're just pulling, hit the cheap and the expensive.\nSo this is the sum right now that we don't want that. What we want is we can take the average or we can take the median in this case, I'm just going to do the average. \nSo just clicking in here, summarize by average. There we go. Now we have the average of those prices and you can format them as you want.\nYou can kind of see the differences between them if you need to.
Create a pivot table for the HDYHAU (How Did You Hear About Us) survey question. Take the average of question 2 (cheap) and 3 (expensive) responses. How much more were word of mouth customers (From a Friend / Colleague) willing to pay versus advertising customers (An Advertisement on Facebook / Google)?
The price Shopify stores is willing to pay is about the same (within 10%) of the price Woocommerce stores will pay.
Which number of month visitors had the highest willingness to pay compared to the lowest willingness to pay and why?
Finding the optimal price point
Our questions were based on Van Westendorp but how do we find the optimal price point based on the responses we got?
Upsert Offices – Later that day
Thanks that analysis was super interesting\nI really thought Shopify stores would pay more, but it looks like the amount of traffic is more important to pricing\nIt's also useful to know our customers from advertising aren't willing to pay as much\nThat will help us guide our strategy ongoing\nAnyway let me know when you have the Van Westendorp chart figured out!
Van Westendorp Chart
Once you have your survey data, you need to create a frequency chart in order to determine the optimum price point. Anyone who thinks the price is too cheap at $10 will also think it's too cheap at $9, so you can count everyone below a price point when plotting the line for 'too cheap'. Equally, anyone who thinks the product is too expensive at $20, will also think it's too expensive at $21, so you can do the reverse for your 'too expensive' line: sum up everyone above that price point. You end up with a cumulative chart which shows the percentage of people who think the product is 'too cheap', 'cheap', 'expensive' and 'too expensive'. \nWhere these lines intersect there's a diamond shape, and that shape determines the price points we care about. The bottom of the diamond is what Van Westendorp called the Optimum Price Point (OPP). This is where an equal number of people think the product is either too cheap or too expensive, so it maximises volume of sales. \nThe point at the top of the diamond is usually to the right of the OPP, at a higher price. This is the Indifference Price Point (IDP), which is also a good choice for your pricing. This point is where an equal number of people think the product is either cheap or expensive. \nFinally between the left and right points on the diamond, where 'too cheap' crosses 'expensive', and 'too expensive' crosses 'cheap' respectively, is the range of acceptable prices. This gives you the flexibility to select anywhere in this range depending on if you want to maximize volume or profits.
Okay. Here's how to create a frequency table for a van Westendorp pricing analysis. \nOkay. So we need the questions. We're going to bring them across. To a new tab, pull that freq. \nSo I just copied and then just pacing them here. And then to the paces across changes, flips price. And we want to know what are the range of the prices?\n\nWe just select those prices and then press control, shift down or command shift down. \nAnd then we looked in the corner, we can see the men and the max zero and 70 if also do these functions. Okay. \nSo we want to go from zero to 70 zero and then that is zero plus one. And then we're just going to grow that down all the way to 70.\nThe reason I did that is just a easier way. There's probably quicker ways. And now we have all the prices from the range. \nOkay. So we need to use the count gift function and count function just works like this. We need a range and a criteria as the ranges, what we're going to look up. And in this case, we just want the two cheap column.\nAgain, your control shift down, Redshift down. And that gives us the full range of that column. And then the criterion as you want to see if it counted, if it equals this price. \nSo in order to do that we just need to put the equal sign in quotation marks, lip, an ultrasound and then click on that price.\nAnd we have the function and that. Looks pretty good. But you can see here that as we go down, the range is changing. \nSo now we're like seven to one 60, so we're not actually getting before. Range. So what we need to do is set some absolute references. We're going to put a dollar sign in front of the numbers, but not the letters because we do want to drag this function across this way.\nAnd therefore we want the range to update from the too cheap column to the cheap, to the expensive. \nSo we're just going to probably do a sentence for the numbers and that way Yeah, it's something that causes a problem when we drive down it. So we get press control. And then that was control, shipped down and then controlled.\nFor pacing that function. Cool. So now, if we look at the range is always the same and then the price is just updating to cool. So you can see, we have the different frequencies. \nOne of the things we need to fix if we drag it across is right now. If we do drag it across, you can see that it's now, you know, the, the range coming across, like.\nThe criteria is going to be two, should be at a two. So we're going to fix that as well. And in this case we would just want to fix the blood to, so we wanted the, a column to not change, but the number we do want to change because we want to be able to dry it down. \nSo got I'm just going to control down provi.\nAnd then just going to drag this across here. I would just check that it's working. \nSo yeah, there, it's looking at the same ranges but it's getting it from there. Cool. All right. \nAnd then just grab those and then click double click in the corner that cool. So we can see that the frequencies of updated.
Hey, we're going to turn this frequency chart into a van Westendorp graph. \nSo the first thing we need to do is get the percentage shares. Great. \nAnd you have that go chat. \nAnd then I want a copy of this whole thing. Ctrl shift down, then copy control C, and then I'm going to paste again and then just get rid of this.\nSo crunch it down control, shift down if you're on a PC and then just press delete. Okay, cool. \nThat's a set up now, how do we add up these percentages? So looking at our frequency chart, we can see, you know, there are nine people who thought it was too cheap as zero. \nAnd then there are four people who thought it was too cheap at one.\nWell everyone who thought it was too cheap, but one also thinks it's too cheap at zero because it was less than the price that they said was too cheap. \nSo for the two cheap and cheap columns, we need to sum up the percentage of people you know, who are below that line. So don't worry. \nThat's going to be more sensitive minute and you'll see.\nSo just going to use. \nAnd we're going to say a, him, you come across as sick call, shut down. Sorry. Now I have the full range B2 to be 72. So we're going to take that, that sum. And then we're going to divide it by the.\nSome of all these people as well. So that gives us a hundred percent because a hundred percent of people thought it was too cheap ads. Because it's the lowest price. And what we need to do is to fix these things, say for press for or you could just put the dollar signs in yourself. We're always going to be summing up the total number of respondents, which is I think 154.\nAnd therefore, you know, we got these dollar signs here where we dragged the formula down or drag it across that range or move. But for this ranger needs something a little bit different. So when we drag it down to. What do we want to happen? We still want be 72. Still want it to go to 72. They put a dollar sign there, cause that's the end of the range.\nBut we actually want the beginning of the range to move up. I want to move to B three, so we're not going to put a dollar sign there. And we're also not going to put a dollar sign in front of B here because we want to be able to drag this function across. Okay, so hit enter, and then we can use autofill or, you know, you can double click on there or you can just press control.\nAnd then V control V for you know, this for reach. Okay. So you can see here. As the percentage decreases, there are less and less people who think it's too cheap based on the frequency, which is what we wanted. And this still works. Have you dragged it across here as well? I'm just going to drive that down so you can see that you know, just as we would expect the percentage of people who thought it was too cheap.\nYou know, lower at the, these low price points or sorry, higher at these price apartments then you know, the ones that the cheap price book. Okay. So we need to do something a little bit different for the expensive crowd. So let me just drag this across because you know, that was not true. That a hundred percent of people photos take sensitive zero we'd have a real problem.\nSo instead we need to do a slightly different range here. And instead of. The 72 hour need to go to D two. So we have this just the range that we're in right now. And then all we need to do is put a gold title in front of here, so, well, that's going to do, it's going to fix it at D two, but then when we drank down and it's going to expand the range that we're looking at.\nSo let's see that. And if we click, okay. Then we can see it's starting to increase. So, you know, there's nobody that thought it was too expensive. Sorry. There's nobody. Who thought it was too expensive below $10. But then as we started to get up to say like $50 you know, up to $60, a hundred percent of people thought it was expensive and we just kind of drank that across.\nAnd then that's the same thing. So we're just going to double click and you can see here, the opposite thing is happening as it did with the too cheap. The too expensive lime is below. Cool. So this is just data, like doesn't mean that much until you graph it and then it would make a lot more sense.\nSo let's do that. We're going to go to insert chart and there you go. Van Westendorp it looks pretty cool. You have this diamond and you can see where the the cheap and the expensive lines cross. Right. Which is, you know, you can actually see this on the chart where I started to see this in the data cheap and expensive where they become equal or roughly equal that's the, the tipping point where an equal amount of people.\nI think that this. Yeah, too expensive or you know, too cheap. So that would be maximizing sales, this Optum that's the that's a point of indifference. You know, I think a lot of people think it's too cheap, too expensive. The optimum pricing point is where this blue line and the green line cross as well.
Complete the Van Westendorp analysis. What was the optimum price point?
Our current price is $50/m. What would you recommend we do to the price after doing this analysis?
Can you think of any potential limitations of Van Westendorp pricing analysis?
This was very helpful, the results are even more useful than I remember from my last company\nThanks for figuring it out for me!\nI'll present this directly to the CEO\nShe'll definitely be impressed with the immediate impact you're having here :-)"