47 minute video. By author Michaela Mora on September 15, 2016 Topics: Analysis Techniques, Concept Testing, New Product Development, Webinar
Concept testing is one of the most common types of market research many companies do. Unfortunately, sometimes no much thought is put into the concept design for testing purposes.
Lack of a clear process to develop good concepts to avoid confusion between product features and benefits or between product and positioning concepts often leads to results that are useless at best or misleading at worst.
To clarify things up, our friends at Alchemer (formerly SurveyGizmo), invited us to discuss issues related to product and positioning concept testing. Give it a listen (47 minutes) or read the transcript below.
Hello and welcome to our spotlight webinar how to get the most out of your concept testing my name is Sandy McKee I am the event specialist at Surveygizmo, and I will be your host today. Helping me on chat is Mel Langworthy, Surveygizmo’s training specialist.
I’m excited to introduce our guest today Michaela Mora. Michaela is the founder and president of Relevant Insights, a full-service market research firm providing highly customized action-oriented market research solutions and advanced analytics. Michaela is a 20-year veteran in the market research industry. She founded Relevant Insights in 2007 to provide direct and personalized access to market research expertise at an affordable price. Welcome, Michaela!
Michaela, before we get started, I have a poll for our audience. Attendees if you can answer this question here. Have you conducted a concept test? Even if it was a while ago, let us know by clicking yes or no so that we can see how many are familiar with concept testing.
It seems to be 50/50.
Okay, it looks like the majority has, Michaela. So, our audience, most of them are familiar with this concept. Concept testing helps you gain consumer feedback early in the process, early hopefully in the development process to minimize guesswork and maximize business results, ultimately to reduce your business risk.
Michaela, you have years of experience in concept testing, and I can’t wait to hear your tips.
I’m going to let you take it from here so go ahead and share your screen with us.
00:02:22 – Michaela Mora
Well, concept testing is one of the most common types of marketing research many companies do. Unfortunately, they are perceived as easy to do, and often it is the case that not much thought is put into their design, leading to results that are useless at best or misleading at worst.
In the next 40 minutes or so, I will be talking about when:
Let’s start with deciding when you need concept testing. In the context of marketing, concepts come in different forms.
There are products concepts or services, positioning concepts, advertising, packaging, website, store concept. Product and positioning concepts are one of the most frequent concepts subject to testing.
When I talk about concept testing today, I’ll be referring to issues and approaches related to the testing of products and positioning concepts. I want to make clear that we will be talking about concept testing, not product testing.
I’ll use the term product to refer to both physical products and services. The main distinction between product concepts and positioning concepts is that product concepts are about products or ideas, mostly focused on features, product attributes offered.
They are about the product itself, which can be clothing, can be houses, can be health insurance, software, while positioning concepts focus on the benefit customers believe they will get when they buy the product which can be feeling special because we get the highest quality, or saving money, or saving time
00:04:43
I want also to make a distinction between product concept testing, positioning concept testing, and advertising copy testing. They are not the same.
Copy testing is needed when you already have a winning concept and you need to test how to communicate it to the target audience. So, you might have learned something new about the audience and want to communicate with a different perspective, or you want to communicate it in a different way.
You might have a new tagline and different visuals, or you may want to address a different market or segment and you want to check if the copy you are using works.
So, to be clear, copy testing it’s about testing ways to communicate, not finding out what needs to be communicated.
When you are thinking about concept testing, particularly if you are discussing the idea of relaunching a current productor come up with a new one because sales are down, it is important to make sure there are no other business issues affecting current product performance such as product quality distribution, issues, ineffective media plan, ineffective advertising, or customer service issues, or any other problems specific to your business that might be interfering with sales.
00:06:18
When concept testing is needed, the most common problems related to concepts are lack of relevance. For example, VHS video recorders. New technologies have made this product obsolete, and it was recently announced in the media that this will be the last year they will be produced. There is no market, no spare parts, so nobody’s using them anymore.
Another reason is when products become a commodity, which often stems from more focus on price, and less on benefits, which leads to the proliferation of generic brands, me-too products.
You may have been too late to the market, so you needed your concept to go against the competition.
Another is competing alternatives that offer a better solution to your needs. We all know how digital technologies have offered better solutions in many fields.
For example, mobile deposits of check deposits have led Capital One to close many branches because many people are not going to them anymore, me included. So, they are now consolidating branches into new ones, which are remodeled and look a lot like Apple stores.
You may not be meeting a current need. This is what T-Mobile found and paid attention to. They saw that people were dissatisfied with the two-year contracts that have been the norm in mobile services, so they introduced the concept of no-contract phone service becoming the “uncarrier,” which has helped them to grow enormously in the last year, and now you can see that competitors are copying this idea.
Finally, you may be ignoring changes in customer behavior, also brought by new technology. A typical example of that is the digital cameras versus the film cameras or digital calendars versus paper calendars.
If you find any of these issues with your current product offering and decide to redesign current products or create a new one, you should then run concept testing to make sure that your offer is what the target audience really needs.
00:08:50
In order to develop concepts that really give you the answers you need, you must be aware of some of the challenges we face when creating the concepts that will be tested.
At the highest level, when going into concept testing, the first challenge is realizing we are not the audience for the concept to be tested. You need to know your current and potential customers’ unmet needs, and that seems obvious, but I have been in many concept tests, I have seen many concepts created with no basis on user research but on assumptions made by clients’ personal experiences or anecdotes.
If there is no prior supporting research about the users’ needs, if the product, engineering marketing research didn’t get together to define the concept, many assumptions are made based on the personal opinions, preferences, and attitudes of the people in the team, and each thinking they know that users best, when in reality there is a lot of personal projection on the concept.
Even when there is research available, the interpretation is often subject to personal opinion so people in the team need you to keep reminding themselves they are not the user or buyer. If something isn’t clear, more preliminary research may be needed before finalizing the description of the concept for testing.
Knowing the target audience’s needs will allow you to determine if your concept solves a problem in the market, if it’s relevant, if there is a real need that needs to be tackled and what type of benefit will the concept offer. Will there be emotional or functional benefits?
Knowing the audience needs will give you the context that should be included in the concept description as a believable scenario to express why your product is needed.
You also need to know how your product is perceived, what type of reactions and feelings incites and engages customers with it.
Finally, you need to know what competing alternatives are available that customers and non-customers, if you’re trying to expand the market, maybe using, o could use if given the opportunity.
All this information would allow you to understand the barriers the concept needs to overcome, and how strong and believable your offer is.
I know this easier said than done, because they are timing and budget considerations that may prevent us from doing more research prior to the concept testing, but when those considerations are brought up then we need to ask the team: Should we invest in a concept test that will give us results that can be useless or misleading because we are testing the wrong thing?
So, be mindful of the trap of thinking you know your audience without having done proper research or you will be wasting much more time and money than you would have then in doing research before launching the concept test.
00:12:11 – Sandy McFee
Michaela, I just want to address that, if you could go back go back to that slide, because you bring up key factors here. This means that you probably need to do a brand awareness study first or a competitive analysis prior to your concept test. I think that’s so important.
00:12:18 – Michaela Mora
It might be part of the research you need to do, yes.
00:12:34
The second challenge is understanding the difference between features and benefits. I have been in many client meetings where features and benefits are confused and used interchangeably and often there is an implicit assumption of the benefits when a feature is presented.
For example, if we have 32 megabytes of RAM in a computer is assumed that it makes it fast, and that speed is important to the user.
However, features and benefits are not the same. Features are part of the product output and answer the question: What does the product offer?
For example, it can be materials, size, color, brand, product selection, quality, service and warranties, friendly service, return policy, price.
All these are attributes, which in themselves, don’t mean much to consumers unless they produce an outcome and translate into a benefit by answering the question: How does this make my life better?
The benefits can go from the practical to the emotional, which is: provides me convenience, saves me time, saves me money, reduces stress, makes me feel happy, allows me to express myself.
Underneath all these benefits, the common theme is how this concept is going to make my life better.
And, although benefits are often classified in functional and emotional benefits, both types of benefits are usually connected.
But why is it important to make this distinction? Because we will be doing a different type of test depending on whether we focus on features or benefits. They have different objectives.
If we focus on features, we are doing a product concept, while if we focus on benefits, we will be doing a positioning concept test.
00:14:54
The third challenge is achieving relevance and simplicity in concept description and this is really, really hard for many teams. In product concept testing we want to answer the question: What features should the product have to provide the benefit customers want?
The answer to this it’s often used to determine which features should be developed, in what the company should invest. So, the concept should include clear descriptions of relevant features to the users and the keyword here is relevant. You can have a lot of features that nobody cares about.
Also, you need to present the context in which this product is used to justify why is this product needed and also be expressed in the language in which the users talk about this product. No marketing, no technical, no corporate jargon. It’s about how people talk about it, so they can relate to the concept.
So, say that through research, you have been able to determine the features and the corresponding benefits. You may have a list of benefits which may appeal to different segments. Now, you want to know how to position your product to reach your target market and make it stand out against the competition with the most important benefit of the list.
00:16:37
So, it is time for a positioning concept testing. In positioning concept testing the most difficult challenge is to simply answer the question: Why should I buy these from you with a positioning statement that we can test?
In the case of positioning concept tests, we are trying to figure out which benefit is the most appealing, which then will be used to advertise the product.
Again, we are not testing advertising, we’re not testing taglines, we are not testing language. We are trying to figure out if people will understand, will get the concept, and will they buy it, based on a particular benefit.
You need a clear, defensible, articulated, and emotionally satisfying answer packaged as a positioning statement.
So, the positioning concept should include a relevant and unique benefit supported by selected features. And important here is relevant, and also selected features, not all the features your product might have. It is just a few that support the claims that you make on a particular benefit.
Include the context, reflecting the need and an emotional state, again just to find why you need this product, and again expressed simply in the user’s language, no jargon.
00:18:02
To do this successfully you need to do preliminary research that can help prioritize the benefits and identify a common denominator across segments, if you have more than one.
If you have not done any preliminary research you are likely to come up with positioning statements that are crowded with features or benefits without a specific focus on anything particular, which gets easily ignored, or forgotten due to information overload or lack of attention or a memory hook.
I encourage you to avoid the kitchen sink approach. In the concept, if you put all the features and benefits that you have, you probably are appealing to many people, you are giving a little bit of something too many groups, and it might do well in testing but when it is time for launch, advertising only can focus on a couple of things.
So, at that point, the concept may fail because now you’re narrowing the benefits to a particular segment in the market, and suddenly you don’t understand why it was doing so well in the test, and now we launch it is not doing that well. So, your concept may be focused on their wrong features, missing your target completely if you don’t do the research.
And again, you may have a vague language, full of jargon the audience can’t relate to.
Preliminary research can also reveal issues related to actual product performance and quality, in the case of existing products. The concept of features, benefits and positioning may be appealing and meet a customer need, but the actual product may not be performing as expected. So, instead of spending money on concept testing it will be best to spend it on improving quality and performance.
00:20:13
So, let’s talk about how to do this. The ideal way of running a concept testing is to combine both qualitative and quantitative research.
Many companies stop at qualitative because they think is enough without being aware of the limitations of qualitative research, or there are budget and timing constraints.
But what is the goal of qualitative research? Qualitative research, by nature, is exploratory. You want to understand the range of behaviors, habits, perceptions, what is driving, what is the context in which people use the product.
The keyword here is range. You’re exploring what type of behaviors and needs are out there where my product with certain features and benefits can fit. You don’t know yet. You’re exploring that. You’re going to capture the users’ language, how people talk about your product. It will allow you to formulate hypotheses about what the relevant features and benefits are. It is important.
Hypotheses need validation, so this is the stage where you start asking questions about: With these features, this benefit or this one? We don’t know yet. But this type of research allows you to figure out what to test in the next step.
Please, when possible do this before quantitative. It will save you time and money in the long run, even if you have to make an upfront investment in qualitative research.
The common methods are in-depth interviews, focus groups, online bulletin boards, diary journal exercises, in-context observations, and all of this can be done in person, on the phone, and online.
So, please, iterate when possible. This is the case in which you do a round of qualitative, go back make changes, do another round. This process allows you to add information to the concept in a stepwise manner as you make sure the information added previously is clear, so we now understand people get this benefit in this feature, and then we have the next one. So, you get real-time feedback and can make quick adjustments, allowing you to optimize the final concept before quantitative research.
This is probably the best way you can get the most out of your qualitative research for your money.
00:22:59 – Sandy McFee
We have a question, Michaela. And it is all based on these data collection methods. You don’t list social media. Would that be another channel?
00:23:14 – Michaela Mora
You can use different… it depends on the category. So, you can collect data from social media too. Again, the type of methods you use, it depends on the category, where we can we find the sample, the type of product. So, social media could also be used as a data source for context and how people talk about it.
00:23:42 – Sandy McFee
Yes, yeah, we’re definitely seeing that here more at Surveygizmo. Thank you. Did we have any other questions Mel? All right, please continue on Michaela.
00:23:55 – Michaela Mora
Quantitative research, let’s talk about it, and why do I recommend it so highly? Well, qualitative, while qualitative research is descriptive, quantitative research, if done correctly can be prescriptive.
The first goal here is to test those hypotheses about the features, the benefits that we formulated during the qualitative phase. We want to know, do these hypotheses hold true?
We might have found different things in the qual, but we don’t know what the magnitude of those things are, and this applies also to trying to validate the final concept or concepts, if you have more than one.
What is the magnitude of the appeal and the likelihood to buy this concept? You may have found that maybe the majority of people that participated in the qual, they tend to be leaning towards the concept, [but] you still cannot extrapolate that to the general population or a bigger group.
Qualitative research, by nature, doesn’t allow you to do that. If you do it, it is not really helping you a lot, because this is the type of data that you need to really make go-not-go decisions on product or positioning launch. And so, if possible, do this after qualitative research.
I know some… I have seen projects where people jump directly to the quant. without doing any qual. before, and it’s a very risky proposition because we don’t know really what is being tested.
00:25:43
Let’s talk about the different methods. There are three main groups. The most widely used research designs for concept testing are: the first one is monadic concept test, and many probably who have done concept tests, have done this.
This is where participants are exposed only to one concept, which often consists of a description of either features or benefit sin both text and images. You only see one.
Then there is the sequential monadic testing, in which you have more than one concept, but the concepts are shown one at a time in a rotating fashion, so if I see it in any particular order, the next respondents sees it in a different order, but they will be seeing all the concepts.
And lately, more and more, there are trade-offs techniques that have been used.
And this is the case where several scenarios are presented and require respondents to compare concepts, shown simultaneously, and ask them to select the most preferred.
00:26:59
So, let’s talk a little bit about monadic testing because this is probably the most common test that many use in this area. As I said, we only show one concept to the respondents. If you have more than one concept, then you need to split the sample into cells. If you have two concepts, then you have to split the sample in two cells. Five, you have five cells. What are the pros of this approach? Well, is pretty easy to implement mostly.
Most products can be tested monadically. It is the best approach to avoid interactions, and by interactions, I mean when you see one concept presented, and you don’t get anything else, any other information that might contaminate your perception about that concept, except whatever people have in their mind, which we cannot control, but we are not putting other things around it.
We ask them to purely look at that concept, and sometimes it’s closer to real-life depending on the category where we use one product at a time.
What is the problem with this method? It is that it can become really expensive if you have more than one concept, because you need to have the sample size to be able to compare them, and that can become… you have five concepts and you have a sample of say 300 to be able to find significant differences between those groups, now you have a sample of 1500.
It might not even be feasible for certain categories because of the low incidence of interested groups, if they are very specialized. So, it can become tricky.
Another issue with this type of test, is the metrics that many times are used here, like the appeal, the uniqueness, likelihood to buy, they are based on scales, and rating questions are infamous for having very low discriminatory power.
And because we know that scales mean different things for different people particularly if you go to international studies across cultures. We know they have different meanings. So, you might find… I have seen many concept tests where you end up no finding any substantive difference because the scales might not be working well for that.
0:29:46 – Sandy McFee
Can you reiterate what question type are you using there?
00:29:51 – Michaela Mora
Rating questions.
00:29: 52 – Sandy McFee
Very good. Ok so, not the ranking but the rating for each…
00:29:59 – Michaela Mora
Yes, because when you’ve seen one concept, you’re asking in many times how likely are you to buy or how appealing do you find them in different types of scales, but essentially people are rating that the concept on many different…
00:30:15 – Sandy Mcfee
And, is it okay to use a table of rating questions rather than each one individually?
00:30:30 – Michaela Mora
What do you mean? Like you have several things on one table?
00:30:35 – Sandy McFee
Yes, related to that one concept.
00:30:39 – Michaela Mora
It doesn’t matter because you still are rating so, the issue is not the format, it’s more about the type of questions, you’re asking.
00:30:52 – Michaela Mora
In the sequential monadic testing, in which we have more than one, where people see one or the other in a different order, this is a popular approach mainly to save money because now you have more than one concept and you need less sample. Instead of two, you have two concepts now, you only with one sample you can test both, and it doesn’t require as many as people, and it’s also easy to implement.
The issue with this type of test is the interaction between the concepts because now whatever I saw first is going to influence, unconsciously or consciously, is going to influence my second perception, the perceptions of the second concept that I see.
If you have a very good concept, every time it comes first the second concept is going to have lower scores than… if you had tested that concept in isolation we would probably have higher scores than this type of approach because now it’s being compared unintentionally with the best concept. And again, this one also has rating questions.
00:32:20 – Sandy McFee
So, the order you show them in would be important correct?
00:32:21 – Michaela Mora
Yes, yes and usually you try to do that, you will try to avoid the bias order, but when there are really clear winners, you tend to have lower scores for the less important, I mean the less appealing concept than if you had just tested that one in isolation, you will have a different value there.
0:33:02 – Michaela Mora
Lately there is more and more interested in using trade-off techniques in this field, in the concept testing in which you still have multiple concepts shown, but you see them all at the same time in particular scenarios, so you are asked to compare and select one.
The common methods are pairwise comparisons, you see two concepts which are compared at a time. MaxDiff or Maximum Differential Scale in which you might have a long list of features or benefits or actual concepts, and from a big list and then you show three or four or five at a time and you ask them to select the best, the worst, or the most appealing, the least appealing.
And there is Conjoint Analysis, where different features or benefits are combined in a product configuration to describe a product or service concept within scenarios and you see several of these.
What are the pros of these techniques? Well it really allows you to test for a large number of features and benefits in a cost-efficient way because if you have many different features and benefits you can create many configurations, and if you would have to test those independently it will require a huge sample to test all possible combinations of them.
So, this is a way of testing many different versions of a product in a cost-efficient way which just one sample. The other cool thing about this is that you can test your product, your new concept in the context of your competitors, where you can put it side-by-side your competitors and see what happens. If you do something and if they do something, what happens to your, what is called, share preference because people are forced to make a decision between the concepts these techniques tend to be more discriminant, so they have greater discriminatory power.
It’s a very intuitive task for the people. They just have to choose. And it’s very good for international studies.
00:35:21
You have to make sure the description of your features works well in each culture that you’re testing, but the actual task is pretty intuitive in any culture. And this is the best option to test pricing.
You might be asking yourself, well but there is also… it might be interaction. Yes, it’s always in the context. You will be comparing concepts here, but there is an experimental design in the backend for what is presented to the users that works to avoid that you only see the best option versus the worst option or that one is favored over the other, so there is some considerations in the design that allow you to mitigate that issue.
00:36:16
The problem with this type of technique is they can pose a burden on respondents if too many features and products are shown. Particularly, if you see those conjoint analyses with a ton of features and benefits.
Many times, if you dig deeper, they haven’t done the qualitative research prior to this to be able to prioritize and say what things we should really be measuring, but these types of analysis have a higher level of complexity in the design and the analysis compared to simple monadic testing.
So, if you’re going to do this, I would recommend that you use an expert, someone who knows what they’re doing. I have been involved in many conjoint analyses in the wine space, and sometimes with just three or four items we’re testing and combining, it becomes really complex because there are a lot of prohibitions between them, so you have brands and you have pricing tiers, and certain brands can only show in certain pricing tiers, and it becomes for just three or four it becomes really, really complicated, so you need to know what you’re doing in this, and due to this complexity it can be expensive that way.
00:37:35
So, to summarize, how to get the most out of your concept testing we have talked about making sure the concept is the problem, and you don’t have any other business issues masquerading here the problem, and so before you launch that just make a business analysis to see what the problem is.
Determine if you need a product or a positioning concept because they have different objectives, and the content that you put in the concept is different too.
Understand the audience needs. Again, remember you are not the audience, so you can have a concept that is on target.
Make sure you understand the difference between the features and the benefits for your products, so your message is clear, and you understand what drives purchase intent.
Create concepts with relevant features and benefits, expressed in the users’ language. This is really very, very important.
Please do qualitative before quantitative tests, so you will save money and time in the long run. Quantitative tests can get very expensive, and you don’t want to get to the end and then realize that you were not testing the right thing, you wasted all that money so you have to start all over, or just forget about it.
Consider iterative qualitative research to optimize the concept so you are sure when you get to the quality you know this is the best concept we can come up with, we have explored all the issues that we needed to, and this is what we need to figure out, and now we can get the hypothesis with that concept validated.
Finally, use quantitative research to validate findings from the qualitative research and make go/no-go decision. Never make decisions just from qualitative research, never ever.
So, that was what I have for you today.
00:39:45 – Sandy McFee
Thank you, Michaela. These are very helpful being in marketing I really appreciate this I think more than anything people skip that qualitative phase before they move to the quantitative, they already have their assumptions and hypothesis and jump right to it, and you make a good point, you know, they want to save money but there are affordable ways to get that qualitative data first to confirm you’re on the right track.
00:42:12 – Mel Langworthy
I would like to add that the MaxDiff and the Conjoint analysis questions are really thoughtful and informative questions that can provide a lot of data, but one of the cons that you mentioned was that there’s that additional cost that’s associated with that either finding a software provider that has those questions or just the extra time that you would be paying a panelist for example to complete their response.
There is an alternative to that that can be maybe not as powerful but can also provide similar information like a thoughtful checkbox question, or they would be selecting features that are the most important to them, maybe including, you know, only limits on that where maybe you’re showing them 12 options, and they can only select three or four and then using a report like a total unduplicated reach and frequency report would be able to show you the combination of items that would reach the most of your respondents, and that test data as an alternative that would be possibly less expensive than that costly MaxDiff, Conjoint study.
00:41:23 – Sandy McFee
Maybe to your point, you could use that validation and select your top three at least. What do you think Michaela?
00:41:32 – Michaela Mora
No, I was thinking that you if you really do the homework before the conjoint, you can really make it very efficient. It doesn’t have to have a lot of information and burden the respondent…You want to present things in a context particularly if you.
Sometimes you use conjoint for product line optimization and you are not considering the competitive landscape but sometimes you want to see what happens with you, and the good thing about the conjoint and the MaxDiff is that you get simulators at the end, where you can play with different scenarios.
You say well, if you change the price to this level or we have this feature or that benefit what happens to the share of preference, what happens to the competitors, where are we getting… where we’re stealing shares from share or where are we losing shares too, so it depends on the objectives of the study, and the complexity usually can be narrowed down if you do your homework first.
00:45:42 – Mel Langworthy
Absolutely, a little bit of preparation can go a long way to make sure that that analysis phase is a lot easier.
00:45: 53 – Sandy McFee
Right. Well, you guys, we do have a question, and it is talking about the difference between MaxDiff and Conjoint. I don’t think everybody in our audience is familiar with both those terms, so how would you describe when to use MaxDiff versus Conjoint?
Michaela?
0:43:12 – Michaela Mora
Yes. So, MaxDiff is like the poor cousin of conjoint, and it can be done pretty quickly. Essentially what you get out of MaxDiff is the ranking of things that might be most preferred, most importan.t
What you do is: You have a list of, say features, and then you select through an experimental design, you show three to five at a time and you ask people, tell me which one is the most prefer or the least prefer, and you go through several screens through that. So, they are still making a trade-off, but it’s narrow to those in that set of features and there is no combination of things. They are just independent, and what at the end you get in this is a ranked list. Ok, these are the items in the order of preference.
The good thing with MaxDiff is that it gives you the magnitude of the preference, which you cannot do with the scale ratings. You cannot say, someone selects a five and someone selects say a four or two, you can’t say it is twice as much, which you can say that in MaxDiff.
00:44:36
In Conjoint Analysis, what you do is that you combine different… you let things move around and make different configurations of products, so say you are trying to sell houses, and so, you wanted to figure out what type of house will be most appealing to a particular segment, what type of features should the house have to appeal when you to create those model houses to select which models should we go after. So, you start combining different things from the house, the number of rooms, the number of bathrooms, the pricing, so all those that are key.
00:45:17
You figured out those are key variables during the qual because you come to this part of the project, and you just start combining them, and you present them in front of them.
It could be with images, and it could be with text. You see full house descriptions, five by five, you might see three houses and you choose one. The next screen you may see a different combination of houses and you choose another one.
In the backend what we do is, we run a model, a statistical model that estimates the probabilities that people would choose particular combinations, and so it allows you to have a particularly for pricing where you can do a lot of valuations on our price because in MaxDiff you cannot do that.
If you want to test something with prices you just put the concept with the price, and that’s it, but the Conjoint Analysis allows you to iterate different, we call it, attributes and levels so each attribute has several levels.
So, if you have price, price would be an attribute so you have a price and level that would be okay the current price you have 50% more 20% more or 50% less 20% less, and they just try making variations around it to see what price point, combined with others, because also again, as part of the context now you’re trying to ask people to look at this product in total and tell me what would be…, and some things will be more important to people than others, but that’s why you need to do the homework first just to present what is relevant and not omit, because also that’s a key thing in conjoint.
If you omit important variables that people consider when they’re making a purchase in a particular category, then your results will be totally biased because you’re missing a big piece of what people are really thinking. So, to avoid that then you should do your qualitative research.
I don’t know if I answered the question.
00:47:26 – Sandy Mcfee
Very good. We have documentation in our Help section – that gives images of the MaxDiff and the Conjoint Analysis for those who want to know, and you can see how they report as well how the questions set up, and how they report. So, please look at those examples. We’ve got some good ones there, and I think that’s all we have. I don’t see any further questions.
We’ll stay on the line for a few minutes if anybody does want to answer ask a question yet please do.
Michaela, thank you so much this has been really informative. I just find it fascinating of course I am a market researcher, so thank you for your tips.
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