In a previous article about how to write product concepts for testing, I mentioned receiving a survey from a trade association which was trying to gauge my interest in online market research course using a concept description to which I couldn’t relate.

They also tried to estimate how much I was willing to pay for such courses by using a version of the four standard questions from the Van Westendorp Price Sensitivity Meter:

• At what price it is too cheap?
• At what price it is a good value/bargain?
• At what price it is getting expensive?
• At what price is too expensive?

In the Van Westendopr PSM approach, the results are displayed graphically using plots of cumulative percentages for each question by price point in order to find the “acceptable” price range and optimal price point.  The point where Too Cheap and Expensive intercept is considered the lower bound (Point of Marginal Cheapness), while the point where Cheap and Too Expensive meet is the upper bound (Point of Marginal Expensiveness) of the product’s perceived value. The point where Too Cheap and Too Expensive cross is called the optimal price, which is the point where the number of rejectors is expected to be minimized.

This approach is popular among some market research practitioners, because is very simple to implement and intuitive to the respondents and marketers. However, the output is often confusing to clients, not only because of the mental gymnastics they have to do to read all the curves and their relationships in the standard graphic, but also because it has no theoretical foundation.

Another concern with the PSM is that since it relies on direct questions about price, it makes the intentions of the research too obvious for respondents, which usually invites price lowballing. The chart below shows an example of a test we did for an established product, where the resulting “optimal” price point was $10 lower than its current price, which fell completely outside of the “acceptable” price range yielded by the Van Westerndorp PSM. Further tests showed that if we were to price the product as suggested by the PSM, we would leave a lot of money on the table since price was not the main purchase driver and no significant increase in volume could be expected by lowering the price.

Since the Van Westerndorp PSM doesn’t take into account competition, it is usually recommended for new products, but I find counterintuitive the notion that for a totally new product for which potential customers don’t have any point of reference or experience, we ask them to provide an estimation of its value. How can they really give us an accurate estimate?  The Van Westerndorp PSM may be useful for exploratory research to get a ballpark of acceptable price ranges, but I wouldn’t make a decision on its results without further research.

Regarding the case that inspired this post, using the Van Westerndorp PSM was an unfortunate approach. Online training using webinar-like setups are nothing new at this point, so the trade organization that sent me the survey is likely to see lower or similar prices to competitor alternatives. While I was answering the survey, I couldn’t but think of the prices I have seen for online classes and use them to guide my answers. It didn’t help that the concept was not well described, so I didn’t have much to hang on.

Following the questions from the Van Westerndorp PSM, I got this question:

 Really? What about “Over 50%”? Why would I want to get less than that? That’s the mindset we don’t want respondents to have.

As a way of summary, if you are thinking about using the Van Westerndorp PSM for pricing research, think again and consider that this approach:

• Incites lowballing by relying on direct questions about price
• Has no solid theoretical foundation
• Does not take into account competition
• Has no history of predictive success
• Does not allow us to optimize revenue, profits or net present value

 If you still want to do it, regard its results are exploratory and follow-up with more research.

 Which price research the trade association should have used to find the optimal prices and discounts for its online market research classes? Check Conjoint Analysis And Realism In Price Research.

This is part of a series of pricing research posts that Jeffrey Henning and I are writing. The series so far:

- Price Research Review

- Getting The Price Right Takes More Than Guesswork

- Conjoint Analysis And Realism In Price Research

- Making The Case Against The Van Westerndorp Price Sensitivity Meter

- The Van Westendorp Price Sensitivity Meter

- Monadic Price Testing: “Shh, It’s All About Price

- Estimating Willingness to Pay

To learn more about our price research service visit Price Research.

It is often difficult to establish a clear link between marketing research results and business outcomes, which frequently leads organizations to allocate smaller budget and staff to the market research function (if any) or just get rid of it. Among the reasons why this happens, we often find:

• Unclear research objectives.
• Misalignment of research objectives and business goals.
• Lack of a track system to monitor how investments in market research correlate with business results.
• Management’s little exposure to market research and lack of experience with how to use it.
• Poor execution of business and marketing strategies, despite accurate insights.
• Changes in the market driven by competitors’ actions that invalidate research results.

In order to understand market research’s ROI and connect it to the business impact it ought to have, we should:

• Establish a formal process that forces end-users of market research to think through what they want to achieve with the research. Steps in this process should include:
  

1. Ask the end-user to narrow down the scope of the study by filling out a form with questions such as:
   • What business problem triggered the need for the research?
   • How will the research impact the overall business strategies for customer acquisition and retention? What is the priority?
   • What decisions will be made based on the research?
   • What hypotheses, if any, need to be tested?
   • What type of information is expected to be gathered through the research?
   • What recommendations for action are expected?
2. Discuss with the research end-users how certain methodological issues such as sample source, sample size and analytical approach will impact the research outcome.
3. Get the end-user involved in the design of the data collection instrument (surveys, focus groups/IDI discussion guide, secondary data source, etc.) that will be used to answer these questions.
4. Lay out how the final report would look like, how the information will be presented and, once the data is in, provide a draft of the report to the end-user for review before final publication.

Although this step is designed for discussing specific research requests, the first point can also be used to identify the market research needs of different groups within an organization in order to craft an overall marketing research plan the organization should follow. This would help with project prioritization and resources allocation. Of course, the marketing research plan should be communicated to key stakeholders within the different groups in the organization, so they take ownership in the process and are open to use market research to advance the business.

• Create a distribution system to disseminate the research results. This could include:

1. An electronic library of research reports where users can find current and past research (which would avoid duplication of efforts).
2. Mini-workshops with key stakeholders of the research to discuss the research results and how they could be implemented.
3. A newsletter providing distilled insights and a summary of research available with links to reports. Use the newsletter to also give visibility to the groups that have commissioned research, which elevates the status of market research within the organization

• Establish a feedback system to monitor how the research results are being used and what impact they have on the business. This system could include:

1. Follow-up surveys, in-person or phone interviews with key stakeholders to track the decisions made based on the research.
2. Track the amount of money spent on research and compare it with the business outcomes (sales, savings, retention, etc.) based on decisions guided by the research.
3. Track key performance metrics using internal data (sales, operations, customer service, etc.) and analyze how they correlate with results from the research.

Connecting marketing research to business results is not easy, but it can done with the help of a systematic approach is adopted in order to get key stakeholders involved in the research process, share research insights and track their impact on the business.

To request consumer shopping behavior data and insights don’t hesitate to contact us.

Consistency and quality are key drivers in customer satisfaction and loyalty. This is quite obvious, but the fact is that many times they don’t move in the same direction.  Some companies offer high quality products, but the quality of the customer experience when acquiring or consuming the product is a hit or miss. Other companies are very consistent at providing mediocre products and bad experiences. This is why I don’t completely agree with Charles Blakeman when he says that the lack of a consistent customer experience is the reason why customers don’t buy your product. I think product quality matters, maybe more in some product categories than others and more for some customers segments than for others.

 I do agree that companies should have a customer satisfaction process in place that creates a consistent and good experience for all customers. However, a “good” experience is likely to mean different things to different customer segments, hence the need to tailor the process based on customer segmentation.

Most importantly, a customer satisfaction process should be anchored in a customer satisfaction measurement system that provides customer insights by monitoring key performance indicators (KPIs) that are relevant to the customer experience and the products and services offered by the company. KPIs can include different metrics based on data collected from customer transactions (internal data) and self-reported data (customer satisfaction surveys, interviews). Some of the most common KPIs are:

• Customer retention (tenure, repeated purchases, etc.) and churn (inactives, cancelled, etc.)
• Self-reported levels of customer satisfaction
• Likelihood to recommend the product and services to others
• Likelihood to continuing patronizing the brand or defect to competitor alternatives
• Performance evaluations of the company’s products and services
• Perceptions about the company and key competitors

Each of these KPIs can be customized for different teams in the organization and combined through a key driver analysis model that can tell us each team’s contribution to the company’s efforts in providing the optimal customer experience. This approach would allow the company to pinpoint where problems arise and find a solution to fix them.

To learn more about our customer satisfaction and loyalty research service visit Customer Satisfaction and Loyalty Research.

To request consumer shopping behavior data and insights don’t hesitate to contact us.

Marketing researchers are in the business of gathering data, analyzing and providing insights, which marketers, in turn, should use to develop marketing and branding strategies. However, sometimes marketers feel disappointed, when results from branding research show insights that were pretty obvious. They feel they wasted money in branding research, expressing their disappointment by saying aloud “I didn’t need to do research to know that.” My question is always: Why didn’t you act on such obvious insights? The answers are often:

• I wasn’t sure
• Too obvious, there must be something more to it

In a recent article about how insights can be used to build strong brands  by Notre Dame Marketing Professor Carol Phillips, she argues that we should not reject an insight just because it seems obvious. Before we put it aside, we must first ask:

• Does it reveal something about the target?
• Does it relate to the category driver?
• Does it capture how consumers want to feel?
• Does it speak to an enduring value?
• Does it challenge the brand to act in new ways?

I totally agree with Professor Phillips when she says that if you can answer yes to some or most of these questions, chances are you have an insight for building a powerful brand.

Conversely, I think these questions can be used not only to spot relevant insights (pun intended) to help build a brand, but also to assess the quality of the branding research provided. These questions should guide the research design and the analytical approach of any branding research endeavor to be able to obtain actionable insights, obvious or not. A branding research study that can’t answer yes to at least one of these questions is totally useless. Isn’t it obvious?

To learn more about our consumer data service visit Consumer Shopping Behavior Insights. To request consumer shopping behavior data and insights don’t hesitate to contact us.

I recently received a survey from a trade association exploring my interest in online marketing research courses, which I assume they are planning to offer. I was a little surprised to see the simplistic concept test approach they used to explore not only my interest, but also the price points at which I may be willing to buy one of their courses. 

Concept testing is a very valid approach to mesure appeal of product and services, but when it is not well designed, this type of research tends to yield general information that is not strong and granular enough to support decision making.

The first step in concept tests is to develop product concepts that clearly describe the “reasons-to-believe” in the product and touch on the experience the customer may have with it. The best source for good product concept descriptions is the potential customer himself. This is a case, where exploratory qualitative market research can bring a lot of value by uncovering what it is important to customers and what language they use to talk about the product. I wonder if the trade association that sponsored the aforementioned survey did its homework in trying to identify what features are really important to potential end-users of the product being tested.

The image below is a snapshot of how the concept was presented in the online survey. Of the four features described in the concept, the only one I found appealing is the 24/7 accessibility. The other three are quite vague and somewhat irrelevant.  What does it matter if the courses will have 3 to 8 hours of total instruction if I don’t know the length of each class or module? Is it 30 minutes, 45 minutes, 60 minutes? My work schedule and home life may only allow me to sit for 20 minutes at a time to attend an online class.

I quite frankly don’t know what they mean by “comprehensive instructions.” Are the classes task-oriented, will I need to do a lot in preparation to take the class? I associate the word “instructions” to manuals, so when I read this I feel weary already. Who has the time to read manuals nowadays?

“Dynamic interfaces” doesn’t tell me much either. A more concrete example would have helped to set my expectations. The image they use doesn’t have any indications of what the dynamic changes may occur. Without any guidance, my expectations could be too high, which can lead to a big disappointment if the courses are not on par with my notions of what a dynamic interface is in this context. A short video tutorial showing how this will work would have provided a better illustration of what the user can expect from the interface.

The most important feature of all for the target audience (which I represent) is the actual course topic and this is absent from the product concept. You may say, well, there are many topics of interest and we only want to test interest in the format. To which I would respond that the format is irrelevant if the topic is not of interest. The approach followed here doesn’t really reflect how the end-user thinks about this product. If topic is the most important feature in buying an online class, then excluding it creates an artificial product concept to which is difficult to give an accurate answer. When they asked if I would be interested in these courses, I could only say “might or might not.”

If you are going to conduct meaningful product concept tests:

1. Conduct qualitative research with members of the target audience.  Avoid “inbred” concepts based only on input from internal staff – A few interviews with marketing research professionals would have provided a richer and more realistic foundation on which to base the concept for online marketing research courses.
2. Create concepts that are concrete and put them in relevant contexts – An online course on a particular topic would have allowed me to give a more realistic response. A video could have shown me what to expect from the ”dynamic  interface.”
3. Write concepts in the target audience’s language – No “instructions” please!
4. Focus on Reasons-to-Believe arguments that highlight what is important to your audience – I need more than 24/7 accessibility to assess the value of this service. Topics are a good start.

This survey also attempted to measure price points that end-users are willing to pay for the online courses. I don’t think the pricing research approach they used gives the association the most bang for their buck, but that’s the subject of another article.

To learn more about our Product Concept Testing service visit Concept Testing and Product Optimization.

To request consumer shopping behavior data and insights don’t hesitate to contact us.