as published on January 27, 2012 by the Dallas Business Journal

Customer satisfaction and customer retention, although correlated sometimes, don’t have a straightforward relation.

Customers may continue buying your products and services because of:

• Habit or inertia when the cost and risk of changing is perceived to be higher than the benefits and the customer experience may be “good enough.”
• Competing alternatives are as good or nonexistent.
• Price.
• Clearly superior products and services as well as excellent customer experience.

In customer satisfaction research, we typically ask about overall satisfaction with products or services. When inertia, lack of competition, price and partially good offerings are the main reasons why customers continue patronizing a product or service, an overall customer satisfaction score may be misleading.

To avoid being misguided by an overall customer satisfaction metric, you should include other metrics, such as likelihood to continue being a customer and likelihood to recommend the products and services to others. The fact is that no single customer satisfaction metric alone will be accurate enough.

Before putting a lot of weight on a single satisfaction score, making business decisions or basing employee compensation on it, design a customer satisfaction research plan with metrics that reflect the performance of your business in key areas, customer touch points and how you stand against the competition. Consider monitoring:

• Product/service design and performance
• Customer experience with your product or service
• Customer service
• Usage and satisfaction with competing alternatives
• Price sensitivity

When it comes to customer retention, adopt a holistic approach, use more than one metric and focus on key drivers.

There is a lot of debate about how to use social media content in market research and in which category it fits: Quantitative or Qualitative research?

The massive amount of content generated by social media and the proliferation of sentiment analysis tools attempting to quantify it, give the impression that it can be considered quantitative research and thus quantitative analysis methods (e.g. t-testing, regression, etc.) can be applied to it. However, the issues of data accuracy and representativeness have not been solved yet.

DATA ACCURACY

Anybody who has done coding of open-ended questions in surveys knows how difficult this is. Finding categories to classify the answers is a very subjective process. To attain some level of objectivity and find categories or codes that accurately reflect the content in these questions, we often need several iterations and different coders to achieve consensus.

In social media, as in surveys, more often than not, people write incomplete and grammatically incorrect sentences, and use irony, sarcasm or humor to convey their meaning. In social media it is even more difficult to discern what people are talking about, as there are no survey questions to filter the information by.

Unfortunately, there is not a good text analytic tool yet that can interpret language nuances as well as a human coder. Sentiment analysis tools still need to be fed with codes and definitions of positive and negative content defined by someone in order to count and classify content.

REPRESENTATIVENESS

Linked to data quality is the problem of representativeness of opinions. From customer satisfaction research, we know that people, who decide to provide feedback, are either very happy or very unhappy with the issue they give feedback about. Those who are in the middle often don’t bother to comment.

The level of category involvement also affects representativeness. Not all products command enough attention to be topic of conversation in social media, unless there is something that surprises or annoys the public (e.g. banks imposing debit card fees).

Then there is the issue of how we separate unpaid opinions from unpaid opinions, which are becoming more common.

APPLICATIONS

For the moment, until better text analytic tools allowing more accurate data cleaning and other tools that would help identify who is behind the opinions, are available, I think social media content should be considered as a tool in the qualitative research arsenal to explore and sometimes dig deeper in certain issues. Among its applications, social media content can be used to explore:

• Likes and dislikes about a product, brand or company
• Language used to talk about needs, expectations, barriers
• Problems with products, customer services that need a quick response
• Topics of interest within a product category
• Perceptions about a brand and its competitors

Social media content can be a source of rich insights, but we should be aware of its limitations and do not equal access to large amounts of text to quantitative research.

A client recently asked for advice about usability testing approaches. Her internal client wanted to do a traditional usability lab test, while she was wondering if a quantitative online usability approach was a better fit.

This question got me thinking about the advantages and disadvantages of each approach. As usual, no research method is perfect and each has his strengths and weaknesses. There are many tools available to do quantitative usability testing online faster and cheaper. Although these can also provide qualitative data, usability testing in the lab environment can give you a deeper layer of insights into user behavior on specific issues.

The table below shows what I have learned about usability testing, after managing two usability labs in my past life as a corporate market researcher.

Each usability testing approach has a purpose and complement each other. If timing and budget permit, you should use both. If you can only afford one or the other, think hard about the objectives and the type of decision you will make based on the results.

For detecting major problems or understanding at a deeper level why people find certain tasks difficult to do or what their expectations are, a qualitative approach is a more appropriate. On the other hand, if you need to make a decision about major changes or a redesign and need to know how big of a problem you have in your hands, or how you compare to your competitors, a quantitative approach would do the trick.

Not long ago I got a call from a potential client asking for research to determine why a recent marketing campaign failed to increase sales, despite a significant increase in awareness.

He had conducted an advertising awareness survey, and the results showed that many in the target audience had noted the advertising and gave it high ratings, but didn’t make a purchase. All possible explanations were merely speculations. He couldn’t pintpoint to any particular cause for this. The main problem was that he wanted to obtain evidence of a cause-effect relationship, but the research design was not appropriate for that.

The main method for causal research is experimentation. In experimental-based research, the causal or independent variables are manipulated in a relatively controlled environment. This means that other variables that may affect the dependent variable (e.g. sales) are controlled and monitored as much as possible.

In this case, the client had conducted the survey and analyzed the data without taking into account the effectiveness of the different marketing collaterals used, its market penetration, competitor activity, and some characteristics of the purchase decision makers. After doing some digging around, we uncovered that in some markets, competitors had launched high frequency advertising campaigns which helped the client indirectly by increasing category awareness, but not his sales. Also, the program targeted customers who were recent buyers and probably didn’t have a need for his products at that particular moment.

Surveys that are not designed as part of an experimental approach may show correlations, but not causality. To really connect the dots between cause and effect, we needed to create an experiment including different renditions of the marketing collaterals, different markets, customers at different stages in the purchase cycle, and different actions taken by competitors.

Experimentation in marketing has traditionally taken the form of standard test markets, in which test market are selected, controlled advertising is put in place, and the product is sold through regular distribution channels. The drawbacks of this type of test are that they can be time consuming, are often expensive and may be difficult to administer.

A more palatable solution is what is called simulated test markets in which individual are selected, exposed to the product or concept (e.g. via actual marketing collaterals), given the opportunity to buy the product in real life and if they buy it, they are asked to evaluate the product and state their repeat purchase intent. The trial and repeat estimates are combined with data about promotions, distribution levels, competitor activity and other relevant pieces of information.

Another possibility can be found in the popular freemium model, adopted by many businesses both in B2B and B2C, which mimics this process to some extent. This model can be used for experimentation and as a rich mine for insights at a low cost. The basic principle is to let people try it and observe what decision they make, after which research can follow to understand what drove their decision, controlling for other variables that may be affecting the outcome.

In short, if you want to understand cause and effect, you need to conduct experiments, which may include surveys as data collection method, but surveys in themselves can’t provide the answer. It is the  experimental design what will lead you to it.

Once you get over the AHA moment of the new idea for a product you just got, the question you should ask yourself is how you are going to position it. This is valid also for old products that need a makeover and boost in sales.

New products usually come in:

• A new form but with similar function as other alternatives (e.g. new bottle shape for a hair product)
• A known form with new functions (e.g. car with GPS)
• New form and functions combined (e.g. iPhone)

Product positioning often takes two forms: functional or experiential. Although, you can find a little bit of both in many ads, there is usually a focus on one of them.

In functional positioning, utilitarian benefits take the front seat by focusing on product attributes, how it works, how helpful it is and what needs it meets. An example is the 2011 ad for Boyardee Ravioli below. It uses its long tradition and beginnings to emphasize quality ingredients and non-preservatives as its main product attributes.

Experiential positioning, on the other hand, is about hedonic benefits, how they product makes you feel. A stellar example is the recent years’ Old Spice commercials telling women how they would feel if their men were to use Old Spice body wash: “We’re not saying this body wash will make your man smell into a romantic millionaire jet fighter pilot, but we are insinuating it.”

Recent research (Noseworthy & Trudell, Journal of Marketing Research, Dec. 2011, Vol 48, p. 1008), shows that new products that are moderately incongruent with what consumer expect from it, but positioned with a utilitarian angle like in the Boyardee’s ads, tend to receive more favorable evaluations than typical, congruent products or highly incongruent products. However, in experiential positioning, this seems to work in the other direction. In this study, congruent products were more likely to receive favorable evaluations than products that came in an atypical form.

This research, validated across 5 different product categories, found that “when a product is positioned on functional dimensions, moderately incongruent form causes consumers to perceive more hedonic benefits, whereas when a product is positioned on experiential dimensions, moderately incongruent form causes consumers to perceive less utilitarian benefits.”

These results suggests that consumers put more value on hedonic benefits once they understand what the product does, which seems logic, but not always considered. Have you ever seen a commercial and wonder what is it for? Check the G commercial created when Gatorade did a brand makeover a couple of years ago and left consumers scratching their heads.

Before you decide on how to position your product, I suggest doing research to understand:

• Prior knowledge about the brand, product or product category
• User behavior
• Awareness and usage of competing alternatives
• Perceived risks
• Price perceptions and willingness to pay

With this knowledge, you can create both functional and experiential positioning versions and test them before you decide which version to go with. One test may not be enough. Test a version, refine it based on the research results and test again until you feel confident that the positioning chosen is going to advance your product.

as published on December 30, 2011 by the Dallas Business Journal

Although brand awareness can boost purchase consideration, the actual buying decision is likely to be done well before a customer may be aware of a brand, recent research indicates.

New findings show that buying decisions are triggered rather by a need which sets the buying process in motion.

After making the decision to buy, potential customers often start researching what options are available, even if they are already aware of certain brands.

Being part of the initial consideration set increases a brand’s likelihood of being purchased, but there is still a chance for low-awareness or even unknown brands to be considered if they are discovered while the customer evaluates different options and the offer is compelling, affordable and inspires trust, among other factors.

Thanks to widespread Internet access, the growth of social media and the explosion of information sources on the Web, the evaluation of different options is easier than ever. This is why search engine optimization (SEO) is so important for new and small businesses.

If your brand is unknown or suffers from low awareness, first invest in researching your target markets before you start spending money in launching an awareness campaign or doing SEO, including:

• Needs and purchase occasions
• Category- and product-specific behavior
• Perceived differences between you and your competitors
• Appeal of your value proposition
• Demographic and psychographic characteristics
• Media consumption behavior, including the Internet and social media

Learning how your potential customers make buying decisions will allow you to invest your marketing dollars more effectively.

Whether you are starting a business that needs a website to represent it or already have a website that needs a makeover, you should consider testing different design alternatives before launching into development. Don’t assume you know your audience if you have never tested how it would interact with your website. Testing website designs doesn’t have to be complicated or very expensive.

In the concept stage you can do it as simply as using still pictures of different designs showing how it may look like. Do it with real content and as close as possible to a finished look. Even if the interactive piece is missing in this approach, you will learn tons about the first impression a design gives and its capacity to grab attention and invite visitors to come in and explore your website site.

By comparing website designs in a simple concept testing you will learn how different elements speak to your audience, including:

• Color scheme
• Layout
• Content organization
• Navigation expectations
• Potential sources of abandonment
• Brand image elicited by the design
• User identification as a member of your target audience (Is this website for me?)
• User concerns and anxieties about using your website
• User reaction to different calls to actions and labels

Testing these elements with your target audience (there is no such thing as ‘my product/service is for everybody’) early in the design phase will save you time and money in the long run as you will be able to launch a website that will work for your business from the get go. Of course, testing shouldn’t stop there as website interaction is a big factor in the user experience, and for that you may need qualitative and qualitative usability testing. However, if your budget is tight, the more reason to start with a simple design concept test. It would be better than just relying on personal taste or misleading assumptions about your target market.

To learn more how we can help you with this type of research check our Website Design Optimization Service. You can also check the case study about what we did we our website.

At the root of survey gamification are good, sound survey design principles. That’s the main message from Reg Baker’s presentation at the MR Festival.

Baker follows the cognitive process (Tourangeau, Rips and Rasinski, 2000) involved in how respondents process information and survey questions and points out the opportunities to create engaging surveys. When faced with survey questions respondents go through different phases:

• Comprehension: Understand the information, apply logic, connect key terms. Survey design can help comprehension by keeping questions simple, avoiding vague concepts, being specific, defining ambiguos terms and providing examples.

• Retrieval: Memories are retrieved and blanks are filled in. Survey design can make retrieval easier by offering cues, providing keys to important events, and decomposing the situation the question refers to.

• Judgement: Asses relevance, integrate material, draw inference. Survey design can aid judgement by managing the context to which the question applies, decomposing the question and discouraging overthinking questions.

• Response: Categorize, edit responses. Question formatting can improve response rate by avoiding certain question types (e.g.  open-ended, numeric questions, long grids) and using meaninful scale anchors.

Survey tool providers are racing to create different question formats (e.g. sliders, heatmaps, etc.) to make the survey-taking experience more engaging and minimize abandonment rates. However, with the increase of surveys and DIY research done by inexperienced people, the quality of survey design has declined. Writing surveys looks easy, but it is not. Fun and cool question formats can’t compensate for ill-designed questions.

I have to agree with Baker that the greatest improvement needed now to engage respondents is in survey design.

as published on October 7, 2011 by the Dallas Business Journal

Entrepreneurs often find themselves making decisions in uncertain situations when starting a business. Because of tight budgets, overconfidence or misconceptions about market research’s benefits and cost, they often resort to using emotions, intuition and mental shortcuts to make decisions.

But intuition doesn’t come out of the blue. It is the result of experience and practice to the point where knowledge is internalized and guides us without having to think all over again when faced with certain decisions. There is no denying the importance of emotions — in fact, without them, we can’t decide at all. However, what feels like “gut-feeling” or intuition sometimes may be only the expression of one of many innate flaws our brain has.

One such flaw is loss aversion. Research has shown that the pain of loss is twice as strong as the pleasure we get from a gain, so we will do anything to avoid loss, even if it leads us to do things that don’t benefit us in the long run.

I have observed it in many entrepreneurs I meet. They may be aware of the need to do research that will help grow their business in the long run, but struggle with the decision to do it because they think of research as a sunk cost and not an investment. The outcome is often one of these two:

• Renounce to the idea of doing any market research, arguing they trust their intuition (even if there is not much to support it).

• Take market research on their own hands (even without experience in market research) and use family members and friends for feedback or create online surveys. But this approach can be biased and ineffective and rarely reflects what the target market will think or do. Others try to be more objective and, to save money, run online surveys using one of the many affordable survey tools available today. However, often surveys are not well designed, samples tend to skew towards certain segments in the target market, and analysis is reduced to counts and percentages.

Entrepreneurs’ focus on immediate cash loss can lead them to future bigger losses without realizing it. Lack of research or use of ill-designed research can result in misguided decisions and derailed intuition by feeding bad information to the source that nurtures it.

You have probably heard about customer discontent with Netflix’s latest price increase and separation of services. The company expects to lose about 1 million subscribers by the end of Q3 2011 due to the prices changes. On 9/16, the WSJ reported that the stock was down 44% ($169.25) from an all-time high in July ($304.79). I still remember 4 years ago when the stock was $18. It is still high, but the decline is significant.

The decision was driven by Hasting’s vision about the future where video streaming should dominate, but he seems to have ignored the present forcing an experience on its customers that they were not ready for yet. He admits a certain arrogance based on past successes. It is a pity he has fallen in the same trap that other companies that get too big and overconfident. He should learn from competitors’ mistakes that at one point were considered too big to fail.

In none of his comments and late apologies he made any reference to customer research and feedback so I assume this was absent or if done, totally ignored.

As a former Director of Research at Blockbuster Online, a direct competitor of Netflix, I can testify that our team knew better than changing the customer experience and prices without doing research. Of course there were other factors influencing pricing decisions, but customer feedback was the most important by far.

Never forget how a price change may affect customer perceptions and ultimately their experience with your service. In this case, Netflix users not only got higher prices but also more work to do. Those who want both DVD and streaming video content have now to manage two accounts.

If Netflix had done some basic research it would have come obvious that people want simple solutions, not more things to do. This was actually one the drivers that led us to develop Blockbuster Total Access, as service in which we combined the online and store experience in one. By the way, Blockbuster has been quick to offer a 30-day free trial of this service. I got this flier in the mail today.

As for pricing, there are several approached you can use in pricing research, but measuring willingness to pay is tricky and asking questions in a realistic context is key to get accurate results.

A method, we often used at Blockbuster Online was conjoint analysis, which gave us insights into customer experience and perceptions regarding the value of different service features in relation to its price through the trade-offs they were willing to make (e.g. number of DVDs at a time vs. price) taking into account other competing alternatives for watching movies in the market (e.g. video rental stores, video on demand, movie TV channels, Hulu, and even Netflix, etc.).

This approach proved to be invaluable then and continues to be so for many of my clients across industries. Although, conjoint analysis may be impractical in some circumstances (depending on the competitor landscape, product or service features or simply budget), the lesson here is to do research before making pricing decisions and while you at it don’t forget the implications for customer experience. No approach is perfect, but they may prevent you from creating a Neflix-like pricing and customer experience mess.

Update 10/10/2011: It seems that Netflix learned its lesson the hard way and now reversed its decision to split the DVD rental and video streaming services in two after the strong customer reaction. A little research could have saved Hasting all this headache and would have prevent Netflix from losing subscribers and revenue.

To learn about other pricing research methods check Pricing Research Overview.