The Do’s and Don’ts of Marketing

Marketers fall into many traps in the quest for understanding their customers.

By Greg Kitzmiller

Don’t assume anything. We’ve all been told that dozens of times but executives still fall into the trap of making assumptions.

In life there are basic assumptions we can rely upon, such as the assumption that the world won’t change all that much in a day or two or the assumption that employees will come to work. However, there are other assumptions that are unreliable. For example, companies cannot predict future demand for products or sales based on past sales. While some use regression formulas to carve out future directions based on the past performance, there are in fact so many variables that can influence future sales, including competitors and trends.

Case in point: there has been a drop in consumption of many national beverage brands like Pepsi and Budweiser. These days both alcoholic and nonalcoholic beverages are in trouble and losing share to niche brands. The lesson here is never assume that big national brands are always going to be stable.

Not all Customers are Like You…

or Your Friends

Don’t believe all customers are like you. In other words, just because you may not like a particular product in development doesn’t mean that the target for that product won’t like it either. It is important to separate your feelings about the product in the context of what is relevant. In other words, it may not be relevant whether or not you like a product in development because chances are you would not be the typical consumer for that product.

And don’t think your customers are like your friends, either. While some entrepreneurs become very successful testing a product on all of their friends, we often forget that the majority of new small business ideas fail. Remember, your friends are more like you than their customers.

Drawing Conclusions from Customer Data

Don’t make false assumptions based on customer data because it often leads in the wrong direction. I’ve even seen analysts draw incorrect conclusions mostly because of the way the data was obtained and the questions asked.

For example, I recently oversaw a project where consumers were asked to rank their favorite ethnic foods. But there was no room for equivalency. In other words, if I like Chinese and Mexican food equally I was forced in this survey to rank one higher. It would then be an incorrect assumption to state that most people like Mexican food better. In that case a Likert scale (i.e., a scale of 1 to 5) would work better so consumers could rate each type of ethnic cuisine based on their preference. Using such a scale could easily show whether respondents liked two types of food equally or liked one more than another. While this explains a basic research error, there are other situations where conclusions are drawn and the data gathering was correct.

Causative Factors

Don’t assume causative factors. If consumers state cause and effect (e.g., because this product was on sale, I bought it) the conclusion is valid. But unless you have baseline data (how much is purchased over a reasonable time period when the product is not on sale) you cannot conclude causation, or cause and effect. This is an error I’ve seen junior research analysts make.

Focusing on Consumer Characteristics

There is no “average” consumer. Sorry, but this is my personal pet peeve. There is no female with 2.5 children, despite the fact that some business people want to refer to “Sally living in the Midwest with 2.5 kids” as an “average” user. It is usually far more appropriate to define consumer groups by characteristics rather than trying to determine the average gender, age, and demographics of one “average” consumer. While grouping consumers into segments is slightly flawed, it is more reliable than trying to define hundreds, thousands or millions of consumers as one person.

Perhaps in the 1950’s through the 1970’s American consumers had more of a desire to move toward some homogeneity by eliminating regional accents in speech and proliferating national chains and brands. Indeed, Ozzie and Harriet may have seemed like the quintessential American family to many and we’d all go eat at a McDonald’s or perhaps stay at a Howard Johnson’s. While national chains and brands are still very powerful, many consumers delight in differences now more than similarities.

It’s Quality, not Quantity

Don’t assume you know everything about customers from scanner or survey data. We are awash in data today. But good old-fashioned observations of and conversations with consumers can lead to a tremendous amount of insight that just can’t be found in masses of quantitative data.

Observing how consumers make choices is key. You don’t have to stand in the supplement aisle of a store very long to realize that many customers are confused by the category. Remember, understanding customers requires solid information that goes beyond the numbers of scanner data.

Today’s Consumers are Very Educated

Don’t think consumers are uninformed. Within minutes most people can get information, good or bad, from the Internet. While some customers are overwhelmed, and others may be confused, some are doing an amazing job of sorting through the mountains of information. As a consumer, I stopped taking a prescription pharmaceutical several months before the FDA pulled it because I was able to access the clinical studies in the Internet.

Today’s consumers can use Google or other search engines to find an incredible array of information that just 10 years ago would have taken them a day’s worth of research at the library. While there are many problems with misleading data on the web, there are plenty of consumers who recognize credible sources and stay very well in-formed. Consumers are not stupid, so don’t treat them like they are. NW