A Market Segmentation Case Study?

Date: June 5, 2012 | Shawn Herbig | News | Comments Off on A Market Segmentation Case Study?

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Market segmentation says that customers of a single business, whether retail or B2B, are not all created equally. When you separate your customers into different groups, you find out that their needs, expectations, and experiences can be completely different, and this can often bring to light gaps or cobwebs in your customer service that you can improve upon to increase customer satisfaction and sales.

Recently, a high end automotive repair shop with multiple locations here in the Louisville area needed some professional research done. The owner was frustrated and perplexed as to why the company’s profits were down, even though he was being told by his customers how great everything was.

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City Research: Beyond the Political Polls, What Does Your Community Really Think?

Date: May 29, 2012 | Shawn Herbig | News | Comments Off on City Research: Beyond the Political Polls, What Does Your Community Really Think?

Professional, targeted research is in a different league than political polling. The kind of institutional research that IQS Research does is not the same kind of research that a pollster does.

Polls can play an important role in city governments understanding their constituents, but the polls are often surrounded by political messages that can be misleading. To really get a tactical pulse on your community and the opinions of constituents, it’s vital to talk to the silent majority who will not hastily and loudly volunteer their needs and views.

From town hall meetings to city and county message boards, often the people who participate — the squeaky wheels — do not represent the majority opinion of the community. It can be too easy to take these participants’ input and run with it because it’s so accessible, but that’s a mistake.

You need to get the opinions of the silent majority, the ones who are sitting in their living rooms or are out working, or are in their neighborhoods volunteering, but are not showing up at meetings. Targeted professional research does just that, and it can reap tremendous benefits for your city or community, as a politician or community manager. Polling cannot.

A good example of this misunderstanding can be the perceptions of the downtown area of a community. Most people think they know what suburbanites think of downtown…it’s dirty, parking is hard to find, it’s dangerous, confusing to maneuver, etc.

But what we typically find is that most people don’t actually think these things at all. Most people who aren’t engaging with your city’s downtown don’t hate anything—they’re just apathetic. There’s a lot competing for people’s attention these days, and most of the time your downtown or the causes you’re focused on just don’t make the cut. It’s not about problems to be fixed; it’s about giving people a reason to care because apathy is the enemy, not negativity.

This insight only comes with a higher level of research, not with political polling. With this higher level research, you can make the changes in your community that will motivate people to make the trek downtown — or whatever large-scale community issue you’re dealing with — and not be distracted by the hidden agendas of a vocal few..

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5 Things Your Retail Customers Want You to Know

Date: May 17, 2012 | Shawn Herbig | News | Comments Off on 5 Things Your Retail Customers Want You to Know

Whether you own a restaurant, a retail store, or even just a gas station, your customers have certain expectations about you and what they want from you. Based on the research we have done for our retail customers, these are five common expectations that most customers share.

"Scan It" self-checkout kiosk at Gia...

  • It’s about the experience, not just the product. In this day and age, you can buy just about anything, sometimes even cheaper, on the Internet. But part of the reason people go to stores particularly local stores and specialty stores is to have the shopping experience. They want it to be clean, well-lit, and pleasant. If you can enhance the experience and give the customer a great feeling as they walk back out the door, your chances of return business grow exponentially.
  • Make it easy to buy. This isn’t limited to “we take Visa, MC, and American Express” it includes everything that touches the customer. From parking, getting in the door, shopping hours, and in-store organization, it has to be easy to fit an interaction with you into their lives. The hassle factor is a huge and it will keep customers out of your store.
  • There are many other options out there. Customers come to you for a reason. If the customer is in your door, they’ve already made at least a partial decision to shop with you. They could have gone somewhere else but chose your store instead. Welcome them and make them feel wanted. If you have a niche shop, then your expertise is valuable and will make customers want to come to you, not just because of products or price, but for the transfer of knowledge and help. But you have to make the experience enjoyable for the customer to learn. See our first point above.
  • Everything in the retail experience counts. If you own a retail store, and have the best and widest selection available. But a lot of your product are kept in the back of the store, the staff is subpar or unfriendly, customers have to navigate though messy aisles, then it will hamper customers’ motivation to come to you, no matter how good your selection is.
  • Customers are not alike. If you own a music shop you need to know that all musicians aren’t the same…a drummer is a different personality than a clarinet player, the rocker is different from the jazz musician. The customers know their own differentiating factors, and if you can learn those differences and adapt and cater to various types of customers, providing them a customized shopping based on their needs, you’ll certainly certainly be one step ahead of your competition..

Understand and follow these five basic customer expectations and you are well on the way to creating a loyal shopping experience where your customers will want to return again and again, and bring their friends.

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Data versus Information versus Insights

Date: May 15, 2012 | Shawn Herbig | News | Comments Off on Data versus Information versus Insights

If you ever decide you need the services of a professional research company, you need to understand the differences among data, information, and insight going into the research process.

And in order to effectively partner with such a research service, you need to be able to understand the data and information the research produces, so you can benefit from its insights.

But in order to be able to understand that, you need to understand the difference between data, information, and insights.

Data is the basic building block in research. These are the cold, hard facts that information and insights are built on. An example of data would be, “our research shows that 32.5% of your sales force reports that if offered a job elsewhere, they would take it.”

As far as data goes, that’s just a number. And depending on your HR knowledge regarding sales force attrition, you might be immediately horrified, or you might think that’s pretty good. But it’s that not knowing that makes data pretty useless. It’s only when the data is placed inside a context — is a 32.5% loss of sales force good or bad? — that turns that data into information.

Information is where things get more interesting and valuable to you as a manager. It’s where you can actually apply what the data means to you. For example, the average percentage of sales force attrition is usually around 33%. Armed with that information, you know your sales team is right on track. And knowing that information can lead to having insights about the research.

Insights are information significant to your organization. This is where the true partnership between you and your research company becomes important. It’s almost a marriage between the two players, with both sides bringing some important knowledge to the relationship. An insight could be that a year ago you implemented a salesforce retention strategy. Based on the earlier score (data) and the comparison to industry average (information) you can conclude that the retention strategy didn’t work.

At IQS, we’re the experts in the research development analysis, but we cannot know the working conditions within every client or posses the industry background of a 20 year veteran. But together, our two organizations can identify some pretty important findings about your company.

To continue with our example, if your sales team is currently lethargic and just not meeting their sales numbers, research might show that only 10% of your sales personnel would consider taking another job (data) which is well under the in the industry average (information). Since that’s below the average, it sounds like people may be complacent. It’s one thing if the sales team was exceeding their numbers, because they wouldn’t want to leave a place where they’re excelling.

But this lack of engagement may represent a toxic level of complacency and laziness within the company. This insight can help you decide if you need to perhaps replace team members or put more or different expectations on them.

From the bricks to the mortar to the design and function, the insights you gain through the use of a professional research team can be well worth the time and effort, because it leads to deeper levels of understanding within your organization.

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McKinsey’s results on employer based healthcare: It’s all in how you look at it.

Date: June 28, 2011 | Shawn Herbig | News | Comments Off on McKinsey’s results on employer based healthcare: It’s all in how you look at it.

McKinsey & Company recently released a report that claims that 30% of employers in the United States will drop their employee insurance coverage in 2014, when the Patient Protection & Affordable Care Act (aka Obamacare) takes full affect.  Before we get into the controversy surrounding these results (and they are indeed making waves across the research and government communities), let’s take a brief look at what the study indicated:

  • 30% of employers will definitely or probably stop offering ESI in the years after 2014.
  • Among employers with a high awareness of reform, this proportion increases to more than 50%, and upward of 60% will pursue some alternative to traditional ESI.
  • At least 30% of employers would gain economically from dropping coverage even if they completely compensated employees for the change through other benefit offerings or higher salaries.
  • Contrary to what many employers assume, more than 85% of employees would remain at their jobs even if their employer stopped offering ESI, although about 60% would expect increased compensation.

The point of contention is generally with the first figure mentioned above, namely that 30% of employers will drop employer-sponsored insurance.  It’s a figure that you see popping up all over the place, cited by the New York TimesNational Public RadioLos Angeles Times, and the Wall Street Journal (to name a few); not to mention all the independent bloggers and journalists out there posting on the topic.  In response, McKinsey has released its methodology and even has created a separate email address to direct all inquiries of the study.  The survey itself has also been released.

But why is this turning into such a controversy?  Simply put, it does not correspond with the past figures citing attrition of ESI due to the Affordable Care Act.  Furthermore, it is being used as political fodder among the Republican presidential nominees to attack Obamacare.  Other research conducted by the Mercer Group , the Rand Corporation, and the Urban Institute have all cited attrition projections that are much lower than McKinsey’s 30%.  And, what is more, it took McKinsey some time to release the methodology (they rejected any requests upfront, until they began to feel the pressure of every major news outlet screaming for it).

It is easy to become caught up in the controversy surrounding this, but a researcher, I am more curious as to the reasons why the controversy exists in the first place; particularly the data underlying the results and the way in which it was collected.

To be forthright, the methodology of the research seems to be sound enough, and the questionnaire itself does not appear to be skewed in such a way as to solicit particular responses.  But if this is the case, then why all the fuss?  The answer to this question lies beneath the surface of all this, as it is a function of context framing rather than accuracy.  And this, to some degree, is addressed by McKinsey in their methodology response.

McKinsey’s study was a study of perceptions, while Urban Institute et al used forecasting models to predict the impact the healthcare bill would have on ESI.  Given this delineation, it becomes clearer perhaps why such discrepancies exist between the various studies.

But why, you may ask, should these two models differ so drastically, and which one is more correct and reliable?  Well, for the second question, only time will tell and I’m not about to about to open that can of worms, but the first question can be answered pretty simply.

Perception studies, like the one McKinsey performed, are based on responses during a single point in time and are influenced by the emotions around that topic at that time.  As we have seen, the emotions surrounding this topic are particularly contentious right now.  This is not to say that all perception studies are fraught with emotion and because of this emotion they cannot be trusted.

In this case, the employers were asked if they would continue their ESI based on a specific scenario.  Some 30% indicated that they likely would not.  When 2014 arrives, maybe all 30% will do exactly as they indicated, but more likely, some of the respondents will change their minds based on the final financial implications as well as new information at that time.

Forecasting models, on the other hand, are designed to take into account numerous scenarios based on what the healthcare bill may provide and the predicted responses to the same.  Typically using regression modeling and past performance to functionally predict the behaviors of both people who indicated they would drop ESI and those that didn’t.

Perhaps emotions will die down and a larger percentage of employers will decide to stay with their ESI, or perhaps the forecasting models are underestimating the actual response come 2014 – time will provide that answer.  McKinsey’s study should not be discounted because it results differ from previous predictions.  And let’s not forget that the perceptions and opinions that they measured are indeed those of the decision-makers themselves.  However, this is a perfect example of how people can be misled by statistics and figures that give the appearance of contradiction.  I’m not trying to argue which model is right or which is wrong.  Both are valid and serve a valuable purpose.  My point here is an attempt to shed some light on perhaps why these models differ.

Research is about providing answers and both models provide different parts of the answer.  If we allow our own emotions and preconceived notions to take control then we will lose this answer in the midst of controversy.

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