Marketing 101: Market Targeting

Recall that a customer driven marketing strategy consists of four distinct "steps".  Previously I focused on the first step: Segmentation.  I defined Market Segmentation as dividing a market into smaller groups that contain distinct needs, characteristics, or behaviors that may require distinct products, services and marketing mixes.  Because buyers have different wants, desires, needs, geographic locations, economic resources, buying attitudes, and buying practices, we use segmentation to divide markets into "pieces" that can be reached more effectively.  Market segmentation reveals our potential opportunities.  Once we have segmented the market, we must decide what parts of it to target.

Targeting the Market
We can define a Target Market as a set of buyers that share a set of common needs or characteristics that we can decide to serve.  When targeting a market segment we must look at three factors: a segment's size and growth trends, a segment's structural attractiveness, and our own company's long term objectives and available resources. The first factor consists of the type of research we have explored in the past when discussing Primary Data.  It is vitally important that we collect and analyze data on current segment sales, it's growth rates and potential profitability.  Once we have that data, we must compare it to the size and growth characteristics that our own company is seeking.

Next, we must investigate the segment's major structural factors that will determine how attractive our participation will be.  There are many reasons a segment may appear unattractive.  First, a segment is generally less attractive if it contains numerous strong and potentially aggressive competitors.  More competition usually results in many alternative products that create price competition and limit available profits.  Second, a segment is less attractive if buyers have more power, forcing participants to keep prices lower in order to increase market share, which also reduces  profits.  Third, a segment is less attractive if there are suppliers with strong influence in the micro-environments that actively try to hold material costs at a certain level, with increases our cost of goods, which also reduces potential profits.

Once we have produced a detailed evaluation of the target's structural factors, we must consider our own long term objectives and available resources.  Quite frankly, your company may not have the skills, knowledge, intellectual property and resources to succeed in a particular market segment.  A company should enter a segment only if they can offer outstanding value and can gain and retain competitive advantages over other companies in a given segment.

Choosing a Marketing Method
Once you have selected an attractive market segment, it's time to determine the marketing mix through a targeted marketing method.  Targeted Marketing is generally conducted at four distinct levels.  These levels are based on the relative size of the targeted segment.  In order of large to small, these levels are: Undifferentiated Mass Marketing > Differentiated Segmented Marketing > Concentrated Niche Marketing > Micro-marketing at a local or individual level.

Undifferentiated Mass Marketing
Undifferentiated Mass Marketing is a marketing strategy where a company chooses to ignore market segment differences (presented by their Primary and Secondary Data) and go after the whole market with one distinct product offering.  This type of strategy focuses on the most common needs of consumers, rather than on what is distinctly different between them.  This is a classic strategy from the early to mid-1900's, with the goal of appealing to the largest group of buyers possible in order to create as many sales as possible.  This is the classic volume-based tactic.  Product margins are low, and the value given to the customer is marginal as well.  Most modern marketers do not believe this strategy is very effective.  Today it is very difficult to make a product that appeals to mass-markets due to extreme competition from more focused niche products.

Differentiated Targeted Marketing
Differentiated Targeted Marketing is a strategy where we select several market segments, and design focused products and marketing mixes for each one, with the goal of higher sales and a relatively stronger position within each segment.  The advantage of Differentiated Targeted Marketing is that it typically gives a company higher gross sales across segments.  However increased sales also bring increased costs, because it can be more expensive to develop and produce 10 units of 10 different products (versions that are focused towards specific types of buyers) than 100 units of one product (for mass appeal or niche segments).  It also costs more to market for multiple segments, because each segment requires separate marketing research, analysis, planning, and channel management.  Due to these disadvantages, a marketer must weigh the prospects of increased sales versus the potential increased cost of business when choosing a differentiated marketing strategy.

Concentrated Marketing
Concentrated Marketing is a marketing strategy where a firm chooses to pursue a large share of one distinct segment or a few segments or niches.  Concentrated Marketing allows a company to achieve a stronger market position within a segment due to their greater knowledge of consumer needs and desires within that segment, fine tuning product features and prices over time in responsive to changing trends.  Concentrated Marketing is very appealing for companies that have relatively limited resources for product development and marketing.   Concentrated Marketing is also attractive, because segments are generally smaller and usually attract very few competitors, allowing for higher margins.  However Concentrated Marketing comes with higher than normal risks.  Because most of your business is focused within one or few segments, you may suffer large financial losses a segment turns sour at any time. 

Micro-Marketing
Micro-Marketing is a strategy where companies tailor products and marketing mixes to the needs and wants of specific individuals or local consumer groups.  Micro-Marketing generally involves consumers in all phases of product development, giving consumers opportunities to practice self-marketing during the buying decision process.  Micro-Marketing can give consumers extraordinary value, and can give the companies extraordinary value and consumer equity in return.  However Micro-Marketing tends to increase product development and marketing costs by reducing natural economies of scale inherent in manufacturing.  Micro-Marketing is also logistically complicated due to the numerous requirements of executing different regional and local marketing mixes.

Once you have evaluated and chosen a segment to target, we must work on Differentiation: differentiating the market offering (ie: the product) and thereby creating superior customer value.  I will explore this topic in my next post.

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Marketing 101: Sampling Plan

In the last Marketing 101 post we examined common Contact Methods for acquiring Primary Data.  I listed three traditional methods: telephone, mail, and focus groups.  The fact of the matter is that online technologies have completely changed how we as marketing directors and CMO's do our jobs.  I truly believe this is for the better.  It so so much easier to collect the Primary Data we need via online methods, and it tends to be more cost effective than offline methods.  However there are also challenges to online methods, and some of the same issues exist when it comes to the reliability of the data we collect.

Whether it's online or offline, if we're not doing focus groups, we're usually using surveys to collect Primary Data.  Surveys give us the opportunity to draw conclusions about different groups of consumers by studying a small statistical sample of the total consumer population.  The "sample" is the key.  A sample is usually defined as a segment of the population selected for our research that will represent the larger population as a whole.  Whether or not a sample is good enough to make observations with, depends on how we've designed it.

Designing a sample is a three step process:
1) Decide who you are going to survey
2) Decide how many you are going to survey
3) Decide how you are selecting the participants in the sample

Let's examine each of these three steps a little more.

1) Decide who you are going to survey
First, you have to decide who you are actually going to survey.  In more statistical terms, we are asking "what is the sampling unit"?  Any group of people can be used as a sampling unit.  What I mean here is children, adult women, men, etc.  Your sampling unit should be determined by the target groups in your survey, and the data you have about your target customers. If you don't know who your target customer is, then you have some research to do first.  Choosing the wrong sampling unit will waste your time and your money.  It will give you data that you cannot use, because the results from that group will be irrelevant.

2) How many should be surveyed (what is the sample size)
When we are asking ourselves "how many should be surveyed", what we are saying here is "what is the sampling size?"  Sample sizes that contain more people usually give us increased accuracy. For you statistical junkies, there are certain facts of mathematical statistics that describe this, such as the law of large numbers and the central limit theorem.  To keep this simple for our discussion, larger samples will give you more statistically reliable results than smaller sample sizes.  However, larger sample sizes will cost you more money.  Do not assume that you need to attempt to sample an entire population segment (which would take forever, and be almost impossible).  Usually less than 1 percent of a population segment will provide statistically reliable results.  There is a down-side to Probability Samples: cost.  Depending on your Contact Method, larger samples will result in drastically higher costs.  When cost is a factor, then researchers turn to Non-Probability samples.

3) How should the people in the sample be selected?
What we are asking here is, "What is the sampling procedure we are going to follow?"  There are two different types of samples we can choose from: Probability Samples, and Non-Probability Samples.  Probability Samples give each population member (a.k.a. a potential participant) a possible chance of being included in the sample.  Because you are not sampling the entire population, probability samples will always contain margin for error.  The larger the margin of error, the less trust you can place in the data you have that is supposed to represent your "population".  Larger samples give you less margin of error, and less margin of error lets you trust your data more.

There are three different types of Probability Samples:
Simple Random Sample
Every member of the population has a known and equal chance of selection.

Stratified Random Sample
The population is divided into mutually exclusive groups (such as age and race) and random samples are drawn from each group.  Basically, you are splitting your population into defined groups, and then sampling each of those groups.

Cluster (area) Samples
The population is divided into mutually exclusive groups (such as blocks, and they are relatively homogeneous) and the researcher draws a simple random sample of each group.

Non-probability sampling is much less expensive than doing Probability Sampling, but the results are of limited value, because the data is less reliable.  Non-probability samples should be used with caution. Non-probability sampling techniques cannot be used to deduce generalizations from the sample to the general population. Any generalizations created from a non-probability sample MUST be filtered through the researcher's knowledge (and yours) of the customer population being studied.

There are three different kind of Non-probability samples:

Convenience Sample
In a Convenience Sample, the researcher selects the "easiest", most convenient to locate member from the immediate population to obtain research data from.  I would consider this one of the most hap-hazard methods.  There is practically nothing you can generalize about the data you obtain, other than considering it a "snapshot" of a a particular group, at a particular time, at a particular place.

Judgment Sample
In a Judgment Sample, the researcher will use his/her judgement to select the the people sampled.  Immediately you have to ask...how good is their judgment in selecting a good candidate?  Again, the data that you obtain from this sort of sampling is just not reliable for generalized conclusions, but it may be interesting to use as a "snapshot".

Quota Sample
Probably the worst method I can think of, a Quota Sample is simply a researcher grabing enough people to meet a quota requirement for sampling participants.  Stay away from this sort of methodology.  Your data is practically useless.

Never select a sampling method without taking the time (as you always should) to weigh the needs you have when collecting Primary Data.  Always take into consideration your time-frame and your budget, and always try to be as objective as possible when you are evaluating the Primary Data you have obtained.



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Marketing 101: Primary Data - Contact Methods

In my last Marketing 101 piece, I spent some time introducing the Research Methods that we typically use in Primary Data collection.  Remember that Research Methods consist of surveys, experimentation and observation.  Surveys are the workhorse of Primary Data collection.  They tend to give us the bulk of our information related to customer trends and buying behaviors.  In order to conduct these surveys, information is collected in a variety of manners.  Typically these Contact Methods include mail, telephone, focus groups, and various other online technologies.

Mail
The mailed questionnaire is a classic primary data collection method.  It is very valuable, because it can be used to collect massive amounts of primary data for a very low cost per respondent.  We're talking the cost of paper and postage.  (Remember that you do need to calculate the labor costs of crafting the survey and processing the data once it comes back to you)  The data that you can collect from mail methods is usually considered very good for a few reasons.  First, there is little chance for "interviewer bias", because there is no live person there to ask the questions in a manner that could influence a person to respond in a manner different than they normally would.  Second, because they are not being interviewed in person, the respondents are usually more willing to give more honest responses.  And third, because you are not relying on the interviewer to record responses, no interviewer bias is introduced to the answers.  

However there are downsides to using mail as a contact method.  First, mail-based surveying is not very flexible, because all respondents are required to approach their surveys in the same way.  Second,  collecting primary data via mail is very slow.  It can take months before a reasonable amount of your sample sends the questionnaires back to you for processing.  Third, because written surveys usually take longer to complete, the response rate trends lower - simply because it takes more work.  The response rate is actually considred to be very fair.  It's harder to control the sample, beacuse you don't know which households will respond, let alone who at the residence will respond. 

Telephone
Telephone has always been a fairly good method of collecting Primary Data.  First, it is possible to collect massive amounts of data very quickly by using multiple people at the same time to call and conduct phone interviews everyday.  Second, telephone interviews allow for more flexibility, because your interviewers have the opportunity to provide clarity about any questions that respondents don't understand.  Third, you have excellent control of the sample, because interviewers can screen out callers before an interview is conducted. Fourth, with the right incentives, typically the response rate is actually very good.  

There are problems with collecting Primary Data via telephone as well.  First, the quality of the data you collect can only be considered fair at times, because the interviewer can inadvertently introduce bias into the answers based on how the questions are asked.  Second, because the respondents are interacting with a live person, they may not want to provide completely honest answers to questions that they may consider too private.  Third, telephone surveys are more expensive, because they require more labor.

Focus Groups
Focus Groups are a Primary Data collection standard.  Focus Groups have become a leading method for gaining valuable insight into consumer thoughts and feelings and their buying behaviors.  Traditionally focus groups consist of a moderator leading six to ten people.  However technology has allowed focus groups to be conducted through video conferencing and webinars via the internet, which allows people from different locations to be connected together which can improve sampling. These groups will participate in discussions about products, advertisements, services, and even organizations.  The focus group attendees are usually paid a small sum for attending.  The moderator will attempt to lead an easy and free flowing discussion hoping that free honest responses will be given.  Data is usually recorded by the moderator, however sometimes focus groups are observed by staff members via cameras or through one-way windows.  

Focus groups also have their issues.  First, focus groups use much smaller sample sizes in order to control cost and keep their sizes manageable.  Second, because sample sizes are so small, it is hard to reliably statistically generalize the results.  Third, attendees of focus groups are not always candid and honest.  The phyiscal and sociological environment of the focus group can create peer pressure, which leads attendees to alter their results in order to "fit in" with the people surrounding them. This is being combated by using environments that are relevant to the products and services being studied in order to get more relevant and open responses.  Fourth, focus groups cost much much more to conduct due to the costs of time, labor, location, and data acquisition.  Only use focus groups when it is appropriate and you are looking for specific types of data that you cannot reliably acquire with other Contact Methods.

Online Methods
The internet has single-handedly changed the Primary Data landscape.  Researchers are no longer confined to using mail, telephone, or physically location-bound focus groups.  There are many electronic alternatives to all three primary contact methods.

Email surveys and survey research websites are very affordable alternatives to direct mail and telephone interviews.  Because they are electronic, they are much less expensive to conduct, and data is instantly stored into a database that can be manipulated and analyzed. It is also quicker to create a large sampling, because your contact list can be created by interfacing with your existing customer database, or by purchasing lists of consumers from secondary data companies.  As with mail, the quality of responses tends to be very good, because it is an impersonal process and respondents feel more open to share more "private" information.

Another alternative to the telephone or physical focus group collection methods is Skype, or any other video conferencing type of technology.  Because Skype and services such as Oovoo are available for free or very little cost, it is much less expensive to conduct focus group research when the researcher needs to observe the reactions of the attendees.  These services will usually have the ability to record online "meetings", which allows you to store and refer back to interviews easily.


No matter what contact method you choose to use in your Primary Data collection process, it is important to spend extensive time up front evaluating the type of data you need, and which methods fit your required data types, cost, and schedule.


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Marketing 101: Primary Data Collection - Research

In this edition of the Marketing 101 series we will take a quick look at Primary Data collection.  So far we have been discussing data that is considered secondary.  Secondary data was collected by someone else.  Whether it was your sales department, or a comScore research report that you purchased, it was created by someone else other than your department.  It did not involve any of your department interacting with existing and potential customers to collect data.  It was not collected with your marketing objectives in mind.

There is nothing wrong with secondary data.  You cannot perform any Market Intelligence without secondary data.  It is a great and necessary starting point for any of your research.  Secondary data is critical when you are defining the problems and objectives that are the focus of your Marketing Intelligence initiatives.  However in most cases, you will need to collect primary data of some kind in order to have the information you need to make real decisions.

What is Primary Data?
Primary Data is research that has been conducted by your organization, first hand. It is also known as Field Research.  It is usually more reliable than secondary data, because it is usually more accurate since you collected it yourself.  Primary data is specific and relevant to your products and services. However, Primary Data is often very time consuming to collect, and usually costs more to create than purchasing secondary data reports. You must take special care when collecting primary data.  It needs to be relevant, current, and as unbiased as possible.

Primary Data is relevant when it directly applies to your company's products and services.  It is relevant when it relates to the problems you are trying to solve, and the marketing goals of your organization.  Primary Data is current when it is recent, and directly corresponds to the profile of your customers TODAY.  Primary Data is unbiased when your subjects have been honest and open during data collection.  When constructing your Primary Data collection plan, you must consider research methods, contact methods, the sampling plan, and your research instruments.

Research Methods consist of observation, surveys, and experimentation.  Contact Methods typically consist of mail, phone, personal interaction, and various online methods.  Sampling Plans take into account units, size, and procedures.  Research Instruments typically consist of questionnaires and other mechanical instruments.  Let's start with a quick discussion of Research Methods.  There are three typical ways that Primary Data is collected in marketing: observation, surveys, and experiments.

Observation
Observation is the collection of Primary Data through observing people, their actions and the situations they are in.  Observation may be the easiest research to do.  Typically, observation is also the most cost effective method.  Observation can also give you data that people aren't usually willing to tell you themselves, such as their feelings, emotions, attitudes or the motives behind their buying decisions.

How does observation work?  It's extremely simple.  Take a restaurant franchise owner.  He may be planning on opening another location.  He may also have little or no money to pay for marketing research.  However a lot of the data he needs he can collect himself.  He can get into his car and drive around town, observing the traffic patterns.  He can see where his clientele goes to shop.  He can see what time the traffic appears.  He can call real estate agents and ask them for lease prices for different properties.  He can drive around and look for areas that don't have his type of restaurant, looking for areas of little competition.  He can do all of this for just the cost of the gas in his car.  You can do this yourself.

Surveys
Surveys are the most common method of collecting Primary Data.  Surveys are the best way to get the descriptive information that you need for your marketing intelligence.  Simply put, surveys collect data by asking other people a series of questions about their personal knowledge, emotions, attitudes, preferences, and buying behaviors.  Surveys can provide you a wealth of data.  There is always a golden nugget, a piece of data that can give you the insight you need to figure out the direction of your next campaign.

However, there are drawbacks to the data you collect via surveys.  Often people just don't recall some of the information that you are asking for, and as a result, they are unable to answer the questions.  Therefore the response that they give will not be the complete truth, it may be something that they feel you want to hear.  Sometimes people are unwilling to provide information that they might deem "private".  This prevents completely truthful responses, and it skews the data that you are analyzing.  If the responses seem too good to be true...they just may be.  

Experimentation
Primary Data can also be collected via experimentation.  Experimentation is the practice of gathering data by selecting matched groups of people, giving them different treatments or scenarios, controlling related factors in their environments, and checking for differences in their responses.  Experimentation gives us what we call "causal" data.  Causal data helps us explain cause and effect relationships.  Experimenting helps us try to answer "why" someone is doing something, and what influences their buying behavior.

A common example of experimentation is price testing.  To the buyer, price will be the final emotional factor that determines whether or not they will give us their hard earned money.  Depending on the product and market segment, price may be the most important factor.  How do you know what price is the right price?  You have to test it.  Many companies will test certain prices when collecting primary data on a new menu item that is being developed.  How do you think McDonalds knows how much to charge for a Big Mac?  They tested how much they can charge for that Big Mac, looking for that magic number that will provide the most sales and the most profit.

In my next post we will continue this exploration of Primary Data by examining different contact methods.



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