FIT: The Most Important Thing in Business?

I can't recall how the topic came up, but the other day someone asked me if it bothered me to lose clients.

My answer: "it depends."

If the loss is due to poor service quality or slow response, I hate it.  Fortunately, this has been rare, mainly because my staff works hard to make sure that any problems that arise get fixed ASAP.  We also do root cause analysis to figure out ways to prevent it happening again.

But if the loss is because our services are a poor fit with a client's needs, then I'm fine with losing them.  In fact, at some point, if our clients are successful, their needs outgrow our ability to provide effective service.  Rather than attempt to hold onto them or expand our services, we encourage them to "graduate" which usually means helping them hire their own, dedicated staff as our replacements.

In terms of new customer acquisition, because we aren't under pressure from investors for fast growth, we don't try to work with everyone.  Instead we focus on determining if there is a good fit between what we can do vs. what the client needs.  I estimate that I end up declining (or referring where possible) about 25% of the prospects who approach us because of poor fit.  "Poor fit: doesn't mean that the client is bad (although "nice people" is one of our fit criteria).  It means that after 5+ years doing this, we have a pretty good idea of who we can help vs. who we can't and have experienced the consequence of working with clients with whom we were poor fit. So while it means we may be giving up revenue, it also means we give up:

• Conflicts with clients who have different expectations about the work being done.
• Overextending ourselves into areas where we lack expertise.
• Arguments about our fees.

We look for fit along the following dimensions:

• Fit to our standard offerings vs. having to develop custom capability. 
• Fit to our flat fee revenue model vs. traditionally hourly billing
• Fit between our people and the client (i.e. we don't work with people we don't like)
• Fit between our response time capabilities and the client's response time expectation
• Fit between our quality levels and the client's expectations

And I don't think it actually has hurt our revenue growth.  For the past three years, we've actually grown our business at rates even a VC would find acceptable.  In fact, paradoxically, our focus on fit may have actually contributed because:

• Our sales cycles are short because we have a sharp focus on the value we can provide and what we cannot. We try to be clear telling new prospects what we do, and more importantly to them, what we don't do.
• Our standard operations are tailored to deliver that value making it easier to scale.
• It allows us to focus on improving adding new capabilities valued by the majority of our clients (vs. one offs) in a way which is clear to both parties that these are *WARNING* new services.
• We have high client satisfaction and loyalty which fuels referrals.  In fact we are at the point that over 95% of our new business is by client referral.  This is actually one of the metrics indicative that a business has achieved product/market fit.

In order to adopt a focus on fit, you first must accept the fact that not all revenue is good for your business!  That's tough to do when you are short on sales.  Then you must have an idea of what  your target customer profile is AND what value you provide.  For specifics on how to do this, see two earlier posts:

• Developing a Customer Profile
• Applying the Customer Profile

Third Time Shameless Pitch: BUS213 is On Again!

Yes, it's back!  For the third year in a row, I'll be teaching BUS213-Validating Business Models: Principles of Product/Market Fit at Stanford Continuing Studies (http://bit.ly/O5GXw7).  This six week course starts on September 26, 2012 and is held Wednesday evenings from 7:00-8:50 pm. 

Signs ups are happening now.

How to Set Prices: Customer Value Analysis

5th and final post in a series on How to Set Pricing

I first learned about value pricing as a product manager at Metcal.  At that time the company was a startup making high end hand soldering equipment for PCB assembly houses.  To give you an idea of how high end, at that time a Metcal soldering station sold for 5x that of competitive units, and the consumable tips were 10-15x that of the competition in what most would call a commodity market.  Yet, in eight years, the company went from being the #8 to #2 market share player.

Now while there were many reasons for the company's success  - superior technology, ergonomically friendly design, robust product quality, etc. - the killer app in the company's sales arsenal was a customer value analysis created by one of the sales managers.  This simple spreadsheet model translated the product's feature/benefits into a quantified customer value proposition.

When distilled to the basics, B2B customers buy products and services for three ultimate value objectives:

• Reduce costs
• Increase revenues
• Reduce risks

Faster speed, greater convenience, and growth usually translate into one of these three.  In Metcal's case, the product features translated into the following benefits:

• Superior solder joint quality (reduced defect costs and risk)
• Faster soldering time (reduced labor cost)
• Elimination of calibration (reduced labor cost)
• Faster operator training time (reduced labor cost)

Metcal's value analysis was an Excel spreadsheet that allowed customers to input their time, process, and cost data, compare them against the cost of acquiring new solder stations and more expensive consumables and see the return on investment, payback, and net present value figures associated with the value created.  On top of that, the value analysis often prompted customers to consider factors that they may not have thought of, like training time.  The financial decision makers inside the customer quickly saw that the acquisition cost for Metcal's products was a relatively small percentage of the overall value created (in this case reduced costs), the essence of value pricing.

The main idea behind value pricing is that if your offering creates value, you price such that you and the customer share it.  Normally, this is not 50/50 but weighted in the favor of the customer;  the more value the customer captures, the stronger the value proposition.


Value pricing is widely practiced in B2B markets, especially where relationships are complex and long term.  Examples include logistics outsourcing where the supplier is paid on the basis of procurement costs reduced; SaaS vendors often price their subscription services to capture 10-30% of value created for customers over a three year time horizon vs. using a traditional enterprise software solution.

To create a value analysis requires a deep understanding of how your offering impacts a customer's business economics.  Gaining this insight takes time.  For a startup to gain this insight, it typically must have access to a someone with extensive, specific domain expertise, one who understands the customer's business model well enough to know where the lever points are that have the greatest potential to affect profitability and growth.

Creating a Value Analysis
In order to create a value analysis, you need to know the following well enough to code it into a spreadsheet:

• What is the main value proposition you are offering to your target customer?  Lower costs, higher revenues, lower risk?  For Metcal it was mainly lowering the per unit cost of production.
• How does this tie into the customer's value calculation? For Metcal, this had a direct impact on the direct labor line in cost of goods sold on a P&L.
  
• What are the factors used by the customer to assess value?  For Metcal, production rate, labor cost, defect rate, calibration and setup time were input factors in assessing value.
• What factors are not used by the customer to assess value and should be?  For Metcal, many customers neglected to factor in operator training time.
• What is the feature => benefit => value proposition chain for each of your offering's features?  For example, Metcal's superior technology => x% defect rate reduction => y% less rework => z% lower cost.
• What is the relevant payback factor used by the customer?  Is it payback time?  IRR?
• What is the relevant payback time used by the customer? 

Assuming that you can create a value analysis, two value methods can be used to set  pricing.


Method 8:  Share of Value Pricing
In this method, a "typical" customer use case is created using the value analysis.  Pricing is then set at 10-30% of the value, adjusted as needed for competitive market conditions.  This method is practiced by many SaaS companies relative to traditional enterprise software offerings.

Method 9:  Performance Pricing
Alternatively, for a specific customer, using the value analysis, compensation is based on a defined percentage of the value created (i.e. savings or revenue growth).  This method is often practiced by industrial logistics suppliers, auto parts suppliers, electronic contract manufacturers., and cost-control consultants.  Think of it as the corporate equivalent of a commission plan.  Because payment is dependent on performance, using this method requires you to have a good handle not only on the customer's economics, but your own.

Summary of Pricing Methods
To summarize the nine different pricing methods discussed, they are:

1. Cost Plus Pricing
2. Direct Market Competitive Pricing
3. Competitive Substitute Pricing
4. Target Customer Survey
5. Price Bracketing
6. Price/Feature Stripping
7. Customer Set Pricing
8. Share of Value Pricing
9. Performance Pricing

Happy pricing!

How to Set Prices: Value Pricing Methods

4th in a series on How to Set Pricing

Last post we discussed tangible pricing methods.  We now turn to value pricing methods.  Simply put, value pricing methods seek to establish a price based on some percentage of the value perceived by the customer.  While this seems straight forward in theory, this can be difficult to establish in practice for the following reasons:

• One must understand what the customer perceives as value in your offering
• One must understand the customer's time frame over which value is calculated
• The full value may be in intangible areas that the customer may not be aware of

Customer Perception of Value
In order to determine what percentage of value you can capture in your pricing, you must first understand what your offering's value is to the customer. This means you must first understand who your customers are.  Again, while this seems like a no brainer, I've found that for most startups, while they have strong beliefs about who their customers are and what value they are offering to them, they actually have NO CLUE.  Beliefs unsupported by data means NO CLUE!

Does that sound harsh?  See if you can answer the following question about your customer value:

• What is the demographic profile of your target customer?  What hard evidence do you have to support this?  Can you put this on paper?
• What are their acute pains in ranked order and what is your supporting data?
• How does your offering's features address each acute pain and what customer evidence do you have to prove this? (Not what hypothetical, logical reasoning you have that it should address this?)
• What competitive substitutes are your target customers using today to address their acute pain and how do you know this?
• What does your customer's life look like before they start using your offering?  How is it different afterwards?  What facts do you have to support this?
• Can you construct a mathematical model for value analysis that shows how different levels of acute pain reduction translate into customer value?  (This will be the subject of the last post in this series.)

If you can't answer these questions, I would argue that you don't truly understand the value of what you are offering your customers.  For help on this, see my previous post "Developing a Customer Profile".  A large part of the value of Steve Blank's customer development methodology is to convert these customer beliefs into customer facts.

There are a couple of methods that can be used to collect value data.  But unlike the four tangible pricing methods discussed previously, value pricing methods require (1) talking directly with individual target customers (2) an attempt to close a sale and (3) involve the risk of alienating a target customer to get the data.
The reason for this is that the only form of validated value data is a sale or other binding purchase commitment.  What people tell you they will pay in conversation is very different than when you ask them to sign a purchase order.

Each of the methods described below requires that you:

1. Know and have access to customers who fit your target profile
2. Have a hypothesis about your offering value that you can quickly communicate to customers (see my post on "Focused Selling")
3. Have hypotheses about how different features of your offering address target customer acute pain

Method 5:  Price Bracketing
Start discussion with an initial set of target customers.  Once you think you have a good understanding of the reasons the customer might buy and they have a good understanding of what you have to offer, to get an initial feel for value, ask two questions:

• Below what price would this be a "no-brainer" purchase that you could commit to today?
• Above what price would there be no chance of them ever buying and why?

Once you've determined this, tell the customer your pricing is coming in at a figure that is 75% of the range (i.e. if the "no brainer" price is $100 and the "no way" price is $1100, the 75% figure is $850).  Try to close the sale.  Most likely when (not if) they balk, find out what's stopping them from making a commitment today and pay attention.  Assuming you still can't close the deal, thank them for the valuable information and let them know that you obviously have some work to do on your costs and find out if they would be willing to talk again in the future.  Most likely, if you do this with 3-5 target customers, you'll quickly be able to determine what parts of your value proposition are holding up and which need adjustment.  Adjust accordingly.

Method 6:  Price/Feature Stripping
Armed with a new offering presentation from Method 5, ideally meet with a different set of target customers.  (If you are in a small B2B market with a restricted set of target customers, you may need to go back to the first set).  This time, once you think you have a good understanding of the reason the customer might buy and they have a good understanding of what you have to offer, try to close a sale at the 75% price number from Method 5.  Depending on which reaction you get do the following:

• Customer Accepts:  Congratulations, you've gotten a sale...but you haven't learned much.  Raise the price by 20% before you talk to the next target customer.
• Customer Rejects:  Understand why.  Then get a counter-offer.  Once you have it, talk about which features you can strip to get to the counter-offered price.  As you have the feature stripping discussion, you should get a feel for the relative value of each feature.

Again, 3-5 target customers should give you a good feel for how your value proposition should be adjusted.  It should also give you a feel for your minimum viable product.

At this point, go back to the first set of target customers and let them know that you've found some ways to work the cost issue both internally and by removal of certain features to get closer to the the previously discussed "no brainer" price.  See if you can close the sale again, this time at the average counter-offer price from the second set of target customers.  You will then get one of two reactions;

• Customer Accepts:  Congratulations, you've gotten a sale and validated the feature/value hypotheses.
• Customer Rejects:  Understand why.  In many cases, the new objections won't be price based, but will be sales process based.  Congratulations, you can now move forward to address the non-price related set of impediments to gaining market traction.

Method 7:  Customer Set Pricing
One alternate method for determining value is to let customers set their own price.  Examples of this include self-published e-books where the author request that people pay what they think the item is worth and museums, which request visitor set donations in lieu of an admission fee.  The most obvious risk of letting customers set prices is not being able to set prices adequate to cover costs, but depending on the nature of your offering this method may work for you.  To be viable it helps to have:

• Large potential customer base where the volume of payers is likely to be large enough to offset the inevitable free riders.
• Target customer base has some social or peer pressure element to pay something - This works for many charitable organization and the museum example cited earlier.
• Low or no incremental cost to delivering additional offering vs. probability having more paying users - In the case of the museum whether they have 500 or 5000 visitors a day does not change their operating cost but greatly increases the likelihood of donations.  For the e-book author, once the book is written, delivering additional copies across the web is pretty cheap.

There is one final method for setting value based pricing.  This involves the creation and development of a mathematical customer value analysis.  Pricing is then based on some percentage of this calculated value.  This will be the subject of the final post in this series.

Next post:  Customer Value Analysis

Service Not Surveys

Lately it seems like you can't shop anywhere without being asked to fill out some survey.  The ones that drive me crazy are "Customer Satisfaction" surveys.  Maybe I'm cynical, but I swear there is an inverse correlation between the length of the survey versus the quality of service delivered.

A case in point: I own a Subaru SUV and overall I'm pretty happy with both the car and the the dealer.  In fact, this is my second Subaru from this dealer.  They had a nice no nonsense sales process.  No "I have to get approval from the sales manager" baloney.  But happy as I am with the sales side, I'm less than impressed by their service department.

A few weeks ago, I was driving down Highway 101 when my "check engine" light flashed on.  Normally, I ignore these as it usually turn out to be something minor, like a malfunctioning knock sensor.  But in this case, Subaru tied it to several other idiot lights. The end result was my dashboard flashing like a Macy's Christmas display.

Fortunately (or so I thought), I was only two exits from the dealer.  What luck!  They should be able to figure out quickly whether or not this is a real issue or the usual trivia. For those of you familiar with the "check engine" light problem, you know that it takes a mechanic about a minute to plug a handheld device into the car and diagnose what the potential causes are.

I pulled into the dealer service department.  Now this is the same group that advertises its concierge type service, white glove treatment, free car wash after every service etc. to justify their premium prices.  This is also the dealership that routinely sends out an annual "customer satisfaction" survey.

The service representative was busy so it took several minutes to get his attention.  No big deal;  after all I'm a drop in.  But once I finally got his attention and described the problem, instead of just plugging a handheld device into the car and figuring out whether I was going to need real service or not, I got some sob story about how busy they were and did I want to be scheduled for an appointment next week? "Maybe, " I replied but first I wanted to know if it was potentially something for which is was worth scheduling an appointment.  The dealer is ten miles from my house; an appointment involves dropping the car off for the day and arranging for a ride to and from work.  I also have to find a day when I don't have any off-site meetings.  This is not something I want to do if it turns out to be a faulty knock sensor or some other triviality.

No luck.  The guy wouldn't budge.  So I didn't schedule an appointment and drove off.

Later that day, I decided to visit the Jiffy Lube four blocks from my house, where I get most of my routine (and substantially cheaper) service done, on the off chance they might be able to diagnose the "check engine" light.  Again, all the mechanics were busy, but the manager took the time to stop what he was doing and talk to me.  Thirty seconds later, he has a handheld plugged into my car.  A minute later he asks me to pop the gas cap cover.  He twists the gas cap into the fully locked position and resets the light.  Problem solved.  He then explains how a missing or loose gas cap is a common cause of a false "check engine" lights without once even implying that I'm idiot for leaving the gas cap loose.

Talk about two totally different ten minute interactions.

Being in the service business myself, it once again reminded me that customers are PEOPLE, not an abstract marketing profile, how important it is to treat people as you with to be treated and how important these little interactions are to keeping customers (i.e. PEOPLE) happy. In Subaru's case, while I love the cars, you can bet I'll continue to look for alternatives to their very expensive service department.  In the case of Jiffy Lube, that manager once again cemented a 15+ year customer relationship.  I should mention, that this is not the first time this group has done some little extra for me that keeps me coming back (on top of their quality work and fair prices).

And its not just in service businesses where this is important.  It is the rare product that requires zero support.  If you analyze your product from a whole product standpoint, you'll see lots of places where a support person at your company needs to interact with a real live human being that is a customer.  SaaS ("software as a service") has been touted as one area where everything is customer self service, but I've found that nothing is further from the truth.  The good SaaS companies understand this.  For example, one of the reasons I like Intuit Payroll (formerly Paycycle) is that their chat help line is great (and I hate chat and instant messaging).  It's convenient, timely, and so far, they've always been able to solve my issues. Think about that if you're a SaaS company striving to reach that magic +90-95% renewal rate that seems to be a threshold for survival.  And in addition to being critical to retaining customers, good service can be a formidable barrier to entry for smaller companies, difficult to replicate by a larger, more bureaucratic competitor.

Now in this case, both Jiffy Lube and Subaru have customer satisfaction surveys.  Jiffy Lube's was a quick online thing which I was happy to fill out.  Subaru's is an annual booklet and bubble chart questionnaire that I expect will arrive in the next few months.

I've scheduled it for an appointment  with my round file.

Applying the Customer Profile

3rd in a series on Customer Segmentation

Two weeks ago, we showed how to construct a customer profile.

Creating a Value Proposition Hypothesis from a Customer Profile
For a startup, one of the most important reasons to create a customer profile is to use it to formulate a value proposition hypothesis, the heart of developing product/market fit.

To illustrate, lets start from the example profile from before, looking at just the two pain points highlighted in red in Table 1:

Table 1

We create a new table (Table 2) with pain on the left, value proposition hypothesis in the middle, and product/service on the right.

Table 2

 Initially, the value hypothesis is an unvalidated best guess.  This needs to be validated in discussions with target customers fitting the demographic column (highlighted in blue in Table 1) of our customer profile.  As we iterate over time, the middle column can be changed from value hypothesis to value proposition.

Note that the value hypothesis describes the benefit derived by the customer in relieving the pain.  Ideally, this should be quantifiable.  Value hypotheses usually tie back to increased sales, increased speed, decreased cost, improved performance, or improvement in quality.

The far right column shows the product feature hypothesis (i.e. the specific product or service) we are offering to deliver on the value proposition.  This too need to be validated in discussions with target customers as to whether these product features actually deliver the value the customer wants.

Lead Qualification Using the Customer Profile
Whether as part of the hypothesis validation process or for sales execution, the customer profile is the starting point for qualifying leads.  To illustrate, focusing on just the two demographic points highlighted in blue in Table 1 we create a new table (Table 3) with questions we can use as part of a qualification script in the middle column and information learned or actions to take listed on the right.

Table 3

A good lead qualification script should shunt a raw prospect into the appropriate customer profile among multiple profiles or completely out of the sales process.  What I've skipped in this example is that we actually have several different customer profiles of which I'm only showing two (highlighted in orange in Table 3) called "serial entrepreneur" and "1st time entrepreneur".  If a raw prospect fits none of our profiles, it means that they are either not a fit or we potentially have a new customer type that requires further profiling.

I'm not going to cover the creation of lead generation scripts here.  But typically it's a flowchart with subsequent questions or action determined by the answer to prior qualifying questions.

Customer Segmentation from Customer Profiles

One of the fundamental premises behind marketing strategy and positioning is the concept that markets can be segmented.  The better your segmentation, the better you can target your offering which if executed properly should enable you to dominate your segment better than competitors who do this less effectively.  That's the theory.

One practical implication of this is in the area of sales resourcing and forecasting using the classic sales funnel.  To see how this works, Table 4 shows a simplified comparison of the sales funnels created from the two profiles highlighted in orange in Table 3.

Table 4

Note that based on our customer profile and our understanding of each type's pain, we have two different value propositions.  And in the case of 1st time entrepreneurs, we know that we likely have an additional step - education - not necessary with serial entrepreneurs and that that step has a fairly low yield rate.  This means that we know that to close the same number of new clients we have to talk to seven times as many 1st time entrepreneurs as serial entrepreneurs (30:4 ratio) and that it takes longer as well.  This has obvious implications about where we target our sales time and resources, what resources we use, and how we use them.

Customer profiles:  don't go to market without 'em.

Developing a Customer Profile

2nd in a series on Customer Segmentation

Last week, we defined a customer as someone who can pay for your product and wants it.  With this clearly understood, we can move on towards actually constructing a customer profile.  What is a customer profile?  A customer profile is a document that describes:

• Who the customer is (demographics)
• What distinguishes that customer from a different type (meaningful differentiator)
• Customer pain
• Customer buying behavior

As an example, here is a format that I use with my clients (there are others):

By far the most important part are the sections highlighted in green which deal with customer pain.  This is where your product's features connect with your customer's needs and are the source of your value.

Note the two right most columns entitled "hypotheses" and "hypothesis validation".  That's because in the beginning, particularly for a startup, these are your best guesses, not facts, and require validation.  This point, of course, is a fundamental tenet of Steve Blank's Customer Development methodology and in particular, the Customer Discovery phase.  The validation process is iterative with hypotheses being reclassified as facts only on the basis of specific concrete data (may be qualitative as well as quantitative).

So how does one begin filling out this matrix and constructing a Customer Profile?  A good place to start is with the generic ideal customer.  While there are several different variants of this running around, mine has just three core plus one nice-to-have attribute as follows:

• Core:  Customer is able and willing to pay for your solution
• Core:  Customer has a problem and is aware of it
• Core:  Customer has acute (or overt) pain
• Nice-to-have:  Customer is able and willing to act as a reference

If the customer does not have a problem or is unaware that they have a problem, then they are unlikely to take action.  In the case of the former, no action is required.  In the case of the latter, you would need to embark on a length education process.  While a large company with resources and time on its side may be able to undertake the process of educating the market, a small company usually can't afford this and would be better off seeking a different customer.  In the case of a startup, having to educate the market can be fatal as the cash usually runs out before the customers get educated.

What's the difference between acute and latent pain? Acute pain can be defined as an immediate discrepancy from a desired state.  This discrepancy can be negative (i.e. a problem that needs to be cured) or positive (i.e. an opportunity that can't be accessed).  In either case, the chance of a customer taking a buy action to relieve the discrepancy is high.  Latent pain can be defined as a potential discrepancy, not yet realized and which may or may not occur, again in negative and positive flavors.  In this case, buy action is less likely and price sensitivity higher.  For examples of each, see my earlier blog post on Confident Selling.

So how does this work?  Again, I'll use an example from my own company.  Here's how the ideal customer criteria flow into the top three row of the Customer Profile:  demographic, overt pain, and latent pain:

From this, the before and after story can be constructed and we can start to identify the basis of some form of ROI or value analysis.  In this case possible ROI bases could be penalty costs, opportunity cost for the entrepreneur's time, and/or expected value outcomes for failing to achieve funding etc.

So once we have this, what can we do with it?  There are three main areas:

• Value Proposition Hypotheses Development (product/market fit)
• Lead Qualification
• Customer Segmentation (basis for competitive strategy)

Next week:  Applying the Customer Profile

What is a Customer?

1st in a series on Customer Segmentation

Recently, I've been helping a couple of clients to profile and segment their target customers.  This is fundamental to developing a successful business development strategy.  It's also a core component of developing product/market fit for a startup.

In spite of the many methodologies developed over the years, customer segmentation still has an element of art about it.  It involves the use of inductive reasoning to infer from customer interviews and various other data sources what the meaningful differentiators are between customer segments.  What complicates this is that customer segmentation can be done on a wide variety of dimensions:  psychographic, demographic, geographic, socio-economic, etc.  But more on this in a later post.

The first step in performing customer segmentation is developing one or more customer profiles which describes who the customer is, what distinguishes that customer from a different type, and other information relevant to connecting what a company has to offer with what the customer wants to achieve.  I will talk more about constructing customer profiles starting with next week's post.

However, in helping clients - particularly startups - construct customer profiles, I often need to first clear up a subtle but critical misunderstanding about what constitutes a customer.

Common but erroneous definition of a customer:  Someone who wants your product.

Correct definition of a customer:  Someone who wants your product and can pay for it.

Let's take a look at both elements.

Someone Who Wants Your Product...
Want is something the prospective customer controls.  But with respect to buying behavior, want come in three flavors with three likely outcomes:

• Acute pain - This can either by negative in terms of a problem that must be fixed or positive in terms of an opportunity that is being thwarted.  The customer is consciously aware of this pain and is willing to pay to relieve it.  The likelihood of a customer taking action is high.
• Latent pain - This is tougher.  This can either again be negative or positive, but in this case, the customer may not be aware that they have a problem.  For example, the customer may be losing money due to duplication of processes in different departments but unaware of it because its not being tracked, or some other reason.  This is often the basis of enterprise software sales.  In this case, the role of the seller becomes converting this latent pain into acute pain by making the customer aware of it in some meaningful context.  This is the essence of salesmanship.  The likelihood of action is low until the latent pain is converted into acute pain.
• Want - This is something the customer might like to have but the presence or absence of this particular feature is unlikely to sway the buying decision nor is the customer likely to pay much for it.  As an illustration, many years ago, I was negotiating to buy a car and the salesperson tried to convince me that the pinstripes on the car were a $300 feature.  So I told him to take it off, knowing full well this wasn't going to happen.  In the end, the pinstripes stayed on the car while the $300 got knocked off the invoice.  The likelihood of action fulfilling a want is slim.

...and Can Pay For It
While a desire for your product is a necessary condition for a customer, it is by itself insufficient.  For example, I would love to buy a Tesla Roadster, but have no intention of paying $100,000+ for it.  But if someone in Tesla's marketing department were putting together a target customer profile based strictly on a demographic profile, I might seem to be a good fit.  (I'll let you speculate as to what that profile might look like.)  Should Tesla count me as a target customer?  Only if they want to waste a lot of money trying to reach me.

So, as my teenage son would say, "duh, isn't it obvious that a customer should be someone who wants and can pay for your product?"  Yet I see regular, ample evidence that this point is not understood.  For example, take a look at the market opportunity section in five startup business plans.  At least three of them will have an estimate of the Total Available Market (TAM) that reads something like this:  "There are 150 million smart phone users in the United States that download at least one application per year.  This means given a download price of $24.99, the TAM for our virtual nose-picker app is $3.75 billion!" (Incidentally, if you're having difficulties seeing the attribution errors here, see this post.)

I also routinely see companies waste sales and marketing dollars trying to reach prospects who might want but don't have money to buy their products.  It's amazing how few salespeople actually ask their prospective customers whether they have money in the budget for the product solution they are offering until they are well into the sales process.

Perhaps a rewording is in order.  Customer:  Someone who can pay for your product and wants it.

Next week:  Developing a Customer Profile