One question to determine a startup’s success?

Let us stop looking for a single predictor of success, be it a startup or an established enterprise. I saw a TechCrunch interview of Mr. Peter Thiel, of Clarium Capital.  The TechCrunch post is titled, “Best Predictor of Startup Success Is Low CEO Pay”, and Mr.Thiel was quoted as saying

In practice we have found that if you only ask one question, ask that.  (CEO Pay)

This is the classic single question trap. There cannot be single metric that can be “the best predictor”.  You should ask

1. Does correlation mean causation?
2. Is there cause-fusion – i.e., do successful startups pay low CEO salary?
3. What about all other lurking variables? What if there is another variable that drives CEO’s low pay and success? (Omitted Variable Bias)
4. If low salary is good, is lower salary better? (reductio ad absurdum)
5. What about other startups that have CEOs with low pay and still fail?
6. A startup, hamstrung by lack of resources and low cash flow may pay low or no salary, is that still a predictor of success?
7. What about the congruence between the startup’s strategy and the needs of the market it serves?

Let us not forget  Predictive Analytics slippery slope. If you want to ask a startup questions, here is my list (not claiming predictability):

1. What jobs will your customers hire your products for?
2. Who do they hire now, i.e., who do they have to fire first?
3. What are their alternatives?
4. How much will they pay for it?
5. What budget will that come from and how big is that budget?
6. Where do they post the job opening?
7. Where do they look for candidates and can you go there without considerable costs?
8. What is their hiring process?
9. What will they find compelling about your product’s candidacy?
10. Will the job exist two years from now?

Predictive Power of Customer Metrics

The usefulness of any customer metric depends on how actionable and how good a predictor of business success it is. Let us define here that business success refers to Sales growth and profitability.

1. Of all the  metrics out there, is there one that serves as a good predictor of sales growth and profitability?
2. Can there be really a single metric?
3. What do you, as a small business owner, an entrepreneur or a decision maker for large enterprise need to know about the single metric trap?
4. What other factors you should be aware of?

Read on.

Let us start with most common customer metrics, including but not limited to

1. ACSI – Average Customer Satisfaction Index
2. Top-2 Box (on a 5 point scale) Customer Satisfaction Score
3. Number of recommendations – WoM, number of customers who actively recommend your product (service)
4. Proportion of your customers complaining
5. The Net Promoter Score

Supporters of some of the metrics claim theirs is the only metric any business need to track. In the data cited we will find a high positive correlation between these metrics and the two measures of business success. You do not need an advanced degree in statistics to question, “Does this correlation mean causation?”. But it does get a little tricky to sift through the data and flaws in analysis of the case for a single metric that predicts business success.

The biggest flaw that can occur in any argument that a single variable alone has predictive power is Omitted Variable Bias. Is there a lurking variable that was omitted in the model that drove both the metric and business success? This is not to say every argument that extends one predictor has Omitted Variable Bias but to raise the possibility that there may exist another variable that may explain the changes in your dependent variable.

Let me use an example to explain what it is before using it explain single metric trap.

This comes from Greg Mankiw. Suppose studies found a high correlation between test score of children and the number of bathrooms in their homes. Is this causation? Is this the single metric that determines success in tests? No. As Mankiw explains, the Omitted Variable here is the IQ of parents. It is possible that parents with high IQ earn high income and hence have large houses with more bathrooms. Their children may have high IQ because of the good genes passed on by their parents.

In the case of customer metrics, what could be the Omitted Variables? Some could be nature of products, your marketing strategy, channel strategy, nature of competition, etc. The question worth asking is,  Is the metric at hand with high correlation same as the number of bathrooms at homes? Let us take the third metric above, Number of Recommendations, as an example just for illustrative purposes. Is it possible that the nature of customers you are targeting have a high propensity to recommend? If you did not consider this possibility then you will incorrectly align all your resources and actions towards improving number of recommendations without any impact on business goals.

That would result in house full of bathrooms but still poor test scores.

I am not recommending that you give up on all metrics but  urge you to understand Omitted Variable Bias and consider the perils of tracking just one variable.

1. What are all the different factors that are relevant to the business you are in and to your customers?
2. How do these factors influence the single customer metric and your business success?
3. After accounting for all these other variables, what percentage of changes in sales growth and profitability can be explained by the changes in that single customer metric you track?

In evidence based management any metric must be questioned for its predictive power and the methods by which the results are arrived at. Simplicity of a metric alone must not be the criteria.

Write to me, I will be happy to break this down more.

Footnote:

For a very readable and clear discussion of Omitted Variable Bias see also this post.

The Percentage Margin Trap

One of the income statement metrics that stock analysts obsessively focus on is operating margin expressed as a percentage.  Stocks get punished when the operating margin drops or did not meet the goals. So businesses align their marketing and operations to focus on this improving operating margin. To an extent operating margin expressed as a percentage shows the profitability of the operations but the obsessive focus on percentage leads to two errors:

1. Information loss - specifically the absolute profit earned. ( I am going to ignore here more a rigorous number, operating cash flow and treat earnings as all cash.) Given two stocks of identical companies in the same market, one with an operating margin of 10% and the other 12%, both with a stated 5 year goal of 4% improvement, can we tell which stock is a better prospect? What about their absolute income level and growth prospects?
2. Causation Confusion - percentage margin is incorrectly treated as the driver of overall profit. Higher the operating margin, higher the profit. Margins do not drive your profits it is the other way.

Operating margin percentage is a computed number not an intrinsic metric that needs to be actively managed and definitely not a driver for your marketing decisions like pricing the products. Let us take the case of Mattel just because it was in the news recently.

Recently Mattel anounced blow out earnings, with 86% increase in profits with only a single digit increase in sales.  This is extraordinary but there is a concern on what they are focusing on. The WSJ news story’s title reads “Earnings Up 86% As Margins, Barbie Sales Jump“. Margins did not drive the profits up. Profits went up because of price improvement on their Barbie line. In its earnings call Mattel CEO, Mr. Robert Eckert, made the following statement

“We will price our products consistent with our goals of long-term operating margin of 15% to 20%,”

Determining the price to sell based on the stated operating margin goals is cost based pricing.  Pricing the products to  meet a derived metric is like putting the cart before the horse. Price is not driven by a businesses need for meeting its operating margin targets  set by stock analysts but by the customer’s willingness to pay. Based that price the business must either try to make the products at costs that are profitable (price driven costing) or choose not to compete in the market. I want to believe that Mr. Eckert meant here choosing only those products that can help Mattel meet its margin goals and not set prices regardless of the customers.

What drives shareholder value is absolute profits. Not percentages. As Ford said about costs, operating margin is always a computed number.

What drives products prices is value to customers and their willingness to pay, not stock analysts.

What sets prices and drives profitability is effective price management not meeting operating margins.

Where To Allocate Your Promotion Dollars?

You have $X dollars to be used as promotional discount to increase your product uptake, i.e., maximize number of subscribers rather than maximize profit. You have two versions of your product, Silver priced at $19 and  Gold priced  at $49. How will you allocate the promotional dollars to drive most uptake? Will you discount your Silver version, Gold version or split between both?

Sidebar: I understand I have  consistently advocated about profit maximization and not using price to drive volume. But let us assume you have a very good reason to do that and it is not permanent price drop but a controlled price promotion. May be you have a freemium model with a Bronze version at $0 and want to move most free customers to paying customers.

Consumer behavior research says, based on Prospect Theory (Kahneman and Tversky 1979), you are better off spending the promotional budget on discounting the lower priced version than the higher priced version. While rational economics states (assumed?)  a $5 discount is the same regardless of the price, consumers look at $5 with reference to the base price. Consumers value $5 discount on $19 version more than then do the discount on the $49 version.  So  discounting your silver version maximizes new customers.

However there is an exception – when customers’ reference price (the price they expect to pay for similar products regardless of their economic value) is lower than the price you charge. Here the effect is reversed so you should discount the Gold version. If you are interested in understanding this case please write to me.

In either case, you are better off allocating the promotional budget to just one version and not dividing between two versions.

How To Price The Second Version Of Your Product?

Previously I wrote about the costs associated with multi-version pricing, this time let me discuss a very simple case of how to price two versions.

Suppose you have just one version of your product(service) and you want to introduce another version of the same. How should this be priced? I was posed this question recently by a small business owner who runs a service business.  Unfortunately  it is not an easy question with pre-built answer, I ended up asking her a lot more questions than I answered. But the questions are about taking a more analytical approach to the problem than just going with what seems like the right answer:

1. Goals: Why do you want to introduce a second version?  Is profit growth or sales growth your goal because increase in sales  does not automatically mean  increase in profit. Can you look at your current pricing to see if there is an opportunity to achieve your goals?
2. Needs of your current customers: What do you hear from your current customers?  What do they say they are missing in your current offering? How many times have you had special requests from your customers? Every touch point you have with your customers, from their call to book an appointment to the time you say good bye there are many opportunities to find out what your customers value. Can you mine this data to see whether your customers are seeking a simpler or premium version or even drastically different version?
3. Needs of future customers: These are the segments who are not yet your customers. Why isn’t your product attractive to them? Is it the features, price or accesibility? Where do these people buy and where do they seek information about products. If you introduced the new version, will these people know about it and decide to try it?  Unlike current customers you do not have an easy way to find the information stated in the previous point. This  requires you stepping out and doing a market research which is not a DIY task. So more most small businesses bits  or atoms I recommend  (2) – serving the unmet needs of current customers before explanding their market.
4. Cost of versioning: What are the costs of introducing a new version? I previously wrote about costs associated with multi-version pricing,  in this specific case the costs are minimal given the nature of the service and it is a simple case of moving from one to two versions. But costs are relevant to see whether the new version delivers incremental profits over a single version offering.
5. Incremental Profit: When you introduce a new version you cannot assume that it will appeal only to new customers or only to the sub-segment of current customers you planned to target. If you have not correctly answered the question in (2) above you might end up giving up profits because your premium customers switched to the basic version.

As I mentioned I did not have a price figure to give to that small business owner. But the questions helped her go seek data that she may already be collecting or can collect to help make the right decision on pricing.

It is never a simple question of “How do i price my second version?”. But it is a problem that can be methodically broken down by using the framework I gave above.

Is Customer Loyalty A Predictor Of Profitability?

Much has been said and written about the need for customer loyalty. The need to focus and attain customer loyalty is intuitively clear to all marketers. Some of the key arguments for customer loyalty include

1. Reduced Customer Acquisition costs – Since it costs $X to acquire new customers, any customer you hold on to saved you $X. For example, it takes mobile providers $350 to acquire new customers and there are similar metrics for most products.
2. The Loyalty Effect: Longer a customer stays longer they keep paying you. There was a book by the same name that claimed up to 75% increase in lifetime value of a customer if they stayed longer.
3. Cross-Sell & Up-Sell: Since you keep your customers and come to know more about them it creates additional revenue opportunities through cross-sell and up-sell opportunities.
4. Price Tolerance: Loyal customers keep buying from you because they are delighted by your product and are less sensitive to prices.  Some even claim that loyal customers do not even bother to use coupons and promotions, thereby saving you money.
5. Decreasing Cost to Serve: The more you understand your customer’s usage behavior and needs fewer the mistakes in servicing them and hence lower the cost to serve them.
6. Bump From Word of Mouth: Loyal customers are also your best marketers, they are happy to write online reviews and promote your products to all their friends and web communities. This means they generate additional incremental revenue.

All these factors seem plausible and the “gut feel” says these must be true.  If even a subset of these six factors are a work, customer loyalty must be a very good predictor of sales growth and profitability.

We should be able to validate the following models

Sales Growth =   Constant  +   ß1 * (Customer Loyalty)

Profitability =  Constant  + ß2 * (Customer Loyalty)

(ß1 and ß2 are the weights of  customer loyalty )

In a study published in circa 2000 in the Total Quality Management journal, researchers studied precisely these two models for a large set of products and services. The result?

Loyalty is a poor predictor of both sales growth and profitability. Their R-square values are 6% for profitability and 2% for sales growth. (For services the number goes to 14.7% and 7.8% respectively). That means only a tiny fraction of the changes in sales growth and profitability are explained by changes in customer loyalty.

Loyalty has positive impact on sales growth but more strikingly, for products, the impact on profitability is negative, which means higher the loyalty lower the profitability. This means any attempt to “buy loyalty” with price cuts does bring you loyalty but at lower profitability.

The net is, what seems too obvious isn’t so. This is not to categorically dismiss need for loyalty but the positive effects of loyalty are clearly overrated. If their effects are so low then there is a high opportunity cost to improving them. You cannot put all the  wood behind the loyalty arrow!

Sidebar:

Correlation means two variables are associated and the extent of association si expressed as correlation coefficient. It ranges from -1 (low,high)  to +1 (high,high). A value of 0 means no correlation.

Predictability, R-square, means one variable is a predictor of other. It is measured as a square of correlation coefficient. So two variables that have a correlation coefficient of 0.8 have a predictability of only 0.64. R-square is usually expressed in %, so 64% means 64% of changes in dependent variable are explained by changes in predictor variable. That said, correlation does not mean causation. There are other factors to consider including but not limited to statistical significance of weights of variables, omitted variable bias, etc

4 Costs of Versioning

Versioning is about delivering multiple product (service) versions at different price points for targeting different segments. Since not all customers are alike and their needs and willingness to pay are different, versioning helps to reach a larger customer base. It is the right step in the direction of profit maximization. Pigou said, “if one price is good, two are better”, and I have echoed the same in many of my posts on the need for versioning. But how far can we take this?

1. Are 3 versions better than 2?
2. Are 4 better than 3?
3. How about infinite versions  or one version per customer for each purchase occasion? (the case of different price per customer for the same version is First degree price discrimination and is impossible in practice)

While versioning is the right step in the direction of profit maximization it is not without costs.

I classify the costs into four main types:

1. Product Costs: Is your product amenable to versioning? What is the incremental cost of creating and packaging each additional version?  Can the new versions be produced on the same infrastructure? If not what are the capital needs? If you are a bootstrapped tech startup or a cash strapped small business (like Crispy Green) it is almost impossible to find the resources to invest in versions.
2. Sales and Marketing Costs: It is not enough that your product is versionable at low costs – you need to invest in building the brand, marketing, training the sales team (if you have one) and the channel partners. What is the sales learning curve? How fast and easily can you train your sales team on the different versions, their target market and price? If your sales team has high churn then you will incur these costs over and over.
3. Menu Costs: These are the costs associated with creating the SKUs, price lists and operationalizing the pricing strategy. Arguably these costs are lower for information goods (software and information services) and use of pricing software will help those selling physical products. Nevertheless the costs exist in creating, maintaining and updating the many different price lists.
4. Customer Costs: This is the cost incurred by your customers in understanding all your many different versions to make a choice. These are also the costs you have least control over. The costs may not be incurred in the form of dollars but there are definitely cognitive costs and opportunity cost to the customer. Worse, the effects of these costs do not end after version selection. Theoretically, after the customer spends the time to make a selection those costs should not matter to their continued use of products (because those costs are in the past and hence are sunk). But research published in the Journal of Management Information Systems Winter 2007-08, show that cognitive costs are sticky – customers remember and associate these costs with overall product experience.

All these costs mean there are real limitations to the number of versions that can be developed and marketed. Product Costs, Sales & Marketing Costs, and Menu Costs mean, even if the versions can find new customers the incremental profits from them must justify the additional costs incurred. Is there adequate ROI on these additional investments from the incremental profits and how does this ROI compare to other opportunities available?

If resources are not a issues and breaking even each month is not a problem you struggle with everyday (for example P&G) you can afford to make those investments. But what about cognitive costs?

Researchers, Iyengar and Lepper say in their work in Journal of Personality and Social Psychology (2000)

Customers are more likely to make a purchase when offered a limited array of options than a wide range of choices. Subsequent customer satisfaction is higher if the selection choice set is small.

If a marketer can achieve clear separation of the segments and target them with exclusive versions, they can reduce Customer costs.

The net is there are limitations to versioning strategy and the number of versions that can be offered to customers.

What is the ideal versioning strategy?

How do you know when to version?

What is the right number of versions that will delight your customer?

Should you create vertical or horizontal product line versions?

How can you profitably operationalize your versioning strategy?

I will be happy to talk to you.

Do Not Think Like Your Customers

What does it mean to think like a customer?

Which customer segment exactly?

How static is that thought, what else influence customer thinking?

Why should a  marketer think like her customer?

I will start with the last question and say, a marketer must not think like a customer but must understand what the customer is trying to solve with your product.

When a marketer thinks like a customer, they are just thinking how she would make buying decisions as a customer and not how her customers make their buying decisions. Besides not all segments think the same, which one do you want to focus on? Even within the same segment customers think differently based on the purchase occasions. Their thinking is also not static, it is malleable through marketing.

Trying to project your shopping behavior or generalizing one customer behavior across all segments will lead you to make pricing and product mistakes and lost profits.

In a Times article on a small business, Crispy Green, that is addressing its growth strategies its owner Ms. Anita Liu said

I think like a shopper. What I don’t want in the middle of a recession is for prices to go up on a favorite snack.

In case of Crispy Green, the problems are more than just pricing, it involves understanding target customers, defining Go-To-Market strategy and ultimately what the business goals are. But focusing on the pricing problem, intuition and instincts are not the way to make business decisions.

Yes, some customers will not like price increases in the middle of recession, but will they stop buying? What percentage of sales will you lose (i.e., price elasticity of demand)?  Will the price increase deliver incremental profits?

Don’t think like your customer but understand what they want in their life and how your product can play a role.

Buying Loyalty – Does Drop In Defection Make Up For Lost Profit From Price Cuts?

In my previous post on MetroPCS $10 price drop I overlooked a key aspect – increase in profits from customers staying longer because of the price cut.  Thanks to Gerardo Dada for pointing out the scenario of increased customer retention. In my previous model I accounted only for new subscribers and said they needed an additional 1.65 million subscribers (to their current 6.6 million sbscribers). The correct model for break even profit should look like

Lost profit per month =  Incremental % customers retained * 6.6 * $40 +

Incremental new customers * $40

units are $ million, and $40 is revenue per customer and marginal cost is $0.

The two extremes are

(1) No change in churn rate (currently 1.77%), which means MetroPCS must add 1.65 million new subscribers (add 25%)

(2)No new subscribers added, which means they must retain an additional 25% of customers. Since their current churn is 1.77% per month, this case is impossible.

The best churn rate in the industry is 1.1% (AT&T). That is for its subscribers under 2 year contract and driven by iPhone. Even if MetroPCS can reach this level, that is a savings ofonly $1.77 million, it still needs 1.6 million new subscribers to make up for the lost profit.

The net is, while price cuts  help stop customer defection they resulting increased profits are not enough to make up for total profit lost. Brands need to find considerably large number of new customers to make up for lost profit from price cuts.

I stand by my previous claim, price wars lead to value destruction!

Dropped Mobile Profits

There is a price war starting now in the prepaid mobile sector. MetroPCS wants to attract new customers (and keep its current customers) by paying all their taxes and fees, which amounts to a price cut of $10.  Technically the list prices remain the same but instead of the customers paying all the taxes and fees, MetroPCS picks it up. Since the 6.6 million MetroPCS customers are not under any contract, all of them can get this  $ 10 price cut - a profit loss of $66 million a month!

MetroPCS said that they will make up for the lost profit through increased addition and retention. But the stock market is not buying that argument. To compensate for $66 million lost profit MetroPCS must add, at least, a total of  1.65 million new subscribers (assuming a generous profit per customer of $40). That is 25% of its current subscriber base just to get back to where it was before the price cut.

MetroPCS has a churn rate of 1.77% per month (percentage of subscribers who quit). Even if it acquires additional 1.65 million subscribers, it has to find 144,000 new subscribers every month, unless it reduced the churn rate. The lowest churn rate in the industry is 1.1% but that is for subscribers under contract. Prepaid customers are by definition susceptible to high churn.

Other prepaid players like Boost and Leap are not going to stand still. MetroPCS said it wants to be the low price leader but tha is possible only of other prepaid operators cannot match the price cut. Since the marginal cost to serve one single customer is  $0 and all the investments in the infrastructure are sunk, no one player can claim price leadership. If Boost and Leap match the price cuts, MetroPCS will simply end up with lower profits despite gaining some customers.

It is not a surprise that the stock market is feeling less positive about all the prepaid operators. War results in destruction and casualties and price war leads to value destruction.

Does Presence of Customer Reviews Drive Down Product Returns?

Does presence of customer reviews and the number of reviews drive down returns by customers?

According to Internet Retailer (thanks to Gerardo for the link), that is the case. The article says, reviews has helped Petco considerably

Petco’s approach to gaining more customer reviews has paid off. On average, products with reviews have a 20.4% lower return rate than products without reviews. The return rate continues to decline as a product gains more reviews. Products with more than 50 reviews have a 65% lower return rate than products with no reviews.

Since returns eat into profits reducing returns goes directly to the bottom line there is no question here. But can presence of reviews drive down returns? Is there a direct causal relation or is this just correlation.

If the  case of customers who took the time to write reviews I can see that their return rate will be much lower than the return rates among those who did not write one. This is the Commitment and Consistency bias that is explained very well in the book Influence by Robert Cialdini. When the customer “commits” by writing how good they feel about the product their internal system compels them to act consistently to their previous commitment. So they keep the product.

This does not mater whether or not customers wrote the review because of their LOVE for the product or because they were paid in coupons or raffles. This does not apply to negative reviews, but according to one research, most reviews are positive reviews and there is generally high product ratings.

However commitment and consistency bias alone cannot explain the drop in returns because this is still a small number of reviews compared to products sold. But another cognitive bias that could be at play is conformity bias. When customers make the purchase based on many reviews by “customers just like them”, they tend to confirm to those peer reviewers. This will compel them to “like” the product and keep it. Again, Cialdini has chapters describing Conformity bias in his book.

On top of the cognitive biases, it is possible that there exists another common variable that both drives up number of reviews and drive down returns – for example the product experience matches its promise.

There is one way to answer many of these questions and to find out whether or not number of reviews drive down returns. It requires doing two sample t-test, showing some of the customers the review,  suppressing it for others and tracking the respective return rates. If the return rates are statistically significant then we can declare presence of reviews drives down product returns.

Next step, if we do the experiments by showing different number of reviews we can even find the linear causal relation between number of reviews and returns.

Are Loyal Customers Less Price Sensitive?

Let us start with seed questions on loyalty:

1. Are loyal customers more likely to be less price sensitive and hence more profitable?
2. Can a marketer maintain price premiums with loyal customers?
3. Does customer loyalty drive long term profitability?

To some the questions will come as a surprise because the answers to them are self evident. But leaving out intuitions, is the causation relationship that loyalty means price tolerance and consequently higher profitability supported in the data? A few studies suggest this causation relationship based on correlation ( see here).

There is one other popular book, The Loyalty Effect, that states, “Companies can boost profitability by 75% by increasing loyalty by 5%”. But that is not based on research. The author makes that statement based on his example that reducing customer churn from 10% to 5% for a business with 90% customer loyalty doubles customer lifetime  (that is correct) and hence the profitability increases by 100% (tautology). However, his model and numbers are not correct  because he confuses two different percentages (see here for explanation).

Let me raise questions on what seems like a self-evident truth:

1. Yes there is correlation but does that imply causation?
2. Is there a hidden variable that drives loyalty and profitability?
3. Is there Omitted Variable bias – that is there exists another variable that drives loyalty?
4. What if price tolerance (and profitability) instead of being caused by loyalty is actually the driver of loyalty? In other words, is it possible that sensing price tolerance and high profitability of certain parts of their customer base, businesses may be doing everything they can to keep them (i.e., increase their loyalty).

I do not have data to prove these three possibilities but I raise here questions you as a decision maker must ask before accepting any claims of the need for driving customer loyalty.

Ten Questions To Ask About Any New Venture

Here are ten questions I ask when I talk to my entrepreneur friends, the questions follow from the framework of business strategy, customer needs and Go-to-market strategy:

1. What jobs will your customers hire your products for?
2. Who do they hire now, i.e., who do they have to fire first?
3. What are their alternatives?
4. How much will they pay for it?
5. What budget will that come from and how big is that budget?
6. Where do they post the job opening?
7. Where do they look for candidates and can you go there without considerable costs?
8. What is their hiring process?
9. What will they find compelling about your product’s candidacy?
10. Will the job exist two years from now?

Anyone can calculate what a cost is, but no one knows what a cost ought to be

This is a direct quote from Henry Ford’s, My Life and Work (now out of copyright). This shows his  remarkable thought process on marketing and price based costing. You do not determine what your costs are and then determine the price (like tacking on a margin). You find what the market will buy at different price points and produce the units at costs that are profitable.

Our policy is to reduce the price, extend the operations, and improve
the article. You will notice that the reduction of price comes first. We
have never considered any costs as fixed. Therefore we first reduce the
price to a point where we believe more sales will result. Then we go
ahead and try to make the price. We do not bother about the costs. The
new price forces the costs down. The more usual way is to take the costs
and then determine the price, and although that method may be scientific
in the narrow sense, it is not scientific in the broad sense, because
what earthly use is it to know the cost if it tells you you cannot
manufacture at a price at which the article can be sold? But more to the
point is the fact that, although one may calculate what a cost is, and
of course all of our costs are carefully calculated, no one knows what a
cost ought to be. One of the ways of discovering what a cost ought to be
is to name a price so low as to force everybody in the place to the
highest point of efficiency. The low price makes everybody dig for
profits. We make more discoveries concerning manufacturing and selling
under this forced method than by any method of leisurely investigation.

Behind Crest White Strips Multi-Version Strategy

P&G practically created the teeth whitening white Strips category. Introduced under the powerful Crest brand it helped create new revenue stream  after all  it is not easy to grow 10% YoY when each brand bring in $1 billion revenue. The part that interests and impresses me the most is their multi-version pricing for the White Strips category. While I expressed concern about P&G’s other brand Downy’s horizontal product line extensions, Crest White Strips serve as an example of effective pricing  strategy, tactics and execution.

Take a look at the Crest White Strips page from P&G and here are some insights on their versioning strategy:

Side bar – Value Tag: For brand managers from Colgate-Palmolive and Unilever this article is worth $9999 to you.

1. If one price is good two are better and four are even better if designed and positioned correctly. Crest offers four different versions of the product, offering increasing benefits from low to high end version.  This is vertical product line extension.
2. Versions are designed in such a way that customers self-select  themselves to the right one (Second degree price discrimination).
3. The lowest priced version is the Classic at $24.99 and the super premium version ($44.99) is the Crest Advanced Seal, introduced in early 2009.  That is a $20 price differential between the lowest and highest product creating great profit opportunity from up-selling.
4. The price jump is non linear and reflects customer’s diminishing utility. From Classic to Premium it is a $10 jump indicating customers assign most value in this upgrade. Between other versions it is $5 jump indicating customer utility flattens out or grows slowly as they move up the versions.
5. Note that the listings are benefits and not product features. Customers care about benefits  and not about the features – compare this to many of the technology offerings that simply list feature differences across versions.
6. Look at  the images showing the packages. These are designed to visibly show that not only are these versions different but also  help “tangibilize the intangible” (Ted Levitt).
7. In behavioral economics, the effect of  presence of high priced versions has been extensively studied. The netof those findings is that while these may not sell much, the  presence of high priced versions help improve customer willingness to pay for the other versions. But that is not the case with Crest Advanced Seal. I make this claim based on the number of reviews and rating for this product.
   

   Versions	Reviews	Rating (on a scale of 5)
   Classic	58	4
   Premium	34	3.75
   Pro Effects	17	3.5
   Advanced Seal	77	4

   If we use the number of reviews as a stand-in for the market share, Advanced Seal, despite being the super premium version, is their most popular seller. The ratings also indicate that customers are happier with their super premium version. At $20 price premium and arguably not much cost difference this is a big contribution to their profits.

8. Their Pro Effects, scored the least both in terms of number of reviews and rating. Until P&G introduced Advanced Seal an year ago, this was their most expensive version. We can hypothesize that it served then as the expensive decoy but did not add as much value to the customers and hence did not get market share. Going forward we should expect to see P&G allocating fewer marketing resources to this version and keeping its price levels.
9. All their prices end in 99, as seen again in behavioral pricing literature this is a good tactic. It is easy for everyone to have prices end with 99 but it takes marketing strategy and a clear understanding of customers to maximize profits.

Overall Crest White Strips serve as a great example of marketing strategy, versioning and pricing for profit maximization done right!