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Decoy Pricing Part 2: Profitable Implementation

June 2014 Pricing

In the prequel to this article I described the pricing strategies of Apple and LinkedIn to explain how decoy pricing leads to a customer upgrading on choice.  In this article I will explain how as a seller one can take advantage of the decoy effect to book more profit.

To begin with we have to understand that any customer is likely to “fall for” a decoy if at the time of buy he is executing a mental trade-off.  The root cause of the trade-off is economic—he is exchanging money for a product and/or a service.  He understands that to garner more benefits he has to pay more.  At the same time he also understands that he has a limit with respect to budget.  Thus begins the trade-off: Which features do I choose to maximize the benefits at the minimum price?

To initiate trade-off thinking, the seller needs to offer multiple immediate choices.  Just like The Economist does!  The snapshot from the India subscription page of The Economist puts the user face to face with the following two choices:

Figure 1

The subscriber begins to decide which offer suits him better—the print or the digital.  He must be going through multiple trains of thought but is unlikely to be thinking about the price—since both the offers cost the same and he knows that he is going to pay INR80.

Now let’s take a look at the rest of the page:

Figure 2

 

All of a sudden the previous two offers begin to look expensive in the face of the third choice.  Let’s explore why—individually the print subscription and the digital subscription have their own set of benefits and limitations.  However, if purchased together, the customer doesn’t need to do any trade-off.  Since individually each cost INR 80, a customer is likely to justify that to avoid trade-offs she must  shell out INR160.  Then comes the third offer—buy both at INR 96!  This third offer is likely to get interpreted as a discount of INR 54 and hence appreciated as the best value offer.  If the same appreciation leads to a sale (of the combo package) then the seller emerges victorious, as he has made the customer pay more than what was budgeted!

Another point to be noted here—an additional digital subscriber doesn’t add on to any variable cost to the company.  Thus effectively INR 16 is additional profit.  On the other hand, if the offer were INR 96 for two print subscriptions, then it would not be a profit initiative but instead a desperate discounting tactic to pull up the top line (a print edition has substantial variable cost).

Even in the case of LinkedIn and Apple explained in the previous article, the additional features cost the sellers little or nothing more.

Hence the first major target a of decoy pricing strategy: earning more without spending more!

To achieve the same the following steps are advisable—

  1. Identify the features that your product is offering.
  2. List out the features that can be fluctuated without change in variable cost.
  3. Create multiple offerings based on fluctuations of the features to build your portfolio.
  4. Plant the decoy.

 

From my understanding I would classify price decoys in the following categories—

1. Binary – Here the decoy rules out a trade-off.  In the case of The Economist the INR 96 Combo offer ruled out the trade-off between digital edition and print edition.

A similar strategy can be adopted by phone makers and other electronics firms to sell insurance deals—

Price of Phone = $200

Price of Insurance = $20

Price of Phone + Insurance = $205

The customer is likely to consider the third offer as a “good deal”.  In absence of the third choice to buy or not to buy, insurance would be the question in his mind.

2. Stepwise – We saw this in the case of the iPhone.  The variable feature was the storage memory.  The customer paid less per unit of memory if she bought the more expensive phone. Increasing storage memory in the phones did not cost Apple much (explained in previous article) and hence the profit on 64GB phone is higher than the profit on 16GB phone.

A recapitulation of the price list—

16GB – $199

32GB -$299

64GB – $399

Here the 16GB price was in fact the planted decoy to make the customer migrate to 32GB or 64GB.  There was no trade-off ruled out in this case, however the customer was upgraded to the “next step”.

A similar strategy can be adopted by most web-based applications and services.  LinkedIn is doing it already with respect to the “job-seeker” accounts.  It’s time for the dating and matrimony sites to take the same route!

Most dating and matrimony sites segment membership plans based on number of made connections.

As example would be:

Plan A

Plan B

Connections

10

50

Price

$50

$80

We could plant here a decoy in the name of “Plan C”.  Let’s consider 2 possibilities for Plan C:

Plan C1

Plan C2

Connections

15

25

Price

$60

$70

If Plan C1 is published then it is likely to push prospects to Plan A.  Between Plan A and Plan C1 the connections increase by 5, but the cost goes up by $10.  Plan A appears more reasonable in comparison to Plan C1.  In this case Plan B would not be a part of the consideration.

If Plan C2 is published in that case there is high probability that Plan B would be chosen for the same reason as explained above.

Thus from profit point of view it makes more sense to launch Plan C2.

Going back to the basics – The decoy mimics one of the plans and highlights that plan as a better choice.

Apart from segmentation there is another important factor that determines whether a decoy pricing strategy is feasible – can the buyer negotiate with the pricer?  If yes, most likely decoy pricing is a no-go.

In the B2B environment, in most cases the purchaser can influence the pricing by negotiating directly with the supplier.

Hence it is unlikely that decoy pricing (or in fact any form of psychological pricing) will work.  An exception would be however with respect to web pricing.  When a buyer is buying components through web without any contact with the supplier’s sales personnel, the buying pattern is similar to that in a B2C environment.  Thus when it comes to selling B2B products via the web, there is a scope of innovation with respect to pricing.  A proposal would be to experiment with different volume break web prices:

MPN

Unit Price (10 units)

Unit price (100 units)

Unit price (120 units)

A

$10

$8

$8.20

Decoy pricing as a strategy could be explored to increase revenue through web sales in the B2B environment.



About the author

Anirban is a core-team member at Lifkart (an Early stage Indian Construction Start-up). Prior to the current gig he worked for about 5 years as a pricing manager at Cypress Semiconductor. He holds a BE in Electrical Engineering from National Institute of Technology , India and an MBA in Marketing from Symbiosis Centre for Management and Human Resource Development (SCMHRD), Pune, India.

Anirban Sengupta
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