#4/25: Experimental Auctions

I decided to write in bullet-point type of stile because these summaries/reviews slowly become wall of texts which for one take long to write and make it, in my opinion, harder to read.

  • Values are revealed by actions — if you pay $2 for some chocolate than you value the chocolate more than your $2
  • How can we measure the value of non-market goods?
  • => Revealed preference methods, i.e. (particular) auctions.
  • Erases the problem of hedonistic pricing which requires market prices a priori.
  • Also better than stated preference methods, i.e. surveys and trails — the big problem is that these methods are hypothetical and allow strategic behavior (manipulation)
  • Experimental auctions are a better choice because of:
  • a) They use real money and real goods.
  • b) They can be carried out in real environments, e.g. supermarkets

Value theory

  • Willingness to Pay (WTP): if person do not own the good, how much is the person willing to pay to get the extra good?
  • Willingness to Accept (WTA): if person owns the good, how much does person need to accept the loss of the good?
  • However difference between WTP and WTA depends on the risk behavior. Problematic: We have to estimate Arrow-Pratt but measuring risk-aversion is hard and destroys the sense of experimental auctions.
  • Furthermore, we have to include time. Proposed formula: WTP today = Expected Value – commitment costs, which includes uncertainty, lack of information, patience, reverse transaction, freedom, etc.


  • What’s the objective? Do we want to test, explore or generalize?
  • Simple experiment design: Attribute vs. Attribute, however we need 2^\text{\#Attributes} different test cases.
  • Better: Fractional factorial design. Assumes there are no interaction effects which makes the main effects separately identifiable.
  • e.g. three attributes (H vs. L, S vs. L and B vs. R). Normal design:
    H S R
    H S B
    H L R
    H L B
    L S R
    L S B
    L L R
    L L B

    Factorial design, just needs:

    H S B
    H L R
    L S R
    L L B
  • Randomize treatment but control for time effects (time of the day, weekday, etc.)
  • Furthermore, control within-subject change. E.g. with ABA designs, i.e. first treatment A, then B, then A.
  • For experimental auctions however a problem, i.e. demand reduction effect. Solution: Only one treatment will be binding and will be picked randomly.
  • Furthermore, external effects, e.g. superior information about market prices. Solution: Inform people as good as possible; you can also provide substitute products for sale at a fixed price.

Field vs. laboratory

  • pro lab: better control, less confounding variables
  • pro field: more realistic, self-selecting population -> less sample-selection bias, more knowledge in established environment & experience, reduced costs
  • Problem: Hawthorne effect, i.e. if people think that they are being watched they change their behavior

Conducting experimental auctions

  • Qualitative study prior designing to learn about decision-making processes and general info
  • Focus groups and pretests to met objective
  • Teach them about your mechanism and optimal behavior
  • Real-money practice rounds with another good helps to learn how auctions work
  • You can do the auction anonymously — but that can be relaxed

Endowment vs. full bidding approach

  • Endowment bidding: Give participants the inferior good or they have it beforehand. Let them bid on how much they want to pay or receive to give up endowed good. This measures the real value between the endowed and auctioned good.
  • Full bidding: Here you don’t get the exact value because of transaction costs, however you have an estimate for the absolute value.
  • Generally things to consider: Is consumption important? Is there reference dependence/loss aversion (esp. endowment bidding)? Does the endowment signal something about prices?


  • English auction: works very well in practice and is highly accurate; furthermore people mostly understand how it works
  • Second price auction: everybody gives one bid, the highest wins and pays second highest price — Works quite well, especially for high value bidders
  • Random nth price: like 2nd price but n is drawn randomly, i.e. the people with the n highest bids get the good for the nth highest price — Similar to 2nd price but works better for low value bidders.
  • BDM mechanism: people bid and random number is drawn, if number smaller than bid, then person gets good for drawn number — good for field studies but creates no real market environment

Some of the case studies
The books presents a lot of different case studies which are quite detailed. I won’t go into them because this would be beyond the scope of this short summary.

Auction design problems

  • novelty of the experiment experience: learning effects; price increases because people learn about the optimal strategy
  • preference learning: high bids to learn about unfamiliar products
  • off-the-margin bidders are problematic => solution: random nth price auction


  • preference reversal: arbitrage causes value adjustments not preference adjustments
  • hypothetical auctions still not revealing => idea: calibration function.
  • => can work in some environments, e.g. trading cards
  • => doesn’t work so well in others, esp. new products

Influences on choice and valuation

  • context matters
  • goods matters
  • information matters
  • exchange institutions matter
  • market experience matters
  • price information sometimes matters
  • substitutes and complements matter

idea: consequential vs. inconsequential mechanisms

  • consequential means that the probability of binding lies between 0 and 1
  • sadly not revealing, real auction still better but not as worse as hypothetical auction

Empirical results

  • internal validity of experimental auctions is high
  • reliability is high, but influences on choice and valuation still matter
  • some anomalies don’t exist in the long run – however, there’s also things like prospect theory and loss-aversion.
  • preference reversal: market creates rationality through natural selection or budget constrains
  • even with anchoring the valuation is still valid in relative terms


  • great tool for the future
  • lots of opportunities for research

I love this book. It has enough theory and a ton of case studies — the authors don’t shy away from real problems and resent possible solutions. I seems like a rather new area but I can see a lot of potential in using experimental auctions. Especially e-commerce sites like amazon could profit highly by providing a service for producers to get WTP estimates. All in all, a superb book, more of such books, please!

Provide services, not just products

In the last two weeks there were some discussions about (enterprise) software sales [1, 2] on hacker news. The main complaint is that software sales are often nontransparent, complicated and highly time consuming.

I think this comment sums the problem up:

As you imply, there are segments in every market. Of course there is a segment of companies with hundreds or even thousands of employees with gigantic budgets. These guys are going to do RFP’s and spend months evaluating the different payroll providers.

Then there is the segment of small guys lik me who have under 10 employees who frankly don’t need anything too complicated. You can say “I am only going to serve large enterprise customers through a complex sales process” and that’s completely fine with me. But don’t pretend to cater to my segment if you are not to adapt your model. —labaraka

The last sentences is probably the most important. Don’t pretend to serve a segment just to be “present” in this segment. If your sales process sucks for this segment then it’s better not to serve this segment at all.
Some big software companies tried to enter the SMB market but most failed. Why? I think that it is really hard to sell for 10-20 years products to big cooperations who want customized modules, pay for consultants and don’t care if a basic module costs $100k and then to try to reduce one’s product, make it easy and create a new sales process for said businesses.
The great thing about this is that there’s always a market for software for SMB even if there are big names out there. Salesforce is such an example. At the time there were big names like Microsoft, SAP or Oracle who fought over market shares for CRM systems but Salesforce decided to gather a different market – a market where people don’t have a multiple millions IT budget or even a IT staff.
But even Salesforce can’t serve the whole tail. Still, there are companies that are overwhelmed by Salesforce’s offer or don’t feel adequately served by them.

In conclusion, as a customer I want to know that somebody cares about my company or my segment. If you are just trying to be present in a segment without really caring, people will go to other companies that care. This will allow entrepreneurs to create companies for different niches that other companies don’t really care about. Care about your customers.

#69/111: Marketing High Technology

What is it about?

We are in 1986. Windows 1.0 will be released in a year and high technology is mostly the  semiconductor industry. William H. Davidow worked for Intel and fought several wars. He explains what is important and why marketing is civilized war.

What can I learn?

Go for defensible market segments: Unbelievable important principle which executives/entrepreneurs often don’t get. What does defensible mean? Firstly, just releasing a product isn’t entering the market. You have to gain customers and establishing your product. Davidow estimated that it takes about 0.7 times the sales volume of the market leader to enter a market. Visualize this. If the market leader in your market segment makes $25mio in sales, you will need approx. a $17m investment just to enter the market. Secondly, you have to defend your position. In the mid- to long-term the two or three leaders dominate a market. If you can gather at least 20% of the market, you will probably vanish in the mid- to long-term. In conclusion, look for an appropriate market segment (i.e. which you can enter), gain enough customers and fight the war!

Create great products, not just great devices: Devices are your fundamental offering, e.g. the code for your software. However, a product is your device plus its marketing (positioning, usability, UX, etc.). What does this mean? If you know a techie, you probably had a discussion over the iPhone/iPod. He says that they are inferior to product X because they don’t have feature Y and Z. This is device stuff. Does the mass care about that? No. They care about the product. It is easy to use? It is trendy? Who else uses it? This takes us back to Baked in. You’re device and marketing have to work together and create a whole product.

Install Marketing Quality Management: If you read the previous paragraph you know how important marketing is. Therefore you should assure the quality of it. It begins which checking the positioning of each product to helping internal cooperation. Only if your marketing and device development are working hand in hand, you can create a great product.


Marketing High Technology was written in 1986. Yes, it about 25 years old and kicks ass of most books released today. This book showed how awesome Intel works like in Only the Paranoid Survive. If your business creates product, this is a must read. There is so much insight which is seldom used today. Recommendation!

#52/111: The Entrepreneur’s Guide to Customer Development

What is it about?

Build a product and they will come? Sorry, probably not. Today, you have to work with your prospective customers from day one. Brant Cooper and Patrick Vlaskovits talk about the Customer Discovery, i.e. finding problems to be solved and building your MVP (Minimal Viable Product).

What can I learn?

Solve needs: You probably don’t have a billion dollars to create demand for your product. So the best thing to do is solve a real need. Why? You don’t have to educate your prospects about the problem you’re solving and they will more likely give you money for your solution.

Get out the building: But what are these real problems? The best way is to talk to your prospects. You can meet them face-to-face, phone them or even write an email. You have the role of an interviewer. Let your prospects/customers do the talking. Often they appreciate that they can talk with you about their business problems.

Test your market: Now that you have identified some problems, you should start building your MVP, i.e. something that will you bring to your next step. Your first MVP is probably a landing page to check if there is enough demand for your solution. Later you could print some mock-ups or build a product that will solve the most important problem you have encountered. This will allow to tweak your product without spending too much time and money.


The Entrepreneur’s Guide to Customer Development is OK. The title is a bit misleading because it’s only about Customer Discovery and I found it a bit too short. However, I think the next book I will review is much more appropriate if you haven’t read The Four Steps to Epiphany before.