The (ahem) "Art" of Pricing

Originally published in 2010. Updated and republished in May, 2015.

A reader asks: "Can you please enlighten me on the art of pricing?"

At the risk of misinterpreting, I believe the reader is asking specifically about enterprise software, where price lists are usually secret, transaction volumes are relatively low, and pricing is a bit of a mysterious process.

So here goes. 

As a starter, here's what is NOT recommended. Below is the process I essentially used many years ago when I was a junior PM and asked to provide pricing recommendations for the first time. I did a lot of good things in my analysis, but I way over-engineered it and spent way, way too much time on it, given that we ultimately went with the CEO's intuition -- something I should have anticipated and been prepared to argue against.

I've also seen many junior to mid-level career product managers fall into similarly overblown processes when they attempt to figure out pricing, so I know I'm not the only one... Consider this your warning.

How NOT to do Pricing...

....a step-by-step checklist.

PART A: Do exhaustive competitive research and analysis

Do your damnedest to find out what your most important competitors are charging.

STEP 1. Get together with your former colleagues who are now at competitors. Get 'em drunk so they spill the beans about their price list. Be warned, you might have to flirt (but please don't flirt if you are unattractive or creepy -- you'll only make the situation worse.) If flirting is out or not your style, try offering alcohol AND free babysitting. Don't forget to ask about the discount schedule.

STEP 2. Ask Sales Ops to notify you of newly hired sales reps who were formerly at competitors. Call these reps their first week on the job. Introduce yourself. Offer to teach them all about the benefits of your product, to help them in any way you can, etc... Be oh-so-very-nice. THEN, a week or two later, check in to see what the new reps think of the price list. "I'm revising it and wanted some 'fresh eyes' to give me some reaction. How do you think customers would react? Do you think we're competitive?????"

If you are charming enough, at this point you'll usually learn a lot about how your competitor prices. If not, you might have to wait a few months, until this sales rep is wandering around the Annual Sales Meeting drunk as a skunk.

STEP 3. Ask friendly customers to tell you what the competitors are quoting them. Again, because an NDA might be in play, flirting, promises of free babysitting, or expensive bottles of wine might be in order. OK, probably not. Maybe just a free training session or customer bitch session where you, Mr./Ms. Product Manager, quietly sit and take notes and mutter niceties like "Gee. That's really insightful and an absolutely stellar feature idea. We'll look into that."

STEP 4. Back the numbers out. Competitors will put out press releases saying they did this huge N-million dollar deal with so-and-so, estimated X-jillion users for these fantastic new products. The number you'll end up with is nonsense, but at least you can compare it to other nonsense (see footnote 1).

STEP 5. Google it. 'nuff said. And don't forget the "way back machine." If government agencies are customers, they sometimes publish the price quotes to the web. Sometimes you can find a price list if you search your competitor's website for "price list" or for all PDF, XLSX, and DOCX files on the site.

STEP 6. Ask those coin-operated Industry Analysts - although these egomaniacs are usually only good for the "official" pricing, which means they are good for nothing. But you already knew that!

STEP 7. Engage "partners" (aka hired spies) - Hire a small "consulting firm" to attempt to purchase the software and identify the pricing model.

STEP 8. Not a great source of pricing info: sales reps who were NOT previously at a competitor. They almost universally believe that you charge too much. Why this is, I do not know. As direct sales people (NOT telemarketers), you'd think they'd like higher prices because it's easier to hit their "number" (aka quota) with a single million-dollar deal than with a hundred $10,000 deals.

PART B: Next, create a ridiculously elaborate pricing model spreadsheet

STEP 9: Design a preposterously complex spreadsheet model that will optimize elasticity curves and spit out prices, the predicted revenue, and resultant market shares of all competitors.

  • Crack out your old Microeconomics text books from B-school.
  • Feed all that demand and supply curve stuff into a crazy-ass Excel Spreadsheet with about 300 VB macros, all lovingly crafted so that you can pretend you are still a "real programmer" even though you abandoned writing code 5+ years ago.
  • Make sure you have some wacky game theory scenarios in there just to be as over-the-top and impractical as possible.
  • Put some Bayesian models in there too, and make sure it accounts for the current price of Pitbull tickets.

STEP 10: Even better, go all "Big Data" on this shit. (Enhance your resume at the same time!)

  • Pull data from Salesforce, internal quoting systems, Zendesk, Jira, your ERP, and any other system you can think of.
  • Dump all this data into your own private Hadoop cluster.
  • Then, spend a full day learning that writing queries in MapReduce is a nightmare, that your data is not really "big", and your data is already in a relational structure.
  • So, backtrack on the "big data" thing and dump your data into MySQL instead.
  • Spend a weekend learning R and machine learning. Also, refresh your knowledge of regression analysis and statistics.
  • Fantasize about unearthing the 3 heretofore hidden criteria that will ensure customers will pay a very high price yet be freakishly delighted by your product.
  • When your machine learning attempts instead pump out nonsensical garbage, because 30 product sales per quarter is not a large enough sample for statistical analysis, ditch the whole idea and go back to your supply/demand curve spreadsheet with all the macros (step 9).

STEP 11: Use this spreadsheet primarily to prove to yourself that even though you didn't get that Investment Banking job out of Business School, well, you DESERVED it. Yes, you DESERVE to collect $600,000 bonuses in recessionary times without creating any value for society. 'Cuz you're that good, you analytical wizard, you.

Oh wait, that massive spreadsheet ostensibly had another purpose... what was it again? .... oh yes, to validate the World's Most Insightful Pricing Recommendations for your fantastic product. You go!

PART C: Get management buy-in for your pricing recommendations

STEP 12: Present your exhaustively researched pricing model and subsequent recommendations to the head of product management, and then the other sundry Veeps (Marketing, Sales, Development, etc). Then, sit and wait while these execs they pick apart your elaborate model and throw out 90% of your analysis in order to retain only that which supports their "gut feel" for price.

STEP 13. Revise your presentation by completely rewriting it from scratch. Don't forget to put clip art of business people in suits leaping over bar charts in the PowerPoint. This is essential for any presentation to be given to the Big Boss (aka CEO or GM).

STEP 14. Present the revised VP-approved analysis to the Big Boss .

STEP 15. Watch as the Big Boss ignores your recommendations and either doubles the price for every product across the board because of "Moore's law" or some other universally misapplied rule-of-thumb that is five words or less (my fave is the Salmonella Avoidance Law: "Don't Buy Sushi on Sundays"), or cuts the prices drastically based on "instinct." This so-called "instinct" will depend on whether:

  • ...immediately before the meeting the Big Boss heard his/her #1 salesperson bitch about prices being too high (in which case, the Big Boss will drop prices)

  • ...the Big Boss has deal-envy of a $10 million deal done by a competitor (Big Boss will send prices higher)

  • The Big Boss read some tech magazine or blog or something about the trend being toward open source and free software (prices go lower)

  • A long-time customer doesn't make his customary big order this year because he's managed to "consolidate his licenses" in a cloud environment or via virtualization (prices go higher).

STEP 16: Now for the product manager's Real Job as the expert in pricing your particular product: edit the official price list with the Big Boss's "inspired" numbers, which have no relation whatsoever to the research you did in Part A. Good thing you listed "Microsoft Office" as one of your skills on your resume. Hope you took good notes, because you are now a transcriptionist!

STEP 17. Now sit and wait for a month or two, while the new prices take effect.

STEP 18. Analyze the next quarter's sales. Observe that although the price of every product doubled, revenue was down. Meaning your volume was cut by more than half.

STEP 19. Next quarter, realize that some deals discounted your product by 95% or more.

STEP 20: Ponder the question "what the hell does a price list mean when discounts are that huge and that variable?" Seek the guidance of your spiritual leader, or at least call into a podcast talk show for psychotherapy, or something.

STEP 21. Vow to never spend more than 30 minutes on pricing again.


Footnote 1: Get it? You know, you can compare apples to apples? And therefore nonsense to nonsense...? Get it?

Sue Raisty

Product management geek, born-again engineer, adoptive mother of boys, coach & mentor, mountain trail runner, tinkerer, no-bull communicator, wannabe writer, room mother & compulsive researcher.

Silicon Valley, California http://blog.sueraisty.com