How Much to Charge for your Product

I’ve mentioned in past posts the challenge of determining product value and pricing.  I recently came across an article on Saastr (Next Time – Ask for $1,000,000. A Year. I’m Not Kidding) and it got me thinking again, not only about how you price a product, but different ways to continuously validate pricing.

Jason Lemkin, the author, starts out with a pretty simple premise:

The first is to challenge them to double their highest ACV ever on the next similar prospect.  If your highest paying customer pays you $30,000 a year … even if all the rest pay you only $3,600 a year (a not uncommon scenario) … then why can’t you get $60,000 a year from the next Big Prospect that come in the door?

He then goes on to describe how he encourages all start up founders and sales people to push the envelope for pricing.  I don’t disagree with anything he mentions in this article except for one thing:

Now, if your biggest customer pays you $60,000 today … asking for $500,000 a year, or even $1m, may sound nuts.

But turns out it isn’t.

Do it when a prospect asks you for something that pushes your solution.  When it’s clear they want to buy, but they want the product to go further than it does today.

“Well, we don’t do that today.  But for $700,000 a year I can commit to having that by Q2’16.”

As a Product Management executive, I absolutely hate the execution of this tactic.  In theory, this is a great way to a) determine what features your product needs for this class/type of customer and b) help determine the price point for it.  In reality, however, what usually happens is you train your sales force to sell any feature request for any price point.

The most dangerous part of this tactic is when you have 10 or more customers that have been promised 10 or more different features and already paid for them.  I have both worked for and witnessed many a startup fail because of this.

As a Product Management executive I proactively coach our sales staff to bring me in early to conversations where they think we can get higher price points for legitimate features.  I encourage them to continually prod prospects, but I am adamant that I am always the one that maintains and more importantly commits to the delivery of features and time frames.

I’m always looking for increased price points, but mitigate the danger to your roadmap and your customer base by making sure everyone understands that it’s not a feature free for all.


Confusing Price with Pricing

I recently came across a really good article by Ronen Nir, Why Startups Shouldn’t confuse “Price” with “Pricing” (and how to tell them apart), in it, Ronen does a great job of laying out the difference between  Price versus Pricing.

Price represents the value that the product or service brings to the customer while pricing is the method by which the company determines the price.

While I dislike Ronen referring to this as Price instead of just sticking with product value, the definition is spot on and a good launch point for understanding how you set product pricing.

I mentor a lot of very early stage startups, usually those that are a single found with an idea, or a pre-alpha product.  Pricing (or product value) v Price can be a confusing concept to impart on someone who doesn’t have a Product Management or Sales background and more importantly, has not actually gone through the process of price discovery.

I have found that the best way to determine price/product value is to spend a lot of time with customers or prospects and document their current environment as much as you can, and then attribute cost structures to it.

As an example, when determining the price for my current product line at LeadingReach, I literally sat at doctors offices for hours at a time with a stop watch and documented every single system they interacted with and how much time (to the second) they spent interacting with it.  Included in this “Time and Motion” study was the time they moved between systems (walking to the printer for a demographic sheet, walking to the fax machine, etc).

After I had collected all of this data, I built a flow chart of what the typical process looked like and color coded each system.  Additional research gave me a good indication of price per minute for various systems.  Adding all of that up, I could very confidently address how much money was spent on this process today.

If my product was 40% more efficient at this process, I now know the price (product value), or “the value that the product or service brings to the customer”.  From here I  worked with our sales team to determine our pricing strategy based on a multitude of factors (Saas v On-Premise, Size of Clinic).

Price (product value) is not a difficult metric to establish, the bigger problem is that most people don’t have experience in determining it.  Time and Motion studies are a great way to determine not only process but other features that your product should include.

Market Size

Benedict Evans has a really good article on Ways to Think About Market Size.

Almost every market sizing article or book that you read tell you to find out how many people or businesses use X and how much they pay for X on average (call it Y).  It all seems pretty straight forward and a lot of people use this simple math to justify their business.

Benedict really lays out why most of this is utter crap and that, in fact, most of the data we use to convince ourselves of market size is completely useless.

This is the problem with forecasting sales of the Apple Watch. Annual watch sales are a bit over a billion units, and people buy watches at anything from $5 (China exported over 600m watches last year at an average wholesale price of $3) to $500, $5000 and $50,000. But this doesn’t tell us anything useful. The fact that you buy a $10 watch, or a $1,000 or $10,000 watch, or buy no watch at all, tells me nothing about whether an entirely new product that you also wear on your wrist would be appealing. The fact that you bought a watch x years ago and the average replacement rate for watches is y tells me nothing about whether you’d replace it with an Apple watch, tomorrow, if you saw one.

He goes on to argue that market size is less about what people have bought in the past and for how much and more with how do spending habits change if it’s cheap.

So, to work out market size, really, you have to work out who will care, if it is cheap.

This is a brilliant observation and one that many people tend to overlook (including myself).

I won’t summarize the entire article here, but it is definitely worth a read, and better yet, clip it to Evernote and re-read it again.