Pricing and sales volume part 1 - framework
Steven Forth is a Managing Partner at Ibbaka. See his Skill Profile on Ibbaka Talent.
For most products in most markets the unit price changes with the volume purchased. These changes need to be designed into the pricing model. If not, they will emerge any way in undisciplined discounting. This is the first of two posts that looks into how to manage unit price change across volume.
Pricing and sales volume part 1 - framework (this post)
A general framework for understanding how and why price changes with volume and how to design pricing that responds to this. The design of pricing to volume relationships is a big part of pricing model design.
Pricing and sales volume part 2 - mechanics
This post will look at the mechanics of different ways to align unit price with sales volume, focussing on both the smooth and stepped approaches.
A general framework for managing unit price and sales volume
One of the five characteristics of a well designed pricing model is that it is scalable. (See 5 characteristics of a superior pricing model). This means that an appropriate price can be generated across different deal sizes.
There are of course three possibilities. Price can decrease with volume, stay the same or increase with volume. Let’s look at each of these possibilities.
Price declines with volume
This is the most common expectation. In many cases it is true because people assume it should be true and proceed to offer price decreases for volume without asking why they are doing so. The first thing to ask here is …
Why should price decrease with volume?
The most common answer to this question is that …
Buyers expect pricing to decrease with volume.
Procurement insists that price decrease with volume.
In other words, pricing power is with the buyer and this is one way they impose it.
In some cases, the buyer and sales are aligned here. The buyer wants a lower unit price and sales does not really care what the unit price is so long as the total deal is bigger. For SaaS businesses, this can play havoc with unit economics.
There are some reasons to accept that unit price should go down with volume: cost and value.
Fixed costs per unit go down as we add more units. I know, Tom Nagle has taught us that we should ignore sunk costs when setting prices. But are fixed costs always sunk costs? Not in SaaS, where there is a built in assumption of ongoing R&D to constantly improve functionality and increase value. This is often the best reason to provide volume discounts, to have more units across which to distribute ongoing investment. Note that this counters the argument that volume discounts can undermine unit economics. If the right investments are being made, then having more users can improve overall economics.
Value per unit can go down as we add more units. There are some cases where the incremental value per unit goes down as the number of units goes up. One can even see Pareto’s law at work here, where the first 20% of adoption delivers 80% of the value. There are many examples of this. Should every salesperson get the very best (and most expensive) sales tools powered with sophisticated AIs or only the 20% that will actually be able to make use of them? Does every customer segment need a value model and value story or just the 20% that drive 80% of the revenue (Ibbaka Valio uses segments requiring a unique value model as a pricing metric).
Price stays the same across volume
Some companies have excellent pricing discipline, the price is the price, and no discounts are offered. These are most often Product Led Growth companies where pricing is published and the transaction is automatic, leaving no opportunity for a buyer to negotiate.
This approach makes sense when costs and value do not change with volume.
Price increases with volume
There are cases where unit price increases with volume. This happens most often when there is scarcity (real or created by the seller). There are also cases where higher volume increases, rather than decreases, variable costs. This is true of many professional services businesses, where the number of skilled people able to do the work is inelastic and the only way to attract more people, or to get the current team to take on more work, is to pay more.
There is even a pricing model used in limited edition art prints, where the price goes up for each print sold. If only ten prints are made, the first print is priced at $1,000, the second may be priced at $1,100, the third at $1,210 and so on up to $2,358 for the final print in the series.
Network effects are an interesting example of unit value increasing with the number of units. Remember Metcalfe’s law.
The original incarnation distinguished a linear cost (Cn), non-linear growth, n2, and a non-constant proportionality factor A “Affinity.” The breakeven point where costs are recouped is given by
Costs x Units = Affinity x Units(Units -1)/2
Affinity is a non-constant proportionality factor. In pricing work, we can use Affinity as a measure of value. The above equation then calculates the breakeven for the buyer in terms of value to customer (V2C).
How should price change with volume?
If one accepts that price should change with volume there are two basic approaches” smooth and stepped.
In the smooth approach, one has an equation where volume or units is the input and total price is the output. There are many ways to design this function and a few will be discussed in the second piece in this series, “Pricing and sales volume part 2 - mechanics.”
Advantages of the smooth, or algorithmic approach, is that there is an equation that can be optimized. This is a big advantage for pricing optimization systems that can connect this pricing algorithm to an optimization function.
The disadvantage is that some people find this less transparent than the stepped approach and that it does not encourage buyers to increase volume to get into a higher tier with lower unit prices.
In the stepped approach, one defines a set of tiers and sets a unit price for each tier. How to do this is covered in the follow up “mechanics'“ post.
The advantages of the stepped approach are that it is conventional, many people expect it, and people are more comfortable buying what they expect. There are also cases where buying behavior changes with scale. It is often easiest to model this using a stepped approach.
Let’s look a bit closer at step changes with scale. In small businesses the CEO may make most of the buying decisions, in mid -sized businesses the operational manner may make the decision, and for large companies there is often a decision making unit (DMU) of three or more people (hopefully not more than seven or the sale may never close). At the enterprise level there can also be a procurement department. When there is a step change in buying behavior it is often easiest to use a tiered approach (this can be done with algorithmic pricing, but it becomes much more complicated).
There are many other examples of this, many of which can be uncovered with a good conjoint study.
Stepped, or tiered models, are harder to design than many realize. There are are four main questions to answer (we will show you how to answer them in the “mechanics” post.
How many tiers
Size of the tiers
Price change across tiers
How to handle transitions between tiers
Questions to ask when designing the pricing model for how price changes with volume
Should price change with volume? Why?
Consider all three possibilities.Unit price should go down with volume
Unit price should remain unchanged with volume
Unit price should go up with volume
If yes, should a stepped design or a smooth design? Why?
Smooth if you want to be able to optimize the algorithm and have a simple input-output pricing model
Stepped if there are changes in behavior across scale or the salesforce is most able to execute on this model
