For market segmentation pricing... what is better for a software product: by features or by capacity?

what do you think is a better style for market segmentation pricing of a software product?...
Option A: By features (Spreadsheet software example)
- Edition Lite: $100 (features: macros and printing)
- Edition Standard: $150 (features: macros, printing and graphs)
- Edition Professional: $200 (features: macros, printing, graphs and pivot-tables)

Or, Option B: By capacity (Spreadsheet software example)
- Edition Lite: $100 Work with up to 3 books and 10,000 rows per book.
- Edition Standard: $150 Work with up to 10 books and 50,000 rows per book.
- Edition Professional: $200 Work with up to unlimited books and 100,000 rows.

The most typical option is By Features, but in a few cases I've seen products priced By Capacity.
Any experiences or ideas about that?

I personally like capacity. You get to use the marketing line "you get the whole product." Upgrading customers is easier in a capacity situation because they may never need pivot-tables, but they may need 100 spreadsheets.

There is no "better" option. They are different and the choice depends on your product and your target audience. For some products, it makes more sense to price by capacity and for others by features.

The answer to this question could be a whole course on customer value perception, and still there would be no clear answer.

Go out and test with your target audience which is better. That will give you a better idea than any opinions that we have.

I agree with John that there is no clear winner, it depends on your product. The big reason to have tiered pricing is so that you don't leave money on the table. If you have just one price, you don't have a way for those that would spend more to spend more, or those that would spend less to still spend something.

I personally prefer capacity rather than features, as I like my users to get the most value out of my software, and I find holding back on features that would help them is a tough call to make.

Another advantage to capacity is it makes the buying decision easy for them, and sometimes a tricky decision means no decision is made, and can cost you sales. Better that the decision of which plan to choose is obvious (ie. I need this many rows.. so this is the plan).

Lastly, capacity is usually an easier correlation to "if your business is bigger, then you will use more, so should pay more". Obviously you can choose features that would more likely be used by bigger companies, but I find capacity easier to do this with.

One main issue with capacity is that anyone that just tips over into the next plan will feel like they are getting a raw deal. For example, if you have two plans, one gives 10,000 spreadsheet rows and the other gives 1,000,000 rows. Someone with a need for 11,000 rows will feel ripped off that they have to pay for much more than they want. Although this can happen with features (ie. they just want one of the features from the next plan up), I think it is less of a problem.

As mentioned at the start, there is no simple right answer. It depends on a lot of factors. Just do spend the time to get your pricing as right as possible early on, as it's hard to change once you have paid users.

Most sentences containing the word 'segmentation' annoy me :)

The short answer is - sometimes apples are best, and sometimes oranges. One fruit is not better than another.

Now, if you want some slightly heavyweight stuff, read on, otherwise please jump off here - shorter answers are available!

So let's start by distinguishing two ideas: customer segments, and pricing structures.

When you talk about a segment, it's shorthand that means, a group of customers who share a bunch of characteristics, generally including at least the core motivation to buy.

When you talk about pricing structures, you're referring to what's offered, what's measured, and the way that charges are calculated.

Two different pricing structures do not create two customer segments.

And by definition, in almost all cases, if you are looking to maximize profit, then different customer segments require distinct pricing structures. (Which is a consequence of the fact that different customer segments require different total propositions.)

This is an important asymmetry, and one you should always keep in mind.

So there is better and worse pricing, and there is better and worse communication of pricing, but pricing structures can only be determined as better or worse when put into the context of the target segment.

Sorry if that all sounded a bit theoretical. Trust me, it's one of the most profoundly useful bits of learning you could acquire. (And I spend some of every year fixing problems that stem from misunderstanding, often by large companies who really should know better!)

In the spreadsheet case you mention, my first question is going to be, who should use this, and why? (Another way into that is to ask, what are the main use cases, and how do they cluster in relation to users? ) This question helps you to drive out possible segments.

So next is the commercial step. What drives value in this segment? If this is a paper exercise, you're going to be applying a lot of judgement that you'll want to verify when you can't read it straight off the use cases.

Here's how I do it.

1. For each prospective segment, I'll list one, two or at most three product or service measures that drive value at the most fundamental level. Then I'll draw up a matrix of segments and measures, and attempt a rough and ready weighting at every point. For the first draft, my scale goes 1, 10, 100, 1000, because I want to focus. It's pretty common, even if I'm disciplined, that most segments will end up with a big handful of value-driving measures.

For the spreadsheet example, "size of spreadsheet," "number of concurrent users," "ability to integrate with back-end data" might turn up - or they might not.

2. So now comes the analytical step. In the ideal case, value drivers would map to features and be mutually orthogonal between segments.

Trust me. That never happens! But it's often the case that a few measures stand out as 'segment separators' - they drive value strongly in some segments, weakly or not at all in others.

3. So next comes the creative step. Where there are segments you'd very much like to separate (for instance because of differences in scale and unit value), but which can't be distinguished based on the measures you've identified, you can look for 'value killers.' These are potentially negative measures that have no material effect on one of the segments but are deeply destructive for the other. (For instance, what about a spreadsheet that couldn't print, or one that didn't support smaller window sizes, or...)

4. And finally there's the pragmatic step.

You've done a lot of work, identified a lot of possible segments, and worked out how to create propositions that fully resonate only with their target segment.

But you've also made a bunch of assumptions, and multiplied complexity in execution.

So it's time to refine.

In many, perhaps most, cases, a startup will end up creating one simple line of propositions, rather than addressing multiple customer segments. The value of the segmentation exercise in this case is still significant. It helps you think about your customers, and to develop coherent propositions, whether to focus on a chosen segment or designed to address a wide range of segments. And it helps you to create experiments in 'segment appeal,' for instance by creating propositions that simply aren't relevant to your core market and where interest and uptake will give you valuable intelligence about the scale and nature of another segment.

But in a significant number of cases, you may discover that there are two or three segments that fit your mission, that can be separated propositionally, and where the potential revenue and profit gain is worth the extra burden of managing multiple propositions.

And in startup terms, where cash is usually at a premium, that can make all the difference in the world.