The process outlined here are the basic steps to optimizing your Average Revenue Per User (ARPU).

Step 1: Who are you selling to?

Remember lesson 1 in validating your system? Here is another place that lesson comes in. If you don’t know who you’re selling to, then you didn’t do your homework in the first place. Go directly to jail, do not pass go, do not collect $200. But I have a feeling if you’ve read this far, you probably know who you’re selling to, or at least have some idea. Now take all the groups you’ve got and segment them in three to five different major groups.

Step 2: Identify the demographics of the groups that will pay the most and get the most value from your SaaS offering.

These are your highest value customers.

What you need to know for each group you’re selling to is:

1. Type of company

2. Company industry

3. Role, position, or title

If possible, get as much info as you can. Information such as:

1. Age range

2. Income range

3. Male / Female ratio

4. Interests

5. Level of computer savviness

6. Education level

7. Anything else relevant to selling your SaaS

Building a customer profile can be very quick or very difficult depending on your product. If you did your validation, you should have this already. But if you’re looking at this area with crossed eyes and thinking to yourself “How and I going to do that?” Then here are your steps:

1. Start with who isn’t using your system. This part is easier since there are a ton of people that aren’t ever going to use your system. For example, people that don’t use the internet are never going to use your system. Sounds silly, but I can’t tell you how many times I have brought up to clients that some of their potential customers will not benefit at all from their digital marketing efforts as they never use the internet.

2. Next, work out your group’s expected professions. In some cases this is simple, whereas in others it is really tough. After a number of Google queries and perhaps a bit of reading in some scholarly articles, you can usually identify some trends.

3. Now that you have a somewhat more narrowed field of users, identify your expected male to female ratio and expected ages of your users as well as their income. A lot of time this is a very telling item. You can often just enter your query into Google to figure this one out, but then sometimes you also need to do some deeper digging.

4. From here, you need to infer some traits of these people. If you suspect someone’s age, income, male to female ratio, and their profession, then you can probably figure out a lot more about them and will now have some ideas about their motivations, your real competition, and much more.

Step 3: Determine Most Valued Features

This is what you’re different customer groups are actually buying.

For each group, there will be a different set of features people want. Of course there will be overlap, but different people’s roles in a business determine what aspects of your SaaS they are more or less interested in and value the most. For example, a CEO is going to be more interested in reporting than a caller at a call center. Conversely, the caller is going to be a lot more interested, relatively speaking, in the speed of the system than the CEO.

So now list out which features you think each group is most interested in. That’s a great start, but the only person who is actually going to tell you what features they’re interested in are the users themselves. Now it’s time to actually ask them what they think! Put together a survey and send it out to everyone.

Don’t have users yet? That’s what that advisory board is going to help you understand.

Step 4: What’s it worth to each group?

Just like the last question, the only person who’s going to tell you how much they will actually pay is the customer. However, at least we know what questions to ask them to get a good starting point on each price point.

So just like the last question, you’re either going to be sending out surveys to everyone, or asking that advisory board for some help with this. If you’re just getting started and using your advisory board, remember that this is a very, very small sample size and different regions around the country and around the world have very, very different values they place on systems.

If you’re not using the advisory board, make sure the take a look at the Van Westendorp’s Price Sensitivity Meter for a list of questions to ask all your users.