Audience data is quantitative data about the users of your website. The best-known and most easily-accessible repository of this can be found in Google Analytics.
Due to their massive reach, Google can put together some pretty strong estimates on who makes up your audience. They do this through a mixture of assumptions and real data about users. The assumptions come from knowing the kind of things people are searching for and clicking on, while the real data is what they know about users who are logged into Google services (like GMail) while browsing. It's anonymised so you can't tell who the individual users are (fortunately, if you're concerned about privacy).
Audience data gives you some basic demographic information, such as age, gender, and location, which starts to build a picture of who your users actually are. You can then use this data to segment your audience or decide who you interview or user test with.
Fire up Google Analytics and head to the Audience section, there you can find the following:
You can then either summarise this data to give an overview of who your users are or you can group them together into what I call 'outline personas'. These are not as in-depth as full personas that have come from user interviews (they will be missing their motivations and behaviours) but they are a good way of turning numbers into something more real. It also allows you to view your audience as three or four types of people, rather than just a single entity.
It can be useful to make segments our of your audience personas—for example if a persona was women aged 35-44 from Canada, you can create a view on Analytics scoped to them. This allows you to study the behaviour of that audience and see how it differs to the average.
Another fruitful area to combine into your personas is the acquisition channel—does one audience tend to reach you from social media, while another from Google searches? This can help shape how you speak to people on those different channels.
Your sample size. In the top right of the age, gender, and interests sections it tells you what percentage of your users it has the data for. The larger that number, the closer to reality it is. Small sizes on low traffic websites can be skewed representations of your audience—as a rule of thumb I ignore it if the number shows less than 20%.
The time period. Don't look at too short a time period or you can twist your data. I like to look at the last three months worth of data when assessing my audience, so it can balance out any random fluctuations of traffic. Many sites see their audiences change at different times of the year, with big events like Christmas.
It's worth checking this data every few months to see if it has shifted (once per quarter is about right). Then update the summary you have of your audience and circulate it around your team. You should also flag any notable changes.
Just because you now know more about who your users are, be careful not to make big assumptions of them, e.g. "Most of our users are young so they can figure out complex functionality". You won't know that until you user test or interview them.
As I've focussed on here, Google Analytics (free) offers this data for your site—though you'll need to turn on the Demographics option to capture all of it. In addition, online marketing platforms like Google Adwords and Facebook Ads give you audience information if you buy some advertising.
It takes an hour or two to study it all, and another couple of hours to create outline personas.
Note: the examples in this guide are for website design, but most of the content is also applicable for native apps and software.