Well, I did promise that some of my blog posts would be about pizza, and now that time has come. Sort of. 

In the world of content delivery, there's this concept called "Bite, Snack, Meal". The idea behind it is that you should only ever present the amount and type of content that your end user is willing and able to consume. Using the pizza analogy, if I only want a little taste of pizza, mini pizza cups are perfect. But maybe I got home from work and dinner is a few hours away. I know I can't wait that long so that little pizza bite won't help me, I want something more substantial like an english muffin pizza. I used to snack on those all the time as a kid/teenager/college student. I might've had some last week while waiting for turkey dinner. Of course being from Chicago, what I really want is that big deep dish pizza meal. I'm getting hungry just thinking about it.

So content delivery, in this case statistics, is similar to pizza. And I'm not just referring to a pizza pie. Get it, pie chart, pizza pie..., olay maybe that's stretching it a little. But the point is, there are people who only ever want a little BITE of market stats. Median price, active inventory, that's all they need. And put a pretty picture on it. Then there's another group of people who want a bit more info. They may care about a few more metrics, or trends over the last year so they can write a blog about current market conditions. It doesn't have to be too deep, but it's definitely more than a bite. These are the SNACK people. Then we get to the people for whom a bite or snack is never enough. They want all the data and all the stats and want to do their own analysis on top of that. The really nerdy ones will even compare it all to what they pull and track in their own spreadsheets. These folks want a MEAL.

The job of the content provider, then, is to give the right amount of food to each user. The BITE person will be overwhelmed if you sit them down for an hour and make them devour a whole pie. The MEAL user will walk away starving and sad if you only give them a tiny pizza roll sized for a toddler. First know your audience, then give them what they want.

Okay, time to tie this back to actual analytics. When we first launched Domus, we came out with a big fancy "meal" called Market Insights and tried to convince everyone how hungry they were. We also had a couple of options for public deployments that were different variations of a few "bites". There were no real "snacks" in that world at all.  Then we listened and learned. On our newest platform, we have Bites, Snacks, and Meals, and the ability to configure them for each deployment.

In the Bite cateogry, we have the Infographic and Website Widget. The Public dashboards can be either a Bite or a Snack, depending on how our clients want to deploy it. Our newest product, Maret Review, is solidly in the Snack category. We've seen this popping up on blogs and forums, posted by engaged agents, and it's only been avaialbe for less than a month! That leaves our flagship product, Market Insights, and our new Pricing Insights as the Meals. I could make a case for Pricing being both a snack and a meal, but that would take a lot of words to explain so I'll save it for another post. Plus, my online order for deep dish pizza from Gino's East arrived today, so I need to go perform some User Acceptance Testing right now.

When I first started thinking about this post, it was titled "Why I hate gauges". And then Ed added a gauge to the Pricing Insights dashboard, and I nearly divorced him for ruining my blog. But we're still married, so let me take you on the journey that led to that outcome.  

Remember the first time you saw a gauge on a dashboard? Of course you do, because it was unlike any chart or graph you'd ever seen before, and that made it sexy! You either wanted to marry that gauge and show it off to everyone, or destroy it for being the prettiest one at the prom. Or maybe you felt a little bit of both, like I did. So I looked at it some more, and realized I didn't quite understand it, which made me think for a moment that gauge was smarter than me. And then I looked at it again, for several minutes, and then several minutes more, and then I decided that I hated that gauge. Turns out I did understand it. But being a bit of a data visualization purist (yes, I've attended whole conferences on just data visualization!), it was very obvious that gauge, through no fault of its own, was one of the worst ways to visually show that particular metric. And ever since that first gauge came into being, more and more of them have appeared, and mostly used in the same horribly wrong way.