Let's look in another experiment, the funnel. Now, as we've talked about, the classic example here of the funnel is, where the funnel starts we're trying to bring a user that's come to our site through to some sort of transaction. Buying something, signing up but this can work equally well in an enterprise context, where we're trying to get a user through some sort of complicated process and we're looking at how we can do that better for them. If we look at this on the question and motivation versus ability usability, this is more sort of over in this direction where we're focused on usability. And the reason is, I'm assuming that we've already fundamentally vetted why the user would want to go through this funnel, now we're testing different ways to make it easier for them. If that's not the case, then that'll be a different type of experiment. If you have any experience with sales or marketing you're probably used to seeing things like this funnel here. On the y axis is number of we'll just call them people because they sort of change from visitors to customers as they move through the funnel and then on the X axis is just time. And in this case we use this set of steps as they, this AIDA framework that we used in the past where the customer, we get there attention and they move through retention. So and we'll use enable quiz, the company is making a lightweight technical quizzing solution as a kind of central example here. And we're going to think about how they would get an HR manager to come to their site. So they might run a Google AdWords campaign, or targeted email, and they're getting their attention, then they're bringing them to the site. Maybe that starts with some kind of landing page that pairs with that ad. And then they move through to some kind of a demo page in the interest step here. We say, hey, this is what the solution does. We think this would be great for you. And we're trying to move them through to taking action, which is in this case signing up for a free trial. That's all we want them to do, that we consider a success. And then onboarding we'll kind of look at separately. We'll look at an example of cohort experiments. So really, what we're going to do here is test this key assumption. If we get HR managers to a landing page with a demo, 10% of them will sign up for a free trial. And we're going to do that by bringing traffic to the site and then showing them a demo page. So really, what we're going to do is we're going to look at this separately in the section on A/B tests. We'll think about different ways that we're going to get the users attention and bring them to the site and test different approaches to that. So what we're going to look at here for the funnel experiment is just the user journey between interest and action. Because the onboarding we're also going to look at that is a separate thing, will actually show you an example when we get to the cohort section on some different things they might test there. So this is our area of interest here between interest and action. And these are the thresholds that they are going to test. Now they're not testing multiple versions of this funnel we'll say in this example because they just want to get a basic version to see how it works out, maybe supplement their observations with some qualitative research about how that's working for the HR managers and then they'll figure out what to do. So their thresholds are that If they get less than 5% of people moving through that have come to the site and signing up for a free trial, they're going to fundamentally revisit the proposition. So then they think it's more a question of motivation or some more fundamental problem. It's not a thing for them to be tweaking on the front end. We'll just say that that's the assumption. If it's less than 10% conversion, then that's still reasonably good but they're going to look at the funnel in more detail. They'll probably focus on getting in touch with some of the visitors and talking about what worked well for them versus what didn't but basically moving backs towards the why and doing some qualitative research on what was happening. So we'll consider that as sort of a minimum pass but needs a lot of fundamental work. And, if it's over 10%, then they're going to say hey, this funnel is working really well. We should probably spend our time in one of these other areas like onboarding and getting more people to the site at over 10% convergence, we think that's pretty good. Now these may or may not be appropriate thresholds for you and your situation. So there are some comparables that I've included in the lesson materials to help you figure out what your thresholds should be. I think about these more as the break points that you want to set for decision making. And there's no separate section on what they're going to do next because they're already sort of described that up here and that's fine to do that. This template isn't setting you always need to follow to the letter, it's just sort of a guideline checklist to help keep you through and help keep you organized. And let's say that they've got a backlog for the execution of this and some growth hacking note back in their venture design docs for the attention campaign. So this is where they're documenting, how long this is going to take. A few other side references here things that may be interesting. David McClure has these, he is a thought leader in growth hacking and startups in general. He has this pirate metrics thing which is a sort of different view of these steps that you can see down here. And, very similar to the AIDA framework but focused on a little bit different stuff, this presentation that he did on this stuff is included in the lesson materials. And that also has some thresholds that you can look at and sort of compare against your own, the type of execution you're doing. And then finally if you use Google Analytics, Google Analyticss is kind of like, it's a sort of a catch-all tool for doing this type of quantitative analysis. And there's other tools out there that are really good at certain things but you can set up a lot of stuff in Google Analytics. If you've used it, you may be familiar with this page here where you can look at the user flows through your site. And this is an example from their page. If you're not familiar with it, go and check it out. It's a very useful tool. It's very easy to set up an instrument into your application assuming it's a web application of some sort. So you've seen how a funnel experiment might work, where you would fit it in, what the experiment might look like and what some of the thresholds might be for decision making.
