If we want to prove without a doubt that our advertising campaigns had a real effect and cost incremental results, well designed experiments are the way to go. As we saw experiments let us prove a causal relationship, between an adult campaign and an increase in results. Facebook offers the option to use experiments to evaluate the effectiveness of your campaigns on its platform. And in this video we'll look at conversion lift studies one of these experiment based tests. Facebook offers two different types of lift tests, conversion lift and brand lift tests. Both of these tests use experimental designs, but they differ in the outcomes day measure. Conversion lift tests measure the effect of ads on conversions, which could be sales add to card leads and so on. Brand lift tests measure the effect of ads on changes in brand recall, and other brand related measures. So in other words, conversion lift tests are all about actions that people buy, whereas the brand lift test is all about attitudes. Did people's attitudes to parts of brand change, and do they remember the brand after seeing the ad? In this lesson, we'll concentrate on conversion lift tests, we'll look at brand lift tests in the next lesson. A Facebook conversion lift test is used to measure conversion lift, which means they measure whether your campaign caused an increase in convergence. As with any test, you start with a hypothesis for the conversion lift test your test hypothesis is that your advertising campaigns on Facebook, caused a significant lift in conversions. Through the conversion lift text, you can evaluate whether your test hypothesis is correct. A conversion lift test begins by randomly assigning people from a campaigns target audience, to either a test or control group. This type of test is sometimes also referred to as a holdout test, since the control group is basically held out from being exposed to your ad. People in the test group can be exposed to an ad, whereas people in the control group won't be exposed to the ad. After that we want to measure the influence of the ad on conversions. In other words we'd now like to see whether the group that did see the ad took more actions or converted more than the group that didn't see the ad. To do that we need to have a way to see whether conversions actually happened. These conversions could be sales or other events like adding a product to a card, downloading an app or more. For Facebook to detect whether the people tested took any of these actions, the advertiser needs to pass back some data to Facebook, using the Facebook conversions API. If you took the first course in this program, you'll remember that we discussed the use of API to pass data related to convergence to an advertising platform like Facebook. An API or an application programming interface is a tool that establishes a connection between two pieces of software. And API allows two applications to talk to each other, in this case the Facebook API makes it possible for a company to connect its software. That monitors conversions or whether or not you bought to Facebook's platform. Facebook in turn can then use that information to help evaluate whether advertising on its platform had an effect on the conversions. I've added a reading in this lesson with more information on the Facebook conversions API. It's an important tool to help you get the most out of what the Facebook advertising platform has to offer. For now, it's good to keep in mind that if you want to measure the effect advertising has on certain actions, you need to be able to monitor whether these actions happened or not. The Facebook API allows you to do that monitoring, and pass the information back to Facebook. The final step in your conversion lift test is measuring the results, and comparing the difference between them. This means you're comparing the actions you see in the control group, versus the test group. The lift in conversions you see between the test and control group, can be attributed to the ads, that lift is the effect of your advertising. Let's look at an example of how these tests can help, let's go back to Calla and Ivy the flower business in Amsterdam. Imra plans to run a campaign with a goal to generate sales during the fall, she specifically wants to sell the foul bouquets that are very popular in her physical store in Amsterdam. For this campaign, Imra recreates carousel ads with images of the different bouquets, and she adds a call to action button shop now. This campaign is focused on conversions, Imra wants to see people buy the bouquet on her website. Imra Steam has integrated the Facebook conversions API, so the data of the sales that happen on the website are sent to Facebook. Every time people buy something on the website, data gets sent back to Facebook to signal a conversion. Imra wants to test the impact of her Facebook campaign, so before starting the campaign, she decides to do a conversion lift test. Her hypothesis is that the campaign she runs on Facebook will significantly increase the number of conversions she sees. Imra targets her campaign to people that have visited the website in the past, of this target audience, a group of people will randomly be assigned to a holdout or control group. And another group is assigned to the test group, to control group doesn't see Imra's add, whereas the test group has an opportunity to see the ad. After the campaign stops running, Imra gets the results, there's a 13% point lift in conversions for people who have seen the ad, and Imra decides that is a good result. Later in this lesson we'll take a closer look at these results, and look at how to best interpret them. But for now let's agree with Imra that her campaign proved to be effective, now you understand how conversion lift tests can be used to evaluate the effectiveness of your conversion campaigns. In our next video, we'll look at what to keep in mind when conducting this type of test, and how it works in practice.
