 Hi, my name is James and I'm a librarian at the University of Alabama. Today we're going to be learning the basics of Simmons Insights, a database that contains data from the National Consumer Survey, an annual survey view as consumers buying in media habits. To use Simmons, you will build cross-tab tables that show how consumer demographic and media use data intersect with consumer habits. To get to Simmons, we're going to start at the UA Libraries homepage and then navigate to the databases page. In the search box, search for Simmons. Now we're at the starting page for Simmons. Simmons has a lot of features, more than we will be using in this video. I definitely recommend taking some time to familiarize yourself with all the features of the database. For now though, we'll be building a cross-tab search. And as an example, we'll be looking for information about ice cream consumption. The new Simmons interface starts us out on the smart search, but I've found that unless you know specifically what you're looking for, it's easier to use the dictionary search. We can change to a dictionary search by clicking Dictionary Search. The first thing we'll want to do is to select the study data to use. Click on Study, then the study you want. I recommend the most recent 12-month study available. In this case, the 2017 12-month study. Simmons has all sorts of data about consumer behavior, so take a look through the categories to see what data you might be looking for, or search in the search box. Being sure to select questions and answers to see what data might be available. To build our cross-tab, there are three things we'll need to consider. The base, the columns, and the rows. According to Simmons, the base is the population you will use to build your study and the population you used when calculating the index, which I'll come back to in a bit. You can leave the base blank, which means your cross-tab will use the whole study population. I often do this myself, but since I'm interested in people who eat ice cream, I'm going to select a base that would indicate this. Thus, for my base, I'm going to select frozen novelty treats household uses, yes. Now I can see the sample of respondents in the study, and the weighted sample, which is an extrapolated number that represents how many people in the U.S. would have answered like this, and that number is given in thousands. Our weighted sample here is over 132 million. Next, we'll want to populate our columns. The recommendation I've continually heard from our faculty is that it's best to put the information we're investigating, brands, consumer behavior, and so on, in the columns. So, imagining that I'm interested in figuring out who buys which ice cream brand, I'm going to select frozen novelty treats, brands MO, MO meaning most often, and drag them over to the columns. For dragging items, you can select single items, or if you want all of them, you can click the whole category and drag it over. Lastly, we'll be adding demographic data to our rows. This way, we can identify what demographic groups are most or least likely to use whatever product or consumer behavior we want to look at. Here, I'm going to look at age ranges, so I'm going to select demographics and age. At a glance, we can see several different age ranges from single numbers to large ranges. This is due to the way that the National Consumer Survey is designed. I'm going to select all of the age choices and add them to the rows. Now, I'm going to hit run and Simmons will generate my crosstab. Looking at the crosstab results, you'll see a lot of numbers. This can definitely be intimidating at first, but as you get used to reading Simmons crosstab results, there are a couple of specific things you'll want to look for. First, you want to look for number results without an asterisk or double asterisk, as indicated by the explanation below the crosstab. An asterisk indicates that the sample is a bit small and the data might be unstable and to be careful about using it. A double asterisk indicates the sample is small enough that you probably want to avoid using that data point. The other major thing to look at is the index. This indicates how much more or less likely a specific demographic is to buy or engage in whatever you're looking for. 100 is the average and the higher or lower a number is above or below 100, the stronger the indication. The other numbers are certainly important as well, but for an introduction to Simmons, these are the most useful things to look at first. Thus, looking at our results, we can see data from respondents at age 18, 19, 20 and 21 is probably not reliable due to the small sample number of those ages in our base. Also looking specifically at Ben & Jerry's, we can see respondents and demographic brackets between ages 22 and 44 are more likely an average to respond at Ben & Jerry's as the brand they buy most often due to the positive index number we see here. But with one asterisk, we would want to use that data with caution. So that's all for now. Thanks for watching. And as always, if you have any questions, contact us or visit ask.lib.ua.edu to ask a librarian.