010 - Results & Reports - Survey Monkey - Tools and Technology

[00:00:00] Mike: [00:00:09] Hello and welcome to the BottomUp podcast. I'm your cohost. Mike Parsons, and as always, I'm joined by Mr. Results, Mr. Chad Owen.

[00:00:19] Chad: [00:00:19] So you spent all that time crafting the survey. You double, triple checked it. You gone and recruited your 80 plus-year-old fish owners in the UK and your results are pouring in.

[00:00:33] Mike: [00:00:33] There's a [00:00:34] deluge. You're swimming in it.

[00:00:36] Chad: [00:00:36] I see what you did there, Mike.

[00:00:37] Mike: [00:00:37] Yeah. Yeah. Yeah. I know, I know. I've been working on that one. So, yeah, you're very, very welcome to continue listening to this podcast, but you will double up the value if you go to Survey Monkey.com and you're logged in there cause you'll understand some of the tips and tricks that we're giving or alternatively come back to this and listen a second time with your browser open.

[00:00:57] But this is all about helping you work out, what's the results here? How do I report it back? Because you got a ton of data. You might have a hundred, you might have [00:01:08] a thousand respondents, and we're now moving into the world of how on earth do we work out what's the story here and where do we extract the most value?

[00:01:17] Because, it's good if you've asked some insightful questions in your survey, but you can actually make the results great, if you know how to do one key thing, and it's a double-barrel concept. It's all about comparing and contrasting the results or the responses of users. [00:01:42] Again, you've got all these users, all of their responses are in the database.

[00:01:46] If you can compare them, and if you contrast them in the right way, this is where you can get amazing understanding of what's going on and you can do this almost forensic isolation of the key drivers of motivation, of intent of activity. What are the real pains that people experience with products and services?

[00:02:11] What are the gains they're looking for? You can often use this [00:02:16] comparing and contrasting, and it reveals magic. And Chad, this is where you and I just go OCD in Survey Monkey. Tell me, what do you love about getting into the analyze results tab of Survey Monkey?

[00:02:31] Chad: [00:02:31] Yeah so, if you're following along with us, the second to last tab when you're creating your survey is the analyzed results tab and you won't have anything here unless you've gotten some responses setting up your collectors. So be sure you've set those up beforehand. And really what Mike's getting at is don't just simply take [00:02:50] the data that you've collected in the survey and just export it and call it a day.

[00:02:55] Because what Survey Monkey allows you to do is both filter and compare the data. So, if we want to know the spending habits of dog owners versus cat owners versus fish owners, by clicking on compare in the filters area, we can compare all three of those and their spending responses, which is something that we could export into a pivot table and manually figure all that out.

[00:03:22] But Survey Monkey does all of that [00:03:24] work for you and it's really simple to set up.

[00:03:27] Mike: [00:03:27] And so the key thing that you can dig around and discover is whether there's, you know, causation between factors. If people live in rural areas, therefore they're 10 times more likely to do X, Y, and Z. So, you might have direct causation, or you might have what we call correlation between data. And whether it's either a cause or a correlation, the power of these insights is very [00:03:58] specific towards taking action.

[00:04:00] The things you should do based on the data that you've collected. We're going to deal with that in our last show on Survey Monkey, but what I really want to get comfortable with, in Survey Monkey in the analyzed results tab is you will see that when you click on filter and compare, you can do some amazing things.

[00:04:19] For example. You could say, I want to filter based on a particular aspect in my survey. I only want to see people that, and through social media, I only want to [00:04:32] see people that answered on a particular day. So, when we talk about filtering, this is your capacity to isolate something. So, let's say I asked people what their age was in my survey.

[00:04:45] Then I might want to filter out any results of 18 to 24-year olds. Or inversely, I might only want to see a snapshot of this segment of my customer base. So, what you do is you select, that question and Survey Monkey reloads the results. only shows you the [00:05:06] answers of the entire survey from those who were in that filter criteria.

[00:05:11] Now, this is really interesting because as you're getting to know your customer, I just chose a simple demographic, but you can actually select a particular question. So, let's say we had a question. Let's keep going with the goldfish angle. Let's say you asked people about their preference on color for goldfish, and you want to identify like what's going on with all the people who love blue goldfish, so you could see only the answers from them.

[00:05:37] And this is the power of filtering. [00:05:40] You can just cut down your data and really see how things change between different segments, different personas that you may have screened into your survey. I mean, this is pretty cool stuff. Chad.

[00:05:51] Chad: [00:05:51] Yeah, and it makes it really fun and easy to highlight the most interesting results from the data. Or even tailored to the audience in which you're sharing it. So if you're the global director of marketing and you're going on tour, you don't really want to bring up your middle East and European and Australian consumer numbers when you're in the US so you can just filter out all the others and only focus [00:06:14] on US respondents.

[00:06:15] It can be as simple as that. Or you could say, I only want US-based, 25 to 34 greater than $100,000 of income, what device do they use? Android, iOS, or none.

[00:06:27] Mike: [00:06:27] So good, but it doesn't just stop at the filtering. Okay, so in the analyzed results tab, you'll see next to filter, right beside that is the compare filter, and this takes things next level because side by side, let's use the age question again. I'm going to choose the question, [00:06:48] which was what is your age?

[00:06:49] I’m going to compare 18 to 24 25 to 34 and 35 to 44 and then I hit activate. And then what happens is the entire results of my survey, are shown in three parts, every single question right next to each other, there's a chart for each of the age categories that I selected.

[00:07:12] I'm actually looking at an old survey we did hundreds of people filled it out, and I can see that 25 to 34-year olds on question three had a [00:07:22] wildly different response then the other two segments. Again, same thing here on the next question. What I notice here on the fifth question is that 18 22 to 24 we're way less likely than 35 to 40 fours on a particular question.

[00:07:38] This is gold because you can see all the variations and permutations in your customers, and this enables you to go, oh my gosh, I think our core audience is 25 to 34s. Or we know that the user behavior of those [00:07:56] 25 to 34 has a much higher frequency than other age segments. This is gold. If you're creating products, if you're launching marketing campaigns, it doesn't matter.

[00:08:07] These insights can all be unlocked by just using these filter and compare options.

[00:08:14] Chad: [00:08:14] Yeah. This is where the fun is in Survey Monkey.

[00:08:17] Mike: [00:08:17] Right. On this survey, Chad, there is, I think more than 20 different compare or filters that we ran on the report in order to try and decode some [00:08:30] insights and some learnings over 20 of these comparisons, try and isolate gold.

[00:08:35] I mean, how cool is that? I mean, that's how deep you can go.

[00:08:38] Chad: [00:08:39] And again, this is the fun part because this is where you're uncovering the insights. Like again, you could export this data and put it into a pivot table and try to figure it out for yourself. But Survey Monkey makes it so easy by using the filter and compare filters under the analyzed results.

[00:08:54] Mike: [00:08:54] And I must say a lot of people who are on a budget, will use Google survey, which just kind of feeds into Google sheets. The [00:09:04] reason we choose Survey Monkey above and beyond anything else over any other option is what we're talking about on this episode, results, and reports. This is the best filtering and comparing you'll be able to do this is what really saves you tons of time and effort and drama trying to work out what it all means.

[00:09:26] This is like a massive accelerant.

[00:09:28] Chad: [00:09:29] Well that and buying targeted responses, don't forget that.

[00:09:32] Mike: [00:09:32] There you go. So, one, two punch. Have we decoded results and reports?

[00:09:37] Chad: [00:09:37] Yeah. But we [00:09:38] can't let these insights stay stuck inside of Survey Monkey. So in the next episode, we're going to talk about how to get all these results out, but not only that but how to best present it to your ultimate stakeholder audiences to be sure that you can get the most out of the data that you've spent so much time and effort to get.

[00:09:55] Mike: [00:09:55] Fantastic. I would say my last advice, probably want to listen to this episode again, make sure you go through and get the most out of filtering and comparing cause you'll have the best results if you do that. So that wraps up the second last part of our Survey Monkey series [00:10:12] here on the BottomUp podcast.

[00:10:13] Thanks for joining us. That's goodbye, from Mike and Chad.