PPC Insights 27: Your Marketing Dashboard Shows WHAT Happened – But Do You Know WHY?

00:00:00: Herzlich Willkommen zum AdStrive PPC Insights Podcast.

00:00:04: Hi and welcome to a new episode of our PPC Insight podcast by AdStrive, And today we're gonna do very special one because I'm joined by Nora from Hungary, which is why we're doing it in English today.

00:00:19: so if you are wondering what's going on that's why but i promise it's gonna be lot of fun and we will get a lot of useful insights from Nora

00:00:29: So you know me, but you might not have seen Nora yet.

00:00:32: So maybe you can introduce yourself just real quick?

00:00:35: Okay hi!

00:00:36: First of all it's nice to be here.

00:00:38: thanks for inviting me.

00:00:39: It is my first podcast with AdStrive.

00:00:43: Yes I'm coming from Hungary and basically more than fifteen years now i am dealing with data analysis and optimization.

00:00:53: so this is my passion.

00:00:55: at INTREN in Hungary at the performance agency, I was leading an analytical team and now i'm also helping clients in Germany to reach their business goals hopefully.

00:01:09: Yeah so Nova is working for our partner agency which is why we love to work on projects together to kind of use the data that we are gathering and then hopefully get some insights and work with that.

00:01:22: And it's kind of what we're gonna to talk about today.

00:01:25: so we are gonna talk a little bit.

00:01:27: how data is giving us the whats then how end up will be actual why?

00:01:31: So basically facts and reasoning... ...and yeah kinda what dashboards

00:01:37: I'm not telling as i would say

00:01:39: Yes this one my favorite topics because.. ..I can see a lot of performance marketers like pulling their hair out because they see a low conversion rate or high bounce rate and they are looking at data in analytics but they are just waiting for the magic to happen, you know

00:02:00: and get that reason, 

00:02:02: the why behind the data.

00:02:04: So hopefully I can give some tips today to

00:02:08: tackle that.

00:02:10: Yeah!

00:02:10: So basically where we want start kind of right.

00:02:13: Let's say we have this beautiful dashboard that our team created.

00:02:17: We are looking at it on a weekly basis, discussing the data, the numbers and then we're looking at our cart abandonment rate and we are seeing that eighty percent of people basically abandoned the checkout which is not nice.

00:02:31: But why is it not enough to simply draw that conclusion like what else should be do?

00:02:36: Yeah so dashboards are great in let's say identifying symptoms, but in most cases, it cannot diagnose you know the reason behind.

00:02:50: It's like going to the doctor and let's imagine that dashboard is your thermometer and you use the thermometer.

00:03:01: You can see that you have a fever of thirty-nine degrees.

00:03:05: It tells you that there is a problem with your system and it's severe because it's thirty-nine degrees

00:03:12: but, you know... it doesn't say it's because you have a flu or an infection or an even more serious problem with your health.

00:03:21: So.. that is when you know asking the questions and finding that the why behind these symptoms comes in place. So GA4 for example Google Analytics can help you find out where is the friction, let's say a huge drop-off in the purchase process.

00:03:46: But it cannot tell you the reason.

00:03:51: like for example on a B2B site You can see that many people leave the form at step two and you start asking questions, why?

00:04:05: Is it because the form was too long?

00:04:08: Or is it because that there was a question which made them uncomfortable.

00:04:14: Or because they had a problem with clicking on button which is / which says next on let's say an old version of Android devices

00:04:27: And this where guessing comes in.

00:04:29: and if you are just guessing the reason behind it, you might go or come to forced conclusions and this can cause you know testing things which might not be the real reason behind it.

00:04:47: So this is why quantitative data from dashboard is just half of the answer.

00:04:53: Yeah, that makes a lot of sense!

00:04:55: So from you we just learned that data is great and guessing

00:04:59: I mean, it's nice but maybe it's not the best thing to do.

00:05:04: So if we shouldn't guess when looking at data what should we do and what should we do next in kind of to identify

00:05:11: not only the friction point because we might have found that already how should we then move on towards why?

00:05:17: Yes basically you have to bridge the gap

00:05:21: and for this the best way is to reach out for qualitative data so you identify a bottleneck and then from looking at the average numbers, you turn to checking individual human behaviors.

00:05:42: And you search for evidence of real users how they use this site and navigate it or even your app.

00:05:52: The most affordable way to do this is by tools that provide you session recordings.

00:05:59: That is there are a lot of tools on the market, even free tools like Microsoft Clarity

00:06:04: but most of the tools have a free version or a free trial.

00:06:10: We use Hotjar we use heatmap tool of VWO called Insights, but there is a tool called Lucky Orange or ClickTale.

00:06:23: Many many other tools.

00:06:25: it really depends on what you can afford how your website is built up and what technicalities does your website have

00:06:35: and based on that you can decide which tool to try!

00:06:39: And for example if your bottleneck is at the checkout process by watching twenty, thirty recordings of sessions of real users how they navigate on your site you can identify patterns.

00:06:56: For example if you see that at the checkout process they are heavily scrolling up and down probably searching for the shipping info which they cannot find there or...they're trying to click on a field of the promo code, but it's not opening.

00:07:18: These insights you cannot get from quantitative data from Google Analytics or any analytical tool.

00:07:26: But these tools not only have session recordings

00:07:29: usually heat maps are also very helpful because these heat maps can show you what area of the page the users simply ignore not even recognizing that there is a useful information because it's like out of their sight.

00:07:48: Or you can even use exit surveys, pop-up surveys asking for example at a specific point in the checkout process when the users tend to leave the site.

00:08:01: this can be identified by you know following the mouser movement and at the perfect point, this exit pop-up can come up asking like what stops you completing your purchase today.

00:08:17: But you know qualitative data can be also coming from in house—from your sales team, from your customer relationships team.

00:08:28: They have a lot of information from your customers or from your users and all this informations can be like compared with quantitative data and basically fill the gaps.

00:08:42: Yeah, I think that's a very relevant point that

00:08:44: first of all obviously there are lot of different tools we can use to kind of gather that information but then it does make a lot of sense to also talk to the salespeople. I think I also experienced so many times that 

00:08:58: they were just giving us the information like, oh people keep calling us because they can't figure out if there is like a package price for a software or something like this

00:09:07: and then they start calling and that is something that like was never really displayed but they had like two or three different types of software and then people wanted the package which completely makes sense.

00:09:17: So it does make a lot sense to kind of talk to the people who might know who are actually in touch with the client.

00:09:24: I think so Yeah, that makes a lot of sense.

00:09:26: And I think we all kind of went back to university when it was about like analytics, statistics and research and when we learned okay there is a place for quantitative data and then there's a place for qualitative data, so that is obviously very valid.

00:09:44: But I think you already gave a lot of great examples for like small things like what an exit survey could look like.

00:09:51: but maybe you can give like a bit more context and give us an another real-world example where you actually experienced that there was a diagnosis that was made up based on the data of the dashboard and in the end it turned out to be kind of wrong or completely wrong?

00:10:09: Yeah, that actually happens many times.

00:10:13: To give you an example from a B2B business they had their main goal was to get as many consultation requests as they can.

00:10:26: so there was the landing page with a form on it and to be honest conversion rate was terrible.

00:10:33: There was a huge drop-off during the process of filling out the form.

00:10:38: And if we would just look at quantitative data, like by a textbook CRO diagnosis... we would have said that okay

00:10:53: the form is too long

00:10:55: it has so many fields.

00:10:56: let's just shorten the form but that might not be real answer.

00:11:02: So, we turned to qualitative data and we started looking at session recordings.

00:11:08: And it turned out that the form started with a field where they requested a company phone number.

00:11:17: And we saw users are starting typing in numbers and then they deleting the characters and then they stopped.

00:11:31: And we thought that probably some of the users were like using their smartphones on the way to work, while they commute or they were just really at the beginning of that buyer journey and they didn't want a salesperson to immediately call them.

00:11:50: So what we advised is to change this first field into from the phone number into a company email address or just a simple e-mail address.

00:12:03: And we can leave the phone number there but as an optional field and we could see real improvement in conversion rate when we did this because it was more comfortable for the users to provide the email address and

00:12:18: they will answer the email whenever it's comfortable for them.

00:12:23: But if we would have shortened the form first, probably we would've removed valuable qualifying data which would be valuable and really crucial for the sales team.

00:12:40: so instead of this we fixed an emotional friction and that led to improving conversion rate.

00:12:47: So that's why it is very, very relevant to actually look at dashboards and also the reason behind why people might not like give you the contact details or why they might not convert in one way or the other.

00:13:01: So I think you hopefully most of those things were already kind of a big inspiration for our viewers or listeners.

00:13:08: so i'm not sure if your watching us on YouTube or listening on Spotify but for those people who are now listening to us talking here If you could give them like one advice or one thing that they could test out this week if they want to make improvements and find a little bit out more about the reasoning behind the things that might not work out so well, what could be that one thing?

00:13:32: I would

00:13:35: suggest you to pick your biggest bottleneck.

00:13:39: So whether it's one of your pages on your website or a step during the purchase process or during the form fill-out process.

00:13:52: Pick just one and check out the data in your analytics tool, whatever you are using but don't do anything on the website yet.

00:14:06: Sign up for a screen recording tool –one of free versions– just to test it out. Implement it on your site.

00:14:15: Give it some time to collect some data from your users and then watch, let's say twenty or thirty recordings of your users.

00:14:27: I'm sure you're gonna find something valuable.

00:14:31: Either identify a pattern or you know just find out something which you haven't thought off and that could give you one testable hypothesis that you can either really test with an A-B testing solution or just try and change it on the website if you are not up to A/B testing yet.

00:14:57: So really, just watch your users struggle

00:15:01: on your website that could be surprising but with fruitful thoughts at the end.

00:15:06: Perfect!

00:15:07: So thank you so much for sharing your insights when it comes to kind of finding out what's the why behind the data that we're seeing in our dashboards.

00:15:17: Thank you Nora for having me, thank you for listening and if do have questions for Nora or us that we could answer in our podcast I think Nora is gonna be back for another episode at least and then probably for some more in the future.

00:15:32: just send us an email to podcast@adstrive.com.

00:15:35: And thanks for listening!

00:15:37: That was the PPC Insights, the AdStrive Podcast and on the theme of performance marketing.