- How marketers can think like analysts
- How you can improve your analytical thinking and skills
- How to get started with analytics
- Top resources for learning more about marketing analytics
Hey everyone and welcome to the Marketing Analytics show. Today you have Khrystyna Grynko, who is the Head of Data at a marketing agency called Better&Stronger. Khrystyna has more than nine years of experience in digital marketing and digital analytics under her belt. She’s a CXL course instructor and the main organizer of MeasureCamp Lyon and DataCamp Lyon.
In this episode, we’ll talk about how marketers can think like analysts, how they can improve their analytical thinking and skills, how to get started with analytics as well as what are the best approaches and resources to learn from.
All right, Khrystyna, thank you so much for joining me and welcome to the Marketing Analytics Show.
Thanks, Anna, thanks for having me.
Let’s jump to the first question. Do you think marketers should think more like analysts and if you could expand on that a little bit and tell us why or why not?
Okay, no problem.
So, I think that our audience mostly consists of digital marketers so if we talk about marketers, we talk about digital marketers. And I think that as digital marketers, we have to be analysts, it’s our obligation because we have access to a lot of data. We see it everywhere in every ad platform, in every analytics tool and we cannot create the campaigns without analyzing something. We cannot stop campaigns or invest more in some marketing campaigns without actually analyzing the previous results. So, being an analyst for a marketer, it’s quite a must, I would say.
Yeah. Awesome. And definitely sounds like marketing is becoming more analytical and more technical so I do agree with you. On that note, so say if I’m a marketer, and if I would like to improve my analytic and analytical thinking and analytic skills, what advice would you give me first?
Now there are plenty of different online courses on analytics. I would suggest some videos of MeasureSchool and CXL courses as well. They have mini degrees in digital analytics and also I would suggest just go in and try to analyze all the data you have in your ad platforms or analytics platforms starting with asking questions.
So, why does this campaign perform better than others? And go deeper and deeper with every analysis like saying, “Okay, there are some advertising groups that were better, there are some keywords that were better, let’s analyze it from different points. Is there something that’s happening on the market? Should we analyze our competitor? Is there something that’s happening in our campaigns? Did we manage to get the keywords that work better? Is there something happening on our website and the campaign will work better because we improved our website?” Try to ask yourself a lot of questions about why it worked and why it didn’t work. Because we usually try to analyze when there’s a problem but sometimes you should analyze when everything’s fine as well.
Yeah, definitely. And you mentioned that marketers should start from their website and from their campaigns analyzing the data there. Could you maybe tell us more about the frameworks which could be helpful for people to start with? Because it sounds super easy when you say it but you’re a super awesome professional so I think our listeners would love to learn more.
For example, there could be this five whys framework or some other frameworks. Was there anything helpful for you personally?
I would say that when you start analyzing, you should choose the most important KPIs for the business. Like for example, the most important KPI is the number of products sold and the revenue that you’ve got. And then, you will need to choose the supportive KPIs like the KPIs that impact directly your most important KPIs, your North Star metrics that you go with. And the supportive KPIs could be like the number of sessions.
So, maybe you’ve got less revenue because you’ve got less sessions on your website. If we talk about the ecommerce website, for example. You can then analyze, for example, their click-through rate that can impact the number of sessions that you’ve got.
For example, “Why do we have less sessions, knowing that our main source of traffic is advertising? What’s happening in our advertising? Let’s analyze our click-through rate. Do we have a problem with click-through rate? Are there less people who click on our ads compared to the people who saw our ads? Maybe we should optimize there?” Then for example, if we’ve got less revenue this month, we can analyze the average basket as well because it directly impacts the revenue you’ve got. You can have the same number of purchases but if people buy the products that are cheaper this month so you’ve got the revenue that decreased.
So I would say for me, the framework is really simple. It’s something that we talk a lot about at every conference. You start with business objectives.
Our goal is to increase our revenue this year by 20%, for example. So, every month or every week we analyze, do we increase our revenue, compared to previous period or to previous year? So, if there’s a problem, let’s try to analyze the supportive KPsI that directly impact the revenue that you’ve got.
So, maybe there’s a problem with conversion rate, your website doesn’t work well and doesn’t convert. Is there a problem with traffic quantity? You don’t have enough people who come to your website in order to have enough revenue and purchases. The problem was the average basket, they buy for less money.
So, the main goal is to choose the most important KPI and to choose several but not too much, like four, I would say four maximum of supportive KPI that can impact directly. It can show you if you should continue analyzing or it is okay. If everything’s okay with supportive KPIs, maybe they are not well-chosen because you don’t have an answer right away.
All right. Awesome. And that does sound like a very simple and yet effective framework. Now, speaking a bit about the process. So, are there any pitfalls in analytical thinking you would say marketers must avoid and if yes, then how can they avoid them?
Oh yeah. There are some.
For example, when you take a decision too quickly, like you say, “Oh, this campaign worked better this month, so let’s invest in this campaign.” And if you take this decision too quickly and don’t analyze what exactly went better, maybe when you invest more in this campaign, you will have a huge problem next month when you start another campaign.
For example, just the simple question of attribution. If you have two campaigns, one grand traffic, and one unknown grand traffic, generic. And if you see it, “Well, grand traffic, it works better.” Yeah, obviously. But if you say, “Hey, why don’t we just buy our grand traffic and that’s it. We can get enough money.” But you will realize soon that when you start another campaign, which supports it really the second one, you will realize that it was a mistake. So, I would suggest that you don’t take a decision too quickly.
Don’t always trust your gut. Sometimes we say, “Well yeah, maybe it’s because of this reason.” Because we think that everybody thinks as we do, which is a huge mistake. Like I would book a hotel on my mobile phone, whereas a lot of people would book it on their desktop device.
When you take a decision too quickly, it’s really subjective, it’s not really data-driven. So I would suggest that you always try to ask more questions and to just go deeper into the data, like we talked about five whys. So maybe you need to ask these five whys before you take a huge decision that can impact your marketing and your business.
And also, I would suggest for marketers to have some basic statistical knowledge. There are plenty of articles out there, statistics basics for marketers or for analysts.
I would suggest that you read it just to understand some basic principles of statistics and analysis. And when you shouldn’t really trust some numbers and results.
For example, when you have like two conversions for one campaign and a 50% conversion rate for one campaign and 5% conversion rates for another campaign, you say, “Well, obviously the first campaign was better.” Okay. But the question is, are your results as statistically significant? If you have two clicks on one campaign and three clicks on another, I don’t think that you should change your decision right away. So be careful. Don’t take decisions too quickly. Just try sometimes to go deeper in on analysis and learn some basic statistics. It’s easy. There are plenty of articles out there in order to improve your analysis.
All right. Thank you so much. This sounds like very good solid advice. And now speaking about all the processes and campaign analytics, suggestions you just made. Could you please tell us more maybe about some specific examples of companies you’ve seen doing it well? Companies or campaigns you’ve seen run successfully using all these frameworks.
I actually did a presentation recently. I’ll present in MeasureSummit on this subject. It’s “When do you stop analyzing and start taking action?” And there’s some framework that we’ve decided to maintain for our clients is that we start all our reports and analysis. The first page was the main KPIs. Then we go to supportive KPIs and then it’s kind of like a tree. Like one KPI shows you, “Where do you need to go in order to understand the problem?”
So it makes the analysis easier in terms of time that you spend on this analysis because with some supportive KPIs, you understand, “Okay, I have a problem with conversion rates.” So probably the problem is on my website. I should check my website. I should go directly to my website and try to make a purchase in order to see if it’s simple for people or not, or maybe ask someone who doesn’t know my website to try to purchase something.
And I will go and see my competitors. Do they do better?
For example, when I followed up with clients, we saw that our conversion rate decreased. We started analyzing our website and we realized that we had a lot of people quit our website after the payment page. Then we went to check our competitor and we realized that our competitor had like five payment options, whereas we had two. So the problem is a no brainer. It’s easy. Of course, they will choose someone who proposes more payment options. It’s easier for someone to pay with PayPal than us who just take a Visa card and that’s it.
So this example for me is just every monthly report, we start with this main KPI. Then we go to supportive KPIs and then it’s all automatic for us. And then if needed, we go deeper on one of the KPIs by analyzing competitors or analyzing the website behavior, or analyzing our campaigns.
It’s rare that we have problems with every advertising on our website and these competitors, or there’s a really big problem that we didn’t see coming. But usually, we stop there. We just have one or two supportive KPIs that explain clearly where we need to go further in analysis to see the problem and solve this problem right away.
Also, the point that I want to explain is that yeah, analysis is great, but you need to take actions regularly in order to be a performer.
All right. Awesome. And yeah, I definitely do agree with you that marketers should tie analytics to their business goals, to their business actions. And also competitor analysis does definitely help bring more data into the fixture to make it a 360-degree overview. Now, if marketers would like to learn more about analytics, statistics, or how to think like an analyst, where would you recommend them to go to, what are the best resources to learn from?
I can’t remember the name of the author of the book, but it’s called Marketing Analytics. It was great, I just can’t remember the name of the author.
There are some books by Gary Angel that are great. I would suggest also just to go and find some basic statistics for marketers or for analysts. There are really plenty of good articles on this subject.
As I said previously, I liked CXL courses’ mini degrees in digital analytics, and also Supermetrics does a lot of great webinars for marketers and analysts. I would suggest you follow with Supermetrics blogs and webinars and yeah, go and follow some digital analyst professionals.
Usually, I would say there are frequent types of digital analysts. Some of them come from marketing like me, for example, and some of them come from more technical backgrounds from developers, for example. So I would suggest following on Twitter or on LinkedIn at some of them to be aware of the different best practices on the subject.
Are there any good names? Are there any good professionals you could recommend follow on Twitter or LinkedIn?
Yes, of course. I would suggest Chris Deciden, for example, Simo Ahava, of course, and actually, he did a great article on the subject of being a non-technical marketer, which he thinks is not possible nowadays. We all are technical marketers and surely there are plenty of them.
I can’t even list all, but there are lists on Twitter that you can follow or like web analytics professionals that are lists that are pre-created for you, that you can follow and they’re all professionals that you need to follow.
All right. Awesome. Yeah, these are super good recommendations. And once again, thank you so much for joining me today, Khrystyna.
Thank you very much, Anna. It was a pleasure to talk to you.
And that’s the end of today’s episode. Thanks for tuning in before you go, make sure to hit the subscribe button and leave us a review or rating on Apple Podcast, Spotify, or wherever you’re listening. If you’d like to kickstart your marketing analytics, check out the 14-day free trial at supermetrics.com.
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