Episode #7 | The Art of Marketing Analytics: A Deep Dive

1. Marketing Analytics as a Strategic Tool: Marketing analytics is the process of collecting, preparing, and analyzing data to make more informed marketing decisions. It helps identify what’s working, what isn’t, and provides insights to improve strategies for better results.

2. Three Key Time Periods for Analysis: Past, Present, and Future: Marketers analyze data from three different time perspectives: the past (analyzing completed campaigns), the present (monitoring current campaigns and results), and the future (predicting outcomes and planning future steps).

3. Key Metrics to Track: Important metrics include Customer Acquisition Cost (CAC), Customer Lifetime Value (LTV), and Return on Investment (ROI). These metrics help determine the effectiveness of campaigns and make informed financial decisions.

4. The Importance of Predictive Analytics: Predictive analytics allows businesses to forecast future results based on past data. This enables companies to not only react to changes but also stay ahead by making proactive marketing decisions.

5. Automation and Process Optimization: Using tools to automate data collection, preparation, and reporting saves time and effort, allowing marketers to focus on decision-making and optimizing strategies based on trustworthy data.

Vadym:
Hey everyone! Welcome back to The Data Crunch Podcast! I’m Vadym, Growth Marketing Manager here at OWOX, and today we’re diving into a topic that every marketer’s thinking about: marketing analytics. 

It’s a huge opportunity to unlock better strategies and results. And to help us unpack it all, I’ve got Ievgen, our Head of Marketing, with me. Hey, Ievgen, ready to break down the world of marketing analytics?

Ievgen:
Hey Vadym! Absolutely. Marketing analytics might sound complex, but it’s really just about using data to make smarter decisions that drive better results. 

More customers, more revenue, lower ad spend, better website conversions, higher lifetime value, you name it.

So the idea is to go through this today, the key parts of marketing analytics it so that anyone listening can start to see the benefits of bringing data into their day-to-day decision-making process around marketing.

Vadym:
Alright, let’s start with the basics.
What is marketing analytics exactly? I know it’s more than just tracking data, right?

Ievgen:
You’ve got it! Marketing analytics is all about the whole process: planning what to measure, collecting the data, preparing it for analysis, then visualizing and analyzing, but then delivering that to the right stakeholders and interpreting data to understand how well your marketing efforts are working, are paying off. 

It’s all about having a map that shows you what’s working, what isn’t, and where you could improve. And actually where you couldn’t, or you don’t have to focus on.
And it typically involves looking at two core areas: the present and the past,
But the potential next step is to look at the future. Making predictions, building plans, etc.

Vadym:
Interesting—so you’re looking at everything from the past to what’s going on right now and then to what’s coming up. Can you break down each of those a bit more? Let’s start with the present first. 

Ievgen:
Sure! For the present, you’re tracking things in real-time or close to real-time, we had a great episode on data freshness - you can watch it on our channel or at the platform you’re listening to us right now.
So for example your paid ads: facebook, google, LinkedIn, criteo - whatever advertising platform you use, you need to have your data handy.
Then website traffic like Google Analytics or OWOX BI Streaming. That’s both for your traffic details and online conversions,
You might add some sales from the CRM in here as well,
and then maybe you’re tracking social media engagements. You want a clear view of how your current marketing campaigns are performing.
What brings you sales, views, and engagements, you need to be focused on the right metrics.

Vadym:
Great! Now that we know about the present… let ‘s talk about the past.

Then, there’s the past. This is where you look back at completed campaigns, sales, your collected data to see metrics like customer lifetime value, acquisition cost, conversion rates, and retention. 

You might build cohort reports, and run RFM analysis - this stands for Recency, Frequency, and Monetary Value - that’s all about how your customers are buying your stuff. What are the buying behaviors?
What worked well? What didn’t? It’s about learning from past results to build a better future for your customers, but also to earn more money… right?

Vadym:
Oh yes, for sure! So, what’s up with the future?

And finally, we have to predict the future.
As good as we can.  So here we’re using data and analytics techniques to forecast future performance. It’s all about using what you’ve learned from the past to get a jump on your next moves.

Vadym:
It’s like having a full timeline of your marketing. So, how does a business get started with marketing analytics?
Where does all this data come from?

Ievgen:
Good question! It all starts with the plan. Every analysis starts with the plan.
I typically divide this Planning stage into 3 core steps: defining clear business goals, asking the right questions, and then defining the metrics to measure in order to answer those questions.

Talk about the Plan

Vadym:
So we always start with the plan. It’s a great approach. As Benjamin Franklin once said, “If you’re failing to plan, you’re planning to fail.” 

All right, so what’s next?

Next comes data collection. This means pulling in data from every platform you need to measure the metrics from the Plan. For marketing data that’s typically advertising platforms, website analytics, CMS systems, maybe social media, email tools, and CRM systems to get the details about the orders or offline conversions. Like if you are in B2B for example, most sales are happening outside of the website, right? But you need that data to be available for analysis. So If you’re touching it in marketing, it should be connected to your analytics.

I just want to note here once again the user behavior tracking.
Website analytics. You want to see exactly how users are engaging with your site—like which pages they’re visiting, what they’re clicking on, and how far they’re going into your funnel. And it’s very important here to trust your data. Because of the privacy restrictions, and cookie expiration time, it’s very important to set it all right and get as much data as possible. I think we’ve started this podcast season from the Episode on the Post-Cookie world, so if that’s what you guys are really affected by, I encourage you to listen to that episode. 

Vadym:
So, it’s not just collecting random data; it’s about collecting relevant data from the platforms, plus seeing how users actually move through your site and engage with everything, right?

Ievgen:
Exactly. And once you have that data, you move into data preparation. Sometimes also called transformation. Because when you just collect your data from different sources - their nature is different. They are all disconnected.

So this stage is about getting all of that raw data cleaned up, organized, connected, and ready for analysis. You’re making sure it’s consistent and structured, it’s linked one to another, so when you dive in, it’s easy to understand and act on. We like to call this process - data modeling. When you create those building blocks, so at the end of the day - you build any report like a LEGO set. 

Vadym:
Got it. And once the data’s all modeled or transformed, what’s the next step?

Ievgen:
That’s when you move into actually reporting, visualization, and decision-making. It depends on who is preparing a report. But basically this is where you make the data digestible for yourself or stakeholders.
You want clear, visual reports that help you and your team or stakeholders quickly understand what’s happening now and what to do to improve.
Charts, dashboards, and anything that makes the data easy to interpret and act on.

Vadym:
Could you please let everyone know briefly how you iterate with data to get something tangible?

So I like using spreadsheets for this task. I don’t use classic BI dashboards, because I can’t play with data over there quickly.
So I collect the data into the warehouse, get it quickly prepared, and then bring what I need into Google Sheets.
And build pivots, pivots and more pivots.
Then I typically decide to slice and dice some data into cohorts or just to look from different angles.
And finally, when I get the sense of something I’ll need to use again and again, or if I need to share that with my boss - I visualize the data with charts, and we’re ready to go. 

Vadym:
Nice. So, what should we actually be looking at?

What are the main metrics in marketing analytics?

Ievgen:
Great question. It often boils down to three big ones for most businesses: Customer Acquisition Cost (CAC), Customer Lifetime Value (LTV), and Return on Investment (ROI).
CAC tells us how much it costs to acquire a new customer.
LTV - shows the total revenue you get from a customer over their whole relationship with you.
And ROI is, of course, how much you’re getting back for what you’re spending.

Vadym:
I see… So those are kind of like the big three metrics that every marketer should keep an eye on. I imagine these give you a good sense of whether you’re making smart investments.

Ievgen:
Absolutely. They’re essential for knowing if your marketing is actually profitable and sustainable.

Vadym:
Alright, let’s talk insights. Once you’ve got all this data, what’s the real value? How can businesses use it to their advantage?

Ievgen:
The insights you get from data analytics are game-changing. You’re not just looking at numbers; you’re learning about your customers—their behaviors, preferences, demographics, products they buy, pages they visit, and what they engage with. All of this lets you tailor your marketing strategies or make some adjustments to really hit the mark with your audience. 

Marketing is always about placing the right message in front of the right person, at the right time, in the right place. That was always like that. 

No matter, whether we’re in the digital age or selling, I don’t know, wine in Ancient Greece. Message, Placement, Audience, and Time.

Vadym:
Sounds pretty powerful. And I bet this also helps with optimization, right?

Ievgen:
Exactly. Once you know what’s working and what isn’t, you can start optimizing. Maybe you shift the budget from one channel to another or refine a campaign to target a specific audience. It’s all about making smarter decisions to get the most out of your marketing.

Vadym:
And how does marketing attribution fit into all this? 

I know it’s a big topic in analytics. How do we make sense of it?

Ievgen:
It definitely is. Marketing attribution is about understanding which of your touchpoints led to a conversion. So, if someone interacts with a Google ad, a Facebook ad, and an email before making a purchase, attribution models help you assign credit to each of those steps based on your business model. 

That’s what Google Analytics doesn’t allow you to do, really customize as you should. That’s why you need your data handy to play with that and model as your business deserves.
This way, you know which channels are really driving conversions and which might need tweaking or switching off - which are not paying off for the overall journey (because sometimes you need to overspend to fill in the Top of the Funnel so then you can convert them later on)

Vadym:
Alright, I can see how that’d be really useful.
And what about predictive analytics? How does that come into play?

Ievgen:
Predictive analytics is huge because it helps you forecast.
You’re using historical data to predict things like upcoming revenue.
It’s super helpful for making proactive marketing decisions, so you’re not just reacting to changes, but actually staying a step ahead.

But one thing stands here - is the quality of your data.
If for any reason you don’t trust your data 100%, or if you have the missing pieces, there’s no way you’ll trust the predictions and make decisions around it.
So get to the predictive analytics ONLY after you have the other pieces in place. 

Vadym:
Awesome stuff, Ievgen. Now, you mentioned that marketing analytics can save a lot of time. Can you give an example of how?

Ievgen:
Sure! One big way is by automating entire reporting.
Because let’s face it - we all do some kind of analytics.
Even if that’s just inside each of the ads platforms,
Or looking at Google Analytics standard reports.

Instead of looking at the data in different corners, maybe manually gathering and cleaning data, it’s always better to use analytics tools to do it all for you on a schedule, so you can focus on making decisions based on the data you trust, coming up with the right and smart strategy and creativity. That’s where AI would never replace us - marketers.
So It’s a huge time saver actually.

Vadym:
So, less time spent on tedious work, and more time spent on the fun stuff. 

I like it. Now, the big question—why is marketing analytics essential for brands today?

Ievgen:
Well, in today’s market, you have to be data-driven to stay competitive. Data analytics helps you make the right decisions, optimize budgets, create targeted strategies, and even spot issues early on before they become big problems. It’s the key to making your marketing more effective and, ultimately, driving growth.

Vadym:
Makes total sense. Before we wrap up, what would you say are the main takeaways for anyone looking to get started with marketing analytics?

Ievgen:
I’d say focus on three things: first, get clear on what metrics matter most for your business.
Second, make sure you have the data to measure those metrics
And third, don’t just look at the data—use it to make more data-informed decisions. Data never lie. Analytics should be an active part of your strategy, not just something you check once in a while.

Vadym:
Great advice! Thanks for breaking it down, Ievgen. 

And to everyone listening, if you want to dive deeper, check out our resources on marketing analytics at owox DOT com. And don’t forget to subscribe to this channel for more insights on leveraging data for growth.

Ievgen:
Thanks, Vadym! And thanks, everyone, for tuning in. Remember, data is there to help you win—just make sure you’re putting it to work. Catch you in the next episode!