Season 2: Episode #9 | A Quick Guide to Data Analytics Implementation

🚀 Want to implement data analytics the right way? In this episode, Vadym and Ievgen break down the six critical steps for setting up an effective data analytics system that delivers accurate insights, seamless reporting, and smarter business decisions.

🔍 What you’ll learn in this episode:
1️⃣ The biggest mistakes businesses make when setting up analytics—and how to avoid them.
2️⃣ How to ensure data accuracy, integration, and automation for reliable decision-making.
3️⃣ Why Google Sheets and real-time reporting are essential for modern businesses.

📈 Ready to transform your analytics setup? Learn how to structure your data for maximum impact and make data-driven decisions with confidence.

➡️ Start building a reliable analytics system with OWOX BI

Podcast listing

Vadym:
Hey everyone, welcome back to The Data Crunch Podcast! I’m Vadym, Growth Marketing Manager at OWOX, and today, we’re getting into a topic that is absolutely crucial for businesses looking to make sense of their data—Data Analytics Implementation.

Let’s be real—everyone wants to be ‘data-driven,’ but very few actually get it right. Why? Because they set up some analytics tool, check a few reports, and think that’s enough. But if your data analytics setup isn’t designed properly, you’re just looking at numbers that might be misleading.

And to break this down step by step, I’ve got Ievgen here with me.

Ievgen, how big of a deal is analytics implementation in your view?

Ievgen:
It’s everything, Vadym. Think about it this way: data is only useful if it actually helps businesses make decisions. But what happens when it’s incomplete, inaccurate, or just a mess? Bad data means bad decisions, wrong decisions.

I’ve seen companies where they thought their marketing was performing well based on their reports, only to realize later that their tracking was broken. Imagine making strategic decisions based on incorrect data.
That’s a disaster waiting to happen.
So today, we’re going through 6 critical steps that businesses need to follow to make sure their analytics is rock solid.

Vadym:
Alright, before we dive into those six critical steps, I want to remind everyone—if you're tuning in on YouTube, do hit that subscribe button and drop a comment below. Your feedback not only helps us improve, but it also motivates us to bring you the most actionable insights every week. 

For those listening on other platforms, be sure to subscribe and get notified of new episodes every Thursday. Your engagement is crucial as it helps us reach more listeners who could benefit from mastering data analytics just like you.

Now, Ievgen, what's the first critical step businesses need to take to ensure their analytics setup is effective?

Ievgen:

First things first – you don’t start with a tool; you start with a clear understanding of your goals.
Because if you don’t know what success looks like, how do you measure it? Businesses need to be crystal clear on:

• What they want to achieve (like increasing conversions or reducing churn).
• How they’ll measure success (which KPIs matter).

For example, an e-commerce company might track average order value, repeat purchase rate, and cart abandonment.
A SaaS business would look at churn rate, MRR, and feature adoption.
But here’s the mistake people make—they track vanity metrics like website visits or social media likes. Those don’t help you make decisions.

Vadym:
Okay, so we’ve got the goals and KPIs. What next? 

Ievgen:‍

A lot of companies collect tons of data, but it’s messy, fragmented, or just unreliable. Businesses need to ask: is our data even in a good state?
So, before anything else, businesses should audit:

• Data completeness – Are all key interactions being captured? Like, do you have at least the foundation for going forward? 
• Data accuracy – Are there inconsistencies or missing values?
• Compliance – Like when dealing with data - Are we meeting GDPR, CCPA, or other regulations?
• And then there’s infrastructure. If you want real-time analysis, you need a system that can handle it. 

No one wants reports that take 30 minutes to load when you press the refresh button. 

Vadym:
Alright, what should be the next step?

Ievgen:
Now, we need to map out how users interact with your business.
Because every business has a different user journey. Like how does the funnel look like. You need to break down:

• What actions users take (signing up, making a purchase, using key features). If that doesn’t look like a funnel, most likely, you’re leaving money on the table. 
• Where they drop off (checkout page, onboarding, specific screen, etc.).
• Which sections matter the most?

For example, an online retailer should track product views, add-to-cart actions, and checkout completion. Meanwhile, a SaaS company needs to focus on how often users engage with core features.
If you don’t understand your own product or website structure, you won’t know what’s worth tracking. And the saddest part - if you don’t know how it works - your customers don’t know that as well.

Vadym:
We will need tools for this process, right? Is Google Analytics a good option?

Ievgen:
Not even close. The right tool depends on your specific business needs.
Yes, for real-time website tracking → yes, Google Analytics 4 is an option, or our tracker -> OWOX BI.
For deep analysis → that should be a bundle of tools, but basically, you need to start with some sort of data storage - BigQuery, Snowflake, ok - it might be Google Sheets, if you’re just starting out. It’s too early to talk about the specific tools.
Each tool has different strengths, so businesses need to choose what aligns with their goals.

Vadym:
Once the tools are chosen, it’s probably time to actually define what to track.

Ievgen:
Yeah, and this is where a lot of businesses go wrong. They just start tracking everything without thinking.

A tracking plan should document:
- What will be tracked
- Why does that matter
- Where those things are triggered

This blueprint ensures everything is aligned with business goals.

Vadym:
Alright, so we’ve got our website tracking in place because that’s where everything starts, and we’re collecting data somewhere. But here’s the thing – most companies don’t just use one tool. They have CRMs, ad platforms, customer service tools, and sometimes even offline data. How do we bring all of this together?

Ievgen:
That’s where data integration becomes crucial. I’ve mentioned data warehouses already. Because right now, your customer data is most likely scattered across different platforms. Marketing teams are looking at Google Ads and Google Analytics, sales teams are in Salesforce, and support teams are in Zendesk. But if these systems don’t talk to each other, you’re missing the full picture.

Vadym:
Yeah, it’s like each department is operating with half the story.

Ievgen:
Exactly. To truly utilize and activate your data, you need to merge these data sources into a central location, like a data warehouse (BigQuery, Snowflake, or Redshift).
That way, instead of working with siloed insights, you get a 360-degree view of your customers. Of the whole business performance.

You can answer questions like:
1. Which marketing channels bring in the most high-value customers?
2. How do customer interactions with support affect retention?
3. What’s the full customer journey from the first ad click to the final purchase?
And the best part? Once your data is unified, you can start automating insights instead of manually pulling reports from different tools and updating them, so to say, manually again.

Vadym:
Okay, so let’s say we’ve got all this data in one place. But there’s another issue, data is messy. What happens if customer names are spelled differently in different systems? Or if some transactions are missing key details?

Ievgen:
That’s a massive problem because, as we already discussed, bad data = bad insights. If you don’t clean your data first, your reports will be unreliable.

The cleaning process involves a few key steps:
1. Removing duplicates – If the same customer appears in multiple databases, you need to merge their records.
2. Standardizing formats – Dates, phone numbers, currency values—these need to be uniform across all data sources.
3. Handling missing values – If your sales data is missing 20% of transactions, that’s a huge blind spot.
Let’s be real - no one wants to tell the CEO their revenue report was off because of a data glitch.

Vadym:
Alright, so now that we’ve got clean, unified data, it’s time to actually do something with it.

Ievgen:
Right. You need a report or a dashboard that tells a story with the raw data.

• Executives need high-level summaries—like revenue trends, customer growth, and overall business performance.
• Marketing teams need channel breakdowns—which ads are driving sales, what content is working, and where conversions are happening.
• Sales teams need pipeline tracking—which leads are hot, where deals are getting stuck, and what outreach is working.

Vadym:
That makes sense. But here’s the issue—some businesses still rely on old-fashioned BI dashboards.

Ievgen:
Yeah, and that’s a huge mistake. Traditional BI dashboards in tools like Looker Studio are fine for basic performance monitoring, but they really don’t scale. 

Listen, until data is not delivered to the tool with UI that is easy to navigate by the business user and the decision-maker, data is not utilized.

So if you want your organization to really make decisions based on data, based on those long-tailed data available, and make those decisions in real time, there are basically just 2 tools for reporting: Google Sheets and Microsoft Excel.

Vadym:
Okay, but here’s the thing: to get insights, everything has to be updated regularly, right? And updating reports manually takes way too much time. How do we fix that?

Ievgen:
Automation. Instead of manually pulling data every day or every week, you should use some sort of reporting tool like OWOX, so that the report consumer sets the schedule to automate data delivery to the spreadsheets.

So yes, you basically need to do 4 things: 

• Extract data from all your sources (CRMs, ad platforms, databases) and store that in the data warehouse.
• Build a solid data model suitable for easy reporting.
• Transform the data from being raw to business-ready - to the format of the model.
• Bring your reports into a reporting tool - Google Sheets. But you can go with some BI tools as well. As everything is ready for getting a report.

We help businesses with all four of those.
From data collection using Free Connectors, then building a data model, launching that from the template in OWOX BI, then transforming data on a schedule with dependency triggers, and then reporting on all your business data in Google Sheets.

Vadym:
So basically, instead of waiting for reports, teams get live, up-to-date insights. On a schedule.

Ievgen:
Exactly. So this is where tools like OWOX BI come in handy. Because it does all the heavy lifting for businesses. Without compromising privacy because everything happens inside the business's infrastructure.

Vadym:
Alright, before we start making big decisions based on this data, how do we make sure it’s actually accurate?

Ievgen:
Testing. This step is all about making sure your analytics setup is working as expected.

Here’s what needs to be checked:

• If it starts from Google Analytics - Are all events firing correctly?
• Do we have relevant data for building reports?
• Do reports match real business numbers?
• Are there any data discrepancies between different reports?

Vadym:
And what if something looks off?

Ievgen:
Then you dig in. Maybe an integration is broken, or a tracking pixel isn’t firing. Fix it before allowing business to make decisions.

Vadym:
So now, let’s say we’ve got perfect reports, accurate tracking in place, a transformation layer, a data model, a reporting system, and everything is automated. Now what?

Ievgen:
Now, you have to make sure people actually use the data. A lot of companies invest in analytics, but then teams don’t know how to interpret it. How to answer questions with data, how to even structure those questions, how to query data to get the information allowing to make real business decisions…

Vadym:
Yeah, I’ve seen marketing teams ignore reports and dashboards because they don’t know what to look for. I see this all the time.

Ievgen:
That’s why businesses need to train employees on how to read and interpret reports. The ideal way would be to set up regular data reviews so insights are actually discussed. This ensures decisions are based on data, not just gut feeling.

Vadym:
And that brings us to the final step—keeping the system evolving.

Ievgen:
Exactly. Data processes need constant maintenance. Sometimes refinement. At least once a year, every business should:

• Review KPIs—are we tracking the right metrics?
• Update tracking setups—are new features being tracked?
• Experiment and iterate on reports.

Vadym:
Wow, that was a lot—but that’s exactly why proper analytics implementation is so important. If you don’t set it up right, you’re flying blind.

Ievgen:
Right! And the best part? Once you have a solid setup, you’ll make faster, smarter decisions that drive real business growth.

Vadym:
And that wraps up our discussion on the six critical steps for effective data analytics implementation. 

Remember, setting up your analytics the right way is not just about collecting data; it's about making that data work for you, so you make decisions that truly drive your business forward.

To help you on this journey, check out the OWOX BI platform. Start for free at owox.com. We offer a range of tools to help you gather, organize, analyze, and report your data. Whether you're looking for easy-to-use solutions or need advanced technical setups, we've got something for everyone. And if you run into any challenges, our expert support team is just a chat away to assist you.

Ievgen:
Absolutely, Vadym. And to further empower your data-driven journey, we’re excited to introduce our latest innovation – the OWOX JS Data Connectors. It’s a FREE way to collect any data into Google Sheets, making it accessible for businesses of all sizes. Check the link in the description of this video for more details and to join our community of data enthusiasts.

Vadym:
Alright, that’s a wrap! Thank you all for joining us today, whether you're listening on YouTube or your favorite podcast platform. Don’t forget to subscribe and stay tuned for more insightful episodes every Thursday. Dive deep into your data, stay informed, and above all, keep making smarter decisions.

So, thank you, Ievgen, for breaking down these steps with us, and thanks to everyone for listening. See you next time on The Data Crunch Podcast!