Big Data Advertising Analytics The Smart Way

“We’re surrounded by data but starved for insights.”- Jay Baer

In 2022, the amount of data we produce every single day is mind-boggling. According to estimations and reports, over 2.5 quintillion bytes of data is generated each day. And with an ever-increasing reliance on the internet, this number will reportedly skyrocket in the next few years.

These days, companies generate large chunks of customer, market research, website, competitive intelligence, transactional and other forms of data. Despite that, most face a hard time processing all of it and gaining true insights to fuel and optimize their marketing campaigns.

Only by focusing on filtered and relevant data sets can companies efficiently fine-tune their marketing strategies and optimize their campaigns for the best possible results.

Want to get a 360-degree view of your audience? Looking forward to understanding what sources you’re driving the most traffic from and whether your marketing strategies are delivering the desired results or not?

With Google Analytics, you can dive deep into your website traffic and gain insights into your target audience, acquisition channels, audience behavior, and more. However, when it comes to finding patterns and diving deep into your data, Google Analytics is not the right fit.

For example, if you want to understand how many people visited a certain page of your website using a specific device and completed one of the goals set by you, then filtering it via Google Analytics will take you forever. And that’s where Gigasheet comes in.

In addition to this, you may want to understand how well your advertising campaigns performed during a set period. Whether you want to understand how much you spent on a particular age group or whether a particular age group who clicked on your ads purchased your product or not, you can use Gigasheet to get down to the brass tacks.

To help you better understand how Gigasheet can help you filter data fetched from Google Analytics or your advertising data, we’ve put together this blog post, where we’ll be sharing a few examples of how we used Gigasheet filters to segment data.

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Navigating the Realm of Google Analytics

From Google Analytics User Explorer, you can fetch Client ID along with their sessions, average session duration, bounce rate, revenue, transactions, and goal conversion rate. So, we fetched data generated between August 21st, 2021, and August 24th, 2022. We exported this data in the .xlsx format and uploaded it to Gigasheet – took less than five seconds to process it upon upload. Now, here’s what the data looks like:

Fun Fact: Google Analytics limits downloads to 5,000 rows, but with Gigasheet Enterprise connectors, you can directly download all data from Google Analytics.

Now, let’s say we want to get our hands on the list of users who visited our website more than 100 times throughout the set duration. So, what we did was – clicked on “Filter” in Gigasheet.  From here, you can create and save your own filters.

We set our filter as:

As soon as we clicked on “Apply,” we instantly got our hands on Client IDs with Session Duration greater than 100.

Let’s narrow things down even further by adding another filter to the already-filtered data to understand how many users with >100 sessions have a 100+ seconds average session duration.  Click on “Filters” again to add another filter.

We can even add an “AND” or “OR” condition.

But here – since we want to find out client IDs with >100 sessions and 100+ seconds average session duration, we’ll set the “AND” condition. We set our second filter as:

And here are the results:

It's as simple as that! You can add multiple conditions to dive deep into the data.

Now, let’s play around a little. Let’s remove the 100+ seconds average session duration filter and set our filter as:

We want to understand how many clients with more than 100 sessions had a goal conversion rate of more than 20%.

And here we go:

Similarly, you can get your hands on your top website visitors and customers.  

In addition, you can save your filters for future use. From within Gigasheet, you can add or remove columns – depending on your needs. Also, you can:

• Split or Combine Columns
• Change Data Type
• Add Formulas
• Explode Dates into their components (Day, Month, Year, etc.)

And do so much more!

Navigating Google Analytics is a great way to understand the behavior of visitors on your website. By discovering your top visitors with a high conversion rate, you can gain insights into their customer journey. By studying their customer journey, you’ll understand what elements of your marketing funnel are working and what aren’t - helping you further optimize your funnel for an increased conversion rate.

Diving Deep into Google Ads Data

For this section, we are going to use a sample data set containing advertising campaigns run by a SaaS company. We have the performance data of advertising campaigns between 16th December 2019 and 07th July 2020.

• Number of Rows – 16,385
• Number of Columns – 16

Here’s what the dataset looks like (sharing two images as the number of columns is 16):

We wanted to understand – which dates we spent more than $200 per day, so we set the filter as:

And we got our hands on the filtered data in no time.

Let’s add one more filter. Let’s set the clicks as “<3.” If you’re spending more than $200 for less than three clicks, then you have an extremely high Cost-Per-Click.

So here’s our filter:

Here are the results:

Now, let’s remove the filters and understand the average advertising costs you’re spending per group. To do that, we’ll group by column “Age.”

Here are the results:

Keep scrolling to the right to find “Spends.” Click on the drop-down menu and select “Average.” You’ll find the average amount you spent per age group.

To find the total amount, click on “Sum.”

You can find the average spend, average impressions and average clicks and average link clicks to understand what age groups are reacting well to your ads.

If you’re spending $200+ each day advertising to Age Group 25-34 yet the average clicks is really low, then something’s wrong with the campaign targeting that particular age group. Maybe, it’s not the right audience. Or maybe something’s wrong with the creatives. Using this data, you can find out that there’s a problem or understand how well your ad campaigns are performing.

We grouped the data by column “Device” and looked at the average spend, impressions, clicks, and link clicks.

And here are the results:

Tap into the Power of Data-Driven Marketing with Gigasheet

Whether you want to understand which of your email campaigns had a 50% open rate or which leads you’ve already nurtured, you can use Gigasheet’s advanced filters, arithmetic functionalities, and groups to get your hands on the right data.

And the best part?

There’s no administrative setup or configuration required. Also, you don’t need to have coding experience to use Gigasheet. If you can use a spreadsheet, you can use Gigasheet.

Sign up for free today!

Author Bio: Ankit Vora is a results-driven freelance content marketer with over seven years of experience in the MarTech space. When he’s away from work, he likes to head over to the beach, spend time with his loved ones and cook.

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