The Basics of Attribution and Analytics (using Excel) Marketers should be familiar with

Photo by Isaac Smith on Unsplash

I’m almost at the end of the Growth Marketing Minidegree program with CXL Institute. It’s been 10 weeks already. This means I have 2 more weeks to round off.

There’s been so much to learn and unlearn in marketing and growth. My summaries on this blog are probably only just a scratch on the surface.

This week, I focused my learning on the Data Analytics Stack of the program covering Attribution, Microsoft Excel, Google Analytics, and Google Tag Manager. Most of what I shared below are focused on the first two courses — Attribution and Microsoft Excel.

Let’s jump right in.

What really is Attribution?

Attribution is about understanding your customer, and trying to understand which activity or step in the funnel is most influential to them.

Attribution is an evergreen topic. We can go on long conversation streaks on it. I’ve been a part of several conversations on various fora and social media platforms.

One thing is clear: since there’s no one size fits all solution, every company has to figure out what uniquely works for them.

Let’s use an example to try to bring this home:

Imagine someone, say Joe, in your target audience searches “Microsoft Excel training in Nigeria” to Google and finds your ad.

If Joe clicks on your ad, visits your website, and proceeds to make a payment for your next training course, how would you attribute that conversion?

To your ad and the last click that drove the visit? Or to any of the 10–40 touchpoints that happened before they saw your ad?

If you use any standard analytics software, you would probably attribute that purchase to your ad, because it was the last trackable interaction (last-click attribution) your new customer had with your brand before making that purchase.

For you, as a marketer, you see your customers going through a customer journey. But no man actually really sees himself as going through stages of a customer journey.

It’s just not a very natural way of evaluating yourself when you want to buy.

Nobody ever thinks “Oh look at that ad, I’m now aware of a new brand. This gets me into phase 2 out of 5! Let’s see if these guys have any great reviews so I can move into the evaluation stage as soon as possible.”

Instead, your audience might see your ad 4–5 times without even noticing it.

Then they hear one of their friends talking about this great new training company they bought a course from.

Suddenly, they start seeing ads from your brand all over the place, because they’re now aware that your brand exists.

The next time they search for something on Google, they might see a blog post from you.

And 4weeks after that…

After seeing an influencer talk about your brand, seeing 10+ display ads, and an interview with your founder… they might proceed to make a purchase.

It could be as many as 6–8 “touchpoints” with your brand before someone is even aware of your existence.

But still, most marketers track “awareness” from the first time someone sees their ad.

This just goes to show that there is no mathematical equation that can be applied to any and all businesses to work out their attribution model.

There are a lot of non-trackable interactions offline, where you have no control over what’s being said.

So what should you do instead?

Understand the value of your conversion

There are two types of conversions:

1. Macro conversions — sales, leads, demo requests, signups, etc.
2. Micro conversions — add to cart, starting a signup process, downloading an ebook, etc

For B2C this is pretty straightforward. You basically have a direct relationship with the consumer throughout the journey and every trackable touchpoint.

For B2B it’s different because there is a lot of activity going on behind closed doors. Multiple individuals across and outside the organization will probably be involved in any consideration process.

What’s important to understand is that you need to complement your digital analytics and trackable touchpoints with some good old-fashioned customer research.

Customer research is just briefly touched upon in this course when the instructor mentions ROPO (Research Online, Purchase Offline), but it would probably make sense to dive a little deeper into that. Because if you think about it:

You need to ask your customers how they make their purchasing decisions and tie that back to your trackable touchpoints.

It’s not enough just using a specific coupon code for your print ads, or a special phone number for your direct mail ads — unless you know what actually influences your customers, when and why, you have no way of knowing how to do attribution correctly.

The two most important takeaways I got from this course was:

1. You need to be able to collect the required data to do attribution correctly
2. You need to have the people, skills, and cross-team alignment necessary to find an attribution model that works for your business

Microsoft Excel for marketers

This course was more of a refresher considering that I’ve been part of a few live courses on Microsoft Excel in the past. It was fun and I love that it was tailored to marketing analytics.

In this day and age, you really can’t call yourself a marketer unless you know how to use a spreadsheet and/or specific tools to analyze and extract value from a dataset.

Almost every tool out there — from Google Search Console to Google Keyword Planner, Mailchimp, Triggerbee, Hubspot, or any other software that contains lists of information (i.e. Contact lists, keyword lists) can be exported as a CSV and then imported to excel.

Yes, these tools will provide you with the raw data. The rest is up to you. it’s up to you to find the value in those datasets.

And to do that, you need to know how to use excel.

This course used a dataset from Google Search Console to show you a bunch of different ways you can manipulate the data.

Some key things every marketer should learn:

1. How to use functions such as SUM, COUNT(IF/A), and VLOOKUP. These can make you stand out.
2. Creating and using pivot tables with filters or calculated columns. This can make your life a lot easier.
3. Creating automated dashboards in excel for a high-level view of your performance
4. Using slicer and timelines to add an additional layer of slicing and dicing

You may want to check Leonine Learning for some live courses on using Microsoft Excel for data analytics. Don’t say I didn’t do anything for you. Ciao!