Chapter 20

Day 20: Take a good, hard look at what you’ve got so far

ecommerce analysis quotes

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Can you believe we’re almost done? If you’re not quite elated by your performance so far – don’t be stressed. This is all part of the process.

I had to remind Amanda of this on more than one occasion.

Another part of the process is digging into what you’ve got so far. You may have noticed that I’m big on performance and results data. I think it’s pretty self-explanatory why that’s the case.

So today, we’re going to – you guessed it – look at your data to see how you’re doing.

Of course, your store hasn’t been open too terribly long. So at this stage, I don’t think you need to be making any drastic changes. But every little tidbit of information you can get will equip you to make better decisions as time goes by.

I truly believe that all you need in order to succeed is to spend time doing the work, and let the data tell you where to go next.

Today, we’re going to:

  • Have a look at your store using the analytics tools we’ve discussed so far
  • Get an idea of the types of signs that tell you when you should change things up

Here we go.

How are your products performing?

Apart from what people are buying (if any yet), you’ll want to see what people are looking at. So let’s direct our attention to activity on your site.

Look at Shopify’s dashboard, if you haven’t looked at it in-depth yet. Click on the ‘View dashboard’ button on the top right corner of the home screen.

analyzing the performance of dropshipping products

Edit the date range to whatever you want to look at (preferably launch day to now), and scroll through the results.

As I mentioned, the results here are like a ‘lighter’ version of what Google Analytics can offer. I would say that if Google Analytics feels overwhelming, you can look at the Shopify dashboard first, then use Google Analytics to dig a bit deeper into certain insights.

Promoted product activity

We’re going to start by looking at the one specific product your Facebook Ad pointed to.

As you recall, we went to the ‘Behavior’ tab to look at the activity that each page received. Let’s go back there.

Go to ‘Behavior’ ➜ ‘Site Content’ ➜ ‘All Pages.’

As you can see, Amanda’s top-performing page was her homepage (this is because she shared it on her Facebook).

The second top-performer was the blanket scarf collection page she was pointing to in her Facebook Ads.

Remember: Amanda messed up here. Do not lead your Facebook Ads to a collection page – lead them to a product page instead to increase sales

But for the purpose of this exercise, we’ll look at her collection page anyway.

When she clicked on this page, she saw:

  • 164 total pageviews, counting whenever a user visited the page more than once in a session
  • 102 unique pageviews, which reflects the number of visits where the user only visited this page once
  • 35 seconds average time on the page
  • 65.75% bounce rate, meaning that 65.75% of these visitors only visited this one page, then left
  • 37.8% exit rate, meaning that this was the last page of the site viewed by 37.8% of all visitors (which means that they could have visited other pages in their session too – but they looked at this one, then left right after)

analyzing product performance in google analytics

These numbers could use some improvement. While 35 seconds could possibly be long enough to make a purchase decision (since it’s not a high-consideration kind of item), she only had her friends’ 2 purchases up to this point.

The bounce rate is a bit high. But as I mentioned earlier, it could definitely be the result of Facebook visitors not seeing the scarf from her photo, so they didn’t care to sift through the inventory until they found it.

As for the exit rate, it doesn’t seem particularly unusual given the other stats.

Looking at ‘Behavior Flow’

There’s a silver lining for Amanda – even though she possibly lost some sales by linking to her blanket scarf collection page, she now has more data about which blanket scarves people clicked when they were presented with all the options.

Amanda Asks

“Dangit. Can I at least see which items people are 
looking at, to have an idea of what I should promote?”

My answer: The Google Analytics ‘Behavior Flow’ tool is awesome. It can look a bit intimidating, but it can show you the journey of your users’ visits.

Here’s how she looked at the blanket scarves people clicked once they were on the blanket scarf collection page.

Go to ‘Behavior’ ➜ ‘Behavior Flow.’

behavior flow google analytics

Told you it’s intimidating. But stick with me.

She looked under the ‘Starting pages’ column and found the URL that described her collection.

starting pages flow google analytics

Then she clicked it and selected ‘Highlight traffic through here.’

highlight traffic through here GA

Looking at this highlighted flow, she looked at the ‘(25 more pages)’ group.

To do this, she clicked it and selected ‘Group details.’ Then it showed her all the pages that people clicked from that collection page.

looking at ecommerce product performance

She could see the most popular items, including the scarves she labeled black, blue grey, and colorful.

This is also a way to see which items are getting no love at all, like her yellow one. Apparently no one is into yellow.

It’s still too early to make any definitive judgment calls about taking any products out of Amanda’s store (and perhaps yours too).

But knowing what to look for is important as more time passes. I would say that in about a month, you should do this exercise again, and look at all the products in your store.

Especially for the products you’re running ads for – if they still haven’t picked up steam in a month, you should consider focusing on something else. And use your data and research to determine what that might be.

Day 20 Recap

Today, you:

✓ Looked closely at how your store is performing so far
✓ Learned how to better identify what’s working and what isn’t
✓ Got some ideas about things you might want to do differently moving forward

Tomorrow. Is. The. Last. Day.

I can’t believe it. See you then.

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