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The importance of platform optimisation in times of expensive ads

The importance of platform optimisation in times of expensive ads

Seb Harris

6 minute read23 Nov 2022

Right now we’re hearing the same thing time and again in the e-commerce world: customer acquisition costs (CAC) and online advertising are soaring, what’s the solution to continue leveraging growth?

And we always give the same answer: data-driven platform optimisation. During the halcyon cookie days pre-iOS 14, many e-commerce brands became over-reliant on online advertising. To be fair, you can’t really blame them. The precision that was afforded to online ads by tracking cookies meant it was a highly effective way to get your brand in front of the right eyes.

However, the negative consequence of this was brands perhaps became a little complacent about acquiring new customers. Now the squeeze is on and it’s both more difficult and more expensive to get customers into your store. iOS-14 has dramatically changed the way we all advertise online, so it’s important to know how to make the most of your sales opportunities.

How does data-driven platform optimisation help? Let’s explain.

Why bother with platform optimisation?

If implemented correctly, data-driven platform optimisation will help you grow your business despite rising CAC. To understand how, it’s important to understand why your CAC is higher now than a few years ago.

During Covid we saw more brands than ever before turn their attention to e-commerce. With stores locked down, online retail was the only viable sales channel, so even those brands that had never dipped their toe in the online market took the plunge.

With this came a surge in competition. Advertising space is more contested now than ever before, naturally making it more expensive. 

Not only this, but as mentioned above, advertising is less precise because we no longer track cookies like we used to. You need to spend more money to guarantee your ads get in front of the right people.

So with all this in mind, it’s imperative that your site is operating at peak performance. You’ve spent all that money getting customers into your store, you need to make sure they spend and keep coming back for more.

How do you do this? By optimising your store experience to the smoothest, most seamless shopping experience on the internet. Guide your customers from entrance to checkout without any distractions, hiccups, load times or wrong turns, and you’ll get them buying more and more often.

But how do you know which features to optimise? That’s the secret of data analysis. 

How to optimise your e-commerce store

Data tracking

The start is always the same: data tracking. Data tracking is the pillar of optimisation and therefore the pillar of healthy e-commerce.  

In the best possible setup, you track absolutely everything available. This makes quantitative and qualitative analysis far easier (more on this below). You may think that some customer behaviours are so insignificant that they’re not worth tracking, but you’d be surprised at what difference you can make to your store with such small details.

You want to track every click and movement your customers make when navigating your store. Every time they scroll. How far they scroll. Every button they click on and every button they ignore. How long they spend on each page. Whether they hover over a banner, use a slider, play a video, add to cart. Every behaviour they make is worth tracking.

Takeaway message: nothing is too small or unnoticeable to track. Track it all.

How to track data post-iOS14?

iOS14 was brought in with much fanfare as the end of cookies and and boost in privacy and data protection. To be clear, we’re in favour of people’s rights to protect their privacy online. However, the wall put up on iOS phones has undoubtedly made e-commerce marketing more difficult.

So what’s the solution? Set up a subdomain for your website and funnel all data towards it, from which point Google Tag Manager can pick it up and take to Google Analytics and your chosen data warehouse.

For example, data from our own website will funnel towards and then onwards to our custom data tech stack.

Important: this is not illegal. The iOS14 update is not a law. It’s a software update related to iOS users and therefore Apple customers. Workarounds are still viable and we’d encourage e-commerce brands to make use of them and continue tracking their customer data.

Qualitative and quantitative analysis

There are two types of analysis that are key to successful e-commerce:

1. Qualitative analysis

Qualitative analysis regards the quality of elements on your page. Is the colour picker a little small? Should the button be moved to the left slightly? Should the collection page display fewer items?

All of the above questions would lead a qualitative analysis into your store. 

2. Quantitative analysis

Quantitative analysis is a pure numbers game. With your tracking setup correctly you can see exactly which aspects of your site are the most impactful. That is, you can see what is being clicked on the most and what is being ignored.

For example, the colour picker is being clicked on a lot. Once you know this, you can decide to try some optimisation experiments on the colour picker to see if you can improve its conversion rate.

You already know customers are using it a lot, so it’s a likely place to get some positive results.

The Growth Loop

Your qualitative and quantitative analysis are the first step of your growth loop, a continuous process of analysis, experimentation, optimisation and evaluation that will grow your e-commerce business.

The growth loop has 4 component steps:

1. Analyse

Track data and complete your store analysis, both quantitative and qualitative.

2. Ideate

With your analysis in place, work out some experimentation ideas. Think of ways that the website could be improved and discuss how to run experiments that will prove or disprove your theory.

3. Frame

Pick an experiment and frame its parameters. What will you test? What are the control variables? What signifies success for your experiment? How will you act after the experiment?

4. Experiment

Conduct your experiment. With the results, optimise your store accordingly and keep track of the results. Simultaneously, you’ll complete some further store analysis that will then start the loop again in a continuous cycle of optimisation.

Watch the keynote

For the full info, for examples from our data clients and for an interactive game you can play along with at home, check out Martijn and Arthur’s presentation from The D2C Summit: Future Commerce.

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