5 things ecommerce advertisers can do with first-party data

First-party data is a valuable and essential resource to leverage across PPC ad platforms. 

It used to be a “nice-to-have,” particularly in Google Ads for ecommerce advertisers with limited value in using interest audiences or audiences generated from these lists.

But in this automation era, data enriches the quality of your targeting, whether you use it directly or not.

Below are five fundamental actions you can take to improve the quality of your ad account with first-party data strategies. 

1. Get your data directly integrated into all of your ad platforms 

It’s no longer just about getting first-party data added, but how. 

Exporting and uploading your data is a good starting point. 

But your audiences will change over time, so the best way to get the most updated list is by integrating your web platform with your ad accounts. 

With the recent deprecation of similar audiences in Google Ads, first-party audience segments will be added as a signal to optimized targeting as a targeting criterion for audience expansion.

This increases the importance of high-quality first-party audience data. 

All the top ecommerce platforms provide direct integrations into the main advertising channels. 

Some involve more attention than others to set up and can be temperamental and drop off occasionally.

Still, most are straightforward and worth any hassle in the long run.

Dig deeper: The search marketer’s new imperative: Capturing first-party data

2. Turn on conversion-based customer lists in Google Ads

Technically, this counts as integrating first-party into Google. This time, rather than your web platform feeding Google the data, they generate it through the enhanced conversion tag.

A new added benefit to enhanced conversions is that Google automatically creates a conversion-based customer list with the correct tag implementation. 

You can opt into this feature at an account level.

As with integrating your first-party data, this will further enrich your audience data. 

Depending on how your enhanced conversions are set up, you can bring in additional data that your platform integration won’t. 

Even if it’s not, it’s good to have a fail-safe in case of any platform integration issues. (Beware of the bespoke platform!)

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3. Focus more on first-party lookalike audiences in Meta

Google might no longer have similar audiences, but Meta still has its lookalike audience feature. 

These lookalike audiences are more important with audience reductions post-iOS 14. 

With fewer interest audiences to choose from, I’ve been relying on them more in the past year or two than ever.

I was always more inclined to use interest audiences over all variations of lookalikes.

Still, the main thing I’ve noticed post-iOS 14 with lookalike targeting is that the best performers come from customer list audiences. 

The bigger the customer list audience, the more reliable the lookalike audience will be. 

4. Test first-party audience signals in your Performance Max campaigns 

I’ve tested this successfully with my clients with big enough audiences (minimum 10,000 per list before importing into Google Ads). 

Essentially, I combine their first-party data audiences with their third-party remarketing audiences and only run with these combined in the audience signal. 

No custom intent. No in-market, affinity or demographic audiences.

Just your own data.

Results are far from conclusive, but around 60% of my asset groups running alongside an existing asset group with a more stacked audience signal perform better in terms of ROAS and revenue (which I can see because of Mike Rhodes’ wonderful Performance Max insights script).

I’ve not seen any issues with fewer impressions or clicks, so the smaller audiences don’t seem to be impacted on reach.

It remains to be seen how impactful audience signals are in Performance Max campaigns, especially those with Shopping feeds, as the product feed attributes such as titles and descriptions are the primary targeting weapons. 

We have been told they are used to help kickstart a campaign and guide the algorithm. 

Even if it gains that extra 1% in performance, I’d suggest testing out some first- and third-party data audience signals – and not just in PMax campaigns.

Dig deeper: How to track Performance Max campaigns with Google Apps Script

5. Segment your data for different user intent

If you have access to multiple lists with significant numbers, you need to segment and tailor toward your campaign objectives.

It will depend on what type of data you have at your disposal. But you should be able to filter based on user quality (i.e., users who have bought more than X amount or have spent more than X amount). 

VIP lists or segments can be created with these parameters in mind within your ecommerce platform. This lets you create high-quality, high-intent lists that can be utilized for lookalike audience creation or Performance Max audience signals at the very least. 

How about users who have bought your product but haven’t returned to buy again for X months? 

Create a bespoke remarketing campaign with a promo code to re-engage with the brand and make them an active customer again. 

How about users who have requested a product sample but haven’t bought yet? 

Create some tailored creative and some unique incentives to grab their attention. 

These high-intent audiences must be separated from the crowd and cultivated with different strategies if you want retention rate and lifetime value to grow. 

You are likely already showing users in the upper funnel different messaging and different creative based on what stage they are in within the purchase funnel.

Extra care and attention must be taken at the bottom of the funnel, where intent is much higher. 

If you have large enough data points to work from, don’t waste it. 

Your data will only grow, so ensure a data funnel is in place to match your retention strategies. 

You’ve more than likely paid for the customer acquisition via paid traffic, so squeeze the true value out of it.

Outside of ad campaigns, you can use these different data profiles to reach out to users via email with surveys on your customer service, product offering or anything else. 

Maybe find out why they’ve bought an often replenished product once but never returned to buy again. 

Even if the lists are small and you have their phone numbers and a quality sales team, go old school and follow up if the average order value is worth the chase. 

The advantages are far beyond tailored targeting for your ad campaigns.

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