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With the privacy changes post iOS 14.5, it's no longer sufficient to send data (events) to ad platforms like Meta using only a browser pixel as increased privacy limits the amount of user data that can be tracked through browser-based methods. This will inevitably lead to a less accurate identification of your target audiences and sub-optimal ad auctions, making your ad targeting less effective. Which is why Server Side Tracking is a must now and as a performance marketer, you must also send the same events server-side using the conversion API (C-API) of the ad platform (e.g. Meta, Tiktok and Google Ads etc).
While Meta's C-API is a standard framework that accepts relevant events, the way you surface, organize, and send your valuable 1st party and Zero-party (customer shared) data through the C-API significantly influences its effectiveness. Hence, various C-API integrations have been designed to help ad platforms identify your target audience and assist the ad auction in determining who should see your ad, when, and how often.
But choosing the right C-API integration can be confusing and overwhelming, which is why in this article we will discuss different C-API solutions, and help you choose one that is ideal for your business.
Let’s dive in!
Before we discuss different C-API integrations, let’s talk about different steps involved in surfacing server-side tracked events to the ad platforms for auction optimization and audience targeting.
Collect events from websites, apps, and backend ordering systems, and identify known users who are not signed in during the current session and thus appear as anonymous users.
As an advertiser, you run paid media campaigns to achieve certain business objectives such as -acquiring new customers, acquiring leads that eventually convert through CRM nurturing, and acquiring high-value customers who will repurchase within the next 3-6 months, etc.
The value of all events you capture varies. For example, not every user who clicks on your ad and visits your site is likely to convert, not just in the current session, but also not convert in the next 7 or 28 days.
Similarly, not all leads you generate will convert through CRM. But, if you can identify high-value leads that are more likely to convert and predict this as soon as you capture that lead, then such information is highly valuable for ad auction optimization.
So, if your goal is to acquire customers who are likely to repurchase in the next 3-6 months (belonging to higher-LTV groups) and you are willing to pay a bit more to acquire such customers so you can improve your LTV:CAC, you will need a reliable prediction of LTV (pLTV) as soon as someone becomes your customer for the first time, or even better, if you have such prediction available even before someone buys from you.
From step 1, identity resolution is used for session stitching - connecting marketing identifiers and user identifiers to the events. This makes the event payload rich with as detailed user information as possible. This allows ad platforms to map the event to their user graph and use the event for ad auction optimization and attribution (reporting).
Now that we understand the steps involved in surfacing events with C-API, let’s talk about different C-API solutions.
Out of the box E-commerce platform integrations like Shopify C-API, BigCommerce C-API etc., as well as Customer Data Platforms (CDP) integrations (e.g. Segment) belong to this category. They merely pass through events as is, with very limited identity and enrichment capabilities. Because of this, you typically see limited event payload for upper and mid funnel events such as add to cart or page view. E-commerce C-API implementations are generally free for advertisers to use and comes with an easy setup process through an intuitive UI.
Most of the 3rd party C-API implementations fall in this category. These solutions perform identity resolution using a graph built off advertiser’s 1st-party data to re-identify past customers and visitors, and enrich event payloads with stitched user and marketing identifiers.
This is a state-of-the-art implementation of C-API. It differentiates itself from the advanced C-API implementation in the following ways:
We hope the above explanations have given you a clearer understanding of different C-API solutions.
When selecting the right C-API for your business, consider the following points:
Below, we have aggregated various C-API solutions, categorized into the three C-APIs types discussed above, so you can choose the one that's ideal for your business.
Now that you know what different C-API solution are capable of, allow us to share what some of our partner brands have been able to achieve with Angler AI’s Predictive C-API.
An apparel brand that wanted to acquire new customers using Meta paid ads. They transitioned from Meta's native C-API to Angler's predictive C-API, optimizing their daily spend with Angler events. Despite similar daily expenditures before and after the switch, this brand saw a 26% improvement in Marketing Efficiency Ratio (MER) for new customers after they made the switch. This improvement reached a higher, steady state almost immediately.
Another consumer brand selling women's clothing switched from their in-house C-API, maintained by their engineering team, to Angler's predictive C-API. Angler was using a 7-day conversion model to identify users who are likely to convert between day 2 and day 7 after engaging with an ad. This brand reported comparable performance on 1-day click purchases, however, a 58% higher ROAS with Angler's predictive C-API. This improvement came from the movable middle segment of their market that converted between day 2 and day 7. This trend continued beyond day 7 as well, with an 81% higher ROAS on 28-day click attribution with a 58% lower cost per order (CPO).
A consumer brand offering home and backyard design services transitioned from their Customer Data Platform (CDP), Segment C-API to Angler's predictive C-API. This brand sells services costing $1,500 or more, with a long consideration cycle. For them, a majority of the conversions occur between day 8 and 28, which is outside of their ad attribution window. The brand was running Meta ads optimized towards lead captures, where users sign up for CRM after completing a design survey. Angler's predictive model identified the top 20% of leads that have a higher than average conversion rate.
And, when the brand switched their ad optimization to high-value leads (custom event optimization) using Angler’s Predictive C-API, they improved lead conversion by 55% at the same cost per lead with Meta Custom Event Optimization, and Reels-ready creatives. This was demonstrated via concurrent campaigns for control and test cells. Month-over-month, their cost per lead (CPL) improved by 24% (pre vs post-test); and year-over-year, CPLs dropped by more than half (-53%) while ROAS increased by 92% (Q1'23 vs Q1'24).
Server-side tracking with Conversions API (C-API) has become a crucial aspect for effective ad optimization given the current advertising landscape with increased privacy regulations. The 3 types of C-API solutions discussed in this article, including Basic, Advanced, and Predictive, offer different levels of consumer data enrichment and identification capabilities. Although the right solution will depend on your business needs and objectives, we highly recommend conducting A/B tests to ensure you have the right configuration capabilities to orchestrate events that align with your business objectives.
At the end of the day, no matter which C-API you choose, it's clear - you absolutely need a C-API solution and server-side tracking. As we continue to navigate the post-iOS 14.5 world, it's becoming more essential to send the best data to ad platforms. This way, your ads can find better customers who love your brand, making your ads more profitable and increasing revenue for your brand.
Learn more about our Predictive CAPI, or start a free trial for 30 days to start optimizing your paid media spend with AI and see the results for yourself.
