| Cover image | |||
|---|---|---|---|
| Explore destinations | /pages/3fae79394ec1bcd92336002b2906125cf9bffa90 | /files/BsjpNkT7jgeL7dCPZRrb |
What do I get with the Recharge integration?
* End-to-end [Google Analytics](/integrations/shopify-to-google-analytics/how-it-works-shopify-to-ga4)) tracking for the subscriber journey * Marketing attribution for subscription revenue * [Custom dimensions](/google-analytics/conversions/customer-lifetime-value-google-analytics) to calculate lifetime value and create custom audiences for retargeting * Ability to segment performance in Google Analytics by payment source, subscription plan type, and product category * Recharge susbcription [lifecycle events](/sources/recharge/how-it-works-recharge-to-google-analytics-connection)How does this improve on Shopify’s native reporting?
* Fix your ecommerce tracking in Google Analytics * Send data to Google Analytics 4 (GA4) and Facebook Conversions API (CAPI) * Attribute recurring payments to marketing campaigns Check out the [complete list of what you can track](/integrations/shopify-to-google-analytics) to see the full scope of reporting.Can’t I just use Recharge’s basic Google Analytics integration?
As the name states, that's just a basic [integration](https://support.getrecharge.com/hc/en-us/articles/360008683194-Google-Analytics). That means your data collection will be limited and have incomplete marketing attribution for subscription sales, plus there is no tracking for GA4 or Facebook CAPI. Littledata's Recharge connection is an advanced Google Analytics integration for Recharge stores. We've worked closely with the Recharge team to make Littledata the most powerful and flexible analytics integration for Recharge — and we continue to update the connection based on the latest product updates from both Shopify and Recharge.I get UTM parameters from the Recharge Subscription API. Do I still need Littledata?
Since the release of Recharge v3.2, the UTM parameters as captured by Shopify on the store landing page are passed to the checkout then [stored on the subscription or customer record](https://support.rechargepayments.com/hc/en-us/articles/360041127093-Using-cart-attributes-and-UTM-parameters-in-URLs). They are available in the `analytics_data.utm_params` field. This is helpful, but it misses a few key parts of what Littledata does: 1. Shopify's own UTM tracking is [far from perfect on most stores](https://blog.littledata.io/2019/02/04/shopifys-sales-by-traffic-source-report-is-broken), and the same mistakes get copied into Recharge's UTM params. 2. The UTM parameters only capture the 'last click' attribution of the subscription; with Littledata + Google Analytics you can look at the contribution from all marketing channels. 3. If you also have one-time orders processed through Shopify's checkout, you need Littledata's [Shopify tracking](/integrations/shopify-to-google-analytics) to compare like-for-like attribution across the two checkouts. 4. In Google Analytics you can look at the interaction between the campaign and other user attributes. For example, you can ask "Do Facebook ads perform especially well in the US, or globally?" Or "are affiliates driving more subscriptions on mobile only?" 5. Tracking Recharge customer [lifecycle events](/sources/recharge/how-it-works-recharge-to-google-analytics-connection) allows you to split post-purchase behavior like cancellations and payment failures as well as edit customer details by the marketing channel that brought them to subscribe.What's the difference between Recharge Analytics and Littledata's integration?
Recharge's [Analytics](https://support.getrecharge.com/hc/en-us/articles/360044363954-Recharge-Analytics) offers easy ways to visualize your Recharge data in the app, while Littledata fixes sales and marketing tracking and sends that data to Segment or Google Analytics. The chart below breaks down the differences between what Recharge Enhanced Analytics offers and what Littledata's Plus offerings for Google Analytics and Segment offer. | **What you can do** | **Recharge Enhanced Analytics** | **Littledata + Google Analytics** | **Littledata + Segment** | | ------------------------------------------------------------------------------------- | ------------------------------- | --------------------------------- | ------------------------ | | Look at trends in subscription signups and cancellations | ✔ | ✔ | ✔ | | Analyze churn rate by cohort or product | ✔ | ✔ \* | ✔ \* | | Visualize cohort retention | ✔ | | | | Analyze multichannel marketing contributions to subscription sales | ✔ | ✔ | ✔ | | Attribute recurring orders back to marketing campaigns | ✔ | ✔ | ✔ | | Analyze Customer Lifetime Value including non-Recharge spend | | ✔ | ✔ | | Track charge failures by any customer attribute | | ✔ | ✔ | | Track subscription cancellations or upgrades by any customer attribute | | ✔ | ✔ | | Track customer updates by any customer attribute | | ✔ | ✔ | | Track usage of the customer portal on your site by any customer attribute | | ✔ | ✔ | | See how any Recharge customer event connects to the pre-checkout behavior of the user | | ✔ | ✔ | | Look at cancellation rate by marketing channel | ✔ | ✔ | ✔ | | Trigger transactional emails based on changes to subscriptions \*\* | | | ✔ | | Retarget segments of your Recharge audience in common marketing destinations | | | ✔ | \* Requires additional analysis in a spreadsheet\ \*\* In Segment destinations such as [Iterable](https://segment.com/docs/connections/destinations/catalog/iterable)How do I know if the integration is working?
* Check out [this guide](/sources/recharge/how-to-check-if-the-littledata-recharge-integration-is-working) to see if the Recharge connection is functioning properly. * [Contact](https://www.littledata.io/contact-us) our team if you have additional questions.Do you alter my historic data?
* No, it's not possible for our app to mess with your historic data (nor would we want it to). * Littledata's improved tracking script only helps with data from the time you install it going forward.How do I uninstall the Recharge connection?
If you need to uninstall the Recharge connection, follow the steps in the Recharge [uninstall guide](/sources/recharge/how-to-disable-the-recharge-connection). But don't forget that you can always [contact support](https://www.littledata.io/contact-us) if you have any questions!.png?alt=media)
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| Cover image | |||
|---|---|---|---|
| Google Analytics 4 | Server-side event tracking, checkout steps, and marketing attribution in GA4. | /pages/8XHXYvZ63FFayBNpeCZg | /files/TaJZ7VjZtO4Ox2u779NU |
| Google Ads | Server-side conversions with Enhanced Conversions for better ROAS. | /pages/NXST3zVRm3JJxIUOgRZl | /files/TkBCOntgeBWZ9EEmewBq |
| Meta Conversions API | Improve match quality and attribution in Meta Ads via CAPI. | /pages/oOqYAY9O429odGWt2xVH | /files/GptKp0uC3pW8411YNgMe |
| Klaviyo | Enhanced identity resolution for abandoned cart and browse flows. | /pages/M5wDjwMmzicjdMZeNCyg | /files/MH0K6LH3ySzIAWglTcd8 |
| Attentive | Expand SMS audiences with cross-channel data stitching. | /pages/gSGbV4i4dy3Bpslyh0St | /files/febrydgZp1FthDzGGE1s |
| Microsoft Ads | Server-side Shopify conversion tracking in Microsoft Ads. | /pages/14ekrn8iMKJ4gJqV33qs | /files/3GGVA29fXowgLYppMuTf |
| TikTok | Improve match rates and ROAS via the TikTok Events API. | /pages/rT76WJ0tNHGuE2qRxaHB | /files/FJkTQbsK9e0xNXolyQDV |
| Better retargeting and audiences via the Pinterest API for Conversions. | /pages/wVgxiRaaIgjLwtXn4xOn | /files/QvBYybriUcFyDkmL62HL | |
| Segment | Use Shopify as a Segment source for warehouses, Mixpanel, Braze, and more. | /pages/tWBXpRRpcynQpybinQFt | /files/1BYagT58DS0nrSeoGOLX |
{% endstep %} {% step %} **Disable duplicate tracking** Turn off other tracking apps that could send duplicate data, such as the Facebook & Instagram sales channel. After you finish, tick **I've disabled other tracking apps** and click **Connect**.  To disable data sharing in the Facebook & Instagram sales channel: 1. Open the **Facebook & Instagram** sales channel. 2. Go to **Settings**. 3. If data sharing is set to **Maximum**, click **Change**, disable data sharing, and save.  {% endstep %} {% step %} **Finish the connection** The Meta connection is now live on your store. {% endstep %} {% endstepper %} # How it works: Shopify to Meta Conversions API (CAPI) ## What you can track Here's what you can track with Littledata's Meta connection for Shopify. All the events below are tracked by default. You can turn events off in the settings. ### Client-side events | **Event name** | **Description** | | ------------------- | -------------------------------------------------------------------------- | | ViewContent | A visit to a web page such as a product page or landing page | | InitiateCheckout \* | The start of a checkout process. For example, clicking the Checkout button | | AddPaymentInfo \* | The addition of customer payment information during a checkout process | | Purchase \* | Completing the checkout and viewing thank you page | \* Only for stores with the Littledata Pixel connected ### Server-side events | **Event name** | **Description** | | -------------------- | ----------------------------------------------------------------------------------------------------------------------------------------- | | AddToCart | The addition of an item to a shopping cart or basket. For example, clicking an Add to Cart button. | | InitiateCheckout | The start of a checkout process. For example, clicking the Checkout button. | | AddPaymentInfo | The addition of customer payment information during a checkout process. For example, a customer clicks to save their billing information. | | Purchase | Completing the checkout and receiving an order confirmation | | Post Purchase Upsell | The completion of an upsell purchase, that will contain only the newly added products. | | Recurring Purchase | The completion of an automatic recurring purchase, such as a recurring order from Recharge subscriptions. | Note: **Remove from cart**, **view item list** and **refund** events are not officially supported by Meta Conversions API. This is a limitation on Meta's side, not Littledata's. {% embed url="
![]({require("../../.gitbook/assets/cart-to-buy-in-action.png").default})
{% hint style="success" %}
**Pro tip:**
Keep your Adds to cart column nearby - as it helps you quickly control the volume i.e. the significance that a particular row of data has in the overall traffic
{% endhint %}
With Littledata CAPI feeding your Meta account you can be sure that 100% of add to cart events are properly logged and surfaced in reports!
Once you create the described Cart-to-buy metric you'll know how easy it is to choose and combine metrics from the dropdown of all available numbers in Meta.
In the next chapters we'll focus on metrics specific to Littledata Meta connector as they carry great value for e-commerce advertisers.
By using these metrics you'll be able to distingush between net-new acquisition and returning loyalists (among other benefits) and solve one of the biggest problems in Meta advertising: **Attribution Theft** (where ads claim credit for customers who would have bought anyway).
Here are 5 advanced custom metrics you can build using Littledata's specific events:
## Customer acquisition cost (CAC)
Calculating this metric is simple, right?
CAC = Amount spent / New Customers acquired
Only problem is that New customers is NOT measured in Meta ads.
Unless you use Littledata connector :)
Apart from the standard events we see here - there are 5 more events being sent to your Meta account if you're using Littledata CAPI connector:
* Returning customer purchase
* Recurring purchase
* New customer purchase
* First recurring purchase
* Post purchase upsell
We ordered them just like in the screenshot above, and we're going to use them for calculating eye-opening metrics that help advertisers understand what REALLY performs (and what doesn't!) in Meta.
In order to use these in calculated metrics, you need to [register these events as custom conversions](/integrations/facebook-capi/meta-ads-custom-events-verifying-new-and-returning-customer-purchase#measuring-new-andor-returning-customer-purchases-in-meta-ads-reports).
That step is necessary because the Littledata custom events are not standard in Meta and there are no accompanying metrics for them (e.g just like we have out-of-the-box metric "Purchases').
After registering them you'll be able to see them as column in ANY campaign, ad set or ad, just like this:
In the example above we can see how many new customers are coming from each ad set, and you think it looks cool, right?
Wait till we show you the actual calculated metric which everyone understand (C-suite especially!) Customer acquisition cost!
Now given that you're a doer and not only a reader you'll go ahead right now and replicate the steps explained, and if you do you'll be able to surface a report like this and finally give your ads a fair comparison:
Kaboom! Now you can see what price do you pay for new customers for each ad set! (Can be applied to campaigns and ads as well)
If you're confused with the front\¢er column for new-customer purchases Conversion value - it's available by default based on the real value of the proper purchase events.
## New Customer Index
Before we show you how easy it is to create the super-insightful metric called New Customer Index let's underline that Meta reporting is event-based, NOT user-based!
We mentioned earlier that calculating metrics and different ratios in Meta reports serves the purpose of comparing assets against each other, and shouldn't be mistaken for absolute truths. It's no accident we repeat it now, because in the CAC example above, have in mind that a new customer purchase can happen only ONCE per user - so it doesn't matter whether we talk about user- or event-scope, the numbers match either way.
In this example we'll use the "return-customer-purchases" count which can happen more than once for any single user so the customer index is somewhat skewed (doesn't represent with 100% accuracy ratio of new vs returning customers - which is why we used "index" and not "rate" to define it)
Our numbers tell quite an interesting story (and it's the last time we'll screenshot how the custom metric looks in the report itself, this looked too good to be skipped):
Again, we're keeping the Purchase column handy, to quickly understand volume impact.
This metric is the "truth serum" for the **brand-scaling** campaigns. A campaign might show a high ROAS in Meta, but if 80% of those buyers were returning customers, it means you're doing a poor job on acquisition.
It also serves as a diagnostic tool for creative performance. It tells you if a specific creative angle appeals to cold audiences or if it only resonates with people who already know the brand.
## Subscription CVR
If you already registered "First Recurring Purchase - Littledata" as a custom conversion, all you need to do is:
**Sub CVR = first-recurring-orders / clicks**
You can also test Landing page views instead of clicks if you noticed that these two metrics differ significantly. The gap between clicks and LP views happens due to site load speed issues or ad blockers / safe browsers.
{% hint style="info" %}
**Geeks-only DIY**
Can you create a custom metric that will quantify this problem?
HINT: divide LP views by link clicks (remember - All clicks mean ALL clicks!)
{% endhint %}
## Subscription Retention
*This metric is applicable ONLY for long-standing "evergreen" campaigns that promote subscription products.*
The formula is:
SR = recurring-orders / first-subscription-orders
It will help you understand which asset produces long term success and which low value customers.
{% hint style="warning" %}
**Do you understand Meta attribution?**
This metric should be used with caution as [Meta attribution](/integrations/facebook-capi/why-is-meta-attribution-different-from-ga4) i.e the way the platform awards conversion credit can **strongly** affect numbers.
{% endhint %}
## Upsell Rate
Littledata CAPI connector is designed with one thing in mind: to help ecommerce advertisers pull the most out of their dataset.
That's why we made sure to "notify" Meta each time an upsell has happened. Comparing that number against All purchases (or even more specifically new- or returning-customer purchases) can help you better understand how each campaign performs when it comes to upsells!
Uspell rate = upsells-littledata ÷ Total Purchases
## Conclusion
Relying on out-of-the-box reporting often obscures true profitability, masking whether you are fueling actual growth or simply recycling existing customers.
By leveraging Littledata’s granular events to calculate metrics like CAC or Subscription CVR, you help Ads optimize for genuine value instead of vanity metrics (like clicks or impressions).
# Maximize conversion value based on customer LTV
Stop bidding on orders and start bidding on customers. Use Littledata to sync Shopify LTV to Google and Meta Ads for smarter, value-based optimization.
Most e-commerce brands are trapped in a "blind spot" of optimizing their Meta (and/or Google!) campaigns based on the immediate value of a transaction. E.g if a new customer spends $5 and a returning customer spends $20, standard tracking tells the platform that the purchase made by the returning customer is four times more valuable.
In reality, the opposite is often true. This traditional approach ignores the long-term potential of a new acquisition, leading to inefficient bidding and missed growth opportunities.
## The technical bridge: Littledata & server-side tracking
To fix this, you need to provide the advertising platform with better "insider information". Littledata bridges this gap by sending more than just a "vanilla" purchase event. Using Shopify server-side data, it identifies the customer's history and fires two additional events:
New Customer Purchase: fired when a user makes their first-ever purchase.
Returning Customer Purchase: fired for every subsequent order.
Because this happens server-side, it uses Enhanced Conversions (Google) or the Conversions API (Meta) to stitch the hashed email from a Shopify order with the platform-obtained email (hashed, ofcourse). This ensures 100% accuracy in identifying whether that customer interacted with your ads, regardless of cookie restrictions.
This is how these event appear in Meta events manager:
and this is from Google's Goals (aka conversions) section:
## Programming the campaigns
Once these events are flowing, you can stop relying on the "raw" order value and start assigning manual value for each new customer based on your brand's actual data.
Example:
You know that a new customer, over their entire lifespan with your brand, is worth $600 (LTV). Meanwhile, a repeat purchase from an existing customer brings in an average of $100.
By [manually assigning these values](/integrations/facebook-capi/meta-ads-custom-events-verifying-new-and-returning-customer-purchase#using-new-or-returning-customer-purchase-events-as-conversions) to the respective events in your account, and using the "Maximize conversion value" strategy - you are explicitly instructing the platform's algorithm on the relative worth of these users.
In the screenshot above we can see that this setup in Meta is chosen on the Ad set level, whereas in Google it's a campaign-level setting:
By using this setup - you are telling the "Maximize Conversion Value" strategy that each new customer is worth six repeat purchases.
## Training your ads for growth
This setup fundamentally changes how your budget is managed. Instead of the platform hunting for the "cheapest" immediate sale, it uses the 6:1 ratio (from the previous example) to:
* Prioritize [high lifetime-value users](/google-analytics/conversions/lifetime-value-in-ga4) by bidding more aggressively for a user that has never bought before because it sees a $600 opportunity.
* Optimize ads by “seeing” which combination of hooks and creatives is actually driving long-term growth versus one-off discount hunters.
* Balance the budget to find the optimal mix of new acquisitions and repeat sales based on the value you've defined.
## Conclusion: Playing the Long Game
This approach shifts the role of the E-commerce Manager from adjusting manual bids to defining customer worth. Without the specific distinction between new and returning events provided by Littledata, this level of optimization isn't possible.
The bottom line is simple: your campaign is only as smart as the values you feed it. By programming the ratio of new versus returning customer worth, you move past the "one-off" order value race and start playing the long-term game to outsmart your competitors.
# Why is Meta attribution different from GA4
If you’re coming from the GA4 world, you know that the default attribution relies primarily on session context. Session channels are clearly separated from the First-user touchpoints with your website. Together they help you get a more nuanced understanding of [how various traffic sources contribute to conversions](https://support.google.com/analytics/answer/11080067?hl=en#zippy=%2Cin-this-article). Advanced analysts can use GA4’s attribution dimensions to distribute credit for conversions across the entire purchase journey.
And then you open Meta Ads Manager, and the attribution suddenly feels completely different! In this article we’ll explain what the differences are (and mention a couple of similarities).
## What attribution means on Meta platform anyway?
Let’s be clear from the start - the word “attribution” doesn’t refer to the same concept in GA4 and Meta. With Littledata feeding [100% of purchases as optimizing signal to Meta](/integrations/facebook-capi/how-it-works-shopify-to-meta-conversions-api) it's essential for advertisiers to have trustworthy report covering what drove these purchases in the first place. And while GA4 is a neutral observer of all traffic sources, Meta’s attribution is designed to prove the value of its own ads and optimize delivery based on those rules. GA4 revolves around traffic source(s) which led to conversions. Meta tracks users instead and assigns conversions to different actions they took within the Meta ecosystem.
Let’s go through Meta attribution basics before we dive into key differences.
### Attribution setting for reports
Just by looking at the attribution models offered in Meta you see their only goal is to measure how Meta ads contribute:
One, seven or twenty-eight day click models mean that Meta will award full credit for a conversion if it happens in these respective timespans *after* an ad has been clicked - by clicked Meta means *all clicks*!
These are the attribution models for analyzing ads in retrospect.
{% hint style="success" %}
In GA4, the attribution models can be compared in the Advertising section.
{% endhint %}
When analyzing performance of your Meta ads - you have the option to compare various attribution models side-by-side. You can add this to your report at the bottom of "Columns" dropdown.
### Attribution setting for ads
There is another context when you think about Attribution in Meta. During the Ad set creation you have the option to choose which attribution should your ad be optimized around.
{% hint style="warning" %}
Meta attribution setting affects delivery also, not just reporting!
{% endhint %}
The choice of models is way more limited when it comes to ad setup:
If you already deployed tons of Meta campaigns, but have never seen this option before, don’t worry - this setting is hidden in the ad set “Show more settings” setup:
Default attribution is 7-day click & 1-day view meaning that Meta will go after users who buy either 7-days after clicking on the ad OR 1-day after seeing it. Dropdowns reveal quite disappointing limited choice of options, as you can only turn each one of them OFF, or reduce click-through to 1-day click:
This setting is important as Meta will optimize delivery around this rule, e.g if you reduce click-through to 1 day your ad will be served for quick-pull-trigger customers who buy within a day from clicking the ad (obviously not a good idea unless you have some kind of super hot FOMO promotion to offer!)
Now your GA4-trained brain is ready to understand where Meta’s logic diverges and why your reports almost never match.
In GA4, switching from last-click to data-driven doesn’t change how your campaigns run. It’s just a new lens on historical data. Meta’s attribution setting is different because it is baked directly into delivery optimization.
Example: If you set Meta to 7-day click and 1-day view, the algorithm hunts for users who are likely to convert under that exact rule set. Change the window to 1-day click only, and you are training Meta’s system to ignore people who might convert later.
GA4 mindset shift: In GA4, attribution is a reporting decision. In Meta, it is a strategic campaign lever. Meta attribution setting will affect delivery, unlike in GA4 where attribution is strictly for reporting purposes.
## Click attribution means ANY click
GA4 only credits clicks that generate a session. E.g a click on a Facebook ad that opens your site is credited to session source = Facebook once the GA4 tag fires.
Meta is far more generous with what counts as a click. Any interaction such as liking an ad, expanding its image, or watching part of a video starts the attribution clock. If the person converts later within your set window, Meta gives itself credit, even if there was no tracked site visit.
This is why you will often see Meta reports self-attributing conversions that GA4 does not credit to Meta. GA4 never “saw” the visit because it didn’t happen, and no session was recorded, the click kept the user within Meta boundaries.
## View-through conversions exist in Meta, not in GA4 (by default)
To a GA4 analyst, what you’re about to read often feels like giving credit to a billboard that someone drove past on their way to the store, or even last night while driving back home from work.
GA4 does not give credit to an impression unless you want to do so manually by analyzing Google Ads impression data. Meta, on the other hand, credits view-through conversions by default, if view attribution is on (defalt setup). If someone saw your ad and converted within a day, Meta will attribute that sale to 1-day view attribution.
## No session context in Meta
In GA4, the idea of session-scoped attribution means all activity within a session shares the same attribution source. Meta ignores session boundaries entirely. Its attribution logic is user-based, not session-based. The moment you open the attribution window by clicking or seeing an ad, that ad becomes eligible for credit, regardless of what else happens up to the moment of the conversion.
{% hint style="info" %}
Meta attribution logic is user-based, not session-based!
{% endhint %}
## First conversion reporting ≠ first user dimensions
In [GA4’s Exploration section](/google-analytics/behavior/ga4-explorations-complete-guide-for-ecommerce-growth) you can easily surface which first user source/medium brought any group of users to the website for the very first time. Meta’s “First Conversion” is completely different reporting simply removes repeat conversions from the count within the attribution window.
This means Meta’s First Conversion is more about deduplication than about true first-touch channel attribution. It does not help you understand initial acquisition, but only how many unique conversions happened after an ad touchpoint - think of GA4’s Total Purchasers vs Purchases comparison.
## Incremental attribution is Meta built-in feature (kind of)
From recently, Meta has an “Incremental Attribution” setting that uses internal models to filter out conversions it thinks would have happened anyway, i.e without a Meta ad.
But the details are opaque. In practice, this is still a black box, and the difference between the current “greedy” model and incremental is really subtle. Let’s see a real-world example of “incremental attribution” applied:
## Meta’s scope is self-referential
GA4 attribution spreads credit across all tracked sources in your ecosystem: organic, paid search, email, social, affiliates, referrals, direct, etc. Meta’s scope is entirely self-referential. It only asks “Did Meta help cause this conversion?”
This means Meta’s numbers can never be directly compared to GA4’s total channel mix. They are answering different questions. GA4 is multi-channel. Meta is single-channel but multi-touch within its own channel.
## Why do the numbers rarely match?
If you have ever tried to reconcile Meta and GA4 reports, you know it is frustrating. Meta counts:
* Clicks GA4 never saw as sessions
* Views GA4 cannot track at all
* Conversions outside of session scope
* Different conversion counting rules
GA4 counts:
* Only visits tracked in sessions
* Attribution across all channels
* Conversions based on your chosen model
The result: GA4 is your wide-angle camera. Meta is your zoom lens, focused on one player only. Same scene, completely different framing.
## Final thought
If you understand GA4 attribution, the easiest way to approach Meta’s system is to stop thinking in terms of session context and imagine a sales engineer with only one goal: to persuade you how they contribute to your success. Meta attribution is ad-platform-centric, optimized for its own delivery logic.
Neither is “wrong” but they are designed for different purposes. GA4 gives you the full multi-channel story. Meta tells you the most flattering chapter about its own role.
# New and Returning Customer Purchase in Meta Ads
In this post, we'll cover how to use Littledata's [New vs Returning customer purchases](/integrations/facebook-capi/how-it-works-shopify-to-meta-conversions-api#new-customer-vs-returning-customer-conversions) and use it to boost Meta campaigns.
As marketers, we know that New Customer purchases and Returning Customer purchases are different in nature and shouldn't be treated equally. It's one thing to try to acquire new customers, while it's completely another to optimize ads around returning buyers.
## Adding the purchase events from Littledata
If you are adding our [Meta Conversions API destination](/integrations/facebook-capi/how-to-install-shopify-to-conversions-api) for the first time, the **New Customer Purchase** and **Returning Customer Purchase** events will be selected by default.
If you already have the Meta destination set up, you can enable them from the Events tab located in the Meta destination settings.
## Verifying the new purchase events
New and Returning Customer Purchase events should be immediately flowing into your Meta Events Manager, but at this point they are marked as unverified: