Enrich Your Payments Data to Optimize Every Dollar

Your business needs to see a return on the investment of every dollar spent. Whether you’re kickstarting a new marketing campaign, adopting new processing strategies, or expanding into a new market, every step should contribute to acquiring more customers and growing long-term value. But while you invest heavily to get potential customers to your website or mobile application, what happens after they click “buy” often remains a black box. Did your aggressive retry strategy drive approvals and LTV? Did an AI-optimized ad campaign bring in new customers and revenue to justify the expense—or just increase traffic? Are fraud rules blocking good orders from legitimate customers? 

The answers often live in your payments data. But to extract them, you need more than raw metrics—you need data enriched with business context. Enter the Pagos Enrichment API. 

The Enrichment API gives you the power to attach custom metadata to every transaction you import into Pagos. That means you can tag transactions with real-life business context—marketing campaign, advertising spend, affiliate partners, product type, subscription tier, or retry attempt—and segment your payments performance by these same details. When you can filter metrics like conversion, approval rate, chargeback rate, and average order value by the business decisions they’re tied to, you’ll have concrete proof of what investments paid off and which need tweaking.

Let’s explore how some leading brands are leveraging enriched payments data today.

Assessing Marketing Campaign ROI

To evaluate the performance of your marketing efforts, you can use metadata to tag transactions associated with specific marketing campaigns, advertising, affiliates, or promo codes. While these tags alone are enough to compare base payment metrics like approval rates and transaction counts per campaign side-by-side, they also set you up for deeper filtering opportunities. 

Using the Enrichment API and Pagos’s BIN database, you can combine campaign-level metadata with card-level segmentation to uncover insights like:

• Which campaigns drive higher-value card types (e.g. premium credit cards vs prepaid debit cards)

• Which customer segments churn faster after a promotion ends

• Which cards are more likely to trigger fraud systems

• Do some campaigns perform better or worse when it comes to customers' ability to successfully buy from you?

These aren't vanity metrics—they're the building blocks of smarter campaign targeting and better audience quality over time.

Understanding Value Across Acquisition Channels

Another valuable use-case for metadata is identifying the channel a customer goes through to find your business and complete a purchase. If you sell through multiple entry points (e.g. organic traffic, social media, ad sponsorship), you can tag incoming purchases with the acquisition source to determine:

• Which channels attract customers with higher average order values

• If a particular ad campaign drives traffic to any one channel

• Which types of products are more popular through each channel 

• How successful are customers with completing a purchase across channels?

• Which channels have higher chargeback rates or attract more fraudsters

Data segmented in this way can help you restructure traffic flows and refine targeted advertising—leading to higher approval rates and better campaign ROI. In extreme cases, you may decide to discontinue one acquisition channel or even restrict the types of products or services available for purchase through each.

A/B Testing Fraud Rules 

In a recent blog post, we explored the delicate balancing act that is payments optimization, and how changes targeted at improving one payment metric can inversely impact another. One obvious example is the push and pull between chargeback and approval rates. Relaxing your fraud rules to let in more transactions may increase approvals, but doing so could also increase your fraud exposure and chargeback rate; on the flip side, implementing strict fraud rules could turn away and upset good customers. If your business turns to A/B testing to find this perfect balance, enriched metadata will help you measure the results!

Say you have a recurring business model and process a mix of both merchant-initiated and customer-initiated transactions. You decide to run an A/B test to determine the impact of removing fraud-checks from MIT orders. Using the Enrichment API, you can tag transactions with metadata identifying CIT vs MIT transactions and transactions that skipped fraud checks. You can then easily segment your data to determine the impact of your test on approvals and chargebacks. If approvals increase for the affected transactions without driving up chargebacks, you can estimate the ROI of implementing this change across all merchant-initiated orders!

Maximizing Subscription LTV Through Retries

If you run a subscription business, you've likely built out an informed retry strategy. When a payment fails one cycle, you don’t immediately accept that decline as a churned subscriber, but instead try the transaction at least once more in hopes of reducing churn and retaining the customer’s estimated lifetime value (LTV). Using metadata, you can tag transactions with details like:

• Retry = true or false

• Retry attempt number

• Subscription plan or tier

• Subscription status

• Customer tenure (i.e. how long they’ve been a subscriber)

You can then filter your payments data by one or more of these tags to identify diminishing returns and optimize where to best spend money and resources on retries. Spot when certain subscription plans or offerings have lower retry success overall, or which payment methods aren’t worth retrying past the second attempt. While retries are meant to retain customers and drive revenue, suppressing those with low success rates ultimately reduces operational costs and benefits your bottom line.

More Data, More Optimization, Happier Customers

AI-powered search is swiftly revolutionizing the way people conduct market research and find new brands to buy from. In a recent article on the subject, Bain & Company reported 51% of surveyed customers trust AI shopping assistants for shopping and product recommendations, meaning it’s getting harder by the day to have a direct impact on how your business stands out against the competition. 

With fewer chances to convert browsing shoppers into loyal customers, it’s more important than ever to treat payment performance as a strategic business priority. You not only need faster feedback loops on campaign performance, but also visibility into failure points and the agility to measure the results of A/B tests

The Pagos Enrichment API gives you the foundation you need to do all this and more. It brings your business context directly into your payments data so you can stop guessing and start optimizing. Contact us today!