How Deyga Achieved 20% Lower CAC and 22% Higher ROAS with fastrr

Why Deyga’s Growing Ad Spend Wasn’t Delivering Better Results

A D2C brand can increase its ad budget and still see weaker returns. Sometimes, the problem is not the budget or the ads themselves, but how well the platform tracks results. 

Meta’s delivery system learns from the purchases and other actions a website reports back to it. When those reports are missing or unstable, the system has less to learn from.

Deyga, a natural skincare brand led by founder Arthi Raguram, reached this point while scaling its Meta campaigns. Spend was going up, but results were not following. fastrr Ads worked with the brand to fix tracking first, then build better audiences and creatives on top of it.

Deyga’s Challenge: Scaling Spend Without Scaling Results

Deyga was putting more money into Meta ads, but results didn’t rise with spend. The reason sat in the data. The brand’s event signals were broken, leaving Meta unable to see many real purchases coming from its campaigns. 

Why Does Meta Need Purchase Signals?

Every time someone buys, the website sends a small message, called an event, to Meta to say a purchase happened. Meta uses these events to learn what the brand’s buyers look like and to decide who should see the next ad. If the message does not arrive, or arrives without enough detail to link it to a person, Meta cannot learn from that sale. Meta’s developer documentation says only matched events can be used for attribution and ad delivery optimisation.

How Can Signals Break?

Tracking can fail in several ordinary ways, and a growing store like Deyga can lose sales data without noticing:

• Browser limits: The Meta Pixel runs inside the shopper’s browser. Ad blockers, privacy settings on iPhones and Safari, and slow page loads can stop it from reporting a purchase. Meta notes that the Pixel may lose events because of network or page-loading problems.
• Orders that never reach the confirmation page: If a shopper pays and closes the tab early, or if an order is confirmed later, as many cash on delivery (COD) orders are, the browser may never send the purchase event.
• Missing customer details: An event sent without details such as an email address or phone number is hard for Meta to match to a profile, so it adds little to ad learning.
• Setup gaps: Wrong event names, missing order values, duplicate events, or a theme or app update that breaks the tracking code can all produce unreliable data.

What Did This Mean for Deyga’s Ads?

Meta was learning from only part of Deyga’s sales, so it had a weaker idea of who the brand’s buyers were. As Deyga increased its budget, more of that spend reached people Meta could not target accurately.

The Solution: How fastrr Rebuilt the Signal Layer

fastrr Ads helps brands run and improve their Meta and Google campaigns using first-party commerce data. This is data that comes from the brand’s own store and shoppers. For Deyga, the work followed three steps in order: fix what Meta could see, improve who Meta showed the ads to, and improve what the ads showed.

Step 1: Fix the Tracking With CAPI and Custom Events

Meta’s Pixel is a small piece of code on a website that reports each action, such as a purchase, back to Meta. It runs inside the shopper’s browser, which is why it can miss events.

fastrr added the Conversions API (CAPI). CAPI sends the same information straight from the brand’s server to Meta, so it does not depend on the shopper’s browser. Meta recommends using CAPI together with the Pixel and sharing the same events through both, so that if one route loses an event, the other can still deliver it. To avoid counting one sale twice, each event carries an ID, and Meta uses that ID to count the sale once.

fastrr also set up custom events to track customer actions accurately. Meta has standard events, such as a purchase, but brands can also define their own events to track specific actions on their website. fastrr made sure these events were set up correctly and recorded actions consistently.

Step 2: Improve the Audience With fastrr Signals

An audience is the group of people Meta shows an ad to. Once Meta could see real purchases, the next task was to give it a better audience to target.

fastrr Signals adds buyer details to shopper profiles. These include what shoppers buy, which categories they prefer, whether they tend to choose cash on delivery (COD), and the risk of an order being returned undelivered (RTO). A seller can use these details to pick audiences, instead of relying only on age and location.

Step 3: Tune the Creatives to Convert

Creatives are the images, videos and text used in an ad. With better tracking and a sharper audience in place, the team tuned the creatives to convert. In simple terms, they adjusted the ads to turn more of the people who saw them into buyers.

The Impact: Better Efficiency and Stronger Conversion

The rebuilt signal layer, sharper audiences and tuned creatives led to measurable gains in cost, return and conversion:

What Can eCommerce Sellers Learn From Deyga?

Deyga’s results offer useful lessons for eCommerce sellers looking to get better returns from their ad spend. Here’s what to take care of:

• Check your tracking before you raise your budget: If your ad platform cannot see your orders, more spend only buys more guesswork. Fixing the data can improve results without changing the budget.
• Send events from your server as well as your browser: Browsers can lose events. A server-side connection such as CAPI gives Meta a second route to receive each purchase.
• Use what you know about your buyers: Knowing what customers buy and whether they prefer COD helps you target people more likely to make a purchase. You don’t need to depend only on age and location.

How Does fastrr Support This Customer Journey?

fastrr used its ads platform, conversion tracking and buyer data tools to improve Deyga’s Meta ad campaigns. Each played a specific role:

• fastrr Ads: Created and managed the campaigns, and helped optimise them using first-party commerce data.
• Signals and custom events: Rebuilt the conversion data sent to Meta through CAPI, so the platform could see real orders.
• fastrr Signals: Added buyer intelligence to shopper profiles, which supported sharper audience selection.

Conclusion

Most sellers respond to weak ad results by changing the creative or raising the budget. Deyga’s experience shows why accurate tracking matters when scaling eCommerce ads. Before increasing ad spend, sellers need to know whether their platforms are recording sales correctly and using that data to reach buyers.

If your own ads are not improving as spending increases, open Meta Events Manager and compare the purchases it shows with the orders in your store. fastrr Ads can be what helps you bridge any big gaps.