Square Image

Mohammad Ashraf

Engagement Lead

Attribution Basics

Introduction to Attribution Modeling

Saras Analytics builds bespoke data solutions for eCommerce brands. Their products Daton and Pulse enable brands to build a single source of truth for marketing, operations and finance teams across DTC, Amazon, and retail channels.

In This Article:

In the ever-evolving landscape of direct-to-consumer (DTC) brands, acquiring new customers is critical for growth. Particularly for subscription-based models, the acquisition of a high-quantity of customers isn’t sufficient. They would need to acquire high-quality customers as well, which would lay the bricks for future sustained success.

To optimize their marketing budget, marketers need to know 3 main things: which platforms to spend on, which content or themes to spend on, and where one can spend aggressively versus conservatively.

Yet, optimizing budgets to reach these objectives requires a deep understanding of customer behavior and the effectiveness of marketing efforts. This is where attribution and attribution modeling comes into play.

Attribution is the process of identifying the sources that influenced each customer to make their initial purchase with the brand.

Why understanding acquisition sources is critical

For DTC brands, especially those operating on a subscription basis, not all customers hold the same value. Some customers contribute significantly more to the brand's lifetime value and profitability as compared to others.

Attribution isn’t the only spending optimization solution. Traditional spend optimization solutions also include the likes of Marketing Mix Modeling (MMM) which have been widely used. MMM is ​a technique which helps brands quantify the impact of numerous marketing inputs on their sales or Market Share.

However, its flaw lies in its ability to provide only aggregated answers. In contrast, attribution offers a more granular, customer-level perspective, making it particularly effective for subscription-based DTC brands.

With attribution, brands can measure and track various important metrics at both an aggregate and channel level. This is critical as it gives brands the necessary macro and micro level of insights they need to guide their growth.

These metrics include Customer Acquisition Cost (CAC), Customer Lifetime Value (LTV), Return on Ad Spend (ROAS), and more. Using these metrics, brands can allocate their spending efficiently, and also accurately identify the campaigns that are and are not working.

Data sources for implementing attribution modeling

To effectively implement attribution modeling, brands rely on a combination of online and offline data sources.

Online data sources

Online data sources such as Google Analytics 4 (GA4) and the Shopify Customer Journey API offer valuable touchpoint data. This data allows marketers to stitch together the customer journey leading up to acquisition. This way, they will have a clear understanding of the entire process.

Using that data and information, businesses can build different types of attribution models. These include First-Click (FC), Last-Click (LC), Last Non-Direct Click (LNDC), Linear (L), Time-Decay (TD), U-Shaped (US), W-Shaped (WS), and more. This is important because it enables brands to build them out accurately, and be able to tap onto the insights offered by these models.

Submit the form to read the full article

 Ready to know
your customers better?

View Interactive Demo