Marketing ROI: How to Increase Your Profit Return by Five

Many people still underestimate channel impact and customer lifetime value on their marketing ROI. Therefore, it is essential to adopt a complex multi-attribution model considering customer profitability and allocate marketing budgets accordingly. Discover how we manage to get a fivefold profit return on our marketing spends.

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Implement a modern CLV-driven approach to improve your marketing ROI

Marketing Attribution

Most customer journeys consist of various touchpoints until they lead to an order. Therefore, it is essential to find out which marketing channel contributes how much to which order. That’s the aim of attribution modeling. It assigns a percentage distribution of each order to all involved channels.

Profit Contribution

Take a closer look at customer value. Depending on order frequency, average order value, return rate, and many more factors, some customers will turn out to be more important profitability drivers than others. This can be defined as customer lifetime value (CLV).

Budget Allocation & CLV Steering

When allocating budgets to marketing channels, we need to consider short-term tasks like daily channel operations or monthly attribution optimization as well as long-term strategic business decisions. Therefore, we define a break-even target for each country or brand shop.

Which attribution model is best suited to you?

Last Click Model

While easy to setup, the Last Click Model does not reflect the whole truth and leaves too many questions unanswered. The conversion funnel consists of several steps: awareness, interest, desire, and action. Each of these steps is connected to a touchpoint. And each of these touchpoints drives your conversion process: organic and paid search, referrals, or even social media influencer activities.

“Bathtub” Model

In the Bathtub Model, the first and last touchpoints are credited with a higher attribution percentage than the remaining touchpoints in between, which are equally distributed to the rest of the attribution percentage. However, you will see that this approach still lacks in reliability and needs improvement, as it highly depends on subjectively assigning credits.

Rule-Based Model

The Rule-Based model follows an algorithm reflecting key drivers for generating online orders, leading to the most accurate attribution available. For example: how much time did a customer actually spend evaluating an item? Was the item added to a wishlist? The percentage attribution for each criteria will differ for each customer and must be predetermined with statistical attribution modeling methods.