Independent coffee brand Oakbrew Roasters transformed their customer acquisition by partnering with Adzeta to focus on predicted lifetime value, significantly boosting high-value customer growth and optimizing ad spend.
Oakbrew Coffee Roasters is an independent, direct-to-consumer brand specializing in ethically sourced, premium roasted coffee beans and subscriptions, dedicated to quality and unique flavor profiles.
With a focus on subscription LTV, Oakbrew found standard ad metrics (CPA for first order) didn't identify which new customers would convert to high-value, long-term subscribers.
Relied on optimizing Google & Meta ads for initial purchase or website sign-up, leading to unpredictable LTV and difficulty scaling profitable customer acquisition.
Adzeta implemented its Predictive AI to forecast LTV from initial interactions, enabling Value-Based Bidding focused on acquiring high-potential subscribers.
Leveraged first-party data to train LTV models, then integrated predictive signals with Google (tROAS) and Meta (Value Optimization) campaigns. A/B tested against previous strategy.
Secured a 3.5x surge in high-value "VIP" customer acquisition and slashed CAC by 50% for these segments, all thanks to Adzeta's predictive LTV insights.
How traditional e-commerce advertising often fails to identify and efficiently target high-value customers, leading to wasted budget.
E-commerce brands spend millions on customer acquisition with no way to identify which customers will be profitable long-term. This leads to wasted ad spend on low-value customers and missed opportunities with high-value ones.
Conventional ROAS metrics are limited to early purchases, making it impossible to optimize for customers who will generate the most lifetime value.
Even companies with robust data warehouses struggle to turn their data into actionable insights for smarter bidding strategies.
We developed custom machine learning algorithms analyzing Oakbrew's 100+ customer behavior signals (purchase history, site engagement, product preferences) to predict future LTV with high accuracy (e.g., 92%).
Our platform automatically adjusted bids on Google & Meta based on this predicted customer LTV, not just initial conversion likelihood, ensuring higher bids for higher potential.
We integrated marketing, customer, and revenue data to create a complete view, then seamlessly passed predictive LTV signals to ad platforms via API for real-time optimization.
Adzeta's system continuously learned and improved, automatically adapting bidding strategies as customer behavior patterns and market conditions evolved for Oakbrew.
Adzeta's predictive approach didn't just improve metrics; it fundamentally changed how Oakbrew Coffee acquires customers. By focusing on LTV, they built a higher quality customer base, leading to more predictable revenue and sustainable growth. They could confidently scale their ad spend knowing it was directed towards real profit.
If you're looking to move beyond basic ad metrics and build a truly profitable, scalable customer acquisition engine, Adzeta's Predictive AI and Value-Based Bidding can help.