Fast Failing Culture

Hypothesis Methodology and Optimization

If you want different results, you have to change your current methods or approaches. Therefore, using an overall experimental approach lies in our core.

Thinking differently and daring to make brave decisions. This, by having a clear plan for tests, implementation and follow-up process. Sounds easy, but what does it really mean?

We strive to establish a fast-failing culture together with our partners. This helps us confidently test disruptive thoughts and unconventional approaches while working with a data-driven mindset.

Our process looks a little bit like this.

1. Data-driven hypotheses
2. Planning of test
3. Implementation of test
4. Set time frame for test phase
5. Analysis and evaluation
6. Iteration of text
7. Summary of learnings
8. Ideation of new data-driven hypotheses
9. And on and on…

With the tool box of marketing automation there are endless possibilities of tests to implement.

Send Time Optimization

Send time optimization involves determining the optimal times to send marketing communications, ensuring the highest likelihood of recipient engagement. By utilizing send time optimization, businesses can increase open rates, click-through rates, and overall campaign effectiveness, tailoring their outreach to when their audience is most active and receptive.

A/B tests

A/B testing involves comparing two versions of an element against each other to determine which works better in achieving a specified goal. By using A/B testing, businesses can make data-informed decisions, optimizing their content and design to enhance user experience and conversion rates.

Control groups

Control groups are a subset of participants in an experiment who do not receive the treatment or intervention, serving as a baseline to measure the effects of that intervention. By using control groups, researchers can isolate and understand the true impact of an intervention, ensuring results are due to the treatment and not external factors.

Marketing Persuasion Framework

Evaluates the balance between credibility, emotion, and logic in messaging to resonate with various target audiences. By calibrating these elements, marketers can craft compelling narratives tailored to distinct audience preferences, maximizing engagement and driving desired actions.