What's your process for cross-functional marketing campaign experiments?

To execute cross-functional marketing campaign experiments effectively, start by setting clear objectives and KPIs with input from all relevant departments (sales, marketing, product, customer service). Brainstorm and rank experiment ideas that align with these goals. Formulate hypotheses for expected outcomes, detailing how they impact the customer journey. Assign roles and set timelines for each experiment, utilizing agile methodologies for flexibility. Review outcomes regularly with all stakeholders, integrating findings to refine and improve future campaigns. This collaborative and iterative approach ensures experiments are comprehensive and aligned with broader business objectives, enhancing overall campaign effectiveness.

Start with clearly defined purpose and scope of the experiment. For instance, if we were launching a new product, our goal might be to increase the sell through rate by targeting a specific audience segment. I would start by outlining the hypothesis and aligning with the team. The next step is to define the target audience, example returning customer targeted with personalized product recommendation based on their previous purchase. Other variables would be creatives, geography and demographics. Set success criteria and then measure the right KPI's and in this case, CTR, conversion rate, and ROAS. This alignment ensured smooth execution and data-driven decision making.

When planning experiments, attention to details and team alignment are crucial. Clearly define what is the hypothesis, define what is success, establish the timeline of the experiment, budget, channels, segmentation strategies. Align the resource requirement like creatives. By doing this you create a structured framework that ensures everyone alignment and setting up a common goal. Plan your experiments and meticulously collect all related data to understand the campaign performance. If successful, think about how to scale and if fails, think about the key learnings. Document everything for future reference and best practices.

Execution is key to success. Ensure the experiments are compliant with relevant regulations (GDPR, etc) and approach each channel knowing its uniqueness. Start your experiment small by selecting the sample size based on your hypothesis. Have multiple approach but make sure to document each of them so that you can track the performance and understand which one to scale. Constantly update your team so that they are aligned and part of the journey. Don't hesitate quick corrections or adjustments. Remember its an experiment so approach with a 'pinch of salt'.

This is moment of truth. Approach analysis with open mind and don't get stuck to you hypothesis. Be ready to challenge your thoughts that will help you to achieve best results. Don't start with the end result in mind, but keep them as a moving post and be ready to elope the outcomes to improve your learnings and outcomes. While analysing, check for any known patterns or trends, compare them with your previous experiments and be curious. Analysis phase both help you to validate and invalidate your hypothesis.

I would communicate both good and bad. Celebrate both success and failure. Remember it was a experiment and successful experiment helps to make better decisions and deliver stronger ROAS. Communicate with numbers, use bullet points to highlight the outcomes, especially when reaching out to your senior leadership team. Leave the details behind as addendum. Mark each experiment, name them (we usually named our experiments), I used 'lunch and learn' and showcased the results to involve cross functional teams to attract their attention and support.