How do you integrate experiments with other channels?

To seamlessly integrate experiments across channels, start by defining clear objectives that align with your overarching business goals. Leverage a unified data platform to track user interactions across all touchpoints. Utilize A/B testing tools that work across web, email, social media, and ads to ensure consistency in your experiments. Analyze the data to understand how changes in one channel affect performance in others. Communicate findings and adjust strategies in real-time to optimize for cross-channel synergy. This approach not only enhances customer experience but also maximizes ROI by ensuring that all channels work together towards common goals.

No two channel have similar target audiences and hence where possible: - keep the audience as like to like - if the experiment in an advertising platform, ensure similarity in bidding strategies and align those to your KPI/experiment metric. - define time to see results. If you are on slim budgets, reconsider testing all together.

Example' a bit off. If the idea is channel experimentation, message variation is uncalled for. While the msg may not replicate itself 100% like to like across channels due to nuances and thus the experimenter needs to show finesse is managing that aspect.

In my experience, many experiments fail to achieve the intended objectives because of too much importance provided to some parameters and too little to others. Once, you understand the key objective of the experimentation, then it becomes very clear what parameters to consider. In most situations, the experiments are being done to maximize the response rates of campaigns or to measure the effectiveness of specific channels. If the objective is former, make sure the following parameters are considered - customer segments / micro-segments, messaging, channel and the timing, preferably in the order. Also, time your experiments such that there is no scope for anomaly or external influence.

In my experience, I've seen a lot of enterprises being reluctant to go past AB testing as part of their experimentation strategy. If you want your brand to be a pioneer, then it is important to being brave in experimentation, which is where all the fun lies. It's not that you have to wait for the experimentation to run until the specified duration is met. One of the experimentation techniques, Auto Allocation waits to pre-determine the potential winner well before the duration and starts delivering that variation to more of the audience. Similarly, you should also go beyond experimenting only those parameters within an email or a web page and move to experimenting the entire journey. This will uncover insights that you've never thought of.

One of the weirdest things about experiments is that it encourages marketers to make mistakes. Unless you fail and learn, you limit your potential to coming up with hypotheses that have the potential to turnaround your marketing campaigns. Also, it is important to keep challenging the experiment winner with new challengers over specific frequency to ensure you are being dynamic to changing variables over time and continue having the variant with high potential gets served to your audiences.