How can you balance experimentation and innovation with best practices in your marketing optimization?

Yes before start, Set SMART goals and link your metrics with them to experiment and evolve. These goals should represent your marketing KPIs.

Goals and metrics are critical without a doubt and making them SMART ensures they have clarity in execution. In addition, consider how these goals cascade down from the overall business strategy. Don’t develop campaign goals that are siloed in the impact towards your overall business strategy. Also don’t create them in a vacuum, engage the various stakeholders involved in the successful execution of the campaign from sales to business development to even customer service and tech support in some cases and ensure everyone understands what success looks like in this regard. Finally recognise that being rigid on the outcome will keep you from being innovative and iterating throughout the campaign. So plan for agile changes along the way.

Experimental and innovative methods are scientific and reasonable. Find problems, generate hypotheses, design experiments, collect data, and draw conclusions. This prevents ineffective or destructive ideas and ensures data-based solutions.

To be a successful marketer this is a critical skill. Never stop learning or lose your curiosity. It is important to learn new tools, stay on top of trends, test new technologies (or at least explore their potential impact in your efforts), attend conferences, and ask what else can marketing do to drive business results. What works today might not work in a week or month so keep on testing. Be prepared for change. A solid marketing plan has many components, doesn't rely on one tactic/platform, and includes room for testing new ideas, concepts, technologies etc.

Know that experimentation and optimization do not always equal A/B or multivariate testing. Most websites or marketing campaigns won't have enough volume to make statistically significant, repeatable observations. Implementing ideas, doing pre- and post-analyses, and batching data together from several implementations to understand outcomes is fine. This approach makes experimentation way more accessible for most organizations.

The best marketing optimisation practices is aligning and connecting all marketing functions, also connecting results from different departments. One of the useful practices for example is data fusion. Where data analysis results are verified by profiling team through calling customers and verifying the findings, then using the findings to create the persona that is used by the communication team to use it in campaigns. Finally, communicating campaign results to analysis and profiling team to refine their processes. It is continuous learning optimisation.