- Experiments must run direct-response content, which asks the target to do something. This generates data for you to optimize.
- Test creative and content on landing pages, banner ads, Google AdWords, native ads and email.
- Insights gained from testing can be applied to other mediums. Digital testing insights can apply to traditional marketing. Direct response insights apply to brand.
- Experiments must include a control and variable. Control is what stays the same. Variable is something changed. Document your control and variable to stay organized.
- Design experiments to test only one variable at a time. Isolating one variable proves that a result or effect from the test can be attributed to one, singular change. For example, if testing call to actions on banner ads, keep the banner color, timeframe, channels, visual hierarchy and font the same on both banners, but change your message or CTA only.
- When you place content, make sure the person viewing the content sees only one version every occurrence. Convert.com, Optimizely or Google Experiments help accomplish this task.
- Determine a KPI (key performance indicator). Get as close to the money as you can. For example, a manufacturer with complex distribution would measure actions that indicate leads – like a button that takes customers to the distributor’s website or counting phone calls.
- Segment experiments by persona. Every persona responds differently to the same stimulus. These differences gives us insights into the persona.
- Limiting your experiment to target one persona per experiment shows you the most efficient way to reach that individual persona.
- Channel v. channel tests are valuable. Use one piece of content and test its targeting within a channel. For example, use interest targeting (control) v. behavioral targeting (variable) on Facebook to learn which yields the best traffic.
- Strive for statistical significance when analyzing results. If you ran this experiment more than once, what is the probability the outcome would be the same as what you just calculated? Use a statistical significance calculator to determine that confidence. The higher the percentage (95% or more) the more significant. But there are other factors to keep in mind when applying insights based on statistical significance.
- Experimentation and optimization is the fifth actionable component of Iterative Marketing.
Charity of the Week:
Six Actionable Components are the actions we take as marketers to implement Iterative Marketing. They don’t have to be implemented all at once. They are:
- Brand Discovery: Uncover how your buying audience feels about your product or service and how they rationalize the decision to buy.
- Persona Discovery: Document the individuals involved in the buying process in a way that allows us to empathize with them in a consistent way.
- Journey Mapping: Plot the stages and paths of the persona lifecycle, documenting each persona’s unique state of mind, needs and concerns at each stage.
- Channel and Content Alignment: Align every piece of content and marketing channel/activity to a primary persona and primary marketing stage, identifying new channels and content needs where opportunities exist.
- Experimentation and Optimization: Conduct thoughtful experiments designed to produce statistically significant business insights and apply the results to optimize performance.
- Reporting and Feedback: Report and review data and insights to drive decisions in content and strategy, as well as information to be used by the organization as a whole.
We hope you want to join us on our journey. Find us on IterativeMarketing.net, the hub for the methodology and community. Email us at email@example.com, follow us on twitter at @iter8ive or join The Iterative Marketing Community LinkedIn group.
The Iterative Marketing Podcast is a production of Brilliant Metrics, a consultancy helping brands and agencies rid the world of marketing waste.
Onward and upward!