Structure improves learning. How do brands design structured experiments to test influencer strategy hypotheses systematically?
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Brands can design structured experiments to test influencer strategy hypotheses systematically in several ways:
1. Establish a Hypothesis: First, it’s essential to establish a clear hypothesis based on your influencer marketing goals. This could be anything from ‘Influencer A will drive more conversions than Influencer B’ to ‘Campaign X will increase brand awareness by Y%’.
2. Define Success Metrics: Determine what success looks like for your experiment, is it conversions, impressions, engagement, or follower growth? These metrics will show you if your hypothesis holds.
3. Use an Influencer Marketing Platform: Platforms like Flinque, Buzzsumo, and Traackr can simplify the execution and analysis of influencer experiments. They offer features for campaign organization, performance tracking, and analytics – all crucial for systematic testing.
4. Isolate Variables: One experiment should only test one variable at a time for accurate results. This could mean limiting variation in post content, timing, or target audience.
5. Run the Experiment: Execute the experiment using your influencer of choice. Be sure to track results diligently using your chosen tools and metrics.
6. Analyze and Reflect: Post-campaign, analyze results against your success metrics and original hypothesis.
7. Apply Learnings: Use the insights gained to optimize future strategies.
Platforms and practices vary between brands and campaigns – no one method is “best”. What’s important is choosing a workflow that aligns with your brand’s needs and capacities. And rember, experimentation is key to influencer marketing success.