In the world of marketing, the attractiveness of virality often leads us down a path littered with one-hit wonders and unrepeatable successes. The fascination with dissecting viral phenomena, while ignoring the countless attempts that fall short, presents a skewed perspective on what it truly means to ‘go viral.

It’s crucial to understand that virality isn’t a secret recipe that can be replicated at will. 

Virality is an outcome that can only be optimized through careful analysis and understanding of both successes and failures. Only looking at successes gives you a tiny piece of the full puzzle. Why? Because there are so many more failures than success stories.

The field of marketing research is riddled with studies that focus on singular instances of success, using datasets that lack generalizability. This approach leads to a plethora of unreliable marketing guides that promise virality based on one-time analyses of possibly unreliable datasets or unique cases. These sources often fail to replicate their success in different contexts or with different audiences, leading to misinformation among marketing professionals.

I mean, we’ve all seen those people on Instagram promising to help your content go viral every single time with their secret 3 step strategy right?

Karine Nelson-Field, a renowned researcher in viral marketing, emphasizes the importance of relevance and rigor in marketing research. She argues that true insights into viral marketing come from studies that produce repeatable results across various datasets, using transparent methodologies. Research that is relevant and rigorous creates strategies and insights that are not only successful in a single instance but can be applied broadly across different scenarios.

The truth about statistical significance

Contrary to popular belief, statistical significance in research does not necessarily equate to real-world applicability. Geoff Cumming, a distinguished statistician, points out that the p-value often used to denote significance is more an indicator of variability within a sample than a reliable predictor of success. He cautions against the narrow interpretation of ‘significance’ and stresses that statistically significant results can be misleading, as their replication potential is often weak.

This is exemplified by an attempt by Bayer Pharmaceuticals to replicate 67 published studies on drug efficacy, where nearly two-thirds failed to produce the same results. Such findings highlight the fragile nature of replication in scientific research, underscoring the fact that context, luck, and timing play significant roles in the success of any marketing endeavor.

The key to rigorous research, as Nelson-Field suggests, lies in replication. Only when results are consistent across a range of conditions can they be considered reliable for making predictions. This principle is often overlooked in the rush to replicate viral successes, without understanding the unique factors that made them stand out from the failures.

So how should we move forwards as marketers and business leaders? 

Achieving virality in marketing is not about following a step-by-step guide.  Your goal should be to understand the complex interplay of factors that contribute to success in your case. It involves studying both the successes and the failures, looking for patterns that can be applied across different contexts and then extrapolating that data and applying to your business objectives.

By focusing on research that has stood the test of time and replication, marketers can better optimize their chances of going viral, rather than chasing the elusive promise of guaranteed virality.