Alright, buckle up token founders, because we’re diving deep into a topic that separates the moonshot projects from the… well, the ones that fizzle out. We’re talking about measuring the ROI of your social influence campaigns. Forget just watching the token price – that’s like judging a book by its cover. I recently sat down with Harry, a seasoned marketing strategist in the crypto space, to get the real scoop.
“Everyone’s obsessed with price,” Harry started, leaning back in his chair. “But that’s a lagging indicator. It tells you what happened, not why. We need to understand what drove that price movement, and that means looking at the whole ecosystem of engagement.” He gestured emphatically. “It’s about building a robust attribution model.” So, ditching the rear-view mirror approach, let’s learn from Harry how to build the attribution model.
The Attribution Jungle: First-Touch, Last-Touch, and Beyond
First, Harry broke down the different attribution models. “Think of it like figuring out who deserves the credit for a sale,” he explained. “Did the initial tweet get someone interested? Or was it the last YouTube review that sealed the deal?” The basic models are pretty simple:
- First-Touch Attribution: The first interaction that brought a potential investor into your funnel gets all the credit. Useful for understanding initial awareness campaigns.
- Last-Touch Attribution: The final interaction before the purchase (or token acquisition) gets all the credit. Great for understanding what’s closing the deal.
- Linear Attribution: Every touchpoint gets equal credit. Simple, but often inaccurate.
Harry advised these are useful but not amazing. “The problem is that these models are too simplistic in the age of decentralisation. In reality, people are consuming content from multiple sources before buying. You need to move towards multi-touch attribution to get a more accurate picture,” he explained.
Multi-Touch Attribution: The Holy Grail?
Multi-touch attribution attempts to assign fractional credit to each touchpoint. This is far more nuanced, and more accurate. Several techniques include:
- Time-Decay Attribution: Gives more credit to touchpoints closer to the conversion. This model assumes that the impact of a touchpoint diminishes over time.
- Position-Based Attribution: Gives the most credit to the first and last touchpoints, with the remaining touchpoints sharing the rest. This model assumes that the first and last touchpoints are the most important. For example, the first ad seen gets 40%, the last blog read gets 40% and the middle interaction gets 20% of the credit.
- Algorithmic Attribution: Uses machine learning to determine the optimal weighting for each touchpoint. This is the most sophisticated approach, but also the most complex to implement. Algorithmic Attribution uses Machine Learning to analyse all data (engagement, sales, brand awareness etc.) and calculates the impact of each specific touch point. This allows a business to optimise the campaign for maximum impact.
“The key,” Harry emphasised, “is choosing the model that best reflects your customer journey. Think about how people are finding out about your project and what influences their decision to invest.” He advised using the simpler models to start with, building up to the more complex models as your campaigns grow.
Setting Up Tracking: Getting Your Hands Dirty
“Attribution models are useless without data,” Harry stated bluntly. “You need to set up tracking before you launch your campaigns. It’s like building a house without a foundation.” Crucial here is UTM parameters. They are snippets of code you add to the end of your URLs. This tells you where the traffic came from (source), what type of content it was (medium), and even the specific campaign. Tools like Google Analytics and dedicated marketing attribution platforms can then ingest and analyse this data.
He suggested starting with a spreadsheet: “Manually track clicks, conversions, and associated UTM parameters for a small initial campaign. You can then use this data to build out the attribution model. Once you have the hang of this move to a professional tool”.
Beyond the Clicks: Qualitative Insights
“Don’t just focus on the numbers,” Harry cautioned. “Talk to your community. Run surveys. Monitor sentiment on social media. Sometimes, the most valuable insights come from qualitative data. What language do they use? What problems are they trying to solve?” This will help you adjust your messaging and target specific audience segments more effectively.
Optimise and Iterate: The Never-Ending Cycle
Once you’ve collected data and built an attribution model, the real work begins: optimisation. Experiment with different messaging, channels, and targeting. Regularly review your data and adjust your approach. Marketing is not a set and forget strategy. “It’s an iterative process,” Harry said with a smile. “You’re constantly learning and refining your strategy.”
In short, measuring social influence ROI for token launches requires a shift from solely focusing on token price to encompassing a broader range of metrics such as community engagement and social media reach. To accurately measure ROI, develop an attribution model, set up appropriate tracking mechanisms, and collect relevant data. This is the foundation to analyse results and optimise future campaigns.