An activation metric is a key performance indicator (KPI) that measures how well your product or service is engaging customers. It’s important to businesses because it provides insight into customer behavior and helps them understand what drives retention. In this blog post, we will outline the three-step process outlined by Lenny Rachitsky for finding an activation metric for multi-player B2B Software as a Service (SaaS) products.
Step One – Brainstorming Potential ‘Aha’ Moments
The first step in finding an activation metric is brainstorming potential ‘aha’ moments that can be used to measure customer engagement. What’s a ‘aha’ moment? It’s the moment when a customer realizes the true value of your product or service. If you can identify the key features that generate these moments, then you can use them as a way to measure customer engagement and retention.
To help you identify these ‘aha’ moments, here are some tips:
• Look at successful multi-player B2B SaaS products and figure out what made them successful. What features or functions do they have that make them stand out?
• Talk to existing customers and ask them which features they found most valuable. This will give you insight into what your customers are looking for in your product or service.
• Focus on forming habits around your product rather than just having an ‘aha’ moment. Habits give customers ownership over their experience and increase their loyalty.
Once you have identified potential ‘aha’ moments, you can move onto step two – running correlation analysis to establish milestones-retention relationships.
Step Two – Running Correlation Analysis To Establish Milestones-Retention Relationships
Correlation analysis is a statistical technique used to determine the relationship between two variables – in this case, milestones and retention rates. By running correlation analysis on your data set, you can identify which milestones have the strongest correlation with higher retention rates and use those as potential activation metrics for measuring customer engagement with your product or service.
When interpreting the results of correlation analysis, there are several things to keep in mind:
• The strength of correlations should be evaluated based on both magnitude and direction of effect size
• When analyzing data sets with multiple variables, it is important to consider all factors that may affect the outcomes
• Consider how correlations may change over time due to changing user behaviors or preferences
Once you have identified potential milestone-retention relationships through correlation analysis, it is time for step three – running experiments to identify activation metrics that drive retention rates.
Step Three – Running Experiments To Identify Activation Metrics That Drive Retention Rates Once you have identified potential activation metrics from steps one and two, it is now time to run experiments in order to test if these metrics truly do drive higher retention rates for your product or service. When running experiments, there are several things to consider such as sample size (how many users will be included in each experiment) and length of experiment period (how long each experiment should last). Additionally, it is important to analyze the results of each experiment carefully so that you can make informed decisions about which activation metrics are most effective in driving higher retention rates for your product or service.
Conclusion:
In summary, establishing an effective activation metric for multi-player B2B SaaS products involves three steps – brainstorming potential ‘aha’ moments; running correlation analysis; and running experiments with users – all of which need to be done carefully in order to ensure accurate results. With this information in hand, project founders and CEOs will now be better equipped to create an effective activation metric for their business venture!
