How well do you understand the way your users interact with your product? For early-stage startups, this question isn't just important — it's everything.

In this post, we’re going to discuss why event mapping is significant, what its operational costs are to startups, why they must practice it anyway, and finally, how it could potentially be improved.

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WHAT IS EVENT MAPPING?

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Event mapping, at its core, is a process of tracking specific user interactions, or ‘events’ within a product. Whether it's clicking a button, completing a purchase, or even exiting the app, these events hold valuable insights into user behavior.

So,  why is event mapping so crucial?

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1. Unveiling User Engagement:

‍Event mapping helps you identify which features are most used, which ones are ignored, and how frequently users interact with your product. This can guide your product development efforts towards what users truly want and need.

2. Decoding the User Journey:

‍By tracking the sequence of events a typical user goes through, you can gain a comprehensive understanding of the user's flow through your product. This is invaluable in identifying any points of friction or areas where users tend to drop off.

3. Assessing Feature Effectiveness:

‍Events related to specific features provide data on how these features impact user behavior and engagement. This can influence decisions on feature updates, improvements, or even removal.

4. Guiding A/B Testing:

‍If you're testing different versions of a feature, event mapping can reveal which version resonates better with your users, helping you make data-driven decisions.

For early-stage startups, event mapping takes on an even greater significance. In the early stages, understanding user behavior, validating product-market fit, and iterating quickly based on user feedback are essential to survival and growth. Event mapping can provide the data-driven insights necessary to guide these efforts.

Nevertheless, these benefits are all reasons that startups must employ event mapping despite the associated costs.

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‍COSTS OF EVENT MAPPING

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1. Tooling & Infrastructure:

• Event Tracking Tools: Tools like Mixpanel, Amplitude, and Segment are essential for capturing and managing event data. Each of these tools have their own pricing models, which can depend on factors such as the number of tracked events, the number of active users, and the specific features or services used.

• Server Scaling: As the volume of data increases, so does the need for more powerful servers or cloud-based solutions like AWS or Google Cloud. Costs grow with the amount of data processed and stored, the computational resources required, and the bandwidth used.

• Database Management Systems (DBMS): Managing large volumes of event data often requires a robust DBMS like PostgreSQL and MySQL, or a distributed system like Apache Cassandra. Licensing and maintenance costs for these systems can be substantial, and they may even require additional server resources.

• Data Integration and Transformation Tools: Tools like Stitch or Talend (which costs $12,000 annually!) can be used to integrate and transform data from different sources, which is often necessary when dealing with event data.

• Data Security: Protecting the stored and processed data is crucial, and this can involve costs for security tools and practices, including encryption, intrusion detection systems, and regular security audits.

2. Operations:

• SDK Integration: Incorporating your codebase into your tool of choice is quite arduous. Moreover, it may even require additional developer training if they are unfamiliar with the particular SDK.
  

• Event Logging: Developers need to ensure that every important user interaction or "event" is being accurately captured and logged. Depending on the complexity of the user interface and the number of distinct events, this can be a significant task.
  

• Testing and Quality Assurance (QA): Event tracking implementation must be thoroughly tested to ensure data accuracy. This includes testing under different user scenarios, testing different event types, and stress testing under high event volumes.
  

• Maintenance: Event tracking code will need to be maintained and updated over time, particularly as the product evolves and new features are added. This ongoing development effort is an often overlooked cost.

• Documentation and Training: It's important for developers, product managers, and data analysts to understand the event tracking setup, including what events are being tracked and how the data is being captured and processed. Creating comprehensive documentation and providing necessary training is crucial, but also contributes to the operational costs.‍

• This is arguably the most significant operational cost, given the inefficiencies it causes in terms of knowledge and project management.

3. Data Management:

As event mapping scales, so does the volume of data generated. This creates another set of hurdles that companies have to grapple with while scaling in general.

• Data Volume and Storage Costs: The growth of event data can lead to linearly increasing costs in cloud storage solutions like Amazon S3 or Google Cloud Storage. Data transfer fees can also add to the cost.

• Data Processing Costs: Large-scale data processing with frameworks like Hadoop or Spark can be resource-intensive, leading to rising CPU, memory, and runtime costs.

• Data Intergity: Ensuring this requires time and resources for data audits, and potentially ETL pipelines for data cleaning and standardization.

• Data Compliance and Security:Compliance with regulations like GDPR or CCPA is crucial, and non-compliance can lead to significant fines.

• Data Analysis and Visualization Tools: As data volume grows, more advanced analysis tools (like Tableau or Looker) may be needed, adding to the cost.

• Data Retention and Archiving: Long-term storage of historical data can increase storage costs, especially when using archiving solutions like AWS Glacier.

• Data Infrastructure and Maintenance: Robust data infrastructure for large-scale event data includes servers, databases, and DBMS, all of which come with procurement, setup, and maintenance costs.

4. Analytical Costs:

The true value of event mapping comes not just from capturing data, but from analyzing it to gain actionable insights. This often requires the hiring of skilled data analysts who can make sense of the data and transform it into meaningful recommendations.

• Data Analysts and Data Scientists: Hiring experienced data professionals is crucial for interpreting event data. These positions often command high salaries, given the specialized skills required. This is magnified because of how much of data workers' bandwidth goes into interpreting data for other verticals within an organization.

• Data Modeling and Machine Learning: A facet that is increasingly important, developing predictive models or implementing machine learning algorithms to uncover patterns in event data can be resource-intensive, and may require specialized software or computing resources.

• Data Visualization: Creating intuitive and informative visualizations is a key part of data analysis. While some tools include visualization capabilities, others may require additional software, such as D3.js or Plotly.

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CONCLUSION

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In conclusion, event mapping, while indispensable for early-stage startups, involves a variety of costs. These range from data management and analytical costs, to expenses for tooling, infrastructure, and operational aspects. Despite these, the invaluable insights gained through event mapping make it a worthwhile investment for startups striving to understand their users better.

Here at Crunch, our goal is to help you leverage the benefits of crucial processes like event tracking, whilst mitigating a lot of the associated costs we spoke about above.

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Want to find out how?

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Signup for our waitlist here!

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