Finest-5 Product reads #56
Self-serve vs. sales, value metrics, assumption testing, polling, and the impact of OKRs.
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When companies that are knee-deep in an enterprise sales-led model start to chase these self-serve aspirations, they trip and tumble 100% of the time. And then… the blame game starts.
Three common excuses: Self-serve cannibalises sales revenue, Self-serve deals are not worth the time, and Product teams should focus on customers, not revenue.
Overcome challenges by investing in data analytics, defining growth metrics, understanding the customer journey, and prioritising monetization awareness
Start with interactive self-serve demos, Escalate with trials, Arrive at freemium
A value metric is a way to measure the value exchange in your product, and it is crucial for pricing, product metrics, and team building. A good value metric should be easy for the customer to understand, aligned with the value they receive, and should grow with the customer's usage of that value.
Value metrics are useful in answering two key questions: What does our ideal customer want in a product or service like ours? How much is the ideal customer willing and able to pay?
Subjective analysis and a data-driven approach can help you define your value metric. Test different hypotheses and make sure your chosen metric meets the three key characteristics of a good value metric.
To validate your value metric, use methods like the value metric scratchpad and relative preference analysis to ensure it aligns with customer preferences and expectations.
Assumptions can fall into different categories, including desirability (customer interest and willingness), feasibility (technical and logistical aspects), usability (ease of use for customers), viability (business benefits), and ethical considerations.
The advantage of running assumption tests instead of whole idea tests is that when an assumption test fails, we now know exactly what needs to change.
It's crucial to start small and gradually incorporate testing into the development process. Starting with the smallest, simplest test is a practical way to begin.
We only need to test the riskiest assumptions that could torpedo our ideas or cause harm to our customers or company.
Polling is a communication mechanism where a client system periodically checks with a server system for new data or updates. The client initiates the process by sending a request to the server at regular intervals, and the server responds with the requested data or an indication of no new data. Practical examples include e-commerce inventory updates, social media feed refresh, and monitoring system health.
Polling offers advantages such as simplicity, control over request timing, and compatibility with standard HTTP requests.
It has disadvantages like overhead due to continuous requests, potential latency between data availability and retrieval, and scalability issues with a growing number of clients.
Alternatives to polling, such as webhooks, long polling, WebSockets, and Server-Sent Events (SSE), offer different communication mechanisms based on specific use cases.
OKRs should be applied with care, considering potential side effects on focus, risk-taking, and motivation. The effectiveness of OKRs in decision-making depends on the context, with different challenges arising in uncertain and exploratory environments.
OKRs are not a one-size-fits-all solution, and their impact on decision-making can vary based on the problem space.
In inherently exploratory contexts, emphasizing learning and curiosity over specific goals may be more suitable.
In some cases, high-level goals should be approached indirectly through the means, focusing on problem-solving rather than the validation of specific outcomes.
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