Using Subscription App Benchmarks to Make Better Growth Decisions — Phil Carter, Elemental Growth
发布时间 2024-12-23 10:00:00 来源
摘要
On the podcast we talk with Phil about how to effectively use benchmarks to aid decision making, the limitations of benchmarks, and why even the best companies aren’t top quartile in every single metric.Top Takeaways:📏 Benchmarks are a starting point, not a roadmapTreat benchmarks as directional indicators to uncover growth opportunities and prioritize actions, but don’t chase them blindly. They work best as tools for identifying areas to explore rather than metrics to perfect.🏆 Focus on strengths over chasing perfectionIt’s unrealistic to aim for excellence in every area. The most successful companies lean into their strengths, improve key weaknesses, and focus resources where they will make the biggest impact.⚔️ Beware of misleading benchmarksNot all benchmarks are helpful. Poorly sourced, overly generic, or irrelevant data can lead to wasted effort or misguided decisions. Use benchmarks that are specific to your category, geography, or growth stage.🔍 Metrics only matter with contextNumbers on their own don’t tell the full story. A high churn rate might be fine if you acquire users cost-effectively and retain high-value customers. Metrics need to be interpreted with a deep understanding of your product and target audience.💡 Data is powerful, but intuition seals the dealData highlights where to focus, but the most effective decisions come from pairing metrics with experience, intuition, and a clear understanding of your customers. This balance of analysis and instinct drives smarter, more impactful strategies.About Phil Carter👨💻 Growth Advisor at Elemental Growth, a consultancy dedicated to scaling consumer subscription companies through actionable benchmarks and strategic insights👥 Phil Carter is committed on empowering consumer subscription companies to achieve sustainable growth by leveraging benchmarks, refining growth strategies, and identifying key opportunities for value creation, delivery, and capture.💡 “Where people get in trouble with benchmarks is they try to make them the end-all. be-all right. They try to do more with them than they really should be.”👋 LinkedInResources:Elemental Growth WebsiteFollow us on X: David Barnard - @drbarnardJacob Eiting - @jeitingRevenueCat - @RevenueCatSubClub - @SubClubHQEpisode Highlights:[1:37] The Subscription Value Loop: Phil introduces his framework for driving sustainable growth through value creation, delivery, and capture, and how it applies to subscription businesses.[5:52] Benchmarks as tools: Phil explains how benchmarks are a directional tool to guide decision-making and identify growth opportunities rather than an end-all, be-all.[13:07] Judging good ideas: The team discusses how great execution relies on judgment and filtering good ideas to focus on what moves the business forward.[20:53] Using the Subscription Value Loop: Phil shares how the framework acts as a diagnostic tool for spotting bottlenecks in client businesses and setting growth priorities.[24:47] The impact of pricing and free value: Phil describes a fitness app’s challenge with over-delivering value for free, resulting in low subscription conversion rates and pricing adjustments.[30:26] The power of subscription retention insights: Phil explains how understanding differences in retention between annual and monthly subscribers can shape pricing and product strategy.[36:32] Interpreting benchmarks through context: The hosts discuss how benchmarks differ based on the business model, user acquisition strategy, and market dynamics.[42:46] Paid vs. organic growth strategies: Phil underscores the risks of being overly dependent on paid ads and the value of diversifying acquisition through organic channels.[47:18] Value capture and monetization: Phil explores strategies for optimizing conversion rates, pricing, and paywalls to increase revenue capture from free users.[55:45] What’s next for the Subscription Value Loop Calculator: Phil shares plans for enhancing the tool with better data, new filters, and expanded benchmarks in future versions.
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