The concept of “value” lies at the heart of every product, whether physical or digital. When users perceive value, they engage with the product; if they don’t, they stop. The most successful digital products today share a few key characteristics: they make life easier, more affordable or more convenient for their users.
For product owners, identifying the behaviours that demonstrate users are finding value in your digital product is essential for achieving lasting success. Recognising the moment users experience value can help you attract more users, enhance their satisfaction and ultimately boost revenue. In today’s digital-first world, this value exchange is not always directly linked to money. For instance, user attention can be monetised through advertising, or user data can be used for training machine learning models.
As business profit models grow more sophisticated and complex, understanding how your users derive value from your product becomes more and more important.
Digital product analytics offers a window into the product’s performance, user behaviour and preferences. By tracking the right metrics, you can uncover patterns and insights from real user data collected.
What Are Product Analytics Metrics and Why Are They Important?
Product analytics metrics are quantitative measures used to track and assess the performance of a digital product. These metrics capture how users interact with your website or app, and illustrate how those interactions impact your business.
Product metrics provide insights into various aspects of user interaction, engagement and overall product effectiveness. By analysing these metrics, you can identify areas for improvement, validate assumptions and make decisions based on real user data. Various teams, including product development, marketing and customer success, utilise this data to gain user insights. Companies leverage these metrics to set product roadmaps and strategies, forecast revenue, segment markets and test out hypotheses.
Common Product Metrics to Track
To effectively analyse your product’s performance, it’s essential to understand the different types of product analytics metrics, such as:
Engagement
Engagement metrics track how actively users interact with your product over time. For instance, high engagement metrics indicate that users find your product valuable. Key metrics include:
- Daily active users (DAU): Number of unique users who interact with the product on a daily basis.
- Session duration: Average time users spend on the product per session.
- Feature usage frequency: How often specific features or functions of the product are used.
The AAARRR, or Pirate Method as it’s commonly referred to, is a standard product analytics metrics framework used to systematically analyse the customer life cycle:
Awareness
Awareness metrics measure how well your product or brand is known in the market. These metrics help you understand the effectiveness of your marketing campaigns and the overall visibility of your product. Key metrics include:
- Brand awareness: Percentage of target audience that recognises or recalls your brand.
- Reach: Number of unique users who have seen your content or advertising.
- Impressions: Total number of times your content or ads are displayed on a user’s screen.
Acquisition
Acquisition metrics focus on how users discover and access your product. These metrics help you evaluate the effectiveness of your marketing efforts and identify the most successful channels for attracting new users. Key metrics include:
- Number of new users: Total number of new users acquired over a specific period.
- Traffic sources: Breakdown of where users come from (i.e. organic search, paid ads or social media).
- Cost per acquisition (CPA): Calculated by dividing the total cost of marketing and sales activities by the number of new users acquired.
Activation
Activation metrics measure the initial user experience and how successfully new users complete key actions. Understanding activation metrics helps you optimise the onboarding process so users quickly realise the value of your product. Key metrics include:
- Onboarding completion rate: Percentage of users who complete the onboarding process.
- First use experience: Time taken for a user to reach the first key action after signing up.
- User activation rate: Calculated by dividing the number of users who have performed the activation event by the total number of users.
Retention
Retention metrics measure how well you retain users over time. These metrics help you to understand user loyalty and identify factors contributing to long-term engagement and product-market fit. Key metrics include:
- User retention rate: Percentage of users who continue to use the product over a specific period.
- Churn rate: Percentage of users who stop using the product over a particular period.
- Cohort analysis: Analysis of user groups based on shared characteristics over time.
Revenue
Revenue metrics track the financial performance of your product, which is crucial for assessing and identifying opportunities to increase revenue. Monitoring these metrics provides insights into financial efficiency and profitability. Key metrics include:
- Average revenue per user (ARPU): Calculated by dividing the total revenue generated during a time period by the number of users.
- Lifetime value (LTV): This shows the total anticipated revenue generated by the average customer throughout their entire relationship with the business.
- Conversion rate: Percentage of users who complete a desired action, such as making a purchase.
- Monthly recurring revenue (MRR): Total amount of predictable revenue your product brings in each month.
Referral
Referral metrics measure how effectively your users promote your product to others. Referral metrics provide insights into user satisfaction and the potential for organic growth through word-of-mouth. Key metrics include:
- Referral rate: Percentage of users who refer others to the product.
- Viral coefficient: Average number of new users or referrals generated by each user.
- Net promoter score (NPS): Measures customer loyalty and satisfaction by assessing how likely customers are to promote the product.
Below is a handy table with the formulas to calculate the various product analytics metrics.
| Metric | Formula |
| Cost per Acquisition (CPA) | CPA = Total cost of marketing and sales / Number of new users |
| Activation Rate | Activation Rate = Number of activated users / Total number of users |
| Retention Rate | Retention Rate = (Number of users at end of period – Number of new users during period) / Number of users at start of period |
| Churn Rate | Churn Rate = (Number of users at start of period – Number of users at end of period) / Number of users at start of period |
| Average Revenue Per User (ARPU) | ARPU = Total revenue / Number of users |
| Lifetime Value (LTV) | LTV = Average Order Value x Purchase Frequency x Customer Lifespan |
| Monthly Recurring Revenue (MRR) | MRR = Number of customers x Average revenue per customer per month |
| Conversion Rate | Conversion Rate = Number of conversions / Total number of visitors |
| Referral Rate | Referral Rate = Number of referred users / Total number of users |
| Viral Coefficient | Viral Coefficient = Number of invitations sent per user x Conversion rate of invitations |
| Net Promoter Score (NPS) | NPS = Percentage of promoters – Percentage of detractors |
Choosing Which Product Analytics Metrics to Track
Deciding which product analytics metrics to monitor depends on several factors, including:
Business Goals: Consider your business objectives so you can align the metrics with key performance indicators (KPIs). For example, if your business goal is to increase customer acquisition, focus on acquisition metrics such as CPA and traffic sources to determine the effectiveness of your acquisition campaigns.
Product Lifecycle: The metrics you choose should depend on the product’s lifecycle stage. Different metrics may be more relevant at various stages of your product’s lifecycle, such as launch, growth or maturity.
Actionability: Focus on metrics that have a practical use and avoid vanity metrics that look good but don’t drive actionable decisions. Your metrics should provide meaningful insights and inform decision-making.
Data Reliability: Ensure that you can track the data accurately and consistently, as it’s important to continuously monitor your metrics to identify trends or discrepancies.
Collaborative Analysis: Involve cross-functional teams who will collaborate on the analytic process to gain diverse perspectives on the metrics you need to track.
Tools Used to Measure Product Metrics
There are several powerful tools available to collect, analyse and visualise product analytics metrics. Some of the most popular ones include:
- Google Analytics: A comprehensive tool for tracking website and app performance.
- Mixpanel: A user analytics platform focused on tracking user interactions and engagement.
- Amplitude: A product analytics tool designed to help teams understand user behaviour and improve product performance.
Impactful Product Analytics
Having access to customer insights at different stages of their journey will help business leaders make informed decisions and drive long-term growth. The Data Team at Appsynth works with brands from various industries such as retail, financial services, automotive, and more, design and implement effective product analytics metrics for their digital products.
Get expert guidance on which product metrics to track. Let our experienced team help you identify areas for growth and unlock your product’s full potential through insightful analytics. Contact Appsynth for a consultation.
