How are your users interacting with your product? Where are they getting stuck? Which features are they using most frequently, and which are getting ignored? Product analytics can answer these key questions and many more.
Que sont les « statistiques produit » ?
Product analytics is a category of business intelligence software that captures and exposes usage patterns from digital products like web and mobile applications via event tracking, event properties, and event and property grouping. Product managers, user experience (UX) designers, and growth strategists rely on product analytics (sometimes called “click tracking” or “click path analytics”) to track digital interactions within their apps, websites, and devices. That data informs decisions about how to improve the product experience and drive business outcomes. Usage data tends to be more reliable than user surveys and product testing alone.
L'utilité de ces statistiques pour le chef de produit, le concepteur UX ou le spécialiste de la croissance repose sur la façon dont les données sont regroupées et utilisées. Voici quelques-unes des pistes les plus courantes pour analyser l'utilisation des produits :
Trends: Graph engagement with certain features or pages and compare against other parts of the product over time, or compare engagement with a single part of the product over two different time periods.
Funnels: Track the levels of drop-off at each step across a specific subset of features and pages in the product. With a funnel analysis, any combination of steps can be reviewed in any chronology.
Paths: See all the product journeys users take either leading up to or following a specific interaction, with a measure of how common or uncommon the next step being taken is. Unlike funnels, paths include all possible upstream or downstream interaction scenarios.
Pourquoi recourir aux statistiques produit ?
Connaissance des utilisateurs et ROI
Récemment encore, les décisions concernant les produits dépendaient de la capacité à lancer une fonctionnalité dans les temps. Or, les statistiques produit permettent aujourd'hui aux équipes produit et UX de mieux évaluer l'efficacité de leurs stratégies, l'engagement des utilisateurs ou le retour sur investissement (ROI). Les données de suivi des événements dans une application donnée aident les équipes produit à savoir quelles parties de l'application sont utilisées, à quelle fréquence et par qui, tout en repérant les parcours qui renvoient les résultats les plus significatifs.
Croissance et expérimentation
Product analytics unlocks the metrics by which hypotheses are made and meaningful engagement is measured: adoption by monthly active users (MAU), adoption by daily active users (DAU), stickiness by return rate over time, breadth across features or products, depth across users in a specific cohort or account, and how they relate to business metrics. With product analytics, product managers, UX designers, and growth strategists can observe a challenge or opportunity, develop a plan, deploy the change, measure outcomes, and iterate with minimal latency or dependencies.
Comment utiliser les statistiques produit ?
Pour effectuer des analyses produit, les chefs de produit, concepteurs UX et spécialistes de la croissance doivent d'abord avoir une question à laquelle ils souhaitent répondre. Voici quelques questions auxquelles les statistiques produit sont capables de répondre :
- Dans quelle mesure un changement d'expérience affecte-t-il l'engagement ?
- Quelles fonctionnalités vaudrait-il mieux retirer pour améliorer les résultats ?
- What combination of interactions contributes most to conversion?
- Pourquoi certains produits de mon portefeuille ont-ils une meilleure attractivité que les autres ?
- Where are the biggest frictions and leaks during onboarding?
Avec les outils d'analyse, les entreprises peuvent corréler les informations sur leurs produits avec les statistiques utilisateurs et d'autres indicateurs opérationnels pour visualiser clairement l'impact du produit sur les comportements et les avantages qui en résultent.
Les solutions d'analyse effectuent généralement le suivi de deux types de données d'interactions des utilisateurs :
Event Tracking
User actions are commonly called “events.” Events include clicks, slides, gestures (for mobile and other device types), play commands (for audio and video), downloads, page loads, and text field fills. The event includes the type of element, the name of the element, and the action the user took. Generic examples of events include Create Account, Add to List, Submit Feedback, Share Dashboard, Select Option, Play Tutorial, Change View, and Complete Onboarding.
Event Properties
The way one understands the specific attributes of the tracked interactions is the work of event properties. Product managers, UX designers, and growth strategists don’t only care if something happened, but also the context that distinguishes activity from impact when analyzed longitudinally. Event properties can include details like time, duration, count, device, software version, geography, user demographic, account firmographic, element characteristics (like color, size, shape), boolean (like login: yes/no), and custom attributes (like basic/pro/enterprise).
Quelle est l'origine des statistiques produit ?
For today’s product managers, UX designers, and growth strategists, product analytics is the key to building a product roadmap and driving innovation and continuous improvement. Where web properties were historically judged by metrics that revealed little about the relationship between digital products and business objectives — page views and session duration — the modern app-based web and mobile internet is powered by more telling and contextual interactions: events, engagement, and journeys. The shift toward meaningful insights is particularly relevant in multi-app portfolios — especially across platforms and devices — where tracking and correlating a variety of product data dictate the design, functionality, and experiments that drive product strategy and growth.
Recommended reading
High Growth Handbook by Elad Gil
This book takes readers through how major companies like Stripe, Square, Airbnb, and Twitter grew from ideas to global powerhouses. One of the keys to their incredible success? Product analytics.
Measuring Your Product’s Performance With Benchmarks by Blake Bartlett
Successful PMs constantly measure their product’s performance using analytics. But can they compare that performance with that of peer products? With benchmarks, they can.
Practical Web Analytics for User Experience by Michael Beasley
This book is a must-read for PMs and UX designers alike. Learn how product analytics can help you build a holistic picture of your users’ overall product journey.
The Path to Product-Qualified Leads by Matheus Mello
You’ve heard of MQLs and SQLs, but what about PQLs? Product qualified leads might be the product analytics metric you’re looking for to quantify user delight and success.
Why Product-Led Growth Is of Rising Importance by Wesley Bush
Product-led growth is a new way of running a SaaS business and encompasses an intense focus on product analytics. It’s also non-optional if you want your company to survive long-term.
