Que sont les « statistiques produit » ?
Product analytics is a type 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. This data informs decisions about how to improve the product experience, increase product engagement, and drive business outcomes. Usage data tends to be more reliable than user surveys and product testing alone.
Who uses product analytics?
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. HR and IT managers also rely on analytics to gauge how effective their employee onboarding programs are, strategize ways to improve productivity, and ensure compliance in key areas such as security.
What tools does product analytics provide?
The way the data is grouped and queried plays a major role in how useful product analytics are to the product manager, UX designer, or growth strategist. The same is true for employee-facing roles, be they in HR, change management, or information security. Some of the most common ways to understand product usage include:
- 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.
Chez IHS Markit, the team uses product analytics to pinpoint which features get little to no use, so they can retire them and reduce technical debt. Data from their product analytics system also helps them understand which users were accessing those features, so they can connect with them directly to find a new workflow to achieve a similar outcome.
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, growth strategists, and change managers can observe a challenge or opportunity, develop a plan, deploy the change, measure outcomes, and iterate with minimal latency or dependencies.
Successful digital transformation
A successful digital adoption strategy incorporates product analytics into its gameplan. Robust analytics not only help managers see how well employees are, for example, using a new product feature. They also let teams analyze existing workflows and employee behavior within and across software to help inform decisions about future app purchases and recommended best practices. By making sure a digital adoption plan fits with a company’s culture and habits, managers thereby make it more likely that it ends in success.
How is product analytics used?
For product managers, UX designers, and change managers alike, the application of product analytics starts with a question to answer. Examples of common questions that can be answered by product analytics include:
- Dans quelle mesure un changement d'expérience affecte-t-il l'engagement ?
- Quelles fonctionnalités vaudrait-il mieux retirer pour améliorer les résultats ?
- Quelle combinaison d'interactions influence le plus la conversion ?
- Pourquoi certains produits de mon portefeuille ont-ils une meilleure attractivité que les autres ?
- Où résident les points de friction et les défaut de l'apprentissage proposé aux utilisateurs ?
With product analytics tools, companies can also correlate their product insights with user analytics and other operational metrics to get a clear view of how the product impacts behaviors and leads to key business results such as a reduction in support tickets, increased productivity, and an overall higher ROI on their software.
What type of data does product analytics track?
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, Enter New User, Run Report, 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), boolian (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. Companies are now reaping the benefits of product analytics not just for the software they create for customers, but for their employee-facing applications as well.
Why is product analytics important for digital adoption?
Product analytics matters for digital adoption because in order to assess whether employees are getting the most value out of software, managers have to be able to track how they are using it and what, if any, roadblocks they are encountering within and across it. In today’s workplace, different employees have different needs and pain points when it comes to apps. Robust analytics is essential to arriving at the best ways to reduce friction and optimize software experience across a company’s entire team.
Où peut-on en apprendre plus sur les statistiques produit ?
For those looking to dig a little deeper into product analytics, there are a number of books on the subject, including “High Growth Handbook” by Elad Gil and “Practical Web Analytics for User Experience” by Michael Beasley. Coursera also offers online courses on digital product management and actionable product analytics. Pendo has published information on how to collect product insights and drive feature adoption. It has also published content on how the right digital adoption solution leverages product analytics and the role product analytics plays in bringing about successful digital transformation.