diff --git a/public/images/app.jpg b/public/images/app.jpg index dc72ef6a..9124904f 100644 Binary files a/public/images/app.jpg and b/public/images/app.jpg differ diff --git a/public/images/v2/events-chart.png b/public/images/v2/events-chart.png new file mode 100644 index 00000000..6e11dd0a Binary files /dev/null and b/public/images/v2/events-chart.png differ diff --git a/public/images/v2/events-properties.png b/public/images/v2/events-properties.png new file mode 100644 index 00000000..961014f9 Binary files /dev/null and b/public/images/v2/events-properties.png differ diff --git a/public/images/v2/sessions-activity-properties.png b/public/images/v2/sessions-activity-properties.png new file mode 100644 index 00000000..9e5bc7bd Binary files /dev/null and b/public/images/v2/sessions-activity-properties.png differ diff --git a/public/images/v2/sessions-activity.png b/public/images/v2/sessions-activity.png new file mode 100644 index 00000000..91e86754 Binary files /dev/null and b/public/images/v2/sessions-activity.png differ diff --git a/public/images/v2/sessions-chart.png b/public/images/v2/sessions-chart.png new file mode 100644 index 00000000..bccf25ad Binary files /dev/null and b/public/images/v2/sessions-chart.png differ diff --git a/public/images/v2/sessions-profile.png b/public/images/v2/sessions-profile.png new file mode 100644 index 00000000..61a7c4a7 Binary files /dev/null and b/public/images/v2/sessions-profile.png differ diff --git a/public/images/v2/sessions-properties.png b/public/images/v2/sessions-properties.png new file mode 100644 index 00000000..c0110c79 Binary files /dev/null and b/public/images/v2/sessions-properties.png differ diff --git a/src/app/(website)/docs/menu.v2.json b/src/app/(website)/docs/menu.v2.json index ffa34951..e1278563 100644 --- a/src/app/(website)/docs/menu.v2.json +++ b/src/app/(website)/docs/menu.v2.json @@ -43,6 +43,10 @@ "label": "追踪事件", "url": "/docs/track-events" }, + { + "label": "会话", + "url": "/docs/sessions" + }, { "label": "比较", "url": "/docs/compare" diff --git a/src/content/blog/optimizing-conversion-paths-using-the-funnel-report.mdx b/src/content/blog/optimizing-conversion-paths-using-the-funnel-report.mdx new file mode 100644 index 00000000..b17295ae --- /dev/null +++ b/src/content/blog/optimizing-conversion-paths-using-the-funnel-report.mdx @@ -0,0 +1,127 @@ +--- +title: Optimizing Conversion Paths Using the Funnel Report +description: Understanding conversion paths and user journeys is the first step to optimizing them. +author: Nick Andrews +date: 2024-08-15 +--- + +Understanding conversion paths and user journeys is the first step to optimizing them. If you have already defined those paths, the Umami Funnel report, one report in a suite of product analytics reports, is for you. The Funnel report allows you to analyze users' conversion and drop-off rates at each step of a defined process, surfacing data that can be used to improve user experience, conversion rates, product feature adoption, etc. + +If you don’t have those paths defined and are unsure what paths users take to complete an action, the User Journey report, a complementary report to the Funnel report, might make sense as a starting point. Not to go too deep on the Journey report, but you can simply define a starting point, ending point, and the number of steps in between, and the report will show you the user journey. You can adjust the number of steps and re-run the report to expand your view if needed. This report provides a broader view of user interactions, helping you understand users' various paths before they reach a conversion point. + +However, this blog post focuses on the Funnel report, which allows teams to visualize and analyze how users move through specific sequences of actions or pages. It identifies where users drop off, thus surfacing opportunities for optimization. Combining this data with insights from other Umami reports gives you a clearer picture of your performance and user behavior. + +Let’s jump in. + +# Funnel Report Key Features + +To effectively use the Umami Funnel report, you really need to have custom events set up on your product or website beforehand. Custom events are specific user actions you define, such as 'product added to cart,'' payment information entered, '' signed up for the newsletter,’ etc. Umami then tracks these events, which can be used to create Funnel reports that can be infinitely nuanced to your specific situation. Before we jump into the use cases, let's look at some key features of the Funnel report: + +1. **Flexible Step Definition**: Define specific funnel steps using URLs, events, or URL wildcards. + +2. **Time**: Set the time users must complete the funnel steps. This includes both date range (up to 90 days) and time window (amount of minutes a user has between funnel steps to be counted as a conversion). + +3. **Ordered Step Completion**: Analyze user progression through steps in a specific order. + +4. **Detailed Drop-off Analysis**: This displays the number of users reaching each step and the drop-off rate from the previous step. It also visually shows a progress bar and percent complete for instant analysis. + +# Funnel Report Use Cases + +This section breaks down a few use cases for the Funnel report to get the ideas rolling. However, there are an infinite number of ways to use the Funnel report to uncover insights about your users and product. +Use Case Example: Analyzing Sign-up to Activation Process + +Product teams need to understand how new users progress from initial sign-up to becoming active users. Here's how you can use the Funnel report for this purpose: + +## Setup + +1. Define the steps in your sign-up to activation process. The report needs at least two steps. I have tested it with up to 10 steps. If you have more than ten steps, email us and let us know your use case. It sounds really interesting! + +2. Create a Funnel report with these steps, using URLs or events to represent each stage. + +3. Set an appropriate time window for users to complete the funnel. + +## Analysis Approach + +Once you've set up the Funnel report, you can analyze the data in several ways: + +1. Identify the stages where you're losing the most users, indicating potential areas for improvement. + +2. Compare conversion rates between user segments or acquisition channels to understand which sources provide the most valuable users. + +3. Analyze how sign-up or onboarding process changes impact conversion rates over time. + +4. Use the insights to prioritize product improvements or user education efforts. + +Using the Funnel report can help you optimize your sign-up and activation process, improving user retention and product adoption. + +# Use Case Example: E-commerce Checkout Optimization + +For teams focused on improving e-commerce conversion rates, the Funnel report can be used to understand and optimize the checkout process. Here's how you could approach this: + +## Setup + +1. Define the stages in your checkout process (e.g., add to cart, enter shipping info, enter payment info, confirm order). + +2. Create a Funnel report with these stages as steps. + +3. Set an appropriate time window that allows for a typical checkout duration. + +## Example Implementation + +Let's say you're analyzing the checkout process for an e-commerce website. We might set up the following Funnel report: + +- Step 1: 'Add to Cart' button click event +- Step 2: Checkout page URL +- Step 3: Shipping information page URL +- Step 4: Payment information page URL +- Step 5: 'Order Confirmation' button click event + +## Analysis Approach + +With this Funnel report in place, we can: + +1. Identify the checkout stages with the highest drop-off rates, highlighting areas for immediate improvement. + +2. Compare conversion rates across different product categories, user segments, or devices to understand varying user behaviors. + +3. Analyze how changes to the checkout process (e.g., adding a guest checkout option) impact overall conversion rates. + +4. Use the insights to make data-driven decisions about checkout page design, form simplification, or adding reassurance elements at critical stages. + +This analysis can break down how the checkout funnel is flowing and gives you a blue print for optimizing conversion rates. What’s interesting for this example is that you can get really granular and setup this process for an individual product, or use wild cards in your Funnel report to view product categories or all products. + +# Use Case Example: Feature Adoption Funnel + +For teams looking to increase the adoption of a specific feature, the Funnel report can offer insights into the user journey toward feature engagement. Here's how you can use it: + +## Setup + +1. Identify the key steps to feature adoption (e.g., feature discovery, initial interaction, repeated use). + +2. Create events or use URLs that represent these steps. + +3. Set up a Funnel report with these steps, using an appropriate time window for your product's usage patterns. + +## Analysis Approach + +Suppose you work at a SaaS company and want to increase the adoption of a new feature. You could use the Funnel report to: + +1. Analyze the number of users who discover the feature (e.g., through a product tour button click, etc. You might need to setup multiple funnels for different discovery entry points.) and go on to use it for the first time. + +2. Identify the drop-off between first use and repeated engagement, highlighting potential usability issues. + +3. Compare adoption rates across user segments or onboarding paths to understand what factors contribute to successful adoption. + +4. Use the insights to refine feature introduction strategies, improve in-product guidance, or target specific user groups for additional support or encouragement. + +This approach can help you make data-driven decisions about feature development, prioritizing your product roadmap, user education, and product design to encourage adoption and engagement. + +The Umami Funnel report can enhance your product analytics capabilities by allowing you to visualize and analyze specific user paths through your product. Understanding these conversion funnels will enable you to identify bottlenecks, optimize critical processes, and improve user experience and conversion rates. + +The use cases outlined here are just some of the many ways to use the Funnel report for your team. Its flexibility allows it to adapt to the nuances of your product and requirements, ensuring it can be a fit for your analytics needs. + +Combining data from the Funnel report with insights from other Umami reports and your broader analytics stack, you can understand your users' behavior and make data-driven decisions to improve your product. + +Using Umami, particularly its Funnel report, as a complementary tool alongside your existing analytics stack can enhance your data confidence and insights. By setting up parallel tracking for key conversion funnels and regularly comparing results between Umami and your other analytics platforms, you can validate data accuracy, identify potential blind spots in your tracking, and reinforce the validity of your findings. + +The Funnel report comes standard with all Umami plans. If you have any issues with it or have any questions, please contact us at support@umami.is. We're here to help you get the most out of your Umami account! diff --git a/src/content/blog/understanding-retention-analysis.mdx b/src/content/blog/understanding-retention-analysis.mdx new file mode 100644 index 00000000..9d308ddf --- /dev/null +++ b/src/content/blog/understanding-retention-analysis.mdx @@ -0,0 +1,142 @@ +--- +title: Understanding Retention Analysis +description: Understanding user behavior goes beyond how users discover and start using your product. +author: Nick Andrews +date: 2024-08-20 +--- + +Understanding user behavior goes beyond how users discover and start using your product. It is just as important how they continue to engage with it over time. This is where retention analysis comes into play. The Umami Retention report can be a part of this process, highlighting both short-term and long-term user engagement, which you can then match to marketing campaigns, product announcements, feature launches, social media posts, etc, to see what impacts retention. + +The Umami Retention report, one in a suite of product analytics reports, allows teams to visualize and analyze user retention patterns. It shows how often users return to your website or product, helping you understand short-term and long-term engagement trends and identify opportunities to produce better outcomes. + +# Retention Report Key Features + +Before we jump into specific use cases, let's look at some key features of the Retention report: + +1. **Cohort Analysis**: The report uses cohort analysis to group users based on when they visited your site. This lets you track how engagement changes for different user groups over time. For example, if you launched a new feature on June 15, you can follow that specific cohort of users over the next however many days to see what impact the new feature has on retention. + +2. **Daily Visitor Tracking**: The Retention report is based on a daily cohort of users. + +3. **Return Visit Insights**: You can see how often those users return on specific days following their initial visit, showing your product's "stickiness." + +4. **Flexible Time Frame**: You can analyze retention for any specific month and year to compare retention rates across different periods or seasons. + +5. **Visual Representation**: The data is presented in a cohort chart, making it simple to identify trends and patterns at a glance. + +For a walk-through on how to setup a Retention report, please refer to our [docs](https://umami.is/docs/reports/report-retention). + +# Retention Report Use Cases + +## Use Case Example: Analyzing the Impact of Onboarding Improvements + +Product teams often invest significant resources in improving the onboarding process, aiming to increase user engagement and retention. The Retention report can help you measure the effectiveness of these efforts. + +### Setup + +1. Identify the date when you implemented the onboarding changes. + +2. Create Retention reports for the month before and the month after the changes. + +3. Compare the retention patterns between these two periods. + +### Analysis Approach + +Once you've set up these reports, you can analyze the data in several ways: + +1. Compare the Day 1 retention rates (users who return the day after their first visit) before and after the changes. An increase in Day 1 retention could indicate that your new onboarding process is more engaging. + +2. Look at longer-term retention (e.g., Day 7, Day 14, Day 30) to see if the improvements have a lasting impact. Are users sticking around longer after the onboarding changes? + +3. Analyze retention patterns for different user segments to see if the new onboarding process is more effective for specific users. + +4. If you see improved retention, consider running A/B tests with further onboarding tweaks to continue optimizing the process. + +Using the Retention report in this way can help you quantify the impact of your onboarding improvements and guide further optimization efforts. + +## Use Case Example: Evaluating Feature Launches + +When launching new features, you need to know the initial adoption and how these features impact long-term user engagement. The Retention report can help. + +### Setup + +1. Identify the launch date of a new feature. + +2. Create Retention reports for the month before, the month of, and the month after the launch. + +3. Compare retention patterns across these three periods. + +### Analysis Approach + +With these reports in place, you can: + +1. Look for changes in overall retention rates following the feature launch. An increase could indicate that the new feature is driving more frequent usage. + +2. Analyze how quickly retention rates change after the launch. A rapid improvement might suggest high user excitement about the new feature. Follow up with marketing to see if they are hearing any positive feedback on social channels, or customer support to see if there is any positive feedback, etc. + +3. Examine long-term retention trends (e.g., 2-3 months post-launch) to see if the feature has a lasting impact on user engagement. + +4. Segment users based on whether they've used the new feature. Compare retention rates between users who have and have not engaged with the feature to better understand its impact. + +5. Use these insights to inform decisions about future feature development and resource allocation. I.E., this data can help you determine your product roadmap. + +This approach can help you understand the true impact of new features on user engagement beyond initial adoption metrics. + +## Use Case Example: Seasonal Trend Analysis + +Many products experience seasonal fluctuations in user behavior. Understanding these patterns can help you more effectively plan product updates, marketing campaigns, and resource allocation. + +### Setup + +1. Generate Retention reports for each month of the year. + +2. Compare retention patterns across different seasons or specific periods (e.g., holidays, academic semesters, fiscal quarters). + +### Analysis Approach + +With this data, you can: + +1. Identify periods of naturally high or low retention. This can help you set more accurate retention goals for different times of the year. + +2. Look for consistent patterns year over year. Do you see a dip in retention during the summer months or a spike during the holiday season? + +3. Analyze how different cohorts behave during these seasonal changes. Do users who join during high-retention periods tend to stick around longer? + +4. Use these insights to plan product updates or marketing campaigns. For example, you might focus on re-engagement campaigns during typically low-retention periods. + +5. Compare your seasonal retention patterns with overall usage metrics to understand how seasonality affects your product. + +This analysis can help you anticipate and plan for seasonal changes in user behavior, allowing you to optimize your product strategy throughout the year. + +# Combining Retention Insights with Other Umami Reports + +The data gleaned from the Retention report can be a starting point and other Umami reports can help you double-click into the data. Here are a few ways to combine insights from the Retention report with other Umami reports: + +**Retention + Funnel Report**: Use the Funnel report to identify high-impact user actions, such as making a purchase or completing a tutorial, then use the Retention report to see if users who complete these actions have higher long-term retention rates. + +**Retention + Goals Report**: Set retention-based goals in the Goals report (e.g., "X% of users return within seven days"), and use the Retention report to track progress towards these goals over time. + +**Retention + Journey Report**: The Journey report allows you to analyze user paths with 3 to 7 steps, providing insights into how users navigate your product. Use this report to identify the most common paths of highly retained users, then use the Retention report to analyze if optimizing these paths leads to improved long-term engagement for other user segments. + +**Retention + Journey Report for Feature Discovery**: Use the Journey report to understand how users discover and engage with key features. Then, the retention report to see if users who find and use these features have higher retention rates. This combo can help you prioritize which features to promote or optimize for better long-term engagement. + +Leveraging multiple Umami reports allows you to understand your product's performance and user behavior patterns. The Journey report's ability to visualize complex user paths complements the Retention report's focus on long-term engagement, allowing you to connect specific user behaviors with retention outcomes. + +The Umami Retention report can help product analytics teams looking for a deeper understanding of user engagement over time via visualizations of cohort-based patterns, it enables teams to: + +1. Measure the impact of product changes and feature launches on both short-term and long-term engagement. + +2. Identify seasonal trends. + +3. Set data-driven retention goals and track progress over time. + +4. Optimize onboarding and other critical user journeys. + +5. Complement insights from other reports like Journey, Funnel, and Goals for a comprehensive view of user behavior. + +These are of course just a few key examples that will hopefully get the ideas flowing. Because the Retention report is date-based, you can match the dates to pretty much anything your company is doing on the product, marketing, sales, UI/UX, design, etc, side. + +Reviewing your Retention reports and other Umami reports can provide continual insights to drive product improvements and boost user engagement. + +What’s great about Umami is it can run alongside your existing analytics tools and can act as a second-source of data to help you confirm what you are seeing from other tools. + +Like all Umami reports, the Retention report comes standard with all Umami plans. If you have any questions about using the Retention report or want to discuss how to get the most out of your Umami analytics suite, including how to combine insights from the Retention and Journey reports (or any other report for that matter), don't hesitate to reach out to our support team at support@umami.is. diff --git a/src/content/docs/cloud/import-data.mdx b/src/content/docs/cloud/import-data.mdx index f73f67bf..18dcb0b6 100644 --- a/src/content/docs/cloud/import-data.mdx +++ b/src/content/docs/cloud/import-data.mdx @@ -117,7 +117,7 @@ SELECT we.website_id, we.event_id, we.url_path, we.event_name, - ed.event_key, + ed.data_key, ed.string_value, ed.number_value, TO_CHAR(ed.date_value, 'YYYY-MM-DD HH24:MI:SS') date_value, @@ -237,7 +237,7 @@ SELECT we.website_id, we.event_id, we.url_path, we.event_name, - ed.event_key, + ed.data_key, COALESCE(ed.string_value, '') string_value, COALESCE(ed.number_value, '') number_value, COALESCE(DATE_FORMAT(ed.date_value, '%Y-%m-%d %T'), '') date_value, diff --git a/src/content/docs/v2/sessions.mdx b/src/content/docs/v2/sessions.mdx new file mode 100644 index 00000000..32af28a4 --- /dev/null +++ b/src/content/docs/v2/sessions.mdx @@ -0,0 +1,34 @@ +--- +title: Sessions +--- + +# Sessions + +The **Sessions** screen displays information about your visitors. We are also introducing a brand new component showing you an +hourly traffic breakdown during a given week. Now you can tell when your website is the most busy. + + + +## Visitor activity + +Explore your most recent visitors and discover where they come from in a high-level summarized view. + + + +## Visitor profile + +Clicking on any of the avatars in the activity table bring you to a new page showing details about a particular visitor. It also shows their activity history over time. + + + +## View session properties + +Your custom data can be accessed under the **Properties** tab on the **Sessions** page. +This section will show you all the custom data properties you saved as well as a breakdown of all the values. +To save session properties see [Tracker configuration](/docs/tracker-functions#session-data). + + + +Individual session property data can be viewed at the profile level. + + diff --git a/src/content/docs/v2/track-events.mdx b/src/content/docs/v2/track-events.mdx index bd89e8c4..1766c563 100644 --- a/src/content/docs/v2/track-events.mdx +++ b/src/content/docs/v2/track-events.mdx @@ -63,9 +63,17 @@ button.onclick = () => umami.track('注册按钮'); ## 查看事件 -一旦你的事件被记录，它们将在你的网站的 **详情** 页上可用。 +一旦您的事件被记录，它们将会显示在您的网站 **事件** 页面上。 - + + +## 查看事件属性 + +您的自定义数据可以在**事件**页面的**属性**选项卡下方访问。 + +该部分将向您展示您保存的所有自定义数据属性以及所有值的细分。 + + ## 防止跟踪自己 diff --git a/src/content/docs/v2/tracker-functions.mdx b/src/content/docs/v2/tracker-functions.mdx index 37cfac85..eb84e410 100644 --- a/src/content/docs/v2/tracker-functions.mdx +++ b/src/content/docs/v2/tracker-functions.mdx @@ -13,6 +13,8 @@ Umami 跟踪器提供了一个可以在你的网站上调用的函数，如果 umami.track([payload]); umami.track(event_name, [event_data]); + +umami.identify([session_data]); ``` ## 页面浏览量 @@ -83,3 +85,11 @@ umami.track(props => ({ - 字符串的最大长度为 500。 - 数组转换为字符串，具有相同的最大长度 500。 - 对象最多有 50 个属性。将数组视为 1 个属性。 + +## 会话数据 + +跟踪具有动态数据的会话。您将从跟踪器脚本中调用标识函数，以保存有关当前会话的数据。 + +```js +umami.identify({ email: 'bob@aol.com' }); +```