Goodinformation architecture is essentialto providing a good UX and to accomplishing your business goals. But how can you tell if an IA is “good”? Start by looking at your analytics data.

Analytics systems keep a record of all the actions your users take, and reviewing behavior patterns reflected in this data can direct your attention to confusing, missing, or underperforming content categories that should be optimized or further investigated during user testing. Analytics data is especially useful when you have a large collection of content. Whether it’s blog posts, products, or support articles, presenting your content in categories that are both understandable and interesting makes users more likely to browse (and also improves your search rankings).

Homepage of Garden Design Magazine
Any design which relies on browsing to engage users can use analytics data to optimize topic menus. For example, this site has 3 sets of categories which could be analyzed by reviewing analytics data: the top global menu, the left-side topic navigation list, and the category pages featured in the body of the homepage.

Analytics Metrics That Suggest IA Problems

In order to use analytics data to improve information architecture, you must:

  • Identify which analytics metrics to consider
  • 根据整体设计,用户目标和业务目标的背景解释每个度量。


1. Low Traffic to Categories

The volume of traffic to a category is the most obvious indicator of how useful or interesting the category is to your audience. Traffic can be measured as the number of views of the main category page (e.g.,或通过在类别(例如“/containers/shade.html,”/containers/combos.html,等)中聚合查看类别(例如,“/containers/shade.html)。请注意,不同的工具通常使用略有不同的术语来描述相同的公制;特定页面的流量可以称为“PageViews”,“访问”或某些其他术语,具体取决于您使用的分析工具。

Make sure to exclude repeat views by the same user. The overall traffic volume may be drastically inflated by userspogo-sticking那or repeatedly browsing back and forth from the category page to articles. Most analytics systems provide a separate metric which only considers unique views, and does not count repeated views by the same user in the same session.

How to interpret low traffic:考虑此度量,与企业和用户的类别的战略重要性有关。

  • Is the traffic comparable with traffic to other categories?计算所有类别,总访问量n the average traffic per category, and finally the ratio between each category’s traffic and this average. If theContainer Gardening类别仅收到每个类别的平均流量的5%,可能是与大多数受众无关的主题。
  • Are there other factors (such as page layout) that explain traffic disparities?Some categories may have higher traffic not because they are better categories, but simply because they are more visually noticeable, or appearmultiple times。Don’t compare traffic between categories with significantly different prominence.
3 different duplicate categories on the Garden Design homepage,来自左侧导航的三个类别在页面的主体中具有吸引力的图像。分析可能会向这三个重复的类别表现出更高的流量。这些数字不一定反映对这些话题的更多兴趣;相反,这些类别的受欢迎程度可能是由视觉设计引起的。如果可视化设计可能严重偏置分析数据,请谨慎谨慎进行。
  • Would you expect higher traffic based on the importance or relevance of the topic?Sometimes mission-critical categories don’t get the traffic you would expect. In those cases, it’s worth trying alternative names for those categories to increase discoverability and findability.
  • Is the category strategically important, even though it has low usage?有时类别的性质是它只使用一次,或很少。或者它只能通过一小部分有价值的用户使用。如果是这种情况,那么即使它只吸引了一个小型受众,它可能值得保留这一话题。

If the answer to all these questions is ‘no’, then consider eliminating or de-emphasizing the category.有机会成本为没有人感兴趣的主题:相反,您可以使用屏幕空间来指导更多地关注提高参与或扩大受众的主题。



How to interpret low conversions:在基于低转换的决策之前,请准确地了解被视为转换的内容,并查找其他值的信号。

  • Is the category a significant source of traffic to other important pages?Even if a page itself does not convert, it may drive traffic to other pages that do convert (or serve other important functions in the user journey). For example, the方法如何信息category page on doesn’t generate many magazine subscriptions. But如何could still be an important section if it is the main source of traffic to the产品section, which in turn generates significant affiliate marketing revenue.
  • Is the content part of a longeruser journey那which requires several visits before completing a goal?If so, the category may influence visitors who later convert, but the connection may not be measured accurately by the analytics system if your metrics only capture conversions that happen in the same session, or if later visits originate from different devices.


3. High Bounce Rates on Category Landing Pages


How to interpret高反弹率考虑用户在到达类别页面之前的位置,以及一旦他们到达后看到的位置。

  • Does the label accurately describe the category, and could it be misunderstood by users?High abandonment is often driven by unmet expectations. Link labels used on ads or in search results should accuratelydescribe the page they lead to— a gallery of garden photos should not be described as “How to Design a Garden.”
  • Does the page layout prevent people from seeing the content?It’s worth visiting the page yourself or even running a quick usability test to make sure that the page content is visible and discoverable. If you use the same template for all category pages, it’s unlikely that just one category have a bounce-rate issue due to a layout problem. But sometimes content editors make one-off modifications that unintentionally impair the page usability. (Our course onWeb Page UX Designdiscusses many such unpleasant issues.)

4. Low Entrance Rates

The very first page a user sees in a particular visit is theirentranceorlanding page。Entrances are strategically valuable because they represent an opportunity to expand your audience (especially if you filter for entrances by new visitors, who have not visited the site in the past). If a category has few entrances compared to other categories, it does not effectively attract users and may need to be adjusted.

How to interpret low entrances:For the low-entrance categories, check other metrics:

  • Are entrances lower than you would expect based on other factors?If the topic is one you consider to be significant — for example, a category about “Award-Winning Gardens,” which showcases some of your best content — then i lack of effective promotion or poor labeling might be the problem.
  • Is the low entrance rate common across all channels?Segment arriving users by source, and analyze each channel separately. For example, if the category has decent social traffic but poor search traffic, it’s probably a topic that your users care about but you have anSEO problem那such as using与人们搜索的不同术语
  • Does the category have a high rate of conversions among the visitors it does attract?If so, it may be worth keeping since it’s effective for that niche audience.

Always check the entrance rate before you decide to eliminate a category, to make sure you don’t eliminate an important entry point into your content.

5. High Volume of Search Queries

搜索查询表明人们想要什么,也suggest that they could not find it in your current IA. Generate a list of the most commonly searched terms, either directly from your search engine, or from within your analytics tool (if it is integrated with your search function.) The terms that users search for most frequently might be worth adding or prioritizing within your content categories. For example, if “xeriscape” is a commonly searched term, consider adding it as a separate category.


  • 搜索查询是否由类别代表?People often search for terms which exist in the current architecture. If a frequently-searched term corresponds to an existing category, consider promoting the category more prominently to make it easier to find.




In ambiguous cases, supplement your analytics metrics with other types of data. For example, conduct an A/B test to study the effect of renaming a category, or set up a short user survey on a particular category page to gather information about visitor motivations. By focusing your efforts on the warning signs above, you’ll be able to efficiently analyze and improve your IA based on analytics data.