Ecommerce Metrics & Insights for Modern Web Storefronts

Ecommerce shopping experience thrives on data providing critical inputs on whether shoppers are satisfied with the digital experience and what’s needed to accelerate future improvements. Mobify storefront metrics empowers teams to get answers quickly about their front-end operations, and then use that information to accelerate your experience deployments and decision-making.

What are the friction points impacting your storefront’s slow experience?
How well is your backend responding to the requests coming from the storefront?
How did the most recent deployments impact shopper experience?

Get complete visibility with a storefront performance overview

The overview dashboard provides a complete picture of your storefront data to give you the answers you’re looking for at a glance.

Here’s a breakdown of what each metric measures:

Number of users: Indicates how many users have visited the site that day. It is assigned by the user’s browser and will be counted as one for a 24 hour period unless the user clears their browser cookies.

Current Full Page Load: Provides the median Full Page Load (FPL) of your site. It is measured in seconds after the render function is completed and the skeleton of the page has loaded. A good goal to aim for is under 5 seconds.

Daily Cache Hit Ratio: Describes the ratio of cache hits compared to the total number of requests and is expressed as a percentage. A good goal to aim for is 90% or higher.

Cache Miss Response Time: Measures cache misses in seconds from when a request is sent to when a response is received from the application server. This is a median value and only tracks instances where the page being requested was not cached. A good goal to aim for is under 2 seconds.

Backend Response Time: Measures the time it takes for the Mobify’s app server to retrieve information from the backend. This is a median value, measured in seconds. A good goal to aim for is under 250 ms.

Deploys: Counts the number of deployments that went live in production in the last 14 days. It’s a good practice to measure the overall impact bundle releases have on your web performance. You’ll notice on our graphs that the bundles are reflected on the y-axis. In general, deploying regularly is a good sign of healthy development practices.

Optimize the shopper experience with key performance metrics

Web performance teams are continuously looking for ways to measure and optimize the shopper’s experience online. To measure how well your web storefront is performing from your shopper’s perspective, it’s recommended that you track First Contentful Paint (FCP) and Full Page Loads (FPL) as part of your performance metrics.

Such metrics help teams answer:

How much time passes before users see content?
How long does it take to load a complete page?
How long does it take for the backend to return data?

First Contentful Paint measures the time from navigation to the time the browser renders the first bit of content from the document object model (DOM), this could include any text, images, or non-white canvas on the page.

The FCP’s purpose is to communicate to the shopper, “we heard you and we’re working on it,” assuring the shopper that the site is functioning correctly and providing content.

Full Page Load (FPL) is a performance metric that directly impacts user engagement. It indicates how long it takes for a page to fully load before a user clicks a link or makes a specific request.

Google rewards sites that deliver better user experiences and faster performance with higher search rankings. Since Google encourages sites to optimize their online experience for the end users, FCP and FPL are two metrics that are measured in Google PageSpeed Insights.

Tracking both FCP and FPL metrics give you a much more precise way to measure the exact moments when your users perceive that your site has started to render content, and the point where the site is fully loaded – enabling the user complete their goal.

How to use this graph (measured in percentiles):

Make sure that the gap between FCP and FPL is as small as possible for the optimal user experience.
A spike in FPL without a similar spike in FCP might suggest that something is wrong with the application code, as the site elements were received quickly, but are taking a long time to render.

Track backend response times to address bottlenecks

The web storefront needs to deliver fast experiences to shoppers, but rendering user requests quickly requires getting the backend data as fast as possible.

Mobify uses APIs as a more efficient way to fetch data and orchestrate complex tasks, but backends can still experience degradation in performance.

To stay on top of the performance of your entire ecommerce stack, Mobify provides visibility into how your backend is affecting the overall performance of your site. It measures the time it takes for the Mobify’s app server to retrieve data from the backend because identifying when specific calls result in slow responses gives you an opportunity to address possible bottlenecks.

How to use this graph (measured in percentiles):

If the 99th percentile spikes, a small number of calls to the backend are resulting in extremely slow responses. A large spike in the 99th percentile might indicate that a call to the backend is blocked and is unable to respond to the request.
If the 50th percentile spikes, then a large number of common calls to the backend are slower than they were previously.

Measure caching performance to optimize content delivery

Caching plays a big role in the delivery of the shopper experience and how your content is being served, not to mention how fast your site is performing. Mobify’s storefront has a built-in CDN where we track both cache hit ratios and cache misses, so you can optimize for a faster loading experience.

Cache hit ratio measures the percentage of requests the CDN is able to serve from its own internal cache (cache hit), versus the requests for assets in which the CDN has to pass it to the backend (cache miss). Optimizing this ratio is key because requests with cache misses are typically 90% slower (e.g. between 2 seconds to 100 mls).

How to use this graph:

Make sure there are as many cache hits as possible.The goal to aim for is 90%, as this leads to faster FPL and FCP across your site.
Check to see that there are as few cache misses as possible, as they lead to a slower median FCP and FPL.
At any particular point, the hits, errors, and misses should all add up to 100%.

Cache misses are measured in seconds from when a request is sent to when a response is received from the Mobify storefront.

How to use this graph (measured in percentiles):

If the 99th percentile spikes but the 50th percentile doesn’t, that indicates a few longtail pages have had significantly worse performance.

If the 50th percentile spikes, then that indicates a large number of the pages on your site have gotten slower.
Try to ensure that the 99th percentile and the 50th percentile are as close as possible.

Insight is power

Your web storefront is an important touchpoint for delivering innovative shopping experiences. With visibility into the right metrics, you can examine the data to continuously optimize the user experience, see how various systems are impacting performance, and proactively mitigate any potential issues. These web storefront metrics are available to all customers using Mobify’s storefront for headless commerce. Get in touch with one of our headless commerce experts to learn more.