How leading retailers can maximize performance and online revenue

January 2, 2020

For retailers, Winter holiday shopping season is like a yearly championship series. How well mobile apps and web sites perform during this crucial November-January period can make or break an entire year.

Can a mobile shopper quickly and reliably connect? Search and compare products? Load a cart and check out? Check account status? Always important, these basic online tasks are crucial during the busiest buying times.

In top world markets, holiday sales alone can account for 20-25% or more of annual revenue. Percentages are lower in Latin America. But projected ecommerce growth of 15-20% a year, and the world’s fastest growth in mobile commerce (36%), make the region one of the hottest online shopping markets in 2020 and beyond.

Like all teams, online retailers come to the annual winter competition with both strengths and areas needing improvement. Winners build on the former and work hard to improve the latter. The bigger the brand, the more challenging (and crucial) to get and stay in top shape for the holidays and the rest of the year.

The reason is simple: Regardless of geography or season, there’s a straight line between high-performing shopping apps and maximizing sales:

  • A global study by Google found that as page load time goes from one to five seconds, the probability of a bounce increases 90%.
  • Akamai found that a 100-millisecond delay in website load time can hurt conversion rates by 7%.
  • Amazon calculates that every 100-millisecond delay leads to a 1% loss in sales. That means a five-second delay can cut sales by 50%!

In this post, we’ll identify top issues that shopping apps face and provide recommendations based on proven general fixes, derived by our AI engine, to uncover new opportunities for ecommerce optimization that can provide benefits during peak season. We’ll also show how AI-driven testing can help online retailers improve mobile app performance to enable increased sales year-round.


Domain Sharding

Cause: This technique can be effective with a code base optimized for web applications, but it’s a problem for mobile apps. An application using multiple subdomains to serve resources in parallel. Performance issues arise because mobile devices and the Web have different connection pool limits. Each additional connection on a subdomain requires a DNS lookup and new TCP/TLS handshakes, causing significant overhead. Resources from within an app must be better served to avoid problems here.

Solution: Request all resources from a single domain. That will reduce performance impact from connection re-use issues, DNS lookup time and packet loss.

Connection Reuse

Each new connection incurs a performance cost. When many new connections are made repeatedly, costs adds up, slowing and negatively impacting user experience.

Cause: This happens when the application creates new TCP connections instead of reusing existing ones. If keep-alive connections aren’t enabled, or the timeout is set too low, client connections terminate prematurely, resulting in unnecessary TCP/TLS handshakes for impacted hosts. This can lead to repeated spinning wheels.

Solution: So the first step here is to check the keep-alive settings on the host server.

HTTP Redirects

These can be costly, especially if they introduce a new host. Doing so can incur additional DNS, TCP, TLS and request-response roundtrips, which add unnecessary delays. The fix starts with a systematic, detailed review of HTTP response status codes.


For our performance deep dives, we conduct sessions, not emulations or simulations, under real-world conditions using the HeadSpin Digital Intelligence Platform. Our tools identify, prioritize and visualize mobile app performance improvements using AI-powered issue detection.

HeadSpin’s AI powered platform drills down and analyzes issues in three different dimensions: By Location, Device, and Carrier, to help us assess individual and combined impact of each issue on user experience.  More importantly, it will prioritize the most impactful fixes.


This example of a “forest-level” assessment shows how well an app performs across the network, carriers and locations. It delivers a high-level summary of the most important and actionable insights. These include: key findings and test statistics, benchmarks and comparisons, and high-fidelity video examples of key user sessions, before and after potential improvements.

To ensure statistical significance, the HeadSpin AI engine analyzes several sessions, checking every possible combination of location, device and carrier. Doing this test first helps focus our efforts and provides initial, AI-driven identification and prioritization of issues.

Here’s the high-level Waterfall view of overall results for a session that shows the issues impacting the user experience. The middle section with flags shows details of Domain Sharding, down to the server level. The video screen at right shows what the user sees at that and every step.

Here’s the Burst view….

In both views, you can easily spot familiar issues (Connection Reuse, Domain Sharding. HTTP Redirects).

Example Issue: Domain Sharding

In the above example, the yellow-orange line at the top right shows that fixing Domain Sharding would yield a 7x benefit. In other words, every dollar invested in fixing the issue would return seven.

The bottom bar shows similar benefit for fixing Slow Server. Let’s drill down on this property to analyze further with the BurstUI.

The mobile device screen at the top left shows what the user is seeing during the testing moment (in this case, permission to track location). The bar graph to its right reveals the combined impact of the four biggest performance issues: 2.19 seconds.

In both the peak of the line graph (middle) and the Issue Cards (below), we see that Loading Animation and Slow Server have the biggest negative impacts on user experience.

For this example, optimizing for Location will provide the most bang-per-buck in remediating all the problems identified.

HeadSpin’s “Potential Improvement” capability shows the net impact of fixing user experience issues. Using the data from the First Load Report, we can see the effect of remedying individual problems or combinations.

For example, this chart shows that 95% of user flows would at least be 3.27 seconds faster by fixing the issues identified by the First Load report. (We can easily analyze the performance impact and percentage of users impacted by other improvements.) While every retailer doesn’t need world-class speed, every fraction of a second translates into real revenue.


Winter holiday season is crucially important for online retailers. Systematically improving the performance of mobile apps and websites helps sellers perform their best during busy times, and throughout the year.

Leading retailers have created quick, solid, multi-functional shopping apps. They’re fast-starting, but can get bogged down during use and peak season. Our tests pinpoint technical issues, including slow animation, connection reuse, domain sharding and HTTP redirects. Each could be fixed and optimized for faster, smoother mobile shopping.

By continuing to create better online experiences for customers, retailers can further their own transformation, strengthening revenues and position in the highly competitive retail market.