Want to know how much website downtime costs, and the impact it can have on your business?
Find out everything you need to know in our new uptime monitoring whitepaper 2021



Your e-commerce business only generates earnings when someone purchases an item from your site. Monitoring your add-to-cart rates can help you identify problems with your sales process and improve your conversion rate, and a higher conversion rate means increased revenue and profit.
The add-to-cart metric monitors the percentage of visitors to your site that add one or more items to their shopping cart. In conjunction with the bounce rate (the percentage of visitors who leave your site after visiting a single page) and cart completion rate (the percentage of visitors who purchase something), monitoring these metrics will give you an insight into the behavior of both customers and potential customers and allows you to troubleshoot your online business. In particular, your add-to-cart rates tell you a lot about your prices, product selection and marketing efforts.
If your site has a low add-to-cart rate (below 5%), you may have problems with site navigation, products offered, product pricing or product presentation. For example, your site may be difficult to navigate, so customers may have difficulty finding the products they wish to purchase, or your product selection and pricing may not compare favorably with your competitors, so your potential customers make their purchases elsewhere. Any improvements you can make in these areas should cause your add-to-cart rate to improve and improve your conversion rate.
Your add-to-cart rate can provide valuable information about the effectiveness of your marketing efforts. For example, say your average add-to-cart rate for the past year for customers who visit your site by clicking a link in a marketing email is 10%. After you launch a new email campaign, you can monitor your add-to-cart rate and see if it changes. An increase means that your campaign is effective, and you should continue to use that type of campaign.
Likewise, you can conduct the same type of analysis for any SEO strategies or search engine marketing campaigns. If your add-to-cart rate from search engine traffic generated by your new SEO strategy is below your long-term average for SEO-generated traffic, you’ll know that you should tweak the new strategy to make it more effective.
Unfortunately, e-commerce industry studies show that only between 30% to 40% of items visitors place in their shopping carts are purchased. Of course, not all sites experience such a low cart completion rate, but if your site is one of them, even a 5% improvement in the difference between your cart completion rate and your add-to-cart rate can give you a substantial increase in revenue.
It’s worth taking the time to analyze customer behavior in your shopping cart to see how you can increase your conversion rate. There are many possible ways to improve performance. For example, you can look at the completion rates for first-time customers and repeat customers. Logic would tell you that returning customers would be more likely to complete their purchases than first-time customers. If this is not the case, perhaps you have inadvertently made it more difficult than it needs to be for returning customers to reorder items. By tweaking your reorder process, you might be able to generate more sales.
Analyzing metrics can be tricky, but it’s worth the effort.
Share this
4 min read How AI Is Shifting Software Engineering’s Primary Constraint For most of the history of software engineering, the primary constraint was production. Code was expensive, skilled engineers were scarce, and shipping features required concentrated human effort. Velocity was limited by how fast people could reason, implement, test, and deploy. That constraint shaped everything from team size,
5 min read Autonomous Code, Trust Boundaries, and Why Governance Now Matters More Than Ever In Part 1, we looked at how AI has reduced the cost of building monitoring tools. Then in Part 2, we explored the operational and economic burden of owning them. Now we need to talk about something deeper. Because the real shift isn’t
6 min read The Real Cost of Owning Monitoring Isn’t Code — It’s Everything Else In Part 1, we explored how AI has dramatically reduced the cost of building monitoring tooling. That much is clear. You can scaffold uptime checks quickly, generate alert logic in minutes, and set-up dashboards faster than most teams used to schedule the kickoff
5 min read AI Has Made Building Monitoring Easy. It Hasn’t Made Owning It Any Easier. A few months ago, I spoke to an engineering manager who proudly told me they had rebuilt their monitoring stack over a long weekend. They’d used AI to scaffold synthetic checks. They’d generated alert logic with dynamic thresholds. They’d then wired everything
3 min read In the previous posts, we’ve looked at how alert noise emerges from design decisions, why notification lists fail to create accountability, and why alerts only work when they’re designed around a clear outcome. Taken together, these ideas point to a broader conclusion. That alerting is not just a technical system, it’s a socio-technical one. Alerting
3 min read In the first two posts of this series, we explored how alert noise emerges from design decisions, and why notification lists fail to create accountability when responsibility is unclear. There’s a deeper issue underneath both of those problems. Many alerting systems are designed without being clear about the outcome they’re meant to produce. When teams
Find out everything you need to know in our new uptime monitoring whitepaper 2021