Start with the path from each traffic source to purchase: landing session, product view, add to cart, checkout start, purchase. Split it by source, device, country, and landing page. The first step that drops sharply tells you where to look. Weak product views point to ad-to-page mismatch or navigation. Weak add-to-cart suggests product clarity, price, delivery, or trust. Weak checkout starts call for testing the cart and checkout when accessible.
Then watch a small set of recordings from that weakest segment to see what caused the drop. Since AOV looks steady, I would leave bundles and pricing alone initially. Change one thing for a week, then compare the same segment again. That keeps the dashboard from turning into a list of unrelated guesses.
@Olivaa.13 ,
I usually start by looking at the conversion funnel rather than individual metrics. If traffic is increasing but orders arent the problem is often on the product pages or during checkout.
After that I check session recordings and customer behavior to see where visitors are dropping off. Real user behavior often reveals issues that analytics alone dont.
Hi there @Olivaa.13
A good rule of thumb is to compare every step of your funnel rather than look at aggregate numbers. Look at the landing page, add to cart rate, checkout start, purchase complete to find out where the drop is. Sesion recording and heat maps may identify friction, and product page, mobile and site speed reviews may highlight low-hanging fruit. Testing small changes on a single issue at a time also allows you to better track what’s having a genuine impact on conversions.
Hey, @Olivaa.13
I trust all is well on your end!
I usually start with conversion funnel. If traffic is hot but order is flat, I look at where people are dropping off product pages, add to cart, checkout and payment. Session recordings and heatmaps can reveal a lot of friction that analytics alone won’t show.
Agreed, the more data there is the more confusing things get
Instead, I think it’s best to try working backwards through the customer journey to find where the biggest drop-off is.
For example:
Traffic → Product page: Are visitors landing on the right pages, and are they engaging?
Product page → Add to Cart: If this is low, I usually review product images, descriptions, pricing, reviews, and page speed.
Add to Cart → Checkout: If this is where people drop off, I look at shipping costs, payment options, checkout friction, or unexpected fees.
Checkout → Purchase: This often points to payment issues, trust signals, or abandoned checkout behavior.
After that, compare performance by product rather than looking at the store as a whole.
Sometimes one or two products are responsible for most of the revenue, while others get plenty of traffic but rarely convert. That makes it much easier to prioritize what actually needs attention.
Thanks, @SealSubs-Roan! I like your point about focusing on the funnel instead of aggregate metrics. Breaking it down step by step definitely makes it easier to spot where the biggest opportunity is. Do you have a favorite tool for session recordings or heatmaps?
Thanks, @dolia_goprofit! Looking at performance product by product is a great point—I hadn’t considered that angle. Have you found that a small number of products usually account for most conversion issues, or does it vary a lot from store to store?
Appreciate the insights, @LitExtension! I agree that it’s often a combination of small friction points rather than one major issue. Out of the areas you mentioned, which one tends to deliver the quickest improvement in your experience?
Thanks, @SectionKit! That’s a helpful way to think about it. Starting with where customers drop off instead of looking at individual metrics makes a lot of sense. Have you noticed any particular friction point that shows up more often than others?
Thanks, @rshrivastava63! I like that approach. Session recordings can definitely reveal things that reports alone don’t. Have you ever been surprised by something users were doing that you wouldn’t have expected from the analytics?
Thanks, @ReviewMyEcom.com! I really like the idea of following the customer journey by traffic source instead of looking at everything together. Focusing on one change at a time also makes it much easier to measure what’s actually making a difference.
@Olivaa.13 ,
Definitely! One thing that surprised me was seeing users repeatedly clicking on images or text that they expected to be clickable. Analytics just showed they were leaving the page but the session recordings made it obvious they were getting frustrated. I’ve also seen people abandon checkout because a shipping cost or payment option appeared later than they expected. Those are the kinds of insights that are hard to spot from numbers alone.
