Sometimes the problem isn't traffic. There are enough visitors. People find the store, browse the products, and leave. Or they buy, but less than they could.

That was exactly the situation for one Estonian niche e-commerce store. Organic traffic was high, healthy, and stable. Customers had a clear need. But revenue had plateaued.

We started with an order data analysis

Before making any changes, we ran a thorough data analysis. The store had years of history, which meant there was real data to work with. We looked at order history: seasonality, most purchased products, cart value distribution, purchase frequency, and customer behaviour patterns.

One question came up early in the analysis - was this simply a saturated market? The store sold primarily in Estonia, with smaller volumes to Finland, Latvia, and Lithuania, but wasn't actively expanding. The niche nature of the business meant a loyal but limited customer base.

We also looked closely at cart behaviour. In one of the analysed months, around 2,500 visitors had reached the cart, but only about 1,400 made it to checkout. That gap isn't unusual in itself - cart abandonment is a given in e-commerce - but it pointed us in the right direction.

One of the most significant findings concerned the distribution of cart values. The arithmetic average showed 70 euros, but the actual weighted average was considerably lower, around 30 euros. Most orders were small and inexpensive, with a handful of larger orders pulling the average up. The arithmetic mean had been hiding this pattern.

Looking at all the data together, we concluded that there was still room to grow revenue within the existing market. The store also wasn't running any paid advertising at the time, which further supported the hypothesis.

What we changed

The analysis pointed to specific friction points in the user experience. The changes weren't dramatic - they were precise.

  • Navigation: we restructured the menu layout and behaviour so that finding products required less effort. A customer should be able to find what they're looking for without thinking.
  • Banner: we added a persistent banner at the top of every page with key sales incentives. Information that had previously been buried was now visible at all times.
  • Product page: simplified. Unnecessary elements were removed, and the essentials - price, availability, buy button - were given clearer placement and hierarchy.
  • Product card: simplified the information shown in catalogue view. Fewer elements, clearer focus on the product.
  • Minor fixes: smaller detail and SEO improvements flagged during the audit.

Setting a free shipping threshold

Research shows that 40-50% of shoppers abandon their cart due to an unexpected extra cost, most often shipping. More than half of shoppers won't buy from a store that doesn't offer free shipping at all. And on the other side: when free shipping is available, over half of shoppers add products to their cart specifically to reach the threshold.

The threshold amount wasn't arbitrary. Since the weighted average cart value was around 30 euros, we set the threshold a few euros above that. High enough that most customers would need to add something extra, but low enough that it didn't feel out of reach. Had we gone by the arithmetic average and set it at 70 euros, it would have been too far for most customers and the effect would have been lost.

We brought the free shipping information to the front - the homepage, the cart view, and the header. A customer who can see they're 5 euros away from free shipping behaves differently than one who can't.

Immediate and long-term results

Alongside the changes, we also ran some ad campaigns. Results came quickly - in the first weeks after the changes were in place and campaigns live:

  • Week one: 40€ ad budget brought in 1,000€ in sales
  • Week two: 80€ brought 2,000€
  • Week three: 80€ brought 5,400€
  • Conversion rate from ad visitors: 6.6% - 2% higher than organic purchases
  • Average cart from ad visitors: 125€

These numbers don't come from the ads alone. Ads bring someone to the page, but the page itself has to be ready to receive them - simple navigation, visible incentives, clarity and focus. The same changes outlined above.

The longer-term picture is equally clear. Over 1.5 years, average order value has grown from around 70 euros to around 100 euros - a growth of over 40% without opening new markets or significant additional cost. The ad campaigns were temporary. The changes stayed.

What this shows

Conversion optimisation isn't just A/B testing or changing button colours. It starts with data - understanding who the customer is, how they behave, and where they get stuck.

A surface-level analysis would have shown a 70-euro average cart and suggested a matching free shipping threshold. A deeper analysis showed a different picture, and that difference made the decision more precise. Every store is different - the right decision always comes from the actual data, not a general rule of thumb.

When that picture is clear, the changes tend to be smaller and more targeted than expected. And targeted changes hold up longer.