Amazon Conversion Rate Optimization: How to Turn More Clicks Into Sales

Why Traffic Alone Rarely Fixes Weak Sales

Every seasoned Amazon seller can relate to the situation when there is a steady increase in sessions with no progress in sales. What most sellers do is purchase more traffic, raise their bids, or start yet another promotion. It makes sense, indeed, but the cause of their problem may lie elsewhere namely, in their listing. As customers become interested in the products and click on sponsored advertisements, they go to the product page, examine the offer, and continue browsing without purchasing anything.

Amazon CRO focuses on figuring out why relevant customers do not buy. Let's take into account one theoretical product that receives 6,000 sessions per month with the unit session percentage at 9%. This means that there are 540 units ordered. If the percentage increases to 11% under the same conditions, 660 units will be ordered for the same number of sessions, 120 more than before. The exact numbers can differ but the example is sufficient enough to understand the importance of CRO.

This article explains the basic principles of Amazon CRO, what metrics to track, how to distinguish the issues of conversion from those of traffic, and how to prioritize changes without jeopardizing the profits.

What Amazon Conversion Rate Optimization Covers

Conversion rate optimization on Amazon refers to the improvement of the listing and overall shopping experience, with the aim of making the relevant shoppers purchase. It is not copywriting. The images, title, bullet points, and A+ content are important, but price, promotional actions, reviews, delivery time, stock level, and Featured Offer ownership, which is shown in the main shopping area, are also crucial factors.

Even the best-written listing cannot make up for any issues with the offer. In case the product is out of stock, the delivery time is not competitive or the price is unreasonably high, even the most compelling images and copy will be unable to retain the shopper.

It is also important to consider traffic quality. A listing might be getting enough shoppers but still convert badly because of ads targeting irrelevant search terms or shoppers expecting something else in terms of size, compatibility, quantity, use case, etc. Competitors' offers affect the choice too, since customers tend to compare several products before purchasing.

This way, effective CRO implies analyzing the whole shopping experience. Conversion rates are not the only thing that should be improved. The purpose is to facilitate informed purchases made by the right shoppers.

Measuring Conversion Without Fooling Yourself

Unit Session Percentage is often used at the product level in Seller Central Business Reports. It is calculated as units ordered divided by sessions, multiplied by 100.

For example, ASIN 1,500 sessions and 180 units ordered give a unit session percentage of 12%:

180 ÷ 1,500 × 100 = 12%

It is important to note that it calculates units, not unique customers that place orders. If a buyer buys three units in one session, then all three units will be counted in the numerator. As a consequence, unit session percentage can be greater than the percentage of sessions leading to an order, especially when it comes to multipacks, consumables, and goods that are sold in multiples.

Use it but do not forget about the meaning. Business Reports is a good source for comparing sessions, units ordered, sales and performance of the ASINs. Before comparison of the numbers in different dashboards, make sure that periods of time, definitions of the metrics and attributions are the same.

A percentage number without explanation can cause incorrect conclusions. Always check the traffic, units, money and changes in the offer along with the conversion rate.

Listing Conversion and PPC Purchase Rate Are Different Problems

Product conversion and advertising metrics refer to different stages of the customer journey. The Unit Session Percentage metric is a product metric that compares units ordered to listing sessions. On the other hand, the Amazon Ads Purchase Rate metric refers to the number of purchases divided by the number of ad impressions, as per Amazon's definition of the metric.

For instance, consider an ASIN with 4,000 sessions and 480 units ordered resulting in a unit session percentage of 12%. Also, consider a campaign with 20,000 impressions and 300 clicks having 12 attributed purchases, which gives it a purchase rate of 0.06% (12/20,000). However, its purchase to click ratio will be 4%, and that is not a purchase rate but a ratio.

The gap between the overall listing performance and campaign performance does not mean anything about what the problem is. One needs to review the search terms used, targeting, number of clicks, number of attributed purchases, and what the shopper sees.

This is also possible in the opposite case as well. This occurs due to the fact that people who are visiting the site through branded campaigns will differ in terms of purchase intent when compared to people who are searching for information in general terms through non-branded searches. This should be considered separately in two questions.

Building a Baseline That Fits Your ASIN

There are general statements that state that a healthy Amazon conversion rate should be somewhere within the range of 10-15%. These numbers are to be considered in the context only and are not to be taken as universal metrics. Various factors like category, price, brand name, quality of the reviews, traffic sources, seasonality, delivery time, and featured offer position, as well as multi-unit orders, might influence the number.

Each ASIN needs to have its own base metric. For this purpose, it is important to analyze a few recent weeks in terms of sessions, unit session percentage, units sold, and sales volume. It is important to compare the numbers with previous weeks when possible and track any changes related to price, coupons, promotions, inventory, delivery, and any other advertising.

Where available, split performance by traffic sources or campaigns in order to prevent yourself from misinterpreting your changes in the listing as the reason for an increased sales performance when the actual reason is a difference in ads. Compare siblings and competitive products.

A decline in listing from 11% to 8% following an increase in prices calls for investigation. However, prior to any further adjustments in prices, see if there have been any changes in traffic, availability, deliveries, or competition. It is always useful to have a benchmark from which to measure changes.

Diagnosing Where Shoppers Hesitate

For every issue in conversion, there are specific tests and reports to confirm the problem.

In case sessions decrease and the unit session percentage stays the same, then it means that you need to look into the visibility. Look at the keyword ranking, impressions on ads, budgets, and demand.

When sessions stay the same, but the conversion goes down, then you need to look at the offer first. It includes the price compared to the competitors, featured offer status, inventory, and delivery times. After that check the listing content.

If the click-through rate for the ad goes up but there is no increase in the attributed purchases, then you should look at the search term report, relevance, and campaign parameters. When both organic and paid performances are decreasing, then there might be some shared problem related to pricing, availability, delivery or listing description. When one campaign performs badly but the listing performance stays the same, then look at the changes in search terms, relevance, bidding, and traffic quality and rewrite your listing.

Then go through the product page on a mobile phone as if you’re a first-time customer. Does the product become obvious from the get-go? Do the pictures clearly indicate the product’s size, quantity, material, and function? Is it easy to locate the vital details? Look at the comments that users have made to identify common objections. If customers say something is too small, there might be a problem with the sizing info.

What to Fix First

Consider the factors that affect the offer directly: uncompetitive price, loss of featured Offer status, small stock, or an unappealing delivery estimate. Fixing the images won't save a product that is difficult for customers to buy.

First, analyze the primary image and the first secondary images – those that show the key characteristics of the product and allow potential buyers to understand what it is and what questions it solves. Next, work on the title and bullet points, addressing customer questions and not keyword stuffing.

It all depends on the category. Socks and clothing require size information, details about fit, material used, and the number of pieces in one pack. In reusable food storage bags, buyers want to know their dimensions, capacity, the closing system, and the number of bags included. Compatibility and technical characteristics of electronics accessories are essential.

After optimizing the offer and listing, consider whether there is room for improvement of A+ Content, adding video, or creating bundles. At the same time, examine low-intent keywords and implement negative targeting as needed.

A Worked Example, Including Profit

Take for example that an ASIN generates 5,000 sessions and has 8% of unit session percentage, which results in 400 units ordered. The same traffic after an appropriate listing modification gives 10% and generates 500 units. Of course, this is a fictional case. The point is that you cannot conclude that the whole change is caused only by the change made without taking into account the traffic mix, pricing policy, promotions, and other aspects.

The next issue is whether the increased number of sales is profitable or not.

For example, a product is priced at $30 with a total per-unit product cost of $18, Amazon fees, and fulfillment costs. In total, there is a $12 profit per unit, ignoring other costs. In the case of 400 units, there will be $4,800 contribution. In the case when the price is lowered by 20% to $24, the contribution will be $6 per unit keeping all costs the same as above mentioned. Thus, the contribution with 500 units will make $3,000.

It should be compared with the sale of 500 units with a $30 price, which makes a $6,000 contribution under the same conditions.

An enhancement to the list that helps in clarifying sizes, contents, compatibility, and benefits of products will ensure better decision-making by consumers while ensuring that the price is not compromised. It can also ensure fewer unnecessary returns, but this must be proven through evaluation.

Use net profit after discounts, advertisement expenses, Amazon fees, fulfillment, and product costs for measuring the impact. Also measure returns and customer feedback. The goal here is profitable conversion, not maximum conversion.

Testing Without Fooling Yourself

Another one of the most frequent mistakes involves assuming that a change is successful after just one day of analysis. Conversion rates fluctuate due to the day of the week effect, promotions, competitors’ actions, traffic composition, and randomness. There is not any universal duration of the test and number of sessions suitable for all ASINs.

Keep in mind the traffic of the product, the magnitude of the expected improvement, standard deviation, and the period of time that includes representative shopping days. Low-traffic products require special attention since an increase in a few orders may make the conversion rate differ significantly without proving a solid trend.

The Amazon’s Manage Your Experiments feature enables controlled experiments on eligible brand content. The availability of the tool depends on the brand and ASIN eligibility, including enough recent traffic; it differs depending on the marketplace and type of products. If it is available, then a controlled experiment is more informative than an analysis of the comparison of the results prior to and after the changes in listings.

Before implementing it, determine your baseline measurement, your hypothesis, the thing to be changed, duration of the test period, and the business performance dimension that you plan to influence. Try to vary no more than one big thing at once; when doing this, it would make it difficult to interpret the result.

Determine in advance what success means for you. It may well be worth implementing the change if its effect on the business performance measurement dimension selected by you proves to be positive without causing negative consequences for profit, return on investment, or customer satisfaction. If the result is negative, it is time to reconsider your hypothesis.

Your Seven-Day Starting Plan

Select one ASIN and use the first week to research and implement one change supported by solid arguments.

On the first day, export the relevant information from the business report and set up the base value. On the second day, find out if your major problem is related to the traffic issue, conversion issues, or both. On the third day, check the price, featured offer, inventory, and delivery issues. On the fourth day, check images, product details, reviews, and frequently asked questions from customers. On the fifth day, analyze campaign keywords and targeting in case of irrelevant traffic. On the sixth day, select one change and note your reasons why it should work. On the seventh day, implement the selected change and schedule the future evaluation date.

Seven days are dedicated to the audit and first change implementation rather than to the final evaluation.

Conclusion

Conversion optimization on Amazon involves making the most out of the traffic you have attracted. Start off with making sure that the offer is competitive and available, and then work towards optimizing the images and data affecting the decision-making process. First diagnose the metrics, make relevant changes, and finally measure results on the basis of successful conversions, not the conversion rate alone.

What is the most important thing to consider is not only how to bring in customers into the product page. The important questions to be asked are: Why do the right customers doubt? What is the proof that can be offered? What needs improvement for converting them?