What factors may influence your Conversion Rate?

What factors may influence your Conversion Rate?

What factors may influence your Conversion Rate?

What is a website conversion rate in eCommerce? I’ve asked ChatGPT precisely this question, and here is what I’ve received as an answer.

In e-commerce, website conversion rate is a metric that measures the percentage of visitors to an e-commerce website who complete a desired action, such as making a purchase, adding items to their cart, or signing up for a newsletter.

A high conversion rate in e-commerce indicates that a website is effective in converting visitors into customers, which ultimately drives revenue and profitability for the business. Conversely, a low conversion rate indicates that there may be issues with the website design, user experience, or product offering that are preventing visitors from completing their purchase.

To calculate the website conversion rate in e-commerce, divide the number of completed transactions (purchases) by the total number of website visitors during the same period of time and multiply the result by 100.

For example, if an e-commerce website had 10,000 visitors and 500 of them completed a purchase, the website conversion rate would be 5% (500/10,000 x 100).

By tracking and analyzing the website conversion rate, e-commerce businesses can identify areas for improvement and optimize their website to increase sales and revenue. This may involve testing different product offerings, improving the checkout process, or optimizing the website for mobile devices.

The conversion rate is commonly associated with the effectiveness of a website in turning visitors into purchasers. However, it's essential to recognize that while a low conversion rate might indicate issues with converting visitors, there can be other factors influencing the change.

In this article, we will explore several factors that can impact your conversion rate beyond the website's conversion ability. Understanding these factors is crucial because misdiagnosing the true cause behind the decline in conversion rate can lead to taking ineffective actions. In fact, such actions might worsen the situation rather than improving it.

Analyzing Conversion Rate Across Specific Traffic Segments

When assessing changes in the conversion rate, it is important to examine the performance of specific segments, as this allows for a more accurate diagnosis of the problem. Let's explore the typical segments we analyze:

1. Profile Category Segmentation

One of the fundamental customer segmentations we employ for our clients is based on whether a website visitor has previously visited the website or made a purchase. We identify three primary segments:

  • First-time visitors: Individuals visiting the website for the first time.
  • Returning visitors: Individuals who have visited the website before but have not made a purchase yet.
  • Returning purchasers: Individuals who have made a purchase in the past.

Notably (though not surprisingly), the average conversion rate varies significantly across these three segments. Here are the usual conversion rates observed for each segment:

CR% by profile segment
CR% by profile segment
Traffic Proportion by Profile Segment
Traffic Proportion by Profile Segment
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We observe a significant difference in purchasing behavior between Returning Purchasers and First-time visitors, with Returning Purchasers being more than 3 times more likely to make a purchase.

Suppose we analyze the traffic distribution based on a specific profile segment over two particular days:

Day 1 traffic distribution:

Traffic
Orders
CR%
First-time visitor
10 000
250
2.50%
Returning visitor
10 000
400
4.00%
Returning purchaser
10 000
900
9.00%
Total
30 000
1 550
5.16%

Day 2 traffic distribution:

Traffic
Orders
CR%
First-time visitor
10 000
250
2.50%
Returning visitor
10 000
400
4.00%
Returning purchaser
20 000
1800
9.00%
Total
40 000
2 450
6.13%

The only difference between the two days is that there were twice as many Returning purchasers visiting the website on day 2 compared to day 1.

While the conversion rate for each profile category segment remained the same, the overall conversion rate increased.

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This change in overall conversion rate has nothing to do with the website's conversion ability. Instead, it is simply due to the increased presence of Returning purchasers, who, on average, have a higher likelihood of converting.

2. Traffic Source Segmentation

Once again, it comes as no surprise that traffic from certain channels tends to be more qualified than others.

For instance, visitors coming from a Paid Search campaign are typically more likely to make a purchase compared to those coming from Paid Social.

This discrepancy arises because these channels typically serve different purposes. Paid Social campaigns often focus on generating awareness for an eCommerce brand or its products, targeting the upper funnel. On the other hand, Paid Search captures visitors who already have a specific need, such as searching for new shoes, thereby targeting the lower funnel.

Paid Search & Paid Social CR% comparison.
Paid Search & Paid Social CR% comparison.

When launching a large-scale awareness campaign, it is expected that the conversion rate may decrease, as it may attract visitors who are not as qualified. However, it is important to note that this decline is not reflective of any changes in the website's ability to convert. Rather, it is a result of attracting fewer quality leads.

3. Session Activity Segmentation

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Individuals who engage more with a website are more likely to convert.

At Datacop, we typically measure website activity based on the number of product_view and category_view events.

These events effectively indicate the number of products that visitors have viewed on the website during one session.

Additionally, we define non-active sessions as those in which visitors leave the website after viewing only one page.

Typically, around 40% of all traffic falls into the non-active category, which can also be referred to as the bounce rate.

The following distribution represents the usual conversion rate based on the level of engagement during a particular session:

image
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A sudden decline in highly engaged website visitors may indicate several issues:
  • The website's ability to convert has worsened compared to the past.
  • The website navigation has deteriorated compared to the past.
  • You are attracting less qualified traffic to your website.
  • The purchasing power of your website visitors has decreased.

4. Change in product offering or product promotion.

When your conversion rate begins to decline, it can be attributed to various factors related to your product offering. One possibility is that your product offering is no longer as competitive as it was in the past. Another factor could be promoting the wrong product to the wrong audience, or even promoting a product that is currently not in demand (such as promoting boots during summer).

To effectively monitor and analyze these factors, we recommend tracking the Product CR% (Product Conversion Rate), which is calculated as Units Sold divided by Product Views.

Let's consider the following analysis comparing the year-over-year Product CR% for five different product categories:

image

Click here for a full-screen view

From this table, we can draw three key observations:

Observation 1: For product category 1, the Product CR% has significantly decreased compared to last year, while the product views remained relatively stable. This decline may indicate that the product offering within this category is not as appealing as it was in the previous year.

Observation 2: For Product Category 2, it is evident that the category was overexposed last year, resulting in a low product conversion rate despite a significant number of product views. This year, we have adjusted our strategy by reducing the overall exposure of this category (thus reducing product views), which has led to an increase in the Product CR% that is now closer to the average.

Observation 3: Categories 3 and 5 exhibit higher Product CR% compared to the average, indicating that these categories hold greater potential for promotion and marketing efforts.

Comparing conversion rate against the past performance

The conversion rate also exhibits variations depending on weekdays, with each vertical having its own distinct weekday pattern. For instance, in a fast fashion eCommerce store, you might observe a spike in conversion rate every Thursday as website visitors shop for a new look for Friday evening.

image

When comparing conversion rates with past performance, it is essential to ensure that we compare the same days of the week. For example, when analyzing month-over-month performance, we compare today's performance against that of 28 days earlier, rather than 30 days, in order to compare equivalent weekdays.

The same principle applies to quarter-over-quarter (91 days instead of 90) and year-over-year (364 days instead of 365) comparisons.

However, there are exceptions to this rule:

  1. During a sales period that consistently begins on a specific date (e.g., December 1st), when comparing this year's performance to last year's, we need to look back 365 days instead of 364 to ensure accurate comparisons.
  2. If a significant portion of the country's population receives their payday on the 15th of each month, this may cause a spike in your conversion rate. However, it is important to note that this pattern may vary in different geographical regions.

Shop Monitoring - Our Preferred Tool for Analyzing Website Conversion Rate

At Datacop, we recognized the importance of having a user-friendly tool that enables easy analysis and monitoring of a website's conversion rate, along with other essential metrics. To address this need, we developed a powerful tool called "Shop Monitoring."

Shop Monitoring offers a range of features that allow you to delve into your website's conversion rate, providing valuable insights. With this tool, you can break down the conversion rate by various traffic cohorts, including:

  • Profile category
  • Traffic source segmentation
  • Session activity
  • Newsletter subscription status
  • Weekday
  • Landing page category
  • And more

Furthermore, Shop Monitoring allows you to conveniently adjust the comparison periods according to your preferences. This flexibility ensures that you can analyze and compare data over specific timeframes that align with your needs and objectives.

To illustrate the capabilities of Shop Monitoring, below are a couple of example dashboards showcasing the tool's functionalities:

Detailed Breakdown of CR% into specific traffic segments (line chart)
Detailed Breakdown of CR% into specific traffic segments (line chart)
Detailed Breakdown of CR% into specific traffic segments (table)
Detailed Breakdown of CR% into specific traffic segments (table)
Detailed Breakdown of Conversion Funnel into specific traffic segments
Detailed Breakdown of Conversion Funnel into specific traffic segments

With Shop Monitoring, you have the power to explore and understand your website's conversion rate in-depth, utilizing various segmentation options and flexible comparison periods. This tool equips you with the insights necessary to make informed decisions and optimize your conversion rate effectively.

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