Conversion rates aren’t just significant for e-commerce platforms; they hold value for anyone interested in the impact of their design ventures.

Defining Conversion Rate (CR)

Definition: The conversion rate is the percentage of users who take a desired action. The archetypical example of conversion rate is the percentage of website visitors who buy something on the site.

Example: An e-commerce site is visited by 200,000 people during the month of August. During that month, 4,000 users (customers) made a purchase from the site. With this data we calculate that the site’s conversion rate (CR) is 4,000/200,000 = 2%.

How should we define the baseline number of “users”? Should it be based on unique visitors, or should a user be counted multiple times if they visit more than once within the measurement period? (For instance, if Jonathan visits 6 times and Sarah just two, are there 2 visitors or 8?) Both methods are valid; choose the one that best aligns with your site’s needs, but be sure you maintain the same counting method across all measurement intervals — don’t go back and forth as this will “muddy up” your data and can lead you do making wrong design decisions in the future.

Regarding users who take “desired actions” or conversions, how should we count them? The options remain: either count an individual once regardless of the number of times they perform the action, or count them for each occurrence. (For example, if Jonathan makes three purchases and Sarah none, is it one or three conversions?) Ideally, stick to the counting method chosen for the baseline user count, but consistency is key in whichever approach you decide.

A method I use when it comes to measuring Conversion Rate for e-commerce is to segment out converted users by “First-time Customers” and “Returning Customers.” My current role focuses on Conversion Rate Optimization for First Time Customers on a storefront via prospecting (cold traffic) tactics: i.e Paid Social Media. Separating out the two is best practice for us as returning customers are highly qualified buyers (they already know the brand/site) and will ultimately make the relative conversion rate look much better than it really is.

What’s a Conversion Event?

Conversion rates aren’t just significant for e-commerce platforms; they hold value for anyone interested in the impact of their design ventures. A conversion isn’t limited to sales. It can be any vital metric or key performance indicator (KPI) significant to your business. Some instances are:

  • Making a purchase on an online shopping platform.
  • Registering as a user.
  • Saving credit-card details for quicker future checkouts.
  • Enrolling for a subscription, paid or otherwise.
  • Acquiring trial software, insightful reports, or any resource that might lead users further down the sales path.
  • Inquiring about a professional service or B2B offering.
  • Transitioning from a basic service tier to a premium one. Here, the primary user count should encompass users already at the initial tier.
  • Not just downloading, but actively engaging with a mobile app, or still using it after a week.
  • Engaging with a site for a specified duration or accessing a set number of articles.
  • Revisiting the site beyond a specified frequency during the assessment phase. Here, it’s logical to consider the user count as individual visitors.
  • Any specific action, measurable by a system, that you intend users to undertake.

The Significance of Conversion Rates

Naturally, monitoring the total number of valued user actions is crucial. However, when it comes to evaluating your user-interface design and understanding the impact of your UX endeavors over time, the conversion rate often takes precedence over the sheer count of conversions.

Imagine a scenario where, without altering the design, a potent advertising campaign dramatically boosts the conversion count by generating increased interest in your product. Kudos to the marketing team! But this surge in site activity isn’t due to design modifications, so attributing this success to the design team wouldn’t be accurate.

The conversion rate zeroes in on user activity once they land on your site. Since it’s profoundly influenced by design, it’s a crucial metric to monitor to gauge the efficacy of your UX approach.

Witnessing a continuous drop in conversion rates? It might indicate issues with the design, regardless of the inflow of traffic due to stellar advertising efforts.

On the other hand, a rise in conversion rates? That’s a moment to commend your design team. (However, if this increase is primarily due to a sale or discount, attributing the uplift solely to design becomes debatable, especially if other factors remained constant.)

When Raw Numbers Surpass Relative Metrics

While it’s typically more insightful to monitor the percentage of users converting, there are instances where this doesn’t hold true.

In situations where traffic is erratic and varies significantly in quality, relying solely on percentages can lead to skewed perceptions.

An example: Let’s say you or someone on your team published a funny article to Facebook or video on TikTok (something not geared towards gaining sales. Think along the lines of Branded Content) — and it wen’t semi viral. That day the site’s storefront got 8 times as much traffic as it does on a normal day. Even though you had a surge on the site, most of these extra visitors didn’t make a purchase — CR remained at about the same absolute number as on an average day. And after reviewing the data, you note that your conversion rate plummeted to almost a quarter of its normal level.

Now, in any case one shouldn’t obsess over conversion rates to the extent of tracking them on a daily basis. But even after the full week, your conversion rate was about half of normal (because traffic was twice the norm). Was the site design suddenly half as good? Were your products suddenly being rejected by half the target audience? No, what happened was that there were a huge number of one-time visitors who visited the site because of the semi-viral article or TikTok, but who were not in the target audience for buying your product.

If you’re experiencing a sudden increase in traffic, it’s essential to identify its origin. It’s plausible that these new visitors differ from your regular audience and might not convert similarly. While minor variations get neutralized in long-term data, significant spikes demand manual scrutiny. One approach is to examine the total count of conversion events. If these figures remain consistent with previous patterns, it could suggest an influx of visitors outside your primary target demographic.

Choosing the Right Measurement Period

Looking for a straightforward answer? A month serves as a practical timeframe to evaluate both the baseline user count and conversion event numbers.

However, in reality, there’s no one-size-fits-all solution. The ideal period can vary based on specific goals. When determining the length of your measurement period, consider the following:

  1. Frequency vs. Impact: It’s essential for the measurement period to be concise enough that monitoring conversion rates across multiple intervals can still influence business outcomes. While a yearly measurement might offer robust data, it could be too long to extract actionable insights that boost profitability in time.
  2. Consistency vs. Variability: Ensure the period is extended enough to mitigate random fluctuations and capture as many consistent trends as possible. For instance, many B2B platforms see reduced activity during weekends. Analyzing conversion rates daily might result in dramatic fluctuations unrelated to genuine performance. A weekly timeframe would minimize these discrepancies.
  3. Alignment with Development Cycles: The period should be synchronized with your product’s evolution. If significant design modifications are made monthly, adopting a quarterly measurement can be misleading. It’d blend results from different designs, making it challenging to discern which design impacted the conversion rate.
  4. Seasonal Considerations: Whatever period you select, be aware of seasonal variations within that window. For instance, while many consumer sites see spikes during December holidays, niche platforms might observe reduced activity during peak shopping times.
  5. Statistical Significance for Low-Volume Sites: For platforms with minimal activity, it’s vital to have a sufficiently lengthy measurement window. Sparse conversion events within short intervals can lead to inconsistent conversion rates due to random variations. Employ standard statistical methods to ensure the captured data is genuinely indicative.

In essence, while determining the right measurement period, it’s crucial to strike a balance, ensuring you capture relevant data while remaining agile enough to adapt and act.

Coming up, we’ll move into What’s a “Good” Conversion Rate and how it ties in with your sites User Experience and design.