In Part 1, we outlined the relative nature of conversion rate and why it’s necessary to understand that conversion rate can be calculated a number of different ways. We also explored some things to keep in mind when analyzing your conversion data.

Now that we’re settled on what conversion can be, let’s discuss some methodologies used in calculating conversion by channel. Again, for the purposes of this blog, we’re going to focus on digital channels in retail industry.

 

E-commerce

Conversion rate Let’s start with looking into the conversion rates used to monitor your e-commerce performance at a high level. Keep in mind that all of the following rates can be broken down and further analyzed by audience-type, behavior, channel, and more.

Buyer Conversion Rate: The “buyers/visitors rate” is defined as the number of customers converted divided by the total number of visitors to the website during the same period. There are two very important parts of this definition:

  • Buyer conversion rate is a measure of visitors to your site. This is different from the “visits” metric. There is an array of opinions on the definition of “visitor,” as well as questions presented about the accuracy and authenticity of this metric. You can read about some of those arguments here. Regardless, this metric sums the individual users arriving to your site, not the amount of times your site was used.
  • The measure of time in the calculation is crucial. This is because each reported period has an independent or unique number of visitors compared to a separate period even if the length of time is the same. So, summing the two periods together to get the total number of visitors between them is actually an error.

For example:

In January, Luke, Han, and Leia visit your site. Han makes a purchase.

  • 3 individual visitors
  • 1 individual buyer
  • b/v rate = 34%

In February, both Han and Leia come back to your site, and a new person, Anakin visits your site. Anakin and Leia make a purchase.

  • 3 individual visitors again
  • 2 individual buyers
  • b/v rate = 67%

So, was the buyer/visitor rate from January and February 50% (3 buyers/6 visitors = 50%)?

No. The correct number of visitors to your site in the two months is four. When looking at the period from January to February, your individual visitors were Luke, Han, Leia, and Anakin. Summing the total number of unique visitors from each month would have been an error, because you would have counted Han and Leia twice.

So, the actual buyer/visitor conversion rate from January and February was 75% (3 buyers/4 visitors = 75%) because you had four unique visitors over that time frame, three of whom made a purchase.

Here’s a question: What if Han had made the purchase in February instead of Anakin? If this were the case, then your b/v rate would have been 50% 2 buyers/4 visitors = 50%) because as a repeat buyer, Han counted individually in each month but only once if considering data from the entire given period.

See how this affects the buyer conversion rate? The number of unique buyers and visitors is completely dependent on the timeframe in which you’re pulling data.

 

Order Conversion Rate: The “orders/visits rate” is defined as the number of orders taken divided by the total number of visits to the site during the same period. Essentially, this conversion rate is demonstrating how many visits end up as purchasing visits. Again, the reported period is important, but not because each data point is independent or unique. By breaking up a long period of time into multiple windows, you can gain insight into site performance, more so than visitor or buyer behavior.

Here’s what I mean: Because by its nature OCR doesn’t account for repeat purchasing behavior, examining orders to visits can help you to better understand site abandonment issues. If your checkout process is difficult to go through, chances are your orders/visits rate is being negatively affected more than a buyer/visitor rate is. The calculation for this conversion rate is relatively simple:

In January, you experienced 100 visits to your site and completed 50 orders.

  • 100 visits
  • 50 orders
  • o/v rate = 50%

In February, you experienced 100 visits again (so consistent!) and completed 25 orders.

  • 100 visits
  • 25 orders
  • o/v rate = 25%

Looking at the period together, you had 200 visits and 75 orders giving you an OCR of 37.5%. That’s nice to know…but what’s the real story here? By breaking your two months into two different periods of analysis, we can see that you actually experienced a pretty significant drop off in orders placed in February without a corresponding decline in visits accompanying it.

So what happened? Did you make a site change sometime at the end of January that could have negatively affected the user experience in the checkout process, thus causing a spike in cart abandonment? Did you change the product offering on your site? Do you typically see a decline in orders placed during this part of the year? There are a number of questions you can ask to begin solving the problem. By taking your analysis to the next level and looking at your data in greater depth, you can begin to truly diagnose and fix an issue that might have flown under the radar had you stayed at a higher level. This is why timing is important.

These two conversion rates (BCR and OCR) are a great place to start when monitoring conversion performance. Remember, the further you break down these rates by audience group, time, channel, and more, the more insight you gain as to the complexity of your visitors’ online shopping experience. If you need more convincing, the folks over at Web Analytics Demystified have more on the importance of using both of these metrics and not just one or the other.

 

Email

For a lot of online retailers, email is a major part of their marketing mix because it drives a large percentage of website traffic and purchases. Further, email also plays host to a number of unique metrics that affect conversion in ways that other channels don’t – open rate, unique clicks, emails delivered, and more. For these reasons, there are a few different conversion rates to consider that cater to the email channel and can contextualize your email subscribers’ motivation to purchase.

Orders to Delivered Conversion Rate: The order to delivered conversion rate (O/D rate) demonstrates the effectiveness of orders generated relative to the number of emails landing in inboxes. This conversion rate illustrates the email-to-purchase funnel from start to finish. It effectively answers the question, “How many subscribers made a purchase from this campaign?”

As will be the case with most conversion rates, there are some important things to know about the o/d rate:

  • When you are targeting an email to different audience segments, you’re going to see an increased variance in the O/D rate. By rule, the more targeted or segmented the email, the higher the variance in O/D rate.
  • Some email marketers default to clicks/delivered or click through rate as an email conversion rate. Though CTR is a good indicator of email engagement as it measures the unique number of subscribers who are interested in the content of your email enough to “click through” on a link in the email to learn more information on your site, it doesn’t calculate any data related to whether those subscribers made a purchase or not.

Orders-to-Clicks Conversion Rate: The orders-to-clicks conversion rate or the “click-to-conversion rate” narrows down the pool of potential converters from all subscribers who received an email to the ones that clicked through on an email. Essentially, this conversion rate takes a more granular look into the purchasing behavior of your engaged subscribers on a given campaign.

So why is this more helpful than the O/D conversion rate?  Again, this is an example of two conversion rates that can be looked at in tandem. The first (O/D), is an insightful metric to measure conversion from start (receiving an email) to finish (deciding whether or not to make a purchase). The second (O/C), helps isolate the email subscribers who landed on your website. The latter can be helpful in discerning how cohesive the web experience is to the email subscribers who were prompted to click through. In other words, measuring the two together can help you isolate where the hang up is. Are most subscribers abandoning the process after they get to your website? Or are they not even interested in your emails enough to get to your website?

CTOR: Click to Open Rate is equal to unique clicks divided by unique emails opened. It is important to distinguish that CTOR in its nature is a measure of email engagement. It is essentially a measure of how relevant your content is to your email subscribers. Therefore, it isn’t an immediate indicator of website conversion. However, this may be the only metric available if you’re not tracking purchases by source/channel on your website. If this is the case, then it is important to watch your mobile activity. As more and more people are looking to their mobile devices for email, CTOR can be deflated because most popular mobile devices “automatically” download images in an email – thus counting it as an open even though the subscriber didn’t intend to open the email.

Remember, even though these conversion rates are email specific, you can still segment your email audience, or pair this metric to other channel specific conversion rates to gain an insightful look into how well your email marketing efforts are converting subscribers.

Social Media

Social Media is arguably the hardest place to get consumers to make a purchase. Even though social media platforms have been around for a number of years, a lot of the industry is still exploring which performance indicators are most helpful in measuring site effectiveness or conversion against. In fact, most businesses are beginning to move away from “social fan acquisition” as a primary goal in favor of measures that begin to track the number of “social fans” who convert.

Toward that end, many social media platforms are beginning to provide a conversion tracking tool to analyze ROI for running a paid advertising campaign. For example, Twitter offers an entire scope of conversion monitoring that covers all types of ad engagements (clicks, retweets, or favorites) and impressions.

Ultimately, attributing conversions to a social channel is going to be indirect. Social plays an important part in brand awareness and advocacy, which is in itself an important part of the digital shopping experience. It’s more about creating community with your fans and followers than it is about promoting specific products. It’s more about the long play – creating brand champions – and that’s a much different type of conversion than what we’re talking about here.

In summary, all conversions are important, but for different reasons. Understand the differences between them and what they represent or you risk doing your company a disservice by looking at “conversion rate” as an absolute measure covering all aspects of the visit to the sale.

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