The statistics of every campaign in Quanda start with an overview of several numbers. They look self-explanatory, but until you know exactly what each of them counts, it is easy to misread your results. The difference between "total opens" and "unique opens" can shift your idea of a campaign's success by tens of percent. In this lesson we will go through every item in the overall summary and show you where in Quanda to find the details behind each one.

How many emails actually arrived

Sent is the total number of unique recipients the email was sent to. Delivered is the number of recipients who actually received it. Undelivered is the difference between the two, that is, the number of addresses the email could not be delivered to. You will find the list of undelivered addresses, including the reason, at the bottom of the statistics page.

Undelivered addresses are marked as blacklisted in Quanda. It means there was a delivery problem with that address. Sometimes the state is permanent, for example when the address does not exist at all. Other times it is temporary, such as a full mailbox, and Quanda will try to deliver again after a while. When delivery keeps failing, the time on the blacklist gets longer. This protects your domain's reputation, because mailbox providers quickly notice repeated sending to dead addresses.

Opens: total and unique

"Total opens" counts every single time the email is opened. When one recipient opens your email ten times, this number goes up by ten. "Unique opens" counts recipients, not opens. The same person appears there once, no matter how many times they opened the email. Not opened is the number of recipients who did not open the email at all.

When evaluating a campaign, work with unique opens. The total number of opens is an interesting extra, because it shows how often people come back to the email, but do not measure success by it.

Clicks: total and unique

The same logic applies to clicks. "Total clicks" adds up every click on any link. When an email has five links and one recipient clicks each of them, this number goes up by five. "Unique clicks" counts recipients who clicked at least once on any link, so the same person adds one.

You will find detailed statistics for each individual link at the bottom of the page. This is often the most useful part, because it shows which topic or which button people actually cared about. If your email contains social media icons, Quanda tracks clicks for each of them separately as well.

Marked as SPAM and unsubscribed

Marked as SPAM is the number of recipients who reported your email as junk mail. Unsubscribed is the number of those who used the unsubscribe link in the footer. You will again find both lists of names at the bottom of the statistics page.

Watch these two numbers even when they are small. Higher values than usual are a signal that you sent the email to the wrong group of people, sent it too soon after the previous one or that the content did not match what recipients expected.

Where to find the numbers and how to get them out

Below the overall summary, Quanda calculates the percentages for deliverability, opens and clicks, so you do not have to work them out yourself. Next come the lists of recipients who opened the email, did not open it, clicked a link or unsubscribed. You can keep working with these lists when choosing recipients for your next campaign.

You can export the whole statistics to Excel as an xlsx file. It contains everything on the page, organized into individual sheets. This comes in handy when you want to archive your results or compare campaigns side by side in a single spreadsheet.

Open rate and click rate are the two numbers most people use to judge whether a campaign worked. Each of them tells you something different, though, and each has a different level of reliability. In this lesson we will look at how they are calculated, what values are common in practice and why it pays off today to focus mainly on clicks.

How the open rate is calculated

The open rate is the share of unique opens out of delivered emails. When you delivered a thousand emails and two hundred and fifty people opened them, the open rate is 25 percent. Always calculate it from delivered emails, not sent ones. If you used sent emails as the base, undelivered addresses would artificially drag your result down.

The open rate is driven mainly by the email subject line, the sender name, the time of sending and the quality of your database. The content of the email has no direct effect on it, that shows up later in the clicks.

Is 20 percent a lot or a little

On its own, this is a question without an answer, because a lot depends on your industry. According to large international benchmarks, average open rates range roughly from 15 percent for e-commerce and retail up to 26 to 27 percent for government, hobbies or nonprofit organizations. The average across industries stays around 20 percent. Click rates tend to be much lower, commonly between 1.5 and 3 percent.

So when 20 percent of recipients opened your email, you are at a normal level for most industries. What matters more than comparing yourself to someone else's table, though, is how your own numbers develop over time.

Why the open rate is losing accuracy

Opens are measured using a tiny image that loads when the email is displayed. Anyone who has images blocked is not counted as an open, even if they read the email from start to finish.

Since 2021 there has been a bigger problem. Apple introduced a privacy protection feature in Apple Mail that loads images automatically as soon as the message arrives. All such emails are then reported as opened, whether anyone opened them or not. Based on our calculations, for a typical database this means roughly 6 percent of extra recipients among those who "opened" the email without any way to confirm it. If your database contains many iPhone users, the distortion will be larger.

This does not make the open rate completely meaningless. When your database changes slowly, the distortion stays in a similar proportion and the trend over time still tells you something. Just do not treat it as a precise number.

The click rate tells you more

The click rate, also known as click-through rate or CTR, is the share of recipients who clicked a link in the email. Unlike an open, a click is a real action. Nobody clicks a link by accident because of their mailbox settings. That is why it is now the most reliable indicator of whether your content worked.

A high open rate with low clicks is a typical pattern. The subject line did its job, the content did not. This is exactly what the pair of numbers reveals, and it is more useful information than either of them on its own.

What drags the click rate down

• Nothing but promotion. Emails that offer nothing beyond your products are emails people gradually stop opening.
• An impersonal sender. An address like info@company.com feels like a machine. Send on behalf of a real person.
• No personalization. Addressing people by name is the bare minimum today, go further and use what you know about each contact.
• Ignoring mobile. Roughly half of all opens happen on a phone, so always check the mobile preview too.
• Text that is too long. People tend to scan content, noticing headings, images and links.
• An unclear next step. It must be obvious where to click and what happens after the click.
• No testing. Try a button instead of a text link and vice versa, results differ from audience to audience.

The basic terms are the same in every campaign. What differs is how many statistics you get, whether the numbers accumulate over time and where to find them in the first place. In this lesson we will go through five campaign types in Quanda and for each one explain what makes its statistics special and what to watch out for when reading them.

Regular campaign: one email, one set of statistics

The most straightforward case. You send the campaign once, to a selected group of recipients, and you get one overall summary of results. The numbers keep updating for a while after sending, because opens and clicks come in gradually, but the group of recipients no longer changes.

That is exactly why a regular campaign is best suited for comparisons. When you want to find out whether a new style of subject line worked better than last time, compare regular campaigns with each other.

Email series: numbers per part and cumulative

With a series, the Statistics page shows a list of the individual parts and you open the statistics for each part separately. That is a fundamental difference. A series has no single summary number that would make sense.

The second difference is that the numbers accumulate. Different groups of recipients move through the series gradually, so each part is sent repeatedly. The statistics of a part show the total across all of its sendings. So when you look at the same part a month later, the numbers will be higher without you doing anything.

This leads to a practical rule. In a series, do not compare absolute values between parts that have been running for different lengths of time, compare percentages. A drop in open rate between the first and the fourth part tells you where people fall out of the series.

A/B testing: four sets of statistics instead of one

A campaign with A/B testing gives you four views. The statistics of the version "A" email, the statistics of version "B", a comparison of both versions and the overall statistics for the campaign as a whole.

The comparison is the most useful one. At the top of it you will find which version was evaluated as the winner, what its subject line was and what time interval was set for determining the winner. This is followed by a combined chart of both variants, a comparison of results in percentages, the development over time for each variant separately and finally a comparison of clicks on individual links.

The overall statistics add up the results of version "A", version "B" and the sending of the winning variant to the rest of the database. Use them when you want to know the impact of the campaign as a whole, not when you are evaluating the test itself.

Logic campaign: statistics for each email separately

In a logic campaign, recipients branch off based on their behavior, so a single summary would tell you nothing. The Statistics page therefore shows the tree structure of the campaign, and clicking a specific email displays its statistics.

Read them top to bottom, branch by branch. When the open rate drops sharply at some node, you know exactly which email in the sequence is the weak link. This breakdown into individual emails is the main reason why logic campaigns are easier to evaluate than one big mailing.

Birthdays and anniversaries: numbers that grow continuously

Campaigns for birthdays and name days send emails continuously, day by day, as each recipient's date comes up. Name days are a tradition Quanda supports, a personal date celebrated much like a birthday. The statistics are therefore cumulative, just like with a series, and the chart of development over time shows how the counts of sent, delivered and opened emails gradually grow. You can hide or show the individual lines in the chart by clicking their labels below it.

With this campaign type, there is no point in looking at the statistics right after launch. Let it run for at least a month, ideally a whole year, and only then judge whether your birthday greetings are doing their job.

Statistics in Quanda end at the click. You can see who clicked and on which link, but what they did next happens on your website. Quanda cannot see that far. Connecting with Google Analytics closes this gap and lets you work out how many of those clicks actually ended in an order, a registration or a submitted form.

Why the click alone is not enough

The click rate tells you that the content caught people's attention. It does not tell you whether the campaign made money. Two campaigns with the same click rate can have completely different value, because one brought people to a page that sells and the other to an article everyone left.

Making decisions based on clicks alone therefore leads you to optimize emails instead of results. Once you add what happened after the click to your evaluation, you start comparing campaigns by their real contribution.

How to turn tracking on in Quanda

It is set up directly in the email editor, not in your account settings. When you insert a link or a button, tick the "Insert Google Analytics tracking code" checkbox. Quanda then rewrites the link into an address that Google can read and record.

Do this for every link you want to measure. A link without the box ticked will show up in Analytics as an ordinary visit with no information about where it came from.

A keyword that saves you searching

For each link you can enter a keyword. It is optional, but worth filling in. The keyword makes the link easy to find in Analytics and to tell apart from the others.

Choose a system and stick to it. Naming links by their role in the email works well, for example main button, footer link or a specific product. When every campaign names its links using the same logic, you can compare them with each other six months later.

Where to find the results

In Google Analytics you will find them in the Acquisition section, then under all traffic and channels. You can add columns based on what Quanda passes along, that is, the email subject, the campaign name or the keyword you chose.

Data appears in Analytics with a delay, so do not look there right after sending. Give the campaign at least a day or two, especially when you send in the evening.

Without goals, you cannot measure success

For the numbers to mean anything, you need goals set up in Analytics. A goal can be a view of a specific page, a completed order or a submitted form. For purchases, Analytics can also count the amount, so you will see the revenue attributed to a specific campaign.

Without goals, all you learn is how many people came. That is not much. With goals, you learn how many of them did what you wanted, and that is how you justify the time spent preparing the campaign.

Start with one goal, the one that matters most for your business. You can add more at any time later, and above all you will have data you can work with from day one.

Statistics only have value when something comes out of them. In this lesson we will look at how to turn numbers into concrete steps. How to spot the contacts that are dragging your results down, how to lift your click rate with a simple automation and how to build your own baseline, one that is worth more to your business than anyone else's tables.

Compare yourself mainly with yourself

Industry averages are fine as a rough orientation. For decision-making they are almost useless, because they know nothing about your database, the frequency of your mailings or how you acquired your contacts.

Your own baseline is more useful. Take your last five to ten campaigns, calculate the average open rate and click rate, and treat that number as your base. Then compare every new campaign against it. A deviation up or down is a signal you can work with, unlike a comparison with the average of an entire industry.

Segments based on open rate

Quanda can divide your contacts by how often they open your emails. Contact scoring works with the average open rate and sorts contacts into seven segments:

• Fans: 80% to 100%
• Active: 50% to 79.9%
• Inactive: 20% to 49.9%
• Sleeping: 5% to 19.9%
• Zombies: 0.1% to 4.9%
• Ghosts: 0%
• Undetermined: contacts you have sent fewer than six campaigns so far

The Undetermined segment is not bad news, you simply do not have enough data on these contacts yet. Scoring only becomes meaningful from the sixth campaign sent.

Lower the frequency for inactive contacts

Sending emails to people who have not opened them in a long time damages your sender reputation. Mailbox providers watch how recipients react to your messages, and low engagement is one of the reasons emails end up in the junk folder.

That does not mean you should delete Ghosts and Zombies right away. The first step is to lower their frequency and send them fewer, but better emails. When they still do not react after several attempts, removing them from your mailing will help your deliverability. A smaller database that reads your emails brings more than a large one that ignores them.

The second wave: two automations with measurable impact

The fastest way to lift the result of a campaign you have already sent is to reach out to those who did not react. Quanda can do this on its own using automation in a regular email campaign.

The first option is to send the same email again to everyone who did not open it. For one of our customers, the first campaign brought 75 clicks out of 1,465 delivered emails, that is 5.1%. Resending to non-openers after three days added another 16 clicks and the overall click rate rose to 6.2%, an improvement of almost 22%.

The second option is to prepare a new, shorter email for everyone who did not click a specific link. For another customer, the first email brought 390 clicks out of 2,491 delivered, that is 15.7%. The reminder added 324 clicks and the overall click rate jumped to 28.7%, which is 83% higher.

Both automations take a few minutes to set up. Just watch the timing. The delay for the "did not open" condition is counted from the sending of the first campaign, while for the "opened" and "clicked" conditions it runs from the moment the event happens.

What to write down

After every campaign, note down four things: who you wrote to, what the subject line was, what the open rate was and what the click rate was. Add one sentence with whatever the result made you think. After a year you will have your own overview of what works on your audience, and that is worth more than any generic benchmark.