Small Business Marketing 2025 – Part III: Turning Numbers Into Gold

Analytics are quantitative measurements that reflect the performance and impact of marketing campaigns. Monitoring and understanding these metrics are essential steps in optimizing your data-driven messaging strategy.

Defining Analytics

While there are dozens of key performance indicators (KPIs) to track, here are the most essential analytics you should be evaluating along with their respective formulas:

Open Rate

An email open rate is the total percentage of subscribers that took the time to click and open your email campaign.

Open rate = (emails opened ÷ emails delivered) × 100

Click-Through Rate (CTR)

An email click-through rate is how many people clicked on a given call-to-action, hyperlink image or video within a particular email.

CTR = (unique clicks ÷ emails delivered) × 100

Click-to-Open Rate (CTOR)

While this may sound like your open rate, it is very different. The click-to-open rate is the comparison of unique clicks and unique opens.

CTOR = (# of unique clicks ÷ # of unique opens) × 100

Conversion Rate (CVR)

A conversion is the completion of any desired action you want a user to take. It can include but is not limited to clicking a CTA, making a purchase, or completing a sign-up.

Conversion rate = (Number of conversions / total number of visitors) x 100

Unsubscribe Rate

An email’s unsubscribe rate is the percentage of subscribers that choose to opt-out of receiving any further emails.

Unsubscribe rate = total # of unsubscribes ÷ emails delivered) × 100

Bounce Rate

The bounce rate is the percentage of emails that are returned due to delivery failure. It can be either a hard bounce or soft bounce. A hard bounce is an email that failed to be delivered because of an invalid address, while a soft bounce is an email that couldn’t be delivered because of a full inbox or an oversized file.

Bounce rate = (total # of bounced emails ÷ total # of sent emails) × 100

Spam Rate

The spam rate is the percentage of emails that have been marketed as “spam” or otherwise unsolicited. These messages can be marked as spam by not only the receiver but by an email client as well.

Spam rate = (spam rates received ÷ emails delivered) × 100

Return on Investment (ROI)**

This formula allows you to see how much money a given campaign has made. This provides insight into the effectiveness or ineffectiveness of resources spent, so you know if you should ditch or duplicate this strategy.

(Total Profit – Total Budget / Investment) x 100

Leveraging Analytics

There are golden insights to excavate within the metrics of your campaign analytics. Every small business needs to understand how to utilize these insights to their advantage. This is how data-driven marketers stay ahead of the pack and ensure the success of their next campaign.

The Importance of Clean Data

Before you begin analyzing your metrics, it’s imperative that your data is clean and not dirty. Dirty data is data that is inaccurate, incomplete, or inconsistent. It can occur at any stage of the data lifecycle: from collection, integration, analysis, through to deployment. This can be the result of human error, system glitches, outdated information, unifying data, or even from third-party data.

Dirty data means unreliable data, and that means any conclusions deduced from A/B testing or engagement rates may be misleading or completely inaccurate. Even worse, when the data fueling your campaigns is inaccurate, personalization efforts can backfire and have negative results.

Gartner estimates poor data quality costs businesses an average of $12.9M annually. To get the most out of your data and analytics, data should be as accurate as possible.

How to Clean Your Data

Step 1. Remove Duplicate and Invalid Profiles

Duplicate profiles are a common occurrence. They are a symptom of merging databases, unifying data, and human error. Invalid email addresses can be typos, spam-traps, or non-existent accounts. Remove these to have clearer analytics.

Step 2. Identify Inactive Subscribers for Re-Engagement

Instead of immediately removing inactive subscribers, you can segment them out. Omit them from other campaigns, then create a retargeting campaign for these users to attempt to re-engage.

Step 3. Remove Inactive Profiles

Hopefully this number has shrunk due to your killer re-engagement campaign, but if users have remained inactive, it’s time to remove them. When it comes to your subscriber list, bigger isn’t always better. Inactive users skew data, so it’s important to remove them from your list if re-engagement fails.

Step 4. Fix Structural Errors, Then Standardize Conventions

These errors likely occur after unifying databases and can include typos, strange naming conventions, inconsistent capitalization, and irregular punctuation, subsequently resulting in multiple segments denoting the same category, i.e. “millennials” and “Mlnls.” Implement standardized naming conventions and consolidate these inconsistencies.

Step 5. Address Incomplete, Missing or Inaccurate Data

Input data manually only if it can be deduced accurately from accompanying information, such as determining a user’s age/generation from their complete and factual birthdate. Remove data that is incomplete or that doesn’t make sense in user profiles.

Now that your data is clean and accurate, it’s time to examine the numbers.

Find What Isn’t Working

Your unsubscribe and spam rates indicate how many people are opting to leave your messaging list. This is referred to as churn, and it’s a great way to discover what is turning your audience off.

Don’t get dejected if you’re experiencing this. Churn is normal. No business will ever have a 0% unsubscribe rate, but it’s important to keep these rates low. Unsubscribe rates under 2% are within industry norms, and the average unsubscribe rate is 0.17%. Use these indicators to discover what content is not resonating with your audience and alter your approach.

However, a notable increase in your unsubscribe rate–especially if it is above industry standards–is not a good sign and should spark immediate evaluation. While it’s not exactly motivating to feel like your campaign is failing, the good news is there are clear markers to evaluate so you can quickly begin your strategic pivot.

Common unsubscribe reasons include:

• Campaigns that are irregularly timed
• Irrelevant content
• An incorrectly displayed message
• No double opt-in model

Often, it’s a combination of these factors that result in people hitting the “spam” or “unsubscribe” button. But if you iron out all of the above issues, it should help lower these rates.

High bounce rates may indicate you have dirty data, which can happen even after a deep cleaning. Your list is (hopefully) always growing, which means it’s always susceptible to errors. Keep your bounce rates low by regularly practicing good email list hygiene.

These rates influence more than just your own analytics. High bounce and spam rates can negatively impact deliverability and therefore your sender reputation. A good sender reputation ensures your emails land in your audience’s inbox. A bad sender reputation will lead to your emails being automatically routed to the spam folder– a place no email marketer wants to be.

Find What Is Working

High open rates can reveal what content, tone and offers engage your audience, while high click-through, click-to-open and conversion rates indicate what truly resonates with your audience and causes completion of your desired behaviors.

Note what kind of offers, attitudes and topics cause these metrics to trend higher so you can understand your audience’s preferences. A/B testing is a great tool to solidify these findings.

Digging Deeper

Some insights require more nuance.

You may assume high open rates naturally lead to high conversion rates, but sometimes the two are not analogous.

If your campaign has high open rates, but comparatively low click-to-open and conversion rates, it’s time to start digging. Despite your emails performing well, you’re still having trouble getting customers across the finish line. This is a clear indication there is a problem within your email campaign.

Small businesses cannot afford to leave this unaddressed. The more disengaged your recipients become, the less likely they are to open emails from you, causing detriment to your future campaigns. Not only will these users become inactive, but they’ll also become more likely to unsubscribe or mark your messages as spam.

What could be the problem?

1. You have a weak call-to-action
2. You have no sense of urgency
3. You’re using clickbait to engage
4. Your content isn’t optimized across devices
5. Your content isn’t relevant

Troubleshoot:

1. Improve your call-to-action

Your CTA should be direct, short, and immediately actionable. Visually, your CTA should take up space, stand out, and lay “above the fold,” meaning customers don’t have to scroll to find it.

2. Create a sense of urgency

Instill a sense of urgency or exclusivity to motivate your audience to engage. Adding countdowns and deadlines are great ways to achieve this.

3. Ditch the clickbait

Customers hate false promises. It’s a great way to lose their trust. Make sure your email subject lines and content aren’t manipulative or misleading. In the long run, clickbait leads to lower engagement and higher spam rates. Subject lines should always reflect the content and offers within the email.

4. Optimize across devices

A whopping 60% of email campaigns are being opened on mobile devices, so it’s important to ensure mobile users have a seamless experience, too. Always optimize emails and landing pages across devices to avoid losing an engaged customer.

5. Personalize the user experience

49% of consumers felt frustrated after receiving irrelevant content or offers from businesses, and 42% were frustrated by messages that didn't reflect their wants or needs.

Customers will click away if the content of your email isn’t relevant to them. Leverage user data to create smarter segmentation so you can deploy campaigns that deliver curated experiences for your customers. This will be further explored in the following section.

Data-driven marketers gather customer data to fuel their personalization strategy. What they’ve bought, where they travel, where they like to eat — these are all valuable golden nuggets. With it, you can achieve personalization that drives engagement, conversion and ultimately increases ROI — the ultimate motherlode.

While collecting and activating customer data may sound like an intricate process, personalization is easier to achieve than you may think, and you won’t even need a pick axe. However, it’s still important to understand the different types of customer data and where it comes from before you can leverage it like a pro.

The Three Types of Customer Data

Zero and first-party data

Brands collect both zero and first-party data directly from the customer, usually during sales, form completions, or account creation. This type of data can include dates of birth, mailing addresses, past purchases, preference insights, lifestyle signifiers, and more. Because this information comes directly from the source–your customer–it provides valuable insight into how a customer interacts with your brand and how their behaviors change over time. This data is also shared voluntarily, so brands can freely leverage this data to create smarter segmentation and drive personalization.

Second-party data

Second-party data is another organization’s first-party data. Second-party data is shared (not sold) between two trusted companies, and then blended with first-party data to target known and unknown audiences.

Third-party data

Vendors typically collect third-party data, which is then purchased by brands. This type of data can include any number of personal or anonymized data points, such as information on demographics and online activity that can provide inferences about a consumer’s interests and preferences. Third-party data holds some degree of value for marketers, but it carries significant risk.

Utilizing third-party data to drive personalization can be considered creepy and off-putting by consumers. Unlike zero and first-party data, this data contains information your customers never directly shared with you, so seeing it used to personalize their experience can be jarring. The data itself is also heavily based on inferences, so it may also be inaccurate.

Leveraging voluntarily shared and completely accurate first- and zero-party data to inform personalization is proven to build trust and develop stronger relationships between you and your customers.

Collecting First- and Zero-Party Data

First, use the data you already have. Connect your website, business apps and e-commerce platform to your ESP and integrate all that information into your subscriber database.

Then, prioritize learning more about your customer. Name, gender, age, location, birthday, preferences — it is all gold. Customers are extremely willing to share their personal data, especially if you offer something of value in return. This is called the value exchange economy.

You can exchange first- and zero-party data for:

• Unlocking content
• A chance to win a prize
• Entrance to community
• Early/exclusive access
• Loyalty points
• Discounts

The information you ask customers to share about themselves can be used to personalize their experience. Depending on your industry, you may inquire about a user’s gender, t-shirt size, career, favorite season, or anything relevant to your marketing goals.

You can also inquire about communication preferences. Allow users to modify how you interact with them– like choosing to avoid certain topics or favoring a less frequent email cadence– to prevent users from completely unsubscribing. The more you adapt your campaigns to the individual, the more successful they will be.

Activating Customer Data

After collecting all this data, you now have actionable insights that have the potential to drive serious results. Rich Relevance found that revenue is 5.7 times higher in emails that employ personalization.

And the great news is consumers love when brands use ethically collected data to drive personalized experiences. Over 80% of consumers favor brands who use data responsibly to treat them as an individual.

This is because personalized emails are more relevant to them. Instead of batching and blasting the same generic campaign across your entire email list, you can create intelligent list segments that help you better understand the dynamics of your audience. This allows you to create tailored offers and messaging that target each segment, so you can start standing out in the inbox with campaigns that are relevant to your customers’ unique wants and interests.

Getting Personal

Here’s how to leverage common data points effectively:

1. Be on a first name basis

Just by using the recipient’s first name in the subject line, open rates can increase by 26%.

You can also personalize the content of the email by adding the subscriber’s first name within the copy, CTA, or even in images.

2. Remember their special day

A highly valuable piece of customer data to leverage is a day everyone celebrates– their birthday!

Birthday campaigns make your customers feel seen and appreciated. This campaign sends subscribers an early birthday present that includes a 10% off discount code, giving customers a gift just for being them. And it’s widely appreciated! This campaign has a 50% open rate, which is phenomenal by any industry standard.

3. Know that home really is sweet

“Location, location, location” is valuable beyond real estate. It’s data that can enhance your campaigns by denoting exclusivity, setting the scene of the email directly in the user’s backyard.

In a recent campaign, dynamically changing images matching the subscriber’s city of residence were measured against emails with a static, location-agnostic image. The dynamic images outperformed the static images, boasting an email click through rate that was 29% higher by leveraging location data effectively.

Location also indicates language, culture and more. This campaign saves time by using dynamic content to alter language, event recaps, and media based on location so they don’t have to manually build out an extensive number of individualized versions.

4. The past can predict the future

Past purchase history, that is!

If you know what has previously engaged a customer, use that to your advantage. Build out multiple list segments based off of purchase history, then make inferences to determine similar products that they are most likely to enjoy.

Develop targeted campaigns with relevant product recommendations, or really gain their attention with an offer or discount for a product they’re bound to like.

5. A few of their favorite things

Preference insights are the ultimate segmentation tool.

This can look like a news outlet differentiating sports fans, pop-culture aficionados and political enthusiasts so they can tailor each subscriber's top headline accordingly. They can go even deeper by segmenting the hockey heads from the football fans, and the fashionistas from the cinephiles.

Or a clothing brand dynamically changing product images to match users’ favorite color, so everyone receives the most appealing version.

By segmenting your audience with preference identifiers, you can create campaigns that immediately resonate and connect with your customers. This is how you earn their trust and keep them engaged, so your small business can flourish.