In this post, you’re going to learn everything you need to know about behavioral segmentation and how it’s used in marketing. If you already know what behavioral segmentation is, you might want to skip directly to the three examples.

Behavioral segmentation is a form of data-driven marketing, and it means grouping customers based on their online (and offline) behaviour. Your customer’s behaviour is an important criteria to consider when creating audience segments for email marketing, advertising, and onsite marketing. Your customers behavior is highly correlated to intent (i.e. their likelihood to buy).

Here are a few examples of behavioral signals used when creating behavior-based segments:

• Website activity
• Visited pages
• Traffic source
• Purchase frequency
• Discount usage
• Geographic location

Data points like the ones above are combined with static data like geographic location, customer status, and demographics like gender and age in order to create customer segments.

Why is behavioural segmentation important?

1. Focused marketing efforts: By leveraging behavioral segmentation you can exclude uninterested prospects and email subscribers who have never opened an email from you, or haven’t visited your website in months. By using behavioral data in your segmentation you can make sure that your marketing resources are allocated to your most engaged prospects. Instead of casting a wide net and hoping someone will convert, you can tailor your efforts to those individuals who you know have shown a genuine interest in your products. This not only saves money but also increases the likelihood of communicating with someone who wants communication from you.
2. Enhanced relevance and messaging accuracy: Behavioral segmentation empowers you to create relevant messaging angles that makes your content stand out. Even if you only tailor a small part of the message, you can create marketing campaigns that speak directly to the unique motivations of each segment The result? An overall better customer experience, more effective promotions, and content that makes an impact.
3. Proactive marketing: One of the standout advantages of behavioral segmentation is its capacity to make your marketing efforts proactive rather than reactive. Traditional marketing often relies on reacting to generic customer needs or trends. However, with behavioral segmentation, you can anticipate customer actions and schedule campaigns to be triggered in advance, based on past and future behavior. Imagine a scenario where you can identify a potential buyer before they even express their intent to purchase. This level of proactive marketing not only boosts conversion rates but you will also create a better customer experience. Several of our customers are using a strategy called “Buying intent”, which is a simple but effective email or SMS automation that is triggered when an existing customer has visited a certain product or product category 2-3 times within a fixed time frame (usually 7 days). It has a very high open rate (over 50% on average) and conversion rate (up to 30% purchase rate in some cases).

The 4 ways to segment customers

There are four main types of behavioral segmentation:

1. Behavioral segmentation uses digital behavior data focused on how customers interact with a brand’s website or email campaigns. All trackable interactions like website visits, pages visited, email link clicks, and even visitor intent can be used to create behavioral segments.
2. Demographic segmentation divides customers into groups based on age, gender, income, education, and occupation.
3. Psychographic segmentation uses data about lifestyle choices, opinions and beliefs. This data is collected using quizzes or in membership profiles and is also called “Zero party data”. In other words, the user is self-submitting this data in exchange for a better experience or other benefits.
4. Geographic segmentation is data based on a customer’s location or where they live, and regional factors which may influence their purchasing behavior. This data is collected from purchases, delivery settings, membership profiles, and so on.

The main difference between these segmentation strategies is that behavioural data is highly dynamic and changes frequently.

Demographic, psychographic, and geographic data are mostly static and remain unchanged for longer periods of time. These types of segmentation strategies lets you target very broad groups of people.

How is behavioral data collected?

Data used in behavioral segmentation is mainly collected by onsite marketing software like Triggerbee and marketing automation software like Klaviyo and Custobar.

Marketing automation tools needs behavioral data from customers browsing your website in order to trigger automated email flows. But the data they collect is often limited to certain events such as completed purchases or add to carts. Meaning, if you want to use behavioral segmentation effectively you need to collect minor events from your website as well. Otherwise you can’t accurately target your customers with relevant messages.

For example, in order for an email marketing software to be able to send abandoned cart emails, it needs both an email address (the recipient) AND behavioral data that can correctly identify customers on the website who has 1) added a product to their cart, 2) has not yet made a purchase, and 3) has abandoned the website.

Here is an example of what behavioral data is and how it looks in onsite marketing platform Triggerbee:

This is a screenshot of a customer profile in onsite marketing platform Triggerbee. A customer profile is basically a visitors browsing history and a summary of important events from each visit.

The first box (top) named “Onsite campaign activity” refers to all the campaigns this user has interacted with. You can see that this visitor has clicked on the campaign “Membership offer #14124” and have seen at least 3 more campaigns.

The box in the middle named “Goals” highlights important events that was triggered during a certain visit, along with a datestamp.

And at the bottom, you can see each visit with data about their traffic source and how many pages were viewed. This box is a summary of the most recent visits, and if you were to click on a visit you will see the specific activity from that particular session.

All of this data is automatically connected to a person and an email address. Triggerbee remembers this visitor, so whenever they visit the website in the future, Triggerbee knows their browsing history and can target them with new offers and promotions.

This data is also synced to the marketing automation platform this company is using, so they can behavioral data to segment their email campaigns.

The main benefit of behavioral data is that it is collected individually. Because this allows for individual targeting and is the foundation of personalization on the website, in emails, and more.

Example of how behavioral data is collected and used

Behavioral data is collected from every interaction throughout the complete customer journey.

Let’s say you’re shopping for a new bicycle. You already know which type of bike you want, so you go to Google and search:

You take a look at the results and click on one of the shopping ads. This is the first point of behavioral data that you leave to the business whose ad you clicked on.

On the website, you see that the bicycle you clicked on can only be picked up in-store. So you attempt to leave the website…

Suddenly a popup appears that says “15% OFF ON MTB – VISIT OUR STOCKHOLM STORE TO USE YOUR COUPON”.

Awesome. You sign up to get the coupon code, and the business can notify you about upcoming promotions via text messages.

Behavioral data was both collected and used in this example.

The first data point is your traffic source. In the example above, performed a search on google and clicked on one of the ads in the search results. This means the traffic source will be recorded as “Search ad”.

Once you land on the website, the onsite marketing software will check if it can match you with one of the customer profiles that already exists.

If you cannot be identified, the onsite marketing platform could trigger a spin the wheel popup to capture your information and identify you.

However, this popup might not be the same popup as another visitor gets. In this example, the popup appeared only when you attempted to leave the website. This is called “Exit intent” and is a behavioral-based trigger. Geotargeting was also used in this example, to make sure that only visitors living in Stockholm received the message “Visit our Stockholm Store to use your coupon”.

Once you sign up in the form, you will be become identified and assigned a “customer profile” where your website activity will be recorded and saved. All of the data in the customer profile is synced to a marketing automation system where the segmentation takes place.

The next time you return to this website, the company’s on-site marketing software will remember you and your behavior. Instead of showing you the same popup again, you might see a message like “Welcome back” or a unique coupon code.

And if you had bought that bicycle in the store, you might have seen a message asking you to leave a review of your latest purchase.

For future emails, the company can create segments of people with similar behavior to yours. Let’s say that the above popup gets 5000 signups per month. Only a fraction of those will use the discount code.

The company can then create a segment based on their visitors behavior and target people who:

• Visited their website in the last 30 days
• Signed up in the spin the wheel popup
• Has received the discount code
• Did not use the discount code

Where in the customer journey can you collect behavioral data to be used in behavioral segmentation?

Most retail and e-commerce brands have three main “sources” where behavioral data is collected.

1. Self-reported data (from account registration forms, membership profiles, preference centers, gamification campaigns, etc)
2. Purchase data (Address, name, location, product categories, coupons used, etc)
3. Indirect tracking (Visited pages, time on page, traffic source, etc)

These sources are all connected to some type of behavior, whether it’s a customer who visited a certain page or bought a certain product during a promotion. Every important online interaction is correlated with behavioral data, digital footprints.

When a customer buys something in a store, the cashier might ask for their membership ID. And when the cashier scans your membership card, the customer’s receipt is synced and stored in your membership and customer profile that is usually in the marketing automation software and on-site personalization software.

The same thing happens online. If you are logged in on a website and make a purchase, your purchase is synced and stored on your membership and customer profile.

And when you’re not logged in, the receipt is still stored on your customer profile because it’s connected to your email in the marketing automation software.

Memberships are the main data source, because every purchase creates new data. For example, purchase frequency (how long was it since last time you made a purchase), where you shop (online or in-store), how many of your purchases are made with discount codes or during promotions, what type of products you buy, and how much you spend, are all important behavioral data points.

All of this data is then combined, filtered, and used to create behavioral segments that are used for targeting ads, email campaigns, or controlling dynamic content on the website.

Here are the most common variables used in behavioral segmentation sorted by channel type:

Email:

• Open rate
• Click-through rate
• Conversion rate
• Time of day opened/clicked

Website:

• Identification rate
• Logged in / out status
• Returning visits
• Pages visited
• Time spent on site
• Product categories viewed
• Search terms used
• Items added to cart
• Abandoned cart items
• Location
• Device used
• Traffic source
• Buttons clicked

Purchase

• Time since last purchase
• Purchase frequency
• Average order value
• Discount usage
• Date and time
• Location of the purchase (in-store, online)
• Device used

Support:

• Type of support request (e.g., technical, billing, product)
• Frequency of support requests
• Channel used for support (e.g., phone, email, chat)
• Ticket resolution time

In-store:

• Store location
• Purchase history (per store)
• Product purchased
• Time since last purchase

Mobile app:

• App usage frequency
• Time spent on app
• Features used
• In-app purchases
• Push notification interaction
• Location data

Social media:

• Location of followers (aggregate)
• Age of followers (aggregate)
• Content engagement

Real examples of behavioral segmentation

Behavioral segments are created to target certain individuals with certain content. A common example of behavioral segmentation in action is retargeting ads. Retargeting ads are ads shown to people who have visited a website and then left. Sometimes the retargeting ads are only shown to people with a certain cart value or who have spent X amount of time browsing key pages. This ensures that a business only spends money showing ads to visitors which they deem have a high intent of buying.

But behavioral segmentation can also be used to create segments for onsite promotions, email campaigns, and dynamic website content. Here are three real-life examples:

Zalando uses behavioral segmentation to display size recommendations on product pages

Zalando, one of the largest fashion retailers in Europe, takes shopping online to a new level. They use behavioral segmentation on their website to create a personalized customer experience for every visitor. If you’ve bought from them before, they remember what you bought and how you rated the fit. Next time you’re visiting their website and if you are logged in, they suggest the right size for you. But if you’re logged out or an anonymous visitor, they keep it simple without size recommendations until you’ve made some choices. This way, Zalando’s site changes based on who’s shopping.

Amazon uses behavioral segmentation to send out browse abandonment emails

Amazon is the king of website personalization and delivering a great customer experience. Their website might not win any design awards, but they have a superior customer experience strategy that few can compete with. They use behavioral segmentation for a lot of things, and one of those things are sending out browse abandonment emails. Amazon tracks your behavior and which products you have visited. If you haven’t bought any of the products you visited, they will send you a browse abandonment email to win you back and get you back into shopping mode.

CLN Athletics uses behavioral segmentation to recover abandoned carts 

CLN Athletics is a small athletics apparel brand in Sweden. They use behavioral segmentation to recover abandoned carts. By tracking important events on their website such as the “Add to cart”-event, allows them to trigger email automations and onsite campaigns based on their visitors activity. If you add a product to your cart, visit the checkout, and attempt to leave the website before purchasing… they trigger an exit intent popup with a 20% offer to recover the potentially lost cart.

Use cases for behavioral segmentation:

Creating email segments

Behavior segmentation is very useful for creating email segments, both for individual campaigns and when setting up triggers for automated email flows. You can target people who have recently been active on your website or has performed a specific action on your website. For example, if you have a loyalty program you want to have an audience segment that consists of “all members” which have a bunch of sub-segments like “Gold members”, “Inactive members”, “Recently purchased”, “Discount buyers”, etc. Some of these segments should definitely be based on behavior since it will help you uncover new profitable segments.

In our experience having some of the largest retailers in the Nordics as our customers, one of the most profitable segments is Existing members who have visited a product or product category several times within 7 days. A high frequency of visits to one or two products usually indicates a strong interest and intent to buy.

Creating audiences for ads

There are two main approaches to advertising within ecom and retail. 1) Segment based, which means you build an audience in your advertising tool whether it be Meta ads or TikTok ads, and then run ads to a specific segment. Ads running to these audiences will most likely be retargeting ads. 2) Creative segmentation. As the algorithms get better, a lot of brands that rely heavily on Meta ads use their creative to segment their audience. The idea is that a person interested in a certain topic wants to see relevant content for these topics – which your ad is in.

Creating segments for onsite personalization

On-site personalization needs behavioral audience segments to work. Each individual person who visits a website has their own customer profile, and a retailer can show certain types of promotions or dynamic content to visitors within a specific audience.

This is an extremely effective way to promote any type of campaign for a high-intent audience, or make returning visitors pick up where they left off the last time.

It means that the top section of a website can show different content for different visitors. If visitor A is a member in your rewards program, they might see a promotion for the latest membership offers. And if visitor B is a first time visitor they might be offered 10% off for signing up as a new member.

Behavioral Segmentation and privacy

Do not forget that all the data you collect about your customers and visitors needs to be specified in your privacy policy and cookie policy.

The introduction of the General Data Protection Regulation (GDPR) in the EU has had a major effect on behavioral segmentation practices.

GDPR, established in 2018, sets strict guidelines for collecting and processing personal information from individuals in the EU and dictates how customer data should be handled.

Behavioral segmentation often collects sensitive data so ensure that you are complying with local laws and regulations.

Here are some general guidelines, however these could change at any time and should not be considered legal advice.

• Consent and Clarity: GDPR mandates that explicit consent must be obtained from individuals before their personal data is used for behavioral segmentation. This consent should be informed, meaning that individuals must be clearly aware of what data is being collected and its intended use. Companies must provide clear, understandable privacy notices.
• Limiting Data Collection: The regulation emphasizes collecting only the data that is necessary for a specified purpose. For behavioral segmentation, this means gathering only the essential data needed for creating customer segments and not using it for other unrelated purposes.
• Rights of Individuals: Individuals have more control over their data, including rights to access, amend, and delete their data. In behavioral segmentation, this means customers can see the collected data on them and can choose to opt-out or request its deletion, impacting the data available for segmentation.
• Securing Data: GDPR requires companies to implement suitable measures to secure personal data. For behavioral segmentation, this means robust security measures must be in place to protect the data used in creating customer segments.
• Data Transfer Restrictions: The regulation restricts transferring data outside the EU to maintain the protection level set by GDPR. For companies practicing behavioral segmentation, compliance is crucial when transferring data internationally.
• Caution with US-Based Software Companies: When transferring data to US-based software companies, it’s essential to ensure they have the necessary permissions under GDPR. The Data Privacy Framework website (https://www.dataprivacyframework.gov/s/participant-search) offers a search tool to check if a company is compliant.
• Demonstrating Compliance: Companies must show their adherence to GDPR, which includes maintaining detailed records of data processing activities, like those for behavioral segmentation, and conducting impact assessments where necessary.

Impact on Marketing Practices:

• Strategy Adjustment: You need to align your behavioral segmentation strategies with GDPR. This involves securing clear consent, being transparent about data usage, and respecting user choices and rights.
• Emphasis on Data Quality: The focus shifts from the quantity to the quality of data due to pretty harsh consent requirements. A smaller, GDPR-compliant dataset can lead to more precise and effective segmentation.
• Building Trust and Customer Relations: Adhering to GDPR can strengthen trust between companies and customers. Ethical data handling can enhance customer loyalty and improve the company’s reputation.

Aligning behavioral segmentation with GDPR regulations is not only about avoiding fines but also about cultivating a trusting and engaged customer base.

Summary

Behavioral segmentation offers marketers a dynamic and data-driven approach to understand customer behavior and tailor marketing efforts effectively, resulting in more personalized and engaging customer experiences. Unlike demographic or geographic segmentation, behavioral segmentation is dynamic and frequently changing. Data for behavioral segmentation is collected through web analytics and marketing automation software, allowing businesses to target the right audience with personalized messages.

First-party data, such as web activity and email interactions, plays a crucial role in this process. So make sure you are collecting first-party data rather than just looking at analytics. Because that is what will let you target your audience when the Google’s and Meta’s of the world will keep this information from you.

Sources:

• Our own experience working with 400+ of the largest online retailers in Scandinavia (KICKS, Bubbleroom, Jula, K-Rauta, iDeal of Sweden, Caia, etc.).
• https://ischolar.sscldl.in/index.php/IJCSIT/article/view/186146
• https://www.emerald.com/insight/content/doi/10.1108/03090560610702830/full/html
• https://www.sciencedirect.com/science/article/abs/pii/S0167923612001327
• https://hrcak.srce.hr/file/196731

From today (Feb 1, 2024) and onward, Google’s new email guidelines requires senders of over 5,000 emails per day to Gmail inboxes to follow these practices:

• Senders are required to use SPF, DKIM and DMARC for authentication and verification
• Promotional emails are required to have a clearly visible one-click unsubscribe link
• Senders are recommended to use double opt-in to confirm new subscribers
• Senders are required to keep spam rates below 0.1% on average and never above 0.3%
• Regularly send emails confirming your subscribers want to stay subscribed

A sender in this case is referring to your business.

If you’re looking for some practical guidance, this is the article for you. We include detailed explanations and examples of how to make sure you can stay compliant with Google’s full list of new email guidelines.

We also include some tips on how to manage the new unsubscribe link requirement by improving your list building strategy.

Note: Google’s new email rules are mainly to give you a better and safer inbox experience. But similar to how Google wants you to use structured data (Schema) on your website to better be able to display your content in search results, some of these new guidelines also add new features to Gmail’s inbox.

Who does Google’s new email rules apply to?

Everyone who sends emails and especially for companies who send more than 5,000 emails per day (to Google accounts).

Keep in mind:

• Google counts emails sent to personal addresses ending in @gmail.com and @googlemail.com.
• Every email you send, including transactional emails (like order confirmations), adds up to this 5,000 email limit.
• Google will permanently consider you a “bulk sender” from the moment you cross the 5,000 email threshold.

This means you might be reaching that bulk sender category faster than you think. All it takes is one email campaign being sent to 5,000+ recipients.

New requirements for email authentication

The most important part of Google’s new email rules in 2024 is authenticating your email domain. Google wants your “From:” domain to be authenticated with SPF, DKIM, and DMARC.

What is SPF, DKIM, and DMARC?

• SPF (Sender Policy Framework): SPF is used to authenticate you as a sender, and one of the main components of DMARC. With a SPF record in place, your domain is verified and authenticated to send emails to people. It also helps fight domain impersonation and email spoofing to protect your brand reputation.
• DKIM (DomainKeys Identified Mail): DKIM is like a secret code added to your emails. When you send an email, this secret code is attached to it. The inbox (Gmail, Hotmail, etc) checks the code to make sure your email is actually the email your recipients are supposed to get.
• DMARC (Domain-based Message Authentication, Reporting & Conformance): DMARC are a set of rules for what to do if an email looks suspicious. It uses SPF and DKIM to verify and authenticate the sender and domain, and then tells the receiving inbox what to do if the email doesn’t pass these checks. I.e. “if this email don’t pass these checks, put it in the spam folder”.

SPF, DKIM, and DMARC together help make sure that the emails you send and receive are safe and from the right people.

How to check if your email domain is authenticated with SPF, DKIM and DMARC

1. Log in to Gmail on a desktop computer
2. Find an email from your domain. If you send multiple email types from different domains (account notifications, receipts, newsletter), make sure to repeat the steps for each domain.
   
3. Open the email. Click the three dots in the right corner and click “Show original”.
   
4. Make sure the SPF, DKIM, and DMARC rows say “PASS”.
   

If the authentication requests says “PASS” for all your email domains, you have nothing to worry about.

Most major email service providers and marketing automation vendors set up these authentication protocols when you’re setting up your account and verifying your domain. If you’re using a tool like Rule, Klaviyo, Mailchimp, Voyado or Emarsys you just need to follow the above steps to ensure that your domain passes all the authentication tests.

Stricter email subscription guidelines

Google mentions a lot of guidelines regarding how to manage email subscribers. The most important one is that all promotional messages are required to have a clearly visible one-click unsubscribe link by Jun 1, 2024. This means you need to make sure that your emails are not clipped when delivered.

Subscriber and unsubscribe guidelines

Email subscription guidelines:

• Turn on double opt-in to confirm new subscribers in your ESP
• Periodically send messages confirming that your subscribers want to stay subscribed.
• Consider unsubscribing recipients who don’t open or read your messages.

Unsubscribe guidelines:

• Include a clear “Unsubscribe” button in your email.
• Automatically unsubscribe contacts with multiple bounced messages
• Let subscribers see the lists they are subscribed to and unsubscribe from individual lists
• Bonus: Make sure your unsubscribe link is NOT clipped
• Bonus 2: Add the unsubscribe link in the email header.

This is what your unsubscribe link should look like:

The word “Unsubscribe” should be clearly visible and independently linked.

A simple way to confirm that you are doing it right is to open one of your own emails in Gmails desktop client and see if you have a “Cancel subscription” link next to the email subject line.

It should look like this:

Here are some things to check if you don’t have this button:

• Check for missed spaces (i.e. “Click here toUnsubscribe”)
• Are you linking the wrong word? (i.e. “Click here to unsubscribe”)
• Are your emails too long so that your unsubscribe link is clipped?
• If you still can’t get the new button to appear, add the unsubscribe link in the email header.

Here’s how to write a better unsubscribe message in your emails:

Do this:
✅ “Don’t want to receive emails from us anymore? Unsubscribe”
✅ “Want to unsubscribe? You can also change your email preferences under My pages.”
✅ “Change your email preferences or unsubscribe from all future emails.”

You might be thinking: Why would I want to make it easier for my subscribers to unsubscribe?

Well, your email list is your “owned” audience. These people have, in most cases, chosen to receive communications from you. But keep in mind they already know where to find the unsubscribe button if they don’t want more emails from you.

People who don’t want your emails are more likely to report your emails as spam. And since you need to keep your spam threshold below 0.1%, this is beneficial to you.

This is also a good reason why you need a good strategy to grow your email list so you don’t have to rely on new purchases to gain new subscribers. In this article we are revealing 37 top ways to grow your email list.

Stay below 0.1% spam complaint rate

Google wants you to stay below a 0.1% spam complaint rate (on average), and never exceed a 0.3% spam rate at any time.

And as you can see in the quote, Google is using Postmaster Tools to monitor your spam complaint rate. We highly recommend you set it up so you can monitor it yourself.

How to set up Postmaster Tools:

1. Go to https://postmaster.google.com/
2. Add your domain used to send emails from
3. Verify your domain by adding a text file to your DNS records. Ask your developers if you’re unsure of what to do or if you don’t have access to editing DNS records.

However, there’s more to keeping spam complaints low than simply setting up Postmaster Tools.

What you REALLY need to do is…

Send relevant content your subscribers want to read.

If your email strategy consists of never-ending promotions and flash sales, I recommend you read our article about 7 email flows every ecommerce brand needs.

Here are some tips for lowering spam complaints and increasing email engagement:

• Use behavioral segmentation for better targeting
• Use onsite activity and intent signals for improved segmentation
• Set up automated email flows that are tailored based on behavior and interests
• Regularly send out emails asking if your subscribers want to stay subscribed

Affiliate marketing guidelines

If you have an affiliate program, you probably want to refine your current approval process for new affiliates. Google explicitly states:

“If your brand is associated with marketing spam, other messages sent by you might be marked as spam.”

It’s no surprise that the top 5-10% of affiliates bring in the bulk of the revenue generated in your affiliate program. With these new guidelines, we recommend you regularly monitor your affiliates and remove the questionable ones.

Sending volume – Scaling up correctly

How many emails you can send without damaging your domain’s reputation is directly correlated with how you scale your sending volume during holidays and big promotions.

Let’s say you have an email list with 250,000 people. This email list is divided into 3 main segments:

• Customers (80,000 people)
• Subscribers, (150,000 people)
• VIP customers (20,000 people)

For simplicity, let’s say that you are sending a newsletter three times a week to your subscriber segment. That gives you an average sending volume of 450k emails / week. Then comes Black Week and you start blasting your entire list every day. That means you are at a sending volume of 1.7M which is 3x higher than your average sending volume. Not a good idea.

Suddenly blasting your list will lead to rate limiting (lower delivery rate) or domain reputation drops.

Instead you want to scale up your volume over time. Start by increasing the frequency of your emails and progressively add more segments and contacts until you’re close to max volume.

The most important takeaways from Google’s new email rules…

These changes reflect what the majority of consumers would like to see in an inbox. Less spam, more relevance.

The best and most straightforward way to send out more relevant content is by segmenting your audience. So simple. Yet so few do it properly.

You can slice and dice your audience in a million different ways.

Use RFM analysis, behavior segmentation, gender, customer status, first- and zero-party data to tailor your promotional emails to specific segments.

But almost nobody does it. Because it’s time consuming to both collect and use the data they need.

Every year we manually analyze the customer journeys of the top 200 online retailers in Scandinavia. We reveal our findings in a yearly report called “Personalization index”.

One huge part of this analysis includes signing up for every brand’s newsletter. Subsequently, we receive more than 14,000+ promotional emails over the next 12 months from these 200 brands. And more than 98% of their emails end up in the promotions tab. Buried in a heap of “20% off ONLY today” emails.

There are in fact a lot of “spam” out there, even if the emails don’t meet the technical definition of being “suspicious”.

Except for managing the technical aspects of Google’s new email rules, our advice is to focus on customer experience.

A good customer experience lets the user choose their own path. Let them export their own data, unsubscribe from emails, make returns hassle-free, and most importantly… Reduce friction by using modern tools for onsite marketing, marketing automation, and data analysis.

Is 2024 the year you create your first customer experience strategy?

Here are some useful links if you want to read more about Google’s new email rules or see if your martech vendor supports the required authentication protocols.

• Google’s full email sender guidelines
• FAQ for email sender guidelines
• How to set up DMARC
• Google’s guide to setting up DMARC
• Rule’s guide to setting up DKIM & DMARC
• Klaivyo’s guidelines for Google’s new sender guidelines
• Mailchimp email authentication guide
• Emarsys email authentication guide
• Voyado email authentication guide
• DNS Checker tool

Marketers and businesses collect first-party data to gain more insights into their target audience. It is one of the most valuable sources of data, and as you will soon discover, it is also the key to both higher conversion rates and customer loyalty. Moreover, first-party data is fundamental to creating personalized experiences.

Data is a marketer’s most important asset.

Without data, you can’t track outcomes, discover new insights, or decide which campaign to spend more or less money on.

But…

There is a difference between data and data.

It comes from different sources, is used for different purposes, and is even regulated differently under e.g. GDPR and the e-Privacy Directive.

And as more and more browsers move away from third-party cookies (which are a form of third-party data), we are forced to rely on zero-party and first-party data.

What is first-party data? A definition

First-party data is all data that a company collects from its own channels and sources.

In other words, any information about your target audience that comes from both online and offline sources such as…

• Your website
• Your CRM
• Your email system
• Your POS system
• Your apps
• Your surveys
• Your social media

…counts as first-party data.

Most of your customers and users understand that you are collecting behavioral data about them, and there is always a consent form to justify the collection.

When a visitor to your website fills out a form or completes a purchase, they almost expect their data to be used by your company for improving the customer experience.

Advertising (mainly remarketing in this context), email marketing and personalization are three pillars of your customer experience strategy enabled by first-party data.

Here are some concrete examples of first-party data:

• Web activity: Clicks, page views, completed forms and other types of behavioral marketing on your website
• Interests: What areas the person is most interested in on the website, interests shown in social channels.
• Email: Email engagement, opened emails, email clicks, unsubscribes, etc.
• Social media: Likes, comments, interactions with your business page, etc.
• Web analytics: heatmaps, session recordings, visit history, landing page, exit pages, funnel analysis, etc.

The more first-party data you have on each individual customer, the more opportunities open up.

You can combine all these data points into a customer profile that centralizes and unifies your customer data across devices and channels…

…and centralized customer profiles open up a world of new opportunities and marketing activities.

The reason?

Most companies have a similar basic set of technologies that collect data about their customers and audience, consisting of a CRM, an ESP (newsletter tool), a web analytics service, and perhaps a customer case management service.

The problem?

All the data collected by each tool is also isolated to each tool. This makes it difficult to reconcile the data and draw conclusions like:

“Customers with more than 3 support issues within the first 30 days are more likely to respond to a survey”

And:

“Customers who responded to a survey are more likely to take an upsell”.

With centralized customer profiles, all data is collected in a single profile, allowing you to discover relationships without having to import and export from different systems.

It also enables you to display personalized offers for specific users and audiences directly on your website, deliver synchronized messages across all channels, and much more.

However, for first-party data to be valuable, it must also be activated and used regularly.

See how Triggerbee collects first-party data, combines it into your customer profiles, and activates it with personalization.

Why is first-party data important?

First-party data is important because you 100% own the data. It is also free to collect, apart from any costs for the tools.

So collecting first-party data means collecting data from customers and potential customers with whom you have, or will have, a direct relationship!

Here are some concrete reasons why collecting first-party data is important:

• Ownership: You, and only you, own the data you collect about your customers. You don’t have to buy data from external sources, you have all the data you need to analyze and make decisions that drive growth.
• Quality: Because first-party data comes directly from your customers or is a direct reflection of how they use your website or app, you can be sure that the data is reliable and up-to-date. Compare this to third-party data that is collected at a specific point in time and is rarely updated.
• Consent: First-party data is collected with the consent of your customers, meaning they are aware that their data is being collected, stored, and used by your company–and that you are not sharing their data with anyone else. This is important for building trust, but also a requirement for GDPR compliance. Third-party data is often collected without consent, and the same database is often sold to multiple companies.
• Relevance: First-party data is individual, which means you have a higher accuracy rate if you want to target offers or personalize your website for an individual or a target group segment, for example.

Relevance is the key to success in digital marketing and sales.

With more and more companies entering the market, competition is increasing. This means that the baseline for what communication your target audience considers “relevant” is increasing every day.

And with increased competition comes the temptation to buy data and email lists as a shortcut. But this often contributes to poorer relevance and poorer outcomes.

In short:

First-party data is essential to ensure that the insights you collect about your audience are continuously updated, while being collected with the consent of the customer.

First, second and third party data

You already know that first-party data is data you collect from your owned channels.

But what about second and third party data?

Second-party data

Second-party data is first-party data collected by Company A, but used by Company B. This can occur, for example, when two companies enter into a partnership where each company collects leads for the other on their respective websites and shares the data between them. If ICA and IKEA join forces and do an event, ICA could have a form on their website where you can sign up. If IKEA gets access to the information you provide, it is second-party data.

Third-party data is data collected by an organization that does not have a direct relationship with the user whose information is captured. Many times, third-party data is extracted from various sources, websites, and databases, and then aggregated through another provider. This process means that the information is collected at a specific time, and if the company extracting the data does not regularly update and clean it, it only reflects a snapshot.

How is first-party data collected?

The easiest way to understand how first-party data are collected is to give a concrete example.

Example of how first-party data is collected:

Let’s say I have bought a new phone, and I need to buy a case for it. I go to idealofsweden.com and accept that they use cookies. After looking at some cases, a widget appears offering me a 10% discount in exchange for my email address. I fill in the form to get the discount code, and put one of the shells in the shopping cart. I add the discount code, and proceed to finalize my purchase. In the checkout form, I fill in my address, my social security number and additional information about me. Once the purchase is complete, I am asked to leave a review about the shell.

This is all information that I voluntarily and knowingly provide in order to complete the purchase and start a relationship with the company.

If the company in the example above also uses web analytics to analyze and collect web activity, they could use behavioral data and purchase data to target offers in the future.

How do you use first-party data?

First-party data is used to serve ads (retargeting), personalize content on websites, customize messages to different audiences, and get to know the people behind the personal data through various analytics.

First-party data can also be used to create ideal customer profiles (avatars) so that you know, for example, where your target audience spends their time online, what their career and life goals are, what social media they use most, and what blogs they read.

By creating an ideal customer profile, you can better plan your sales and marketing budget and learn how to best reach your target audience.

Here are some examples of how first-party data is used:

1. First names in email campaigns
   If you subscribe to any newsletters, you’ve probably seen your name appear in some of them. This is because at some point you filled out a form or bought something from that company.
2. Advertisement for a product you visited before
   If you’ve seen a Facebook or Instagram ad for a product you’ve looked at before, you’ll see it thanks to first-party data.
3. Analytics and customer profiles
   A customer profile and analytics that by aggregating many different customers is made possible thanks to first-party data.

Zero-party data

There is another level of data called Zero-party data. The term was coined by Forrester in a report to describe all data that customers and users give up voluntarily.

The difference between Zero-party and first-party data is that Zero-party data only includes data that can be traced back to an individual, such as forms, surveys, chats, phone calls and the like.

This data is incredibly valuable, and as marketers become more and more data-driven, Zero-party data is invaluable in today’s competitive business climate.

Summary

First-party data is one of the most important data sources available. Without it, you can’t serve remarketing ads, personalize offers and content on your website, or target emails to specific audiences.

First-party data allows you to create communications that are relevant, specifically tailored to each individual and occasion.

You probably have plenty of first-party data in both your CRM and your email service. But the question is: Are you activating and using it? If not, start doing so today.

The value of your data is in direct proportion to how well you use it. Data that just sits around getting old is worthless, no matter how you got it.

FAQ

What is first-party data?

First-party data is any data that a company collects from its own channels and sources, both online and offline. For example, the website, social media accounts, surveys, forms, point-of-sale (POS) systems, digital behavior, etc.

Why is first-party data important?

First-party data is important because you own the data 100%. It is also free to collect, apart from any costs for the tools.
Therefore, collecting first-party data means collecting data from customers and potential customers with whom you have, or will have, a direct relationship!

How is first-party data used?

First-party data is used to show ads (retargeting), personalize content on websites, adapt messages to different target groups, and get to know the people behind the personal data by doing various analyses.
First-party data can also be used to create ideal customer profiles (avatars) so that you know, for example. Where your target audience spends their time online, what their career and life goals are, what social media they use most, and what blogs they read.

What is the difference between zero, first, second and third party data?

Zero-party data is any data that your customers give up voluntarily in e.g. forms and surveys. First-party data includes data from forms, but also extends to website activity, email campaigns opened, social media engagement, etc. Second-party data is first-party data that another company has collected, but is used by another company. Third-party data is data that is collected from many different sources at one point in time and is aggregated.

Surveys one of the most important parts of your customer experience strategy. But the hardest part of running surveys is arguably writing survey questions that customers want to answer, and that results in a good dataset that you can actually get insights from.

Everyone thinks they are good at writing survey questions.

But the truth is that collecting useful responses is harder than it seems.

TLDR;

1. Don’t use surveys when you can get the data from other tools
2. Use simple, sharp, and clear language
3. Don’t use double-barrel questions
4. Keep survey questions to a minimum
5. Don’t use leading questions
6. Offer incentives
7. Target your surveys to the right audience
8. Let people know how many questions there are and how long it will take
9. Use the same scales in all questions

Let’s dive right in!

1. Don’t use surveys when you can get the data from other tools

Avoid asking questions that you can get the answer to using other tools. If you want to learn how your customers use your website or product… use a tool like Clarity where you get session recordings and can uncover the answer yourself.

Surveys are better used to find out what your users feel when using your product or if they feel something is missing.

“Is the search bar valuable to you?” is a question that caters to your (or someone in your organizations) biases and personal beliefs.

You can easily see if the search bar is used by using free analytics tools. And survey questions like these usually end up in a survey after a discussion between colleagues or teams with different opinions. Don’t let your customers be the mediator in your internal politics.

If you are looking for improvement suggestions, a better question to ask customers is:

“If you had a magic wand that could make any change to [Website/product], what would it be?”.

This type of question gives the participant complete freedom to answer based on their current experience with your website or product. It also allows them to draw on their experience with similar products or websites.

Use simple, sharp, and clear language

Don’t use overly complex words or sentences that can be misinterpreted or use confusing language

Example of a bad survey question: “Imagine you have just come home from work after picking up your children from preschool, and in the middle of cooking dinner, you receive a 25% off SMS discount. How likely are you to make a purchase within 7 days?”

The complexity of this question is exaggerated for the purpose of this article, but it’s not that far off from how some organizations write their questions.

If all you wanted was an answer to whether or not your customers are likely to purchase something when they receive an SMS promotion, you should use a simple question like this:

“On a scale of 1-5, how likely are you to make a purchase from an SMS promotion?”

Cut unnecessary qualifiers, don’t ask participants to imagine a scenario, and get straight to the point.

Don’t use double-barrel questions

Double-barrel questions are asking a participant to provide one answer to two (topically related) questions.

Example of a double-barrel question:
“How would you rate our website and checkout experience?”

The insights from a question like this would be invalid, because you have no idea if participants rate your website OR checkout experience.

With a double-barrel question like this, participants will most likely answer this question based on the best or worse experience with one or the other. Or worse, using a made up “average” based on the full experience.

Another thing to consider is when you present your results and someone asks “So, based on your results… What are the next steps?”

A question like this should be split into multiple questions. Remember, one question at a time that gives a clear answer.

Keep survey questions to a minimum

Never ask questions just to have a certain number of questions. There are no min or max number of questions that you need in order to get good results.

Don’t use leading or loaded questions

You don’t want your customers to be swayed to respond based on your opinions. Adding words like “awesome” when asking participants to rate their experience with support, or using a word like “fast” when asking participants to rate your delivery times will make them respond in a certain way.

The last thing you want when running a survey is to persuade your participants to respond in favor of how you want them to respond.

Here are a few examples:

❌ Leading question: “How was your experience with our awesome support team?”
✅ Neutral language: “Rate your experience with our support team”

❌ Leading question: “Rate how fast our delivery times are on a scale of 1-5”
✅ Neutral language: “On a scale of 1-5, rate the delivery time for your last purchase”

❌ Leading question: “How much did you enjoy your shopping experience?”
✅ Neutral language: “Rate your shopping experience”

Offer incentives

Most people have nothing to gain from helping you improve your business. Sorry, but it’s the truth.

If you offer an incentive on the other hand… Your survey suddenly becomes a lot more interesting.

But keep in mind that you should keep the incentive good enough for your target audience to want to participate, but not so good that you attract people who just want the reward.

A classic example of a “bad” incentive is giving away an iPhone to 1 or more randomly selected participants.

It’s better to use a 10% or 20% discount that participants receive in your store.

Target your surveys to the right audience

This is a mistake we see a lot of organizations make. Especially the large ones.

Most survey requests should not be sent to your full list. Targeting is key to qualitative responses, and even more so if you are using website surveys to evaluate your shopping experience.

If you are using a solution like Triggerbee surveys you can use website behavior, CRM data, location and 37 more criteria to target your surveys to individual customers visiting your website.

Below you’ll find some common surveys and their optimal audience.

• Micro surveys. Targeting: Everyone. Micro surveys target users who interact with a specific feature on your website or perform a specific action.
• NPS Surveys. Targeting: Customers or end-users. NPS surveys measure loyalty and your relationship with your customers. Make sure you target
• CSAT surveys. Targeting: Immediately after purchase. CSAT surveys are great for measuring how your customers experience your website, and is commonly used as a quick post-purchase survey on the thank you-page.

Let people know how many questions there are and how long the survey will take to complete

It’s good practice to be upfront with how many questions are in your survey along with how long it takes to go through them.

This lets users know what to expect and can increase your response rate.

Use the same scales in all questions

If you use rating- or scale-based survey questions, you should aim to use the same scale for all rating questions.

It’s totally OK to mix different types of questions as long as the response criteria is consistent across all questions

For example, don’t use a 1-5 scale question immediately after a 1-7 or 1-10 scale question.

Using the same scale across all similar questions will also allow you to have more questions in your survey. The human brain loves what it recognizes, and the effort to rate a statement will go down the more things you rate.

Basically, it will take more cognitive effort to rate two statements with different scales, compared to rating 3 or 4 statements using the same scale.