Engaging with customers and subscribers is key to building long-lasting relationships and driving conversions. Personalization helps your company connect with customers, but the need for data and changes to consumer privacy policies present challenges to personalizing the customer experience. Let’s look at how you can use the data you already have to improve your company’s email marketing operation and nurture relationships with your subscribers.
Each day, you’re barraged by dozens of emails competing for your attention. Some of it is pure spam. Others are irrelevant. And some succeed in snagging your attention, even if you’re not entirely interested in the company or offer.
Which emails are enticing enough for you to spend more than half a second glancing over them before tapping delete, delete, delete?
They likely leverage some type of personalization intended to grab your attention and call out to you. The subject line probably greets you like an old friend — “Hey, Melissa!” — before referencing one of your interests, likes, or needs the same way a colleague would: “Enjoy your next lunch for 40% off, on us!”
This approach is warm and welcoming. It’s almost easy to forget the sender is some corporation or company. And even then, 40% off your next lunch is tough to pass up, especially when your favorite lunch spot is making the offer.
And so, belly rumbling, you open the email and get greeted with even more personalization. There, under a mouth-watering image of your favorite sandwich — the same one you ordered last week — is your name, front-and-center in bold, with an offer the email claims is just for you.
It’s an experience we’ve all had. The companies we frequently interact with leverage the personal information and data we’ve provided and that they’ve collected to target us with unique, personalized emails designed to retain us as customers and drum up more business.
The same is likely true of your company. Think of all the data you’ve collected in your CRM or data warehouse.
Like the lunch example, you must demonstrate that your company understands your customers. Not only might you address them by name or reference a previous order or visit (“we miss you!”), but show them that your company cares about their likes, needs, and preferences.
For example, a restaurant personalizing a lunch offer may look at your past order history to suggest a meal you haven’t tried yet that matches your assumed tastes.
Past orders may also be compared to that of similar customers to create a personalized suggestion for a meal that fits your customer profile.
Sure, you’ve ordered from that restaurant before and will likely do so again in the future, but at that moment, that check-in engages with you (and your appetite).
But without collecting and using your personal data, that restaurant wouldn’t be able to offer you such a personalized suggestion.
Maybe you’d have been offered a new menu item or one of the restaurant’s most popular orders, but there’d be little guarantee such an offer would convert and have you picking up the phone to order.
Let’s break down how this data influences the way businesses like yours communicate with subscribers.
Image Credit: Ongage
Leveraging this information — which comes from behaviors that include how customers engage with emails, interact with your website, and use your mobile app — enables your business to drive personalization [on] an individual level and continually improve your algorithm.
There are no limits to the types of behavioral data you may find useful. In addition to more generalized (but equally important) data like location and device type, consider looking at behavioral data that includes:
This personalization approach leverages real-time data, past activity, and machine learning to identify new connections between data sets, creating specific and personalized approaches.
But 1:1 personalization needs substantial data to be effective. A restaurant recommending a highly-personalized lunch order can leverage an extensive order history to understand your interests, preferences, and tastes.
If you’ve only ever ordered once — or only ever ordered a roast beef sandwich without mayo — a restaurant must depend on other data and analytics — such as the customer segment you belong — to offer you a personalized recommendation.
However, if you’ve ordered:
From there, you can personalize on a general level or break personalization down into micro-segments.
For example, your favorite restaurant may segment its customers into common subsets based on age, gender, and location. But it may also segment further into micro-segments based on factors such as:
Think of customers who frequently order lunch as a single segment. That segment may then be narrowed down further into customers who frequently order sandwiches for lunch. Or it may be narrowed down even further into customers who frequently order tuna sandwiches for lunch.
The more specific your segmentation, the easier it is to provide hyper-personalization.
You can then leverage these heaps of data to create and generate dynamic content blocks.
Dynamic content enables your company to deliver targeted and hyper-personalized content to segments or micro-segments of your choice. Then, automation can send this tailored content to each subscriber segment without requiring you to create multiple and distinct email campaigns.
Consider a restaurant offering new menu items for breakfast, lunch, and dinner. Through its behavioral data analysis, the restaurant knows vegans make up a sizable part of its customer base.
Upon announcing its new menu items, the restaurant creates dynamic content blocks spotlighting vegan-friendly options for vegan customers. In contrast, the restaurant sends different content to meat-eating customers.
But the possibilities don’t stop there. For example, the restaurant can create dynamic content targeting specific customers, highlighting new vegan breakfast options to those who typically stop in for a morning snack.
By combining dynamic content with automation, your company can tap into its wealth of data to create and launch specific, hyper-personalized email campaigns without requiring much more effort or investment, even as your business grows.
It also helps ensure seamless experiences from one channel to another. The information collected on your website or learned through a chatbot can impact how you personalize messages to that same customer via email or SMS marketing.
However, automation is no excuse for doing away with the personal touch. Companies must find a balance between automation and human interaction. Let automation enhance and empower your approach to personalization, but remember the person (or people) you’re engaging with, too.
We’ve covered many ways you can use personalization to improve KPIs. They’re all important and relevant.
But it’s vital to acknowledge they all rely on quality data, and obtaining it is crucial for effective personalization.
You may think it’s an impossible task for you, but keep on reading and you’ll discover quality data is within reach.
The best approach is adding data into your company’s CRM or data warehouse. Because these tools contain data from every channel, they provide you with a high-level overview of how each of your customers or customer segments behave.
But there’s no guarantee that the data you’ve collected is accurate or complete, potentially degrading the impact of your personalization efforts. To avoid any shortfalls, we recommend using data enrichment tools to complement, improve, and verify the data you’ve collected by adding and connecting data points from multiple channels.
Using data enrichment to enhance your subscriber data lets your company better personalize the customer experience. As a result, your campaigns are more likely to engage with your customers and drive conversions.
But, alas, there are still some obstacles to overcome.
If that’s not enough -pocalypses for the marketer in you, there’s another in the pipe, too. The “cookie apocalypse” — Google’s plan to deprecate support for third-party cookies — is expected to roll out in mid-2023.
Google doesn’t plan to stop there, either. Driven by Apple’s new privacy policy, Google intends to limit data sharing on Android devices within two years.
Though it promises to be less disruptive than Apple MPP, Google’s expansion of its Privacy Sandbox initiative means marketers will lose access to tracking identifiers and other data.
What do these privacy initiatives mean for you?
MPP makes certain metrics — like open rates — difficult or impossible to measure with any degree of accuracy. It also becomes difficult to follow subscribers' mail activity because their IP addresses are hidden.
Google’s cookie apocalypse functions similarly. By deprecating third-party cookies, companies will lose access to user data generated from off-site, diminishing the ability for advertisers to display highly-personalized ads to consumers.
This makes segmentation more difficult, but it doesn’t impact your ability to collect information via first-party cookies on your site or app. You just need to get smart about collecting and using data to personalize the customer experience.
This means you need to create actual value.
Speak to the reasons a subscriber would even consider opening your email. And then, think about what will encourage them to follow through with your CTA.
One way to go about it is to send your emails at the best time possible.
If your platform doesn’t offer this, don’t despair.
Much of the data you collect and analyze can be used to actively and manually calculate the best times to send an email. Consider factors such as recipients’:
Illustration Credit: Ongage
Collating, analyzing, and acting on this information is why your favorite restaurant knows its best shot at bringing you in for a special lunch is that early Wednesday morning email. You’re going to see it, you’re going to be hungry, and you’re going to convert.
Automation may suffer some defeats, at least at the start. For example, open rates are no longer a dependable trigger for sending a follow-up or subsequent email. Similarly, you may have difficulty gathering data from the customer’s entire journey once third-party cookies lose their functionality.
However, this changing landscape also helps automation shine. Automation can function as an alternative to third-party data, especially when coupled with machine learning and AI.
You can leverage automation to create and learn from a first-party ecosystem and all of the first-party data stored in your CRM or data warehouse. This gives you access to whatever metrics you deem necessary and important, like click rates, and provides insight into customer behaviors and interests across every channel you operate in.
The good news is: you likely have all the data you need to implement or improve personalization in your email marketing.
Like a restaurant tapping into its customers' order histories to make highly-personalized and mouth-watering recommendations, your company's CRM and data warehouse represent a treasure trove of information that can improve your customers’ experience and drive conversions.
By leveraging personalization to create value for your customers, you’ll create tangible value for your bottom line, too.
Authors bio:
Each day, you’re barraged by dozens of emails competing for your attention. Some of it is pure spam. Others are irrelevant. And some succeed in snagging your attention, even if you’re not entirely interested in the company or offer.
Which emails are enticing enough for you to spend more than half a second glancing over them before tapping delete, delete, delete?
They likely leverage some type of personalization intended to grab your attention and call out to you. The subject line probably greets you like an old friend — “Hey, Melissa!” — before referencing one of your interests, likes, or needs the same way a colleague would: “Enjoy your next lunch for 40% off, on us!”
This approach is warm and welcoming. It’s almost easy to forget the sender is some corporation or company. And even then, 40% off your next lunch is tough to pass up, especially when your favorite lunch spot is making the offer.
And so, belly rumbling, you open the email and get greeted with even more personalization. There, under a mouth-watering image of your favorite sandwich — the same one you ordered last week — is your name, front-and-center in bold, with an offer the email claims is just for you.
It’s an experience we’ve all had. The companies we frequently interact with leverage the personal information and data we’ve provided and that they’ve collected to target us with unique, personalized emails designed to retain us as customers and drum up more business.
The same is likely true of your company. Think of all the data you’ve collected in your CRM or data warehouse.
- Are you using it all?
- How can you use it better to personalize your emails beyond simple greetings and niceties?
- What are the benefits and impacts of maturing the way your company personalizes its communications with customers?
How to personalize beyond the [FName] in email marketing
71% of consumers expect personalized experiences from the companies they interact with. Using merge tags — dynamic tags like [FName] that include your subscribers’ basic information, such as their First Name — isn’t enough to deliver a personalized experience. It’s only a start.Like the lunch example, you must demonstrate that your company understands your customers. Not only might you address them by name or reference a previous order or visit (“we miss you!”), but show them that your company cares about their likes, needs, and preferences.
For example, a restaurant personalizing a lunch offer may look at your past order history to suggest a meal you haven’t tried yet that matches your assumed tastes.
Past orders may also be compared to that of similar customers to create a personalized suggestion for a meal that fits your customer profile.
How data changes the way we communicate with subscribers
Data enables companies to connect and continually engage with customers. It’s why an email on a Wednesday morning treating you to a discounted and mouth-watering lunch is so effective.Sure, you’ve ordered from that restaurant before and will likely do so again in the future, but at that moment, that check-in engages with you (and your appetite).
But without collecting and using your personal data, that restaurant wouldn’t be able to offer you such a personalized suggestion.
Maybe you’d have been offered a new menu item or one of the restaurant’s most popular orders, but there’d be little guarantee such an offer would convert and have you picking up the phone to order.
Let’s break down how this data influences the way businesses like yours communicate with subscribers.
Behavioral data
Behavioral data is rich with insights into what your customers want and how they think.Leveraging this information — which comes from behaviors that include how customers engage with emails, interact with your website, and use your mobile app — enables your business to drive personalization [on] an individual level and continually improve your algorithm.
There are no limits to the types of behavioral data you may find useful. In addition to more generalized (but equally important) data like location and device type, consider looking at behavioral data that includes:
- Search keywords.
- Referral source.
- How often the customer visits your website or uses your app.
- Time of visit, including its proximity to payday, holidays, or sales events.
- Purchase or order history.
- Session behavior.
1:1 personalization
1:1, or one-to-one, personalization is an intensely focused type of "hyper-personalization" that uses micro-segmentation to understand each individual customer you’re targeting.This personalization approach leverages real-time data, past activity, and machine learning to identify new connections between data sets, creating specific and personalized approaches.
But 1:1 personalization needs substantial data to be effective. A restaurant recommending a highly-personalized lunch order can leverage an extensive order history to understand your interests, preferences, and tastes.
If you’ve only ever ordered once — or only ever ordered a roast beef sandwich without mayo — a restaurant must depend on other data and analytics — such as the customer segment you belong — to offer you a personalized recommendation.
However, if you’ve ordered:
- Once a week.
- On Wednesdays at 11 am.
- And it’s always sandwiches made with French bread, no mayo, and extra tomatoes.
Segmentation
Segmentation lays the groundwork for personalization of any sort, including something as in-depth as 1:1 personalization. It’s what gives you a broad view of who your customers are.From there, you can personalize on a general level or break personalization down into micro-segments.
For example, your favorite restaurant may segment its customers into common subsets based on age, gender, and location. But it may also segment further into micro-segments based on factors such as:
- The usual time of day to order.
- Favorite dishes.
- Preferred proteins, vegetables, and sides.
Think of customers who frequently order lunch as a single segment. That segment may then be narrowed down further into customers who frequently order sandwiches for lunch. Or it may be narrowed down even further into customers who frequently order tuna sandwiches for lunch.
The more specific your segmentation, the easier it is to provide hyper-personalization.
Automation
With so much available data, one of your major concerns may be how to collect, analyze, and use it all in meaningful, actionable ways. Email automation helps streamline this process, segmenting customers based on certain parameters and the data contained within their profiles.You can then leverage these heaps of data to create and generate dynamic content blocks.
Dynamic content enables your company to deliver targeted and hyper-personalized content to segments or micro-segments of your choice. Then, automation can send this tailored content to each subscriber segment without requiring you to create multiple and distinct email campaigns.
Consider a restaurant offering new menu items for breakfast, lunch, and dinner. Through its behavioral data analysis, the restaurant knows vegans make up a sizable part of its customer base.
Upon announcing its new menu items, the restaurant creates dynamic content blocks spotlighting vegan-friendly options for vegan customers. In contrast, the restaurant sends different content to meat-eating customers.
But the possibilities don’t stop there. For example, the restaurant can create dynamic content targeting specific customers, highlighting new vegan breakfast options to those who typically stop in for a morning snack.
By combining dynamic content with automation, your company can tap into its wealth of data to create and launch specific, hyper-personalized email campaigns without requiring much more effort or investment, even as your business grows.
It also helps ensure seamless experiences from one channel to another. The information collected on your website or learned through a chatbot can impact how you personalize messages to that same customer via email or SMS marketing.
However, automation is no excuse for doing away with the personal touch. Companies must find a balance between automation and human interaction. Let automation enhance and empower your approach to personalization, but remember the person (or people) you’re engaging with, too.
We’ve covered many ways you can use personalization to improve KPIs. They’re all important and relevant.
But it’s vital to acknowledge they all rely on quality data, and obtaining it is crucial for effective personalization.
You may think it’s an impossible task for you, but keep on reading and you’ll discover quality data is within reach.
How do you acquire subscriber data?
Despite legal, regulatory, and ethical obligations, acquiring subscriber data may be easier than you think. In fact, 90% of customers are happy to provide you with their data if it means they’ll have a cheaper or more convenient experience.The best approach is adding data into your company’s CRM or data warehouse. Because these tools contain data from every channel, they provide you with a high-level overview of how each of your customers or customer segments behave.
But there’s no guarantee that the data you’ve collected is accurate or complete, potentially degrading the impact of your personalization efforts. To avoid any shortfalls, we recommend using data enrichment tools to complement, improve, and verify the data you’ve collected by adding and connecting data points from multiple channels.
Using data enrichment to enhance your subscriber data lets your company better personalize the customer experience. As a result, your campaigns are more likely to engage with your customers and drive conversions.
But, alas, there are still some obstacles to overcome.
The impact of Apple MPP and the cookie apocalypse on email data and personalization
Apple MPP, or Apple Mail Privacy Protection, is an iOS 15 privacy feature that blocks marketers from acquiring data through an invisible pixel included in emails and newsletters. Since well before its launch in September 2021, Apple MPP was seen — perhaps hyperbolically — as the “emailpocalypse.”If that’s not enough -pocalypses for the marketer in you, there’s another in the pipe, too. The “cookie apocalypse” — Google’s plan to deprecate support for third-party cookies — is expected to roll out in mid-2023.
Google doesn’t plan to stop there, either. Driven by Apple’s new privacy policy, Google intends to limit data sharing on Android devices within two years.
Though it promises to be less disruptive than Apple MPP, Google’s expansion of its Privacy Sandbox initiative means marketers will lose access to tracking identifiers and other data.
What do these privacy initiatives mean for you?
MPP makes certain metrics — like open rates — difficult or impossible to measure with any degree of accuracy. It also becomes difficult to follow subscribers' mail activity because their IP addresses are hidden.
Google’s cookie apocalypse functions similarly. By deprecating third-party cookies, companies will lose access to user data generated from off-site, diminishing the ability for advertisers to display highly-personalized ads to consumers.
This makes segmentation more difficult, but it doesn’t impact your ability to collect information via first-party cookies on your site or app. You just need to get smart about collecting and using data to personalize the customer experience.
How to rely more on clicks than opens as an engagement meter
Across all industries, the average email open rate is 25.39%. But that number is relatively meaningless because:- Open rates are unreliable and don’t necessarily correlate to conversions or sales.
- They’re also skewed by subscribers who use Apple Mail, who are immediately counted as having opened your email.
This means you need to create actual value.
Speak to the reasons a subscriber would even consider opening your email. And then, think about what will encourage them to follow through with your CTA.
One way to go about it is to send your emails at the best time possible.
How to optimize sending time
Email marketing platforms often offer Send Time Optimization (STO) functionality, employing algorithms that use behavioral data to determine the best time to send emails.If your platform doesn’t offer this, don’t despair.
Much of the data you collect and analyze can be used to actively and manually calculate the best times to send an email. Consider factors such as recipients’:
- Time zones: the geographic region they live in.
- Signup time: when they signed up to receive emails from you.
- Real-time engagements: when the subscriber is actively browsing through their inbox, clicking links.
- Cross-channel activity: during periods when the subscriber is interacting or has interacted with your company.
Collating, analyzing, and acting on this information is why your favorite restaurant knows its best shot at bringing you in for a special lunch is that early Wednesday morning email. You’re going to see it, you’re going to be hungry, and you’re going to convert.
How is automation affected?
Both MPP and Google’s cookie apocalypse impact automation, but don’t lead to — as their monikers may imply — the end of the (marketing) world.Automation may suffer some defeats, at least at the start. For example, open rates are no longer a dependable trigger for sending a follow-up or subsequent email. Similarly, you may have difficulty gathering data from the customer’s entire journey once third-party cookies lose their functionality.
However, this changing landscape also helps automation shine. Automation can function as an alternative to third-party data, especially when coupled with machine learning and AI.
You can leverage automation to create and learn from a first-party ecosystem and all of the first-party data stored in your CRM or data warehouse. This gives you access to whatever metrics you deem necessary and important, like click rates, and provides insight into customer behaviors and interests across every channel you operate in.
To succeed with email marketing, prioritize personalization
Eighty percent of customers are more likely to purchase from companies that offer personalized experiences, which only highlights the importance of developing an effective email personalization strategy.The good news is: you likely have all the data you need to implement or improve personalization in your email marketing.
Like a restaurant tapping into its customers' order histories to make highly-personalized and mouth-watering recommendations, your company's CRM and data warehouse represent a treasure trove of information that can improve your customers’ experience and drive conversions.
By leveraging personalization to create value for your customers, you’ll create tangible value for your bottom line, too.
Authors bio:
Melissa Pekel and Haim Pekel (H&M) are VP Marketing & VP Growth @ongage , a nextgen email marketing platform. Prior to Ongage, H&M spearheaded marketing and growth operations at Press on It, their agency. They worked with SaaS, Martech, and software companies, building them from the ground up or leading continued growth in large-scale operations.
