Data privacy continues to be a hot topic for consumers who are worried brands know too much about them, and exploit that information.
This makes email personalization a tough tightrope to walk. It’s true that personalized offers and communication yields higher open rates and conversion rates. But at the same time you don’t want to over-personalize and make customers think you’re surveilling them.
To help you navigate this is Email Kong, an email marketing agency that manages over 150 accounts and has generated a combined $58.2M in attributed revenue for our clients.
Personalization is a huge part of every campaign or automated flow we run. In this guide we’ll explain how we use email personalization without alarming recipients.
Is Too Much Personalization Really A Bad Thing?
The answer to this question is rather interesting. Qualtrics XM Institute’s 2026 Global Consumer Trends Report asked consumers directly about their thoughts on personalized marketing directly - here are the results:
What this data communicates to me is that the majority of consumers want personalization in their email content but are uncomfortable with how that personalization is determined behind the scenes.
This view is echoed by the experts on Reddit. In r/emailmarketing, u/nonam314 wrote that "behavior level personalization is fairly good and performs good, unless you surface it directly and explicitly".
For consumers, it's the thought of being tracked and crunched through an algorithm that is the whole problem. Not necessarily the offers they’re receiving themselves.
Our working rule is: to use what you know, without shoving it in your customers faces. The goal is to be genuinely helpful without reducing someone to ones-and-zeros.
Essential Personalization Needed For Every Campaign
A ‘first name’ merge field used to be the whole of email personalization, it's now much more advanced than that. Below are the three types of email personalization we include in every client campaign.
Write The Subject Line And Preview Text As One Unit
A quick starting tip is to make sure your subject lines are personalized for each recipient, this could be as simple as including their name in the subject line or referencing the product they showed interest in.
Take this to the next level by thinking of your subject line and preview text as one co-dependent organism. They’re both displayed next to each other in inboxes, meaning they’re often read together as a continued sentence.
These two render together in the inbox. A personalized subject line followed by generic preview text wastes half of the only line your reader sees before deciding whether or not to open your email.
Lead with the usefulness. Leave the tailoring unannounced, because a subject line that says what the reader gets will beat one that says what you know about them, and it spends no goodwill doing so.
Recommend Products Based On Their Purchasing Behaviour
Most email personalization happens within your automated flows rather than in targeted campaigns. Two follows are particularly crucial to get right here:
- Replenishment flows
- And flows recommending new products
Replenishment flows are fairly straightforward. If you’re a retailer of hair shampoo, you should have the data to predict when customers are likely to run out and repurchase. Use this timeline to reach out to your customers and ask them if they’re ready to stock back up.
When recommending a new product, our agency has found the most success when suggesting a product that compliments the one they’ve already bought.
For example, if you have a customer who has recently purchased a bathing suit and sunblock, it's safe to assume they’re going to be experiencing warm weather in the not too distant future. So use that assumption to provide other warm weather items such as sunglasses or beach towels.
What we’ve found at Email Kong is that customers appreciate personalized offers when they’re genuinely useful to them.
Swap Body Blocks On A Profile Condition
One campaign can carry different body content for different segments, with the blocks resolving when the email renders against whatever condition you set on the profile.
That leaves you with one schedule, one report and one build. Two or three variants inside a single send beats maintaining separate campaigns that drift apart within a month.
It also beats writing to the average of your list, because the average describes nobody on it. A brand selling both to first-time buyers and to people on their fourth reorder has two audiences, and one paragraph can't serve either of them well.
Mistakes To Avoid With Personalization
Referencing Behavior They Never Shared With You
Most brands observe browsing behavior on their websites. To the customer, this is information they aren’t aware they're providing.
You need to be careful with how you leverage that data. A famous anecdote I’m reminded of is when Target figured out a teen girl was pregnant before her father did based on her purchasing history.
The father complained to Target and had to apologize later on when he found his daughter was in fact pregnant. This is the exact scenario you would want to avoid.
Having said that, don’t be worried about things like abandoned cart emails, which are the norm and expected by customers. These fall on the genuinely useful side of personalization.
Making Incorrect Assumptions About Your Customers
One mis-read signal ships at full confidence, because nothing in the flow stops to ask whether the inference was right.
Amazon learned that in public when it sent baby registry emails to infertile women, who read them as a reminder of something deeply personal.
That same class of mistake caught Adidas, which congratulated its running-shoe customers as part of a Boston Marathon campaign without checking whether they actually ran the race.
Neither brand lacked data. Both inferred an event from one behavior and failed to validate whether it was actually true.
Offering Discounts To Customers Who Don’t Qualify
A super common mistake we see is enrolling subscribers onto welcome flows that have no defined exit.
This often leads to existing customers receiving discounts aimed at new customers, which are then rejected at checkout. Leading to understandable frustration from those existing customers.
Add the purchase exclusion to every acquisition flow before you add anything clever. It takes minutes to set up and prevents non-eligible offers from landing in the wrong customers inbox.
Using AI To Match The Offer To The Person
Klaviyo provides the following forecasts for each subscriber: when they will next order, what they are worth over time, and whether they are about to leave.
Here’s how we recommend you use those data points.
Gate The Discount On Churn Risk
Not every customer needs a discount, least of all the ones who are happily making regular purchases on your website.
Personalized discounts should be reserved for customers you want to re-engage, ones which haven’t purchased in quite some time.
Churn risk is the datapoint which highlights risk-customers. Your AI can identify which customers would benefit most from re-engagement and use that as the trigger to insert contacts in your winback flows
Let The Recommendation Block Pick The Product
Product selection is the highest-yield decision to hand over, because a recommendation block runs per profile against your whole catalog at send time and no hand-built block matches that reach.
Klaviyo extended next best product into SMS and WhatsApp in February 2026, which matters beyond convenience: the same framing rule now has to travel with it, and a text that narrates a browse is worse than an email that does.
Keep hand-picking for the hero placement, where you have a commercial reason for the choice. Let the model fill the rest.
Predicted Value To Set How Big The Discount Is
Your customers spend different amounts on your store, some more and some less. Use the predicted value AI to determine which potential customers will have the highest basked total and then provide them with a higher discount amount.
Customers who only spend a little, need a smaller discount to protect your margins.
Don’t fall into the trap of sending the discount amount to every customer. Your brand has different relationships with these customers. The AI should be able to recognize that and reward customers with a discount value based on their predicted spend.
Data Security And Legislative Rules To Be Aware Of
Personalization reached further into the physical world during 2026, and the law tightened around those same signals in the same twelve months. Both changes land on what you are allowed to build next.
Precise Location Became A Restricted Category
Klaviyo shipped geofencing in January 2026, so a brand can now trigger messages when app users enter or leave an area around a store. Six months later the rules around that signal moved.
Virginia moved on that signal first. In July 2026 the state banned the sale of precise geolocation data, with Connecticut's equivalent following in October. Both statutes treat location as a category needing its own handling.
Capability and permission moved in opposite directions inside a single year. Treat a location trigger as something you need consent for, whatever your platform makes available.
Profiling Decisions Now Need A Written Assessment
Connecticut's amended act requires data impact assessments for profiling that produces legal or similarly significant effects. Privacy notices there must now disclose data used for training large language models.
New Jersey went further still, prohibiting the sale of sensitive data outright, effective immediately on enactment at the end of June 2026.
Each of these duties attaches to the decision your profiling drives, whatever category the underlying data happens to sit in.
A retention program inherits them without being named anywhere in the statute. Record why each predictive segment exists before you extend email personalization further.
Get A Second Opinion On Your Klaviyo Setup
Whoever built a flow can't see it the way its recipient does. Proximity is why these defects survive internal reviews that were careful and well run.
That is the argument for an outside read, and it is why our free Klaviyo audit starts as a teardown of your retention funnel before any conversation about strategy. It opens the places these defects hide:
What we look for in each of those places comes from the retention systems our Klaviyo agency has built for more than 140 DTC brands, worth $58.2M in Klaviyo Attributed Value. Our Trustpilot reviews come from the operators who sat through those audits and then ran the rebuild.
Both of those go into the audit. Book one and we will tell you which of your personalizations are misfiring, and which are worth what they cost to run.