That said, all templating languages have their quirks. Whether it’s Iterable Handlebars, Braze’s Liquid (don’t confuse it with Shopify’s Liquid), Customer.io’s Liquid (yes, it’s different), Hubspot’s HubL, or Klaviyo’s Django, there’s always a steep learning curve when you’re trying to use it in practice.

This is the Handlebars guide we wish existed when we started working with it. Hopefully, this guide helps you avoid some of the hair loss and head-banging that so many people go through when trying to implement it in their messaging.

The “Basics”

Handlebars is a known templating language that existed well before Iterable. Other platforms, like Sendgrid, use it to populate dynamic content in messaging. That said, each platform that uses “Handlebars” has adapted it in special ways that are unique to its platform.

That’s why when you try to search for help on Handlebars, or run an idea through AI, you often get answers that are incomplete, or worse: incorrect. AI and web search discover solutions using the master knowledge base of Handlebars — not Iterable handlebars specifically.

defaultIfEmpty — Your First Line of Defense

This is the helper you’ll use more than any other. It provides a fallback value when a user profile field is blank or missing:

{{defaultIfEmpty firstName "there"}}
{{defaultIfEmpty preferredLocation "you"}}
{{defaultIfEmpty hotel.imgUrl "<https://fallback.example.com/hero.jpg>"}}

We use defaultIfEmpty on virtually every personalized field. The alternative is broken personalization — “Hey {blank}, check out our latest...” — and that erodes trust faster than no personalization at all.

Here are some field examples we protect most often: firstName, preferredLocation, heading or subheading (these are technically #assign variables, but don’t sweat that for now), hotel.url, imageUrl, etc.

If it’s user-facing and dynamic, it gets a fallback.

Date Formatting with {{now}}

Dynamic dates in Iterable use the now helper with Java date format strings:

{{now format='yyyy'}}

This returns the current year — useful for copyright footers that you never want to manually update again.

{{#each}} Loops Patterns

Loops are where Handlebars in Iterable gets genuinely powerful — and genuinely tricky. The {{#each}} helper allows you to “iterate” or repeat content, code, and data fields for customer data that comes to you in a list-like format (a.k.a. “Arrays”). Below are some of the most common #each loops we see:

Cart Recovery URLs

{{#each shoppingCartItems}}
  {{#unless @first}},{{/unless}}
  {{this.url}}
{{/each}}

The {{#unless @first}} conditional prevents a leading comma on the first item. Useful when constructing comma-delimited strings for cart recovery links.

Shopping Cart Item Arrays

For abandoned cart emails, shoppingCartItems is an array on the user profile:

{{#each shoppingCartItems}}
  <img src="{{imageUrl}}" alt="{{name}}" />
  <p>{{name}} — {{color}}, Size {{size}}</p>
{{/each}}

Collection Loops

{{#each collection}}
  {{#ifContainsStr (replace searchTerm " " "") this.category}}
    <!-- render this item -->
  {{/ifContainsStr}}
{{/each}}

This pattern filters collection items based on a search term, with a replace helper to strip whitespace.

Conditional Helpers Beyond {{#if}}

Iterable extends standard Handlebars with custom conditional helpers:

{{#ifEq}} — Exact Match

{{#ifEq teamSport targetSport}}
  <!-- show sport-specific content -->
{{/ifEq}}

{{#ifContainsStr}} — Partial Match

{{#ifContainsStr userCategories "running"}}
  <!-- show "running" content -->
{{/ifContainsStr}}

{{#assign}} — Template-Level Variables

{{#assign "primaryColor" "#FF6B35"}}

Variables set with #assign are available throughout the template. We use these for brand colors, repeated copy, and — importantly — as a workaround for snippet variable limitations.

The Snippet Variable Limitation (And the Workaround)

This catches every team eventually: snippets in Iterable cannot parse Handlebars the way templates can.

The workaround:

1. Store dynamic copy in {{#assign}} variables at the top of the email template

2. Pass those variables through to the snippet using snippet variable references

3. The snippet receives the resolved value, not the Handlebars expression

<!-- In the template -->
{{#assign "disclaimer_text" (defaultIfEmpty disclaimerCopy "Standard terms apply.")}}

<!-- In the snippet, reference the variable -->
{{disclaimer_text}}

This is an architectural decision you make once and bake into your snippet registry.

The {{join}} Helper for Arrays

When you need to display an array as a formatted string:

{{join tags ", "}}

Renders ["running", "yoga", "cycling"] as “running, yoga, cycling.”

Data Feeds: Same Helpers, New Source

Data feeds let you pull external JSON into your template — from your own API, a CMS, a recommendation service, or the pattern we use most often, Airtable. That Airtable approach turns one blast into infinite personalized sends without cloning templates — it’s the single biggest leverage point most lifecycle teams are missing.

Read Our Airtable Data Feed Post Here

That said, from a Handlebars perspective, feed data is just another data source. Every helper you’ve already learned applies:

{{#each feedItems}}

  <h3>{{defaultIfEmpty this.title “Untitled”}}</h3>

  <p>{{this.description}}</p>

{{/each}}

The one Handlebars-specific gotcha: if no rows match your filter criteria, Iterable defaults to the first row. A user who should see nothing sees whatever’s at the top of your feed instead. Guard with {{#if}}.

{{#if partner}}

  <!-- feed-driven content -->

{{/if}}

When to Get External Help

Handlebars can be a lot to keep track of. It can power your messages, snippets, subject lines, segments, and more. If this all feels like “too much, too soon” — consider chatting with us at Modular. We have a proven track record of creating dynamic solutions with Handlebars that directly affects bottom-line metrics (check out this case study), and we’d love to help you.

Learn More

I spoke at a conference on personalization in marketing recently, and during the Q&A session, someone asked me a fantastic question:

“How do you determine what level of personalization is right for your audience and your brand?”

It’s such an important question because while personalization is one of the most powerful tools we have as marketers, there’s a fine line between creating meaningful connections and crossing into territory that feels invasive.

The “Friend Test”

One way to think about personalization is to apply the “friend test.” If it’s something you’d naturally know about a good friend—their favorite color, clothing size, or preferred travel activities—it’s likely appropriate. If it’s too personal, sensitive, or confidential—like financial details, health records, or private conversations—it doesn’t belong in your messaging. This lens helps you focus on data points that feel personal without being intrusive.

Timing Matters Just as Much

Personalization isn’t only about what you say—it’s also about when. A birthday email sent on the actual day feels thoughtful. Adding context, like suggesting an item they’ve browsed recently or a product that aligns with their preferences, makes it even more impactful. The goal isn’t to flaunt how much you know, but to show customers you’re paying attention and care about their needs.

Caring Over Knowing

At the end of the day, personalization should feel like care, not surveillance. Remember the principle: “Nobody cares how much you know until they know how much you care.” Use that as a compass when deciding which data points to leverage, what context to bring in, and how to time your messages.

When done right, personalization builds trust and strengthens relationships—because your customers feel seen, understood, and valued.

Someone recently asked me why I included a “User Stories” section in a project template I created. It was a fair question—it might seem like extra work or formality when you just want to get to the technical implementation.

But here’s the thing: user stories are one of the most powerful tools in a technical marketer’s arsenal, and I’m going to show you why.

What Are User Stories?

User stories are a common product design exercise, and they’re deceptively simple. They force you to put yourself in the shoes of the actual end user of the finished product. All you have to do is complete this sentence:

“As a user, I want to... {{insert end-product use case here}}”

That’s it. But don’t let the simplicity fool you—this exercise does some heavy lifting.

When you write user stories, you step out of “implementation mode” and into “outcome mode.”

Instead of thinking “I need to connect to the API and pull metrics,” you think “I need to see my data in a way that helps me make decisions.” That shift in perspective offers an accessible way to identify technical requirements and challenges before you start the work.

User stories also act as a reality check. They help you catch scope creep before it happens, identify missing questions you hadn’t considered, and—crucially—separate what users actually need from what you think would be cool to build.

Before you dive into the technical weeds, user stories help you narrow down exactly what you’re looking for. They give you a North Star to refer back to when you’re three levels deep in documentation trying to figure out why the API response doesn’t match what you expected.

Example: Email Metrics Dashboard

Let me show you how this works with a real scenario. Say you’re building an email metrics dashboard.

The user stories might look like this:

• “As a user, I want to see all of my email metrics in one spreadsheet.”

• “As a user, I want to see my email metrics grouped by journey.”

• “As a user, I want to easily know what campaign I’m looking at (human readable) when I’m seeing campaign metrics.”

Simple enough, right? These feel almost obvious when you read them.

Here’s where it gets interesting.

A Solution Architect can deduce from these user stories—which you assume are all true—that they must:

• Integrate the marketing platform with a spreadsheet application

• Include or map journey information to the campaign metrics

• Map campaign names to campaign metrics you pull from the marketing platform (probably requires another API endpoint)

But wait, there’s more!

If you dig deeper into those user stories, you’ll uncover even more requirements:

• Data refresh logic: “See all my email metrics” implies the data needs to stay current. Do you need scheduled refreshes? Real-time updates? All of this will need clarification before completing the project.

• Error handling: What does the user see if a campaign has metrics but no associated journey (i.e. a Blast Email)? Do you show an error, a null value, or default it to “Uncategorized”?

• Authentication: You need to authenticate with the marketing platform API. What kind of API key do you need? What permissions are involved with that key? Do you need to handle token refreshes? What happens when credentials expire?

• Data transformation: Email platforms often return nested JSON objects or even CSV responses. You’ll need to parse and format that response into spreadsheet-friendly rows and columns.

• Performance considerations: If you’re pulling metrics for hundreds of campaigns across multiple journeys, you need pagination logic and possibly caching to avoid timeouts.

• Data validation: What if the API returns a campaign with a null name? Or metrics in an unexpected format? You need validation logic before you write to the spreadsheet.

See what happened there? Three straightforward user desires turned into at least nine distinct technical requirements, including multiple API endpoints, error handling strategies, and data transformation logic you might not have initially planned for.

Why User Stories Matter

User stories give you key information about the steps needed to plan and implement a solution. What seems simple or “given” to a user may require several extra steps to complete the project.

That “human readable campaign name” requirement? You potentially need to make an entire additional API call, write data mapping logic, and handle errors.

Without writing these user stories down, you might build a technically perfect dashboard that pulls all the metrics... but displays campaign IDs like “12847” instead of “Holiday Sale - December Promotion.”

Technically correct, functionally useless.

At Modular, our Solution Architects live at the intersection of lifecycle team needs and technical implementation. User stories bridge those two worlds. They force us to think like end users before we think like developers, which means we build solutions that actually solve problems instead of just demonstrating technical capability.

Switching between marketing platforms is hard enough — but half the battle is just figuring out what everything is called. One tool’s “Campaign” is another’s “Broadcast,” and the thing Klaviyo calls a “Flow” might be a “Journey” or a “Canvas” somewhere else.

Same thing, different name.

After managing more platform migrations than I can count during my startup years — and even more after moving into the lifecycle marketing agency world — I’ve learned that terminology is one of the many onboarding hurdles teams face. Whether you’re migrating, collaborating across teams, or just learning a new tool, inconsistent nomenclature slows everyone down.

That’s why we put together this simple translation guide to help you decode the core concepts across Iterable, Klaviyo, Braze, HubSpot, Customer.io, and SFMC. Let’s break it down:

Common “Entities”, Explained.

For lack of a better word, let’s refer to each term we’re going to describe as an “entity” within a marketing platform. Before we dive into the matrix, let’s go over the simple definitions of the most important types of entities:

Blast vs. Trigger Messages

Blast: A one‑time message — often scheduled in advance — sent to a group of people. It can be email, SMS, push, or another channel.

Trigger: An automated message, triggered by an API call or an automation entity in the platform.

Automations

These are automated message sequences that react to a trigger (like a signup or purchase). They may include delays, filters, branching logic, and multiple message types.

Templates

Templates hold your design and content. They can be reused for blast messages or automations.

Snippets

Small pieces of reusable content, like footers or product blocks, that you can use inside templates.

Custom Objects

These hold structured data — like product details, locations, members, promo codes, and more. Some platforms store this inside the tool, while others let you connect an external data feed.

Lists

• Lists: Usually static — they stay the same unless you manually change them.

• Segments: Usually dynamic — people enter or leave automatically based on rules.

Message Channels

Platforms support different message types. Common channels include:

• Email: “Electronic mail”. Look, if you don’t know this one by now — you might just be a time traveller from the distant past.

• SMS/MMS: “Short Messaging Service” or “Multimedia Messaging Service”, a.k.a. Text Messages.

• Push Notifications: These are the little badges and notifications from mobile apps that appear on your phone screen.

• In‑app Messages: In most cases, this refers to overlays and modals in a mobile application. This typically does not include overlays and modals on a website.

• Web Push Notifications: These are little badges that appear in your desktop/laptop web browsers. You’ll often find these opt-in messages on news websites. They typically only work with Chrome and Firefox web browsers.

• Embedded Content: Native-looking content that appears in a web application or a mobile application that is controlled by a marketing platform (rather than directly in the application code).

• WhatsApp: An messaging service that uses WiFi and Internet to send communications, rather than a traditional phone network.

Entity Name Matrix

Email authentication is about to become more critical than ever. With new standards rolling out in 2026, businesses need to take a closer look at their DMARC policies to maintain email deliverability and protect their brand reputation.

Understanding DMARC Policies

Most organizations currently have their DMARC policy set to “none.” This setting, indicated by p=none in your DNS record, allows all emails that claim to be from your domain to pass through, even if they fail SPF and DKIM authentication checks. While these failed messages do generate DMARC reports sent to your designated email address, many organizations set up this monitoring and then forget about it.

The Three DMARC Policy Levels

None (p=none): Everything passes through regardless of authentication status. You’ll receive weekly reports about failed authentications, but no emails are blocked.

Quarantine (p=quarantine): Emails that fail authentication checks are treated with suspicion by receiving servers. These messages typically end up in spam or junk folders rather than being rejected outright.

Reject (p=reject): Failed authentication checks result in complete rejection. These emails never reach the recipient’s inbox and will show up as bounces in your email metrics.

Why 2026 Changes Everything

Email authentication requirements have been tightening since 2024, when Google, Yahoo, and Microsoft began enforcing stricter standards for bulk email senders (those sending 5,000+ emails per day). By 2026, these requirements have become the expected baseline for all serious email senders. Organizations with stronger authentication postures—particularly those with DMARC policies set to at least quarantine—are seeing better email deliverability and enhanced sender reputation.

Think of DKIM as your domain’s cryptographic signature. While SPF verifies that emails come from authorized IP addresses, DKIM adds a digital signature that proves the email hasn’t been tampered with in transit and genuinely originates from your domain.

Email providers increasingly favor senders whose DMARC policy is set to at least quarantine, recognizing them as organizations actively fighting spoofing and phishing attempts.

How Email Authentication Works

Understanding email’s journey helps explain why these policies matter. When you send an email, it doesn’t go directly to your recipient. Instead, it travels through multiple mail servers—digital post offices that sort, screen, and check your authentication records at every step. These servers analyze content, subject lines, and authentication credentials to determine whether messages are legitimate or spam.

Key Points:

• SPF = IP Address authorization (”Is this IP address allowed to send from this domain?”)

• DKIM = Message integrity with cryptographic signature (”Has this email been tampered with in transit?”)

• DMARC = Policy enforcement (”What happens if SPF/DKIM fail?”) + alignment with the visible “From” address

Your DMARC record signals to these servers how to handle suspicious messages claiming to be from your domain. With a “none” policy, servers flag suspicious emails but let them through. With “quarantine,” they route them to spam folders. With “reject,” they block them entirely.

Making the Switch Safely

Here’s the recommended approach for updating your DMARC policy:

Start by monitoring your current DMARC reports for about a week. Make sure everything being flagged looks correct and that all legitimate emails are passing authentication checks. Only then should you switch from p=none to p=quarantine.

Don’t rush to p=reject. Without proper monitoring, you risk blocking legitimate emails from various parts of your organization—invoices from finance, contract renewals from legal, campaigns from marketing, and more. Any team that sends email on your behalf needs to be properly authenticated and aligned with your SPF and DKIM records.

Modular recommends staying at the quarantine level until you’re absolutely certain all legitimate services are authenticated and not failing verification. Moving to reject requires significant time and effort to ensure nothing important gets blocked.

Taking Action

The key takeaway: if your DMARC policy is currently set to “none,” upgrading to “quarantine” in 2026 is strongly recommended. This change will improve your email deliverability and sender reputation as industry standards continue to tighten, while still giving you the flexibility to monitor and adjust as needed.

The shift toward stricter email authentication is an ongoing industry evolution. Email providers have been gradually tightening enforcement since 2024, and by 2026, strong authentication has become baseline infrastructure for reliable email delivery.

Organizations that proactively improve their authentication posture will maintain better deliverability and protect their brand reputation in an increasingly security-conscious email ecosystem.

At Modular, we’ve consistently recommended moving away from image-based emails in favor of HTML-first designs. A recent Gmail update underscores why this approach is more important than ever.

Promotions tab annotations: an overview

Gmail’s Promotions tab supports dynamic modules called annotations, which allow brands to showcase product images, deals, and key details directly in the inbox preview — without the recipient even opening the email.

These annotations are typically coded with structured markup (AMP for Email). However, Gmail doesn’t always rely solely on markup anymore.

Annotations also don’t appear for every recipient. Gmail displays them selectively based on factors like sender reputation, content quality, and inbox density. In our experience, annotations surface for a small portion of recipients — often around one-third — though the exact percentage varies.

Because of this, annotations should be seen as a visibility boost, not a guaranteed placement, and are most effective when paired with HTML-based email builds and deliberate annotation coding.

Gmail’s “Automatic Extraction”

Google recently introduced a process known as Automatic Extraction, where Gmail uses AI to scan promotional emails and extract elements that resemble product content — such as images, prices, or offers. These extracted elements may then be surfaced as annotations, even when a brand hasn’t coded them.

This means Gmail is effectively auto-generating annotations from your email content.

In practice, Gmail’s AI appears to favor simple, product-like images. More complex slices — such as those that combine multiple products, embedded text, or CTA buttons — often don’t register as a single product image and may be ignored. As a result, Gmail may instead surface a less relevant image, such as a small footer icon, instead of the intended hero product.

Real example: In the screenshot below, Gmail ignored promotional slices containing multiple offers and instead surfaced two simple footer icons as annotations.

The above screenshot is from an image-based email with slices. Gmail passed over the slices, which contained multiple products, CTA buttons, and promotional text and instead surfaced icons in the footer.

Does this impact my brand?

Automatic Extraction can potentially affect any brand. However, those still using image-based email builds — such as legacy templates or sliced creative — are most likely to see negative impacts, since Gmail’s AI may misinterpret which image best represents the product.

How to adapt

To ensure your brand has more control over what Gmail displays, Modular recommends:

• Transition to HTML builds (or at least hybrid, drag-and-drop approaches).

• Add AMP annotations if you want to guarantee that specific products or promotions are highlighted (requires HTML development resources).

At Modular, we have deep expertise in both HTML design systems and AMP implementation. If you’d like to safeguard your campaigns from Gmail’s Automatic Extraction — and take advantage of annotations to boost visibility — we’re ready to help. Visit modularmarketing.com to connect with us.

AI tech is already changing a lot of professions, not least of which is CRM and lifecycle marketing. Like so many other software companies, the marketing automation platforms that brands use to send email, SMS, and in-app messages are in a heated race to roll out AI tools and features for their users.

Such a wide variety of options on so many platforms can be more overwhelming than a Cheesecake Factory menu. And similarly, the results can be a mixed bag. So let’s break them down, explainer style. (Yes, I’m a sucker for Vox’s “—Explained” articles.)

Iterable

Iterable has been hard at work rounding out its self-titled “AI Suite” of tools available to its users, and the results have the potential to be highly impactful for marketing teams. Let’s take a look:

Journey Assist

‍What it is: Journey Assist is probably our favorite one of Iterable’s out-of-the-box generative AI features. Think of it like a ChatGPT that will literally create and organize a journey map for you.

How to use it:

• Journey Assist is great for creating journey outlines and combatting Blank Page Syndrome. Tell the prompt you want an abandoned cart flow and within seconds you’ll get the structure you need to get started.

• Journey Assist is great at adding clarifying titles to each journey node, so you know the intention behind each step of the workflow.

• Journey Assist also has several preset prompts to help you get started, which means you might not even have to add in a prompt. Now, this mostly reduces Blank Page “scaries,” but it is still an extremely valuable generative AI tool within the Iterable platform.
  

Things to remember:

• As with all AI features, the input matters most. Writing a descriptive, specific prompt will give you a better result.

• Journey assist isn’t the best at selecting a trigger event, so you’ll still need to understand your custom events and trigger options to set up the flow in the best way..

‍

Channel Optimization

What it is: Channel Optimization is a node that determines which send channel (Email, SMS, In-app, Push, etc.) would be optimal for a particular message step in a given journey, based on the user’s message engagement history.

How to use it: In our opinion, this is a feature most brands miss simply because they’re not used to having the option, and we think it not only helps boost engagement, but also reduces the complexity of multichannel Journeys. Use it by dragging the Channel Optimization node from the Journey sidebar into your workflow map.

‍

Next Best Action

‍What it is: This feature is one of the most exciting use cases we’ve seen come out of Iterable lately. Something we’ve experienced as marketers throughout our careers, and as consultants working with teams, is a starting point of action that indicates what the next step should be to improve a message or journey.

Marketers are often so involved in the day-to-day of their workflows that they have a hard time seeing the “forest through the trees” in terms of their overarching strategic initiatives.

How to use it: Next Best Action points you (the marketer) in a direction, and you can then decide if you agree or disagree. It’s hugely impactful for small lifecycle teams because it empowers them with a simplified decision tree, which allows them to take quicker and more decisive action.

‍

Predictive Goals

What it is: Modular has been particularly impressed with Iterable’s efforts on Predictive Goals. While this feature requires a significant amount of data (minimum 6 months), it can help determine who in your audience is most likely to help you achieve your goals, which makes segmentation that much more methodical and meaningful.

Another really important aspect of this feature is Iterable’s willingness to allow the AI to explain how it reached a conclusion about its audience recommendations, which helps streamline and clarify AI audits.

A note: You’ll notice this theme throughout the article: AI is only as good as the data it receives. A disorganized marketing environment with confusing, undocumented, or redundant events can be counterproductive to marketing efforts as a whole, and especially for AI. Take the time to reduce technical debt on the marketing team before implementing this feature.

Frequency Optimization

What it is: This is an important feature from Iterable that gives AI the power to cap (on a personalized basis) the number of email, SMS, and push notifications each user receives, based on past engagement data (i.e. opens and clicks).

How to use it: Let Frequency Optimization choose a personalized cap for the number of email, SMS, and push notifications you send to each user in an Iterable project, so each user gets the right number of messages for each message channel and type.

‍

Send Time Optimization

What it is: Send Time Optimization (STO) is another feature that is more “algorithmic” than “AI”, but this feature attempts to determine the best time of day to send a message per recipient by analyzing historical engagement data.

The catch? You need historical data.

How to use it: Modular’s recommendation is to first focus on generating that historical data of user engagement, then run several A/B experiments for STO to find statistically significant differences between using the feature vs. scheduling standard sends.

This feature is also best suited for automated journeys as blast messages are typically more urgent and time sensitive for contacts.

‍

Brand Affinity™

What it is: Brand Affinity at Iterable is a score based on a user’s open and click engagements in the platform.

How to use it: Use Brand Affinity to identify actively engaged users (i.e. “loyal” contacts), as well as segment users who could either use a brief message quarantine, or perhaps a different communications approach.

‍

Copy Assist

What it is: Copy assist is a generative AI feature that gives marketers new ideas for content like subject lines and preheader text.

How to use it: AI-generated content is typically very general and “sales-y” (i.e. not great), so we recommend using this feature as a starting point, rather than a finished output.

Braze

Braze is another automation powerhouse that has been making strides in AI lately. One thing to note about Braze’s AI suite is that, outside of the tools themselves, the platform has excellent documentation on each of its AI features, including potential use cases to make it easier to decide how you want to adopt it.

Intelligence Suite

Intelligent Timing

What it is: Intelligent Timing determines when a user is mostly likely to open or click on a message, then holds the send of a given campaign until that time – making it easier for you to know that you’re optimizing for engagement.

How to use it: Use this feature for sending recurring campaigns that aren’t time sensitive, automating campaigns with users from multiple time zones, or messaging your most engaged users.

Intelligent Channel

What it is: Braze’s Intelligent Channel feature automatically sends users messaging through the channel that has the highest likelihood of engagement – for that particular user.

How to use it: Most brands don’t use this feature out of old habits. We think it not only helps boost engagement, but also reduces the complexity of multichannel Canvases. We recommend testing this feature in your next Canvas automation.

Intelligent Selection

What it is: Intelligent Selection regularly analyzes the metrics of a given Canvas or campaign experiment that’s running and will automatically adjust the audience size for each variant based on user engagement.

How to use it: This is a great way to have more confidence in your testing, and to get results faster than a typical A/B experiment. Best for repeated campaign sends and triggered messages, rather than one-off promotions and announcements.

‍

Predictive Suite

Predictive Events

What it is: “Predictive Events” as a feature name can be a little confusing, but this feature aims to highlight which of your users are most likely to trigger a particular event that you specify ahead of time (i.e. a purchase). Once you set a prediction, users are scored from zero to 100 based on their likelihood of completing that event.

How to use it: Segment and message users according to your predictive events goals to drive them to their next action.

Again, we need to shout out Braze’s documentation on these features, which is full of how-to instructions and use case recommendations.

‍

Predictive Churn

What it is: Similar to Predictive Events, Predictive Churn identifies segments of users who are most likely to churn.

How to use it: If you have a robust ecosystem but struggle to identify points of churn, this feature is a great addition to your toolstack and can help you hyperfocus on retention.

‍

Generative AI

AI Liquid Assistant

What it is: Braze’s AI Liquid Assistant helps you generate personalized message content, logic functions, and more from a simple prompt, even if you’re not a Liquid expert.

Templating languages can be difficult to learn, and often have weird quirks. For example, Braze’s version of Liquid is slightly different than Shopify’s, or Customer.io. Iterable’s version of Handlebars varies slightly from the original Git repository.

Brazes Liquid assistant explains the code it outputs, so it effectively teaches you as it helps you.

How to use it: One of the most practical uses of generative AI is a bot dedicated to helping marketers write better templating code. In fact, Modular started creating custom GPTs for templating languages like Handlebars (Iterable), Liquid (Braze, Customer.io), and Django (Klaviyo) as soon as custom AI agents were made available.

But Braze is a step ahead of the game by offering one in-house. We can’t overstate the importance of this.

‍

AI Content QA

What it is: Braze offers an AI Content QA feature that checks your message content for spelling and grammar errors, offensive language, tone, and more. While offensive language and tone are interesting features, we at Modular think the most valuable checks will be for spelling and grammar, as well as accidental content (i.e. extra code, Liquid errors, etc.).

We see a lot of value in a feature like this. In fact, we are building our own AI-powered QA tool, called FlowProof, that optimizes last-mile proof checks for email teams –– all from the simple comfort of one Slack channel.

‍

AI Copywriting Assistant

What it is: Braze offers a basic AI-powered copywriting assistant to add content to your messages. This can help reduce the effects of blank page syndrome, and is particularly helpful when working from a pre-designed template instead of a copy-first approach.

How to use it: Our experience at Modular with AI-powered copywriting is that it’s about as good as a junior intern –– it puts words on a page that you most likely completely rewrite, but it’s a better starting point than zero.

AI-generated copy also tends to have a particular cadence and “dialect”. It’s hard to describe, but it’s just not quite… human. Use with prudence.

‍

AI Image Generator

What it is: Braze’s AI Image Generator taps into the power of OpenAI’s DALL-E 3 engine to create images from AI prompts.

How to use it: at Modular, we have yet to see a realistic and effective use of AI imagery in marketing efforts. As we’ve noted previously about copywriting, AI-generated creative content tends to have its own “dialect”, so-to-speak, which can leave readers and viewers somewhere in the uncanny valley. Use with caution.

Klaviyo

Insights

Personalized Product Feeds

What it is: One extremely cool feature from Klayviyo’s AI is the ability to create a personalized product feed that surfaces product to a user based on what they are most likely to engage with, as determined by AI.

Many platforms require complex logic, templating code, and maintenance to determine potential “related items” that display to customers and encourage upsells. Klaviyo’s feature, however, removes the need for that.

How to use it: Introduce personalized product feeds as an A/B experiment and test their conversion rates against your existing emails, perhaps starting with a high-engagement flow like an abandoned cart series.

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Industry-specific benchmarks

What it is: This feature is incredibly useful because it helps marketing professionals understand how their efforts line up against industry standards.

How to use it: Often marketing professionals work in a silo of their own company metrics. Use this feature to compare your metrics to real-time industry benchmarks when analyzing the health and success of your marketing ecosystem.

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Generative AI

Flows AI

What it is: Klaviyo’s AI will generate a journey map based on a prompt input. Flows AI is great for creating automation outlines and combatting Blank Page Syndrome.

How to use it: Tell the prompt you want an abandoned cart flow and within seconds you’ll get the structure you need to get started.

Segments AI

What it is: Klaviyo allows users to create a prompt to build a dynamic segment, then its AI will go ahead and build that segment.

How to use it: Our experience at Modular is that AI models are typically not familiar enough with your data schema to build reliable segments, so use this feature with caution and always double check the output.

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Message Content AI

What it is: Utilize AI to create first-draft subject lines, pre-header text, email & SMS content, as well as inbound SMS replies.

How to use it: Again, our experience at Modular with AI-powered copywriting is that it’s best for first-drafts –– it puts words on a page that you most likely completely rewrite, but it’s a better starting point than zero.

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Optimization

Email IP & Domain Warming + Reputation Repair

What it is: At Modular, we handle a lot of IP warmups and platform onboarding engagements. One of the most useful AI tools we see from Klaviyo is a “Guided Warming” feature that allows you to warm up a new domain and IP utilizing AI to analyze user engagement and determine send size, audience, and segmentation so you can take the guesswork out of your migration.

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Another hero feature in this suite is Klaviyo’s Reputation Repair AI. When your sending reputation is on the outs, this feature will give you a customized repair plan to improve your deliverability.

Customer.io

Customer.io’s AI features are still experimental, but you can enable them in your account through Experimental Features (see how here).

Generative AI

What it is: Customer.io’s Generative AI feature can be used to generate message content and liquid expressions. As always, a good prompt begets a good response. At Modular, we’re excited to see what else Customer.io will bring to the AI table.

Imagine this: Your CEO is on the phone, and she wants to know why her company’s latest email send arrived with the following disclaimer: “This message cannot be summarized.”

When Apple Intelligence officially rolls out in a month, a lot of marketers at small and mid-sized DTC brands that still use image-based emails are going to be scrambling to get up to speed on email development best practices.

But let’s back up for a minute. Last year, I wrote about why a HTML-first approach to email was superior in every way. Now I’d like to rehash the subject from a new perspective.

AI technology has changed dramatically over the past 12 months, and so have email development norms. But the fact remains: HTML-first emails still reign supreme in this industry. Not only for their flexibility around design, device compatibility, and dynamic features (looking at you, AMP), but also now because they play nice with AI features.

And we know there will be many more of those on the horizon.

Artificial Intelligence Only Increases the Need for HTML-first Emails

Not long ago, Apple announced its collaboration with Open AI to offer generative AI features to its customers. One of those features is an AI-produced preview of your emails (Google’s Gemini offers the same for certain business customers). The AI engine reviews the subject line, the preheader text, and the email body to produce a quick-look at the email content before the user even opens the message.

Email-savvy Apple Mail users were quick to dive into the practical application of this feature, and the results did not disappoint — depending on your point of view, that is.

The AI feature requires content to review and summarize, and the content it receives from the mail client is essentially unrendered HTML. It’s not loading email images and interpreting what’s on them; rather, the AI is looking at the raw code of the email that was sent and trying to generate an overview based on the content there.

Image-based emails in particular lack readable content, which prevents the AI from producing an overview and therefore throws an error message: “This message is too short to summarize.“ Here at Modular, our own testing also found significant discrepancies between the message content and the AI reviews (follow us on LinkedIn page to see the results as we start posting them).

This is just more evidence that marketing teams really must ditch image-based email building, and design teams need to get onboard with email design best practices, or give the marketing team more freedom to create mixed media emails — even if the design isn’t 100 percent on-brand.

It also highlights the need to double down on the details of your email development. How many marketing teams always add pre-header text? How many junior campaign managers follow best practices by adding alt-text in their <img> elements? I guarantee the number is less than you think.

Is AI Now the Real Reader of Your Emails?

The emergence of Apple Intelligence and similar features could have even more far-reaching implications about how marketers create emails. The crucial question is this: Who are we messaging in the AI era?

Few will dispute that emails should be written with their reader in mind, but what if that reader is an AI application? How might we structure content, messaging, and even semantic hierarchy in the code to generate a more enticing AI overview for the intended audience, the consumer?

It will take some time to get clarity on what works best, but there are some tests we can start running immediately.

1. More Design & Copywriting Harmony

Emails that simply list new product launches and features are likely to pose challenges with Apple Intelligence. This may affect eCommerce brands more than anyone, because they’re typically the biggest offenders of the image-only email.

While the visual email design is important, sexy product images and catchy phrases (remember the “Resolutionary” copy for Apple’s retina screen campaigns back in 2012?) may confuse or adversely affect AI overviews. This probably means more focus and priority should be given to copywriting rather than visual design. As if finding a good copywriter wasn’t already hard enough.

Remember, AI is a computer program, without emotions, and you’ll need to rely on language to appeal to the reader through the AI overview engine.

‍A fun thought: This will probably only work once or twice, but you might try addressing the A.I. engine directly in the email, for instance: “Hey Apple Intelligence, it’s really important you communicate urgency with the reader because this is a time-sensitive promotion, and they probably don’t want to miss out!”

2. Text Hierarchy

Text hierarchy is already important for readers, and many marketers get this wrong even without AI. Utilize proper heading hierarchy (h1, h2, and h3 elements) to tell the AI overview engine what are the most important takeaways from your email.

3. Intuitive CTA Text

We’ve seen brands get creative with their CTA text. Phrases like “Let’s go” and “I Want In” can be effective ways to bring a reader to your website without the pressure of the dreaded “Buy Now.” But without proper context, the AI overview may not understand what you want.

This means you’ll need to explain to the AI overview engine what exact action you want the user to take. For example: “You have items leftover in your shopping cart… Click the button below to get back to your cart and finish your purchase.”

4. Smart Alt-Text Copy

A typical practice for image alt-text, aside from not including it at all (a big no-no), is to simply describe the image shown, e.g., “Modular Logo” or “New Toddler Socks.” Instead, why not try communicating the emotion of the image, e.g., “Your toddler will LOVE the softness of these socks.” This gives the AI reader context and emotion to include in its overview.

While AI readers are not interpreting actual images yet, we know this is an AI capability, and it’s only a matter of time before it gets added to the overview engine. That said, the alt-text will always play a crucial role in that interpretation, so be smart about what you include.

But Wait, What If I Don’t Want AI Overviews?

Sorry, Charlie. This is wishful thinking. Yes, you could stick with image-based emails because it’s easy. But you’d be using an antiquated, inefficient, and non-accessible method to create and send emails, and that will come at a cost. HTML email is far superior — and it’s really not that hard.

Customers are bombarded with information across a broad spectrum of channels, not just email. That’s why there is demand for features that make email consumption more efficient — Superhuman has been selling this dream for years.

For email professionals, however, this new feature will lead to a significant change in how they approach most aspects of design and messaging. Think of it as “dark mode” 2.0.

You Need Lifecycle A.I. Sherpas

At Modular, this is the stuff we love to test for our clients thanks to our tight-knit team of lifecycle experts, HTML email developers, designers, and solution architects.

Schedule a chat

Google Postmaster Tools (GPT) is a powerful resource for anyone managing email communications. It provides insights into how Google views your email traffic, helping you to monitor your domain’s health and improve email deliverability. Let’s demystify the process of setting up and utilizing Google Postmaster Tools:

Understanding Google Postmaster Tools

Google Postmaster Tools is a free service offered by Google that allows domain owners to gain visibility into how their emails are being handled by Gmail. It tracks various metrics like spam rates, domain reputation, and feedback from Gmail users. This information is crucial in understanding and rectifying issues that might affect your email deliverability.

Getting Started with Setup

To set up GPT, you may need to collaborate with your IT department, engineering team, or consult someone else in a technical role, like a System Administrator. Begin by visiting the Google Postmaster Tools website and sign in with a Google account. Add your domain (the domain you send emails from) to start the process.

Verifying Your Domain

Verification is a critical step in ensuring that you own the domain. Google Postmaster Tools will provide a DNS TXT or CNAME record. You or your IT team need to add this record to your domain’s DNS configuration. Once done, verify the domain in Google Postmaster Tools. This process proves to Google that you’re the legitimate owner of the domain.

Postmaster Tools Features and Dashboard

Google Postmaster Tools offers various features, including:

• IP Reputation: Understand how Gmail views the IPs sending emails on your behalf.

• Domain Reputation: Track how your domain is perceived by Gmail, which directly affects your email deliverability.

• Feedback Loop: If you’re part of Gmail’s Feedback Loop (FBL) program, this shows data about spam complaints from Gmail users. Spend time navigating the dashboard to understand the wealth of data available to you.

For busy marketing professionals, it’s vital to integrate GPT into your regular schedule. Set aside a weekly or bi-weekly slot to review your metrics. This practice helps in early identification of potential issues and maintaining a healthy email program.

‍Responding to Insights and Flags

If GPT highlights issues like a poor domain reputation or high spam rates, take immediate action. This might involve reviewing your email lists, assessing email content, or even consulting with your email service provider. Proactive management is key to resolving these issues promptly.

Google Postmaster Tools is an invaluable asset for ensuring your emails reach your audience effectively. By regularly monitoring and responding to the insights provided, you can significantly improve your email engagement and deliverability.

Need Extra Help?

Looking for help setting up or managing Google Postmaster Tools or solving other deliverability problems? We can help! Reach out to our team at hello@moduarmarketing.co to schedule time for a call.

Do I Have a DMARC Record Published?

Do you already have a DMARC Record/Policy setup? Check here ➝

• Navigate to MXToolbox.com and enter your sender subdomain (i.e. email.mycomany.com ) or your sender root domain (e.g. mycompany.com )

• Click the MX Lookup submit button

• Scroll to the table that mentions DMARC records to verify whether or not your record is published.

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Note: A DMARC record is different than a DMARC policy. Policies are attributes of a DMARC record and it is recommended that they are initially set to “none”.

What is DMARC?

DMARC stands for Domain-based Message Authentication, Reporting, and Conformance. It’s a way to make sure that emails sent from your domain are legitimate and to tell email servers how to handle emails that aren’t. Think of it as a security guard for your emails.

What Makes Up a DMARC Record?

A DMARC record is a TXT record that lives on your Domain Name Servers. It contains several important attributes that tell email servers about your sender profile, your set of rules for how they should treat emails that do not appear to be from your domain (the “policy), and where to send reports if an email fails a DMARC check (”ruf” and “rua”).

How to Create DMARC Record

1. DMARC records are simple TXT records that follow the syntax found below. Create your own by copying the record below and replacing the reporting emails with your own.
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2. Place the DMARC record on your root domain (i.e. mydomain.com ), even if you send from a subdomain (i.e. mail.mydomain.com ). Your subdomain will inherit any policies you set up in the root domain.

Understanding DMARC Field Attributes

Below are the different attributes in a DMARC record and what they represent:

v: Denotes the record type – this is a DMARC record.

ruf: Tells email servers where to send reports of individual DMARC check failures.

rua: Tells email servers where to send aggregate reports of DMARC checks.

p: Denotes the rejection policy for emails that fail DMARC checks on the root domain.

sp: Denotes the rejection policy for emails that fail DMARC checks on subdomains.

Note: Individual subdomains can have their own DMARC policies that will override the root domain policy. If you’re just getting started with DMARC, stick to just the one root domain record.

DMARC Policy Meanings

There are three main types of DMARC policies:

• none: This tells receiving email servers to not do anything special with emails that fail DMARC checks. It’s like saying, “Just keep an eye on things and let me know.”

• quarantine: This tells servers to put emails that fail the check into the spam or junk folder. It’s like saying, “Put suspicious emails in a holding area.”

• reject: This tells servers to reject emails that fail DMARC. It’s like saying, “Don’t let suspicious emails in at all.”

DMARC Report Monitoring

Don’t fall asleep on your DMARC reports! Monitor the reporting you receive to the addresses you provided in your policy to make sure the emails that the DMARC failure reports denote should be rejected.

Once you are confident that DMARC checks are performing properly, you may update your policy to be more strict (”quarantine” or “reject”).

For the last several years, I have been a steady champion of drag-and-drop email builders. I’ve written several blog posts, numerous slack messages, and had countless discussions with others about why harnessing the power of drag-and-drop builders was the best way forward for non-technical email teams.

But now my position is shifting.

At Modular, we’ve had more opportunities to work with teams at large, global brands who deploy hundreds of thousands—even millions—of emails daily.

And as a marketing automation ecosystem grows in both size and complexity, the approach you take to tactical creation must evolve with that growth. That’s why we’ve shifted to focusing on HTML email development for larger ecosystems.

But we also created a hack that helps us get the best of both worlds for a company of any size. This is incredibly powerful because it brings the design sophistication of HTML to the ease and efficiency (and non technicality) of drag-and-drop.

‍Here’s how we did it: We created an email design and development system that allows us to build customized HTML emails and convert them into drag-and-drop modules.

How our email development system works:

1. Our designers work with brands to create a modular design system of email components. Think hero sections, spacers, product lists, headers, footers, etc.

2. Then, our developers take these designs and create HTML components that are compatible with a drag-and-drop editor.

3. And viola – either the Modular team or a brand’s marketing team can utilize the custom components in this system to visually churn out pixel-perfect, design compliant, pre-tested emails with unique content.

The result is that email messages are more unique and engaging, marketing teams are not overwhelmed with custom development and QA, and the end user experience complies with a brand’s design standards 100 percent of the time.

So Now What?

I get that some teams do not have access to HTML developers nor do they have the time or experience to stand up a modular system like I’ve described above. That’s why I’ve outlined the pros and cons of HTML and drag-and-drop below — so you can start by getting a handle on the differences compared to what you’re doing today.

‍RELATED: Email Design tips and best practices (updated 2023). Share these with your design team to streamline your asset development process.‍

Pros vs Cons: HTML Email Development‍‍

Pros of Developing Emails in HTML

• Complete Control: Offers precise control over every aspect of the email design, allowing for custom and unique layouts and features, as well as pixel-perfect branded emails.

• Optimized Performance: Emails can be coded to be lightweight and efficient, ensuring they load quickly and consistently.

• Custom Interactivity: Advanced features, like hover effects or custom animations, can be implemented.

• Complex Personalization: Custom-coded emails can be seamlessly integrated with a variety of systems and tools, without being confined to a specific platform’s ecosystem.

• Easier Troubleshooting: HTML code can easily be reviewed and errors will point to specific lines of code. Since you have 100 percent visibility into how the email is put together, pinpointing problems and fixing them is faster and easier.

Cons of Developing Emails in HTML

• Requires Technical Skill: Not everyone has the expertise to code emails, and training or hiring experts can be costly.

• Compatibility Errors: Inexperienced developers may not understand what kinds of elements and styles display differently across different email clients and devices.

• Maintenance: As email client standards and practices evolve, manually coded emails might need periodic updates to remain effective and compatible.

Pros vs Cons: Drag-and-Drop Email Editors

Pros of Using Drag-and-Drop Editors

• User-Friendly: Aimed at users of all skill levels, especially those without technical knowledge.

• Quick Turnaround: Ideal for businesses that need to deploy simple emails rapidly.

• Client/Device Compatibility: Most drag-and-drop editors provide modules that are already optimized for multiple devices and email clients, reducing the risk of display issues.

• No Coding Knowledge Required: Marketers typically do not need technical expertise to work with a drag-and-drop editor; however, the initial template build is often tedious.

Cons of Using Drag-and-Drop Editors

• Limited Customization: Advanced and unique designs are typically not possible due to the constraints of the editor. You will not get pixel perfection in a drag-and-drop editor.

• Bloated Email Code: Drag-and-drop editors generate excessive and redundant code which can affect email performance or compatibility.

• Over-reliance & Troubleshooting: Marketers who only work within drag-and-drop editors will lack a deeper understanding of email mechanics, thus troubleshooting issues will be harder.

• Generic Designs: Because many brands use similar templates, there’s a risk of emails looking generic or too similar to competitors. e.g., DTC emails in Klaviyo.

• Communication With Designers: This is a big one. Design teams often do not know or understand the limitations of drag-and-drop editors, leading to internal confusion and disagreement. The stronger the brand guidelines, the bigger the case for HTML.

• Not Built for Personalized Customer Journeys: As your customer experience becomes more personalized and sophisticated, you will find it difficult to include dynamic personalization logic and merge parameters in drag-and-drop editors. It can be done, but it requires more technical expertise from your marketers.

• At-Scale Management: When brands are dealing with hundreds of email templates in their ecosystem (or more), drag-and-drop editors become a hindrance. They can be slow to load and difficult to troubleshoot, leading to lost time and internal confusion.

Email design is a specialized discipline, one that not every digital designer has experience with. There are unique considerations – font compatibility and the limitations of email editors, to name two – that can present hurdles to designers new to email development.

Below we’ve outlined some of the high-level considerations for design teams that are newer to email.

General Considerations

Custom Fonts & Typography Styles

Email clients may not support web fonts, and they often substitute them with default fonts, which can affect the intended typography and branding. Designers often resort to using web-safe fonts to maintain consistency. Similarly, typography styles, like tracking and kerning, may not be customizable in code.

Client Compatibility

Different email clients have varying degrees of support for HTML and CSS standards. While some clients like Gmail and Apple Mail have robust support, others like older versions of Outlook may have limited support. This means that complex layouts, advanced styling, and interactivity may not work consistently across all clients.

Responsive Design

Responsiveness, which allows an email to adapt to different screen sizes, is challenging to achieve uniformly. What looks great on a desktop computer may not work well on a smartphone or tablet. Designers often use media queries to create responsive designs, but some email clients may not fully support them.

Image Blocking

Many email clients block images by default for security and privacy reasons. This can affect the visual impact of an email. Designers need to ensure that the message and call to action remain clear even if images are not displayed. Marketers must add “alt text” to the image data once it is inserted into the email to help account for this as well.

Dark Mode: Designers must consider dark mode in their designs. Nearly 80% of all users enable dark mode. Some email clients, like Apple Mail and Outlook, offer dark mode themes. Dark mode theme settings inverse the colors normally displayed in the emails, and each client has its own way of choosing and rendering that inverse color. Use a tool like Coolors Contrast Checker to ensure that your color scheme has enough contrast so that it is not affected by the inversion of colors using. Additionally, consider creating a white glow or thin outline around dark, transparent images, i.e. your logo.‍

Email Client-Specific Quirks

Different email clients have their quirks and rendering engines. For instance, Outlook relies on Microsoft Word for rendering, which can lead to inconsistent results, especially with complex designs.

Testing Challenges: Due to the vast number of email clients and devices, thoroughly testing an email design is challenging. Marketers should know which email clients are priorities for their audience (create a dynamic segment!) so they know which clients to defer too.

‍Limit of Control: The key challenge in email design is the limited control designers have over how emails will be displayed. Unlike web design, where standards are more consistent, email design must account for a wide range of variables and client-specific behaviors.

‍Drag-and-drop Design Guidelines

‍If you want to better understand drag-and-drop vs HTML email development and how this impacts design, check out this article.

‍Work Within The Row Structure‍

Drag-and-drop emails are built in rows, divided into predefined columns

Images cannot extend across two rows unless the image file is split into two. Avoid text boxes with rounded corners. Also avoid gradients and background images. These are not supported by all email clients.

Use Web Safe Fonts

Custom fonts are only supported by a very small portion of email clients, so they will not show up in most emails even if we add them. However, adding custom fonts is a process that requires engineering and development resources if they are not already set up, so it is generally best to avoid them.

Image File Types

In email marketing, marketers need to optimize for smaller file sizes in images. Typically, PNG works better for graphic images like logos, illustrations, and wordmarks. JPG works better for real-life photos and more complex images. Only PNG files may have transparent backgrounds.

GIF images are supported by email clients and are a great way to embed movement into otherwise static emails. GIFs can be large in file size, however, so a good rule of thumb is to keep them under 200kb.

Image Widths

‍For non-background images: Images placed within <img /> tags in HTML should be at least 2x their intended viewing size. This is due to how images appear on high-definition screens, like Retina Displays. Otherwise, they will appear blurry.

For background images: background images cannot be constrained to a desired size in email, so they must be uploaded in the final size you wish to display them in.

CTA Buttons

CTA buttons in the drag-and-drop editor have specific limitations as well.

• They support only solid-color or transparent backgrounds. They can have borders as well.

• There is no hover state.

• They cannot include background images or gradients.

• They do not support icons, but you may use text characters like “→”. These characters are not supported by all clients, however.

Pixel Perfection

Drag-and-drop editors are wonderful and powerful tools, but they often require compromise. Do not expect pixel perfection for a given design. Being flexible allows marketing teams to iterate and improve on their campaigns while still maintaining the essence of the brand.

Imagine a landscape where every team member, from seasoned executives to developers to new marketing hires, effortlessly navigates your CRM or marketing automation platform and understands what they’re looking at, making swift assessments and decisions about what to improve next.

An Enemy of High Performing Lifecycle Teams

At many companies, especially growth startups, this vision crumbles under the weight of haphazard naming conventions. This seemingly minor oversight is in fact a detrimental mistake, as the resulting inconsistencies wreak havoc on data clarity, campaign testing, team onboarding, and overall efficiency.

Naming conventions are key to a successful CRM and marketing automation strategy. If everything is named consistently, it will be much easier for marketing managers to find what they are looking for and make changes as needed. In this blog post, I’ll go over the importance of naming conventions in CRM and marketing automation, and give some tips on how to name campaigns, lists, and workflows in an organized way.

What is a Naming Convention?

Naming conventions are syntax norms and standards that you implement on your team to make your assets more human-readable.

To put it another way: naming conventions outline how you name a given asset.

Naming conventions should be:

• Easy to understand without context

• Simple to learn and adopt

• Versatile and applicable across multiple CRM elements

• Searchable in the absence of a foldering system

How to Choose a Naming Convention

There are a few factors you should consider when choosing a naming convention for your CRM:

The size of your team: If you have a large team, you’ll need a more complex naming convention to keep everyone on the same page. If you have a small team, you can get away with something simpler.

The number of CRM elements you’re using: If you’re only using a few CRM elements, you can get away with a simpler naming convention. If you’re using multiple CRM elements, you’ll need something more complex.

The level of detail you need: If you need to be able to search for assets by name, you’ll need a more detailed naming convention. If you just need to be able to identify an asset by its name, you can get away with something simpler.

Maintaining a Naming Convention

Regardless of the naming convention pattern or syntax you use, you need to get buy-in from your team and be ready to enforce the syntax from whenever you implement it, onward. This is why documentation is key to a successful naming convention*.*

Write it down, share, educate, enforce – this is how to maintain a naming convention once you’ve chosen one.

Tips for Naming Conventions

There is no one right way to set up a naming convention, but there are many pitfalls you can avoid. Try to incorporate some of these tips in your naming convention syntax:

1. Prepend the date to the name in this format: yyyy.MM.dd (four-digit year, two-digit month, two-digit day). This will help you sort objects in chronological order by listing A to Z or vice versa. We typically recommend adding dates to temporary lists (creation date) and blast sends (scheduled/send date). The periods help for readability but are not required.

2. Keep hierarchy in mind: Hierarchy in naming conventions helps with organization and readability. ****Start by including the broadest category in your convention, then get more and more specific. (i.e. 20220905 - Purchase - Holiday Discount 50% Off - High LTV Customers)

3. Be smart about punctuation: It may be hard to imagine at first, but the day will come when you, or someone on your team, will need to tab through campaigns in a file system or spreadsheet. Separate the major categories and words in your naming convention with periods (.) or hyphens (****) – pick one and stick with it. Separate related words and terms with spaces or underscores (_) – pick one and stick with it.

4. Name assets so that a team with little-to-no context can understand them: This means being as detailed as possible with as few words as possible. You also may create abbreviations (i.e. CV for “conversion”, RT for “retention”, etc.) as long as you document their meaning!

In email marketing there are generally two kinds of sends — there are journeys, which are automated lifecycle programs, and blasts, which are one-off emails usually sent on a schedule.

But there are instances when blasts can and should be automated. In this post I’ll explain when, why, and how we tackle automating blasts at Modular. And I’ll use a recent project for an app-based startup in the hospitality space as an example.

Sophisticated personalization can be challenging to automate. When it comes to blast campaigns, personalization is typically done at the level of segmentation: different content for different cohorts. The more cohorts there are, the more campaigns have to be built—and that’s where the custom automation comes in.

Lots of segmented emails, and fast

Our client needed to frequently send highly segmented sets of emails—up to 17—with a very short turnaround time (few hours).

At its most complex, the process of creating an audience, assigning an audience and conversion metrics, QA checking, and scheduling 17 different emails campaigns could take up to 3 hours to complete.

What tools we used

Complex marketing automation tends to be our sweet spot, so we have a number of tools that we draw on. Here’s what we went with in this case:

Airtable

Our client powered many of its internal processes with Airtable, a no-code database platform. We love Airtable’s ability to create a hosted JSON feed of data that can be accessed via RESTful API requests.

Iterable

This client used Iterable for all of its marketing automation. Iterable has a flexible and powerful API, and it’s possible for Iterable users to access external Data Feeds in JSON or XML format to dynamically insert data into messaging content.

Handlebars

Handlebars is a templating language utilized by Iterable. It allows developers to dynamically add content from the User Object, from Events, or from external Data Feeds and Catalogs into their messages. It also contains powerful functions such as “each” loops which greatly reduce production time and make emails more personalized and dynamic.

The Solution

The Modular team designed a system through which a user can identify information that needs to be sent in an Iterable campaign, then setup and schedule that campaign with no more than the click of a button. Here’s how it works:

1. Client data appears in an Airtable view that displays only qualifying data to be sent via Iterable.

2. The user clicks a button that says “Generate Campaign” in Airtable. Our automation does the rest.

3. Modular’s automation compiles the data provided by the Airtable database and sends it to an Iterable template, then creates a campaign and populates the content with the database information. The send segment is also determined by the Airtable data.

4. Our automation sets up and schedules the Iterable campaign.

5. Back in Airtable, our automation updates the status of each record to “Complete” so that it no longer shows up in the “To Send” view.

The Result

What was a 3 hour process of creating and scheduling campaigns became something that takes less than 3 minutes! This is a 98% reduction rate of time spent on each send. Even more important, this automation facilitates a more personalized customer experience even at the level of blast campaigns.‍

Does your company need help with complex marketing automation challenges? Modular has a team of experts in marketing automation, CRM, growth engineering, and lifecycle marketing.

Discover Modular