Our recent search for the latest in email marketing led us to Jessica Mirabelli, Digital Messaging Specialist at Bond Brand Loyalty—who served up three tales (two shareworthy, one cautionary) that put experience front and centre, both for consumers and for marketers.

Knowing her team currently designs, builds and/or deploys campaigns for 15+ brands – we’re glad Jess was able to narrow things down to a few examples that can resonate across the industry. Each of them showcases how optimizing lifecycle email can influence and extend the experience beyond transactional touchpoints, so let’s get to it!

Win #1: Redeeming for travel—and help along the way

Rewards programs and lifecycles go together like, well, pretty much anything that goes together, really. Any program, especially those based on redeeming points, can benefit from having well-mapped triggers going to work for them. In one brand’s case, a comprehensive communication strategy was already surpassing expectations. What led to the positive results? A focus on campaign engagements based on relevant customer journey touchpoints.

If you’re into specifics (we are, obviously), 1 of 5 members redeemed 5X more points than before the triggers were launched—and when it came to cardholders booking travel with their points, Jess and company saw an opportunity.

“Knowing we’d be reaching travellers when it matters was just the beginning,” she told us, “we had to pinpoint useful content, too, and unique ways to deliver it. The ‘what’ and ‘how’ are always just as important as the ‘when’.”

First, handy travel tips, combined with calculated content designed to reinforce the program’s key feature and benefits, hit your inbox post-booking. Then, timely look-aheads – scheduled according to your travel dates – take over with dynamic real-time content to help the brand make the most of the moment and stay with you throughout your travel journey.

Closer to your trip, with the goal once again being to show that the brand’s thinking of you – and to amp up your excitement – you receive an email reminder that your flight is just two days away. What’s packed inside? A checklist of travel essentials, as well as a live weather forecast for your destination. And to cap it all off, a day before your return, you get another checklist, along with a live look at what the weather’s supposed to be like once you return home.

No matter what mother nature has in store, members are left feeling valued and recognized.

Key takeaways:

Win #2: CTR (Convenience Through Registration) and beyond

Of course, you don’t have to have a full-blown program to be sending emails strategically. Say you have an event. And say email is one of your channels of choice for communicating with prospective guests/registered attendees. Now, step out of those hypotheticals and right into this real-life scenario that plays out for Bond every year.

See, every Spring marks a new launch event for The Loyalty Report, a Bond staple and the longest-standing and largest global study on customer engagement, loyalty attitudes, behaviour, drivers and disruption. 2019 marked the culmination of an annual effort to maximize the registration flow and keep one of the company’s calling cards top of mind.

In Jess’ words, “We’ve always sort of tinkered with how we should talk when it comes to events—and how often,” she noted, “this year we upped the cadence a bit, and thought a lot about how we could turn emails that are usually transactional, into key moments in the overall experience.”

That cadence makes up a lifecycle that’s built to expand the experience, while opening the door for engagement before and after the event.

Your Registration/Invitation arrives in your inbox complete with:

Your Weekly Reminders leading up to launch day build anticipation by featuring:

And last but not least, your Post-Event Communications empower you to:

In the end, Bond saw registrants confirm their attendance faster than any other year, and more surveys filled out than ever before.

Jess admitted the results have had a trickle-down effect within the company, since Bond engages an overall audience of more than a million through its email and campaign marketing. “It’s not just huge for us,” she asserted, “it gives us some tried and true best practices, and a solid foundation that allows us to confidently set up other brands for success, too.”

Key takeaways:

Myopic fail: Return to sender

Before we cast off here, we wanted to note: Subscribers may not have even realized these next events took place, so keep’em on the down low, ok? Kidding aside, Bond recently had to navigate some choppy waters after embarking on what’s usually an uneventful migration.

At first glance, everything seemed normal. It wasn’t until a few months after the migration that a deeper look into one campaign revealed a consistently large drop-off in opens for the entire lifecycle. Not just a couple of triggers, every email.

The problem turned out to be simple: A provider was blocking Bond’s domains and preventing the emails from being delivered. 

The solution? It ended up being fairly simple, too, but here’s what played out. Contact was immediately made with the provider to remove the block and correct the issue.

The issue itself served as a catalyst for the team to implement critical changes:

“It’s led us to a more fine-tuned process, for sure,” Jess admitted, “it’s even shown us how we can get our Decision Sciences team involved early and often, so we can paint a really clear picture when it comes to the data that matters to our clients.”

Key takeaways:

It was a pleasure having Jess share these email insights with us. Thanks to her, and to Bond, for putting the time in. We posted the link earlier, but if you want to know more about what they’ve got going on, you can check out the Bond website anytime.

Huge thanks to Zach Cosby, Associate Creative Director/Copywriter at Bond Brand Loyalty, for his contributions on this piece!

July has come and gone, August is here and before you know it September will be over, and Holiday commercials and emails will start dropping left and right. 

This is a busy time of the year for email marketers as they plan their holiday campaigns and end-of-year strategy. Spending countless hours preparing layouts, messaging, subject lines, etc. it’s easy for a very important part of the process to get lost in the chaos – email list hygiene.

Get all the inspiration you need to sleigh your holiday revenue goals. Download our lookbook: 9 Solutions (With Real-Life Examples!) to Retailers’ Biggest Holiday Email Headaches!

We’d like to focus on steps that are sometimes overlooked when planning holiday marketing campaigns. Take these measures to make sure your messages reach the inbox during the busiest time of the year. 

1. Start Growing Your List Early

If you’ve waited to grow your email lists for the holiday season, you’re already behind. If your goal is to drive the maximum sales at the end of the year, you should have started to grow your data months ago; you have some ground to catch up on! But avoid the temptation to cheat the system and buy email lists; nothing good comes out of a bought list. There could be hidden threats such as honeypots, spam traps, bots, screamers and much more in that data you just purchased.  (Read: 7 Reasons Why You Should Never Buy An Email List

2. Clean Your Data 

It’s imperative that you run your email data through email hygiene processes. Why?  Because email hygiene detects more harmful threats in your data, unlike verification. According to a report from The Relevancy Group, “ Real-time email verification is a necessary tactic to ensure that email addresses are valid, but it is an incomplete defense. To improve deliverability and suppress against multiple threats, marketers need to adopt verification and email hygiene.” 

Email verification is a great solution to detect bounces but it does little to guard against those threats such as spam traps, honeypots, moles, bots and much more that can tarnish your sender reputation and deliverability right as the holiday season ramps up.

3. Enrich Your Data

Today’s consumers expect personalized, relevant experiences. And to provide those, you need relevant data – usually lots of it. 

Research indicates 3% or more  of customer data becomes obsolete due to changing conditions. Customers move, get married, change names, and adapt to new lifestyles. 

Marketers are always in need of updated and accurate customer profile information. They can either obtain this information by searching for supplementary data or purchasing new data from other parties. The reliability of these options varies greatly, and it’s hard to guarantee that the information you have purchased is valid. If you need to enrich your data to fill in the missing or outdated consumer information, consider data appending

Data Appending is simply filling in the missing pieces of your data, completing the puzzle you’ve already started. As long as you have some sort of information such as an email, phone number, or name, there can be more added. This reveals the complete customer picture and essentially saves data that might otherwise have been lost or set aside.  

More About Data Appends and How They Affect Email Success

4.  Target Audience & List Segmentation 

Without segmentation, your engagement rates tend to suffer. Open rates usually decline, while unsubscribes tick up. It’s hard to keep emails relevant and engaging if you’re sending the same thing to everyone.

Segmenting your list based on demographics, behavioral history, and transactional history helps maximize with your content relevancy. According to Mailchimp, “segmenting your lists had open rates that were 14.37% higher, clicks that were 64.78% higher, and unsubscribe rates were 8.89% lower than people who don’t segment their lists”. 

List segmentation can drastically improve your email marketing campaigns. Your audience is not all the same, and you know that. So why target them all the same, if they’re completely different? 

If you want your email campaigns to be successful this holiday season, one of your first priorities should be email list hygiene. Clean, reliable data truly is one of the most important components of email marketing!

About the Author 

Jenna Devinney has been the Marketing Specialist at Webbula for 2 years. Her key responsibilities are social media, and content marketing, and has written dozens of articles in the data solutions space. Check out Webbula’s Intelligence report page to learn more about what Webbula has to offer. 

About Webbula 

Webbula is the undisputed industry leader in data quality technology. Our emailHygiene and Data Appending services mitigate delivery threats, enhance data lists for email campaigns and create actionable audiences for online ad serving. Webbula has a proven track record of helping our customers navigate hazardous data quality obstacles and increase their return on investment.

Our passion remains what it has been since day one, to provide the confidence and reliability that our customers have come to depend on. Webbula pioneered and perfected email hygiene, the ability to detect Spam Traps, and much more – all in pursuit of truth in data. We look forward to another decade of leading the way and of helping all of our customers succeed.

Machine learning is one of the most talked about “new” strategies and technologies in the industry today, but we often find that it is highly misunderstood — and many times, that’s our fault on the vendor side.

It’s our goal to clear up machine learning and decipher what it means for marketers and the amazing benefits it can provide on even a day-to-day basis.

Machine learning is simply a way to apply an algorithm on top of data to process and make decisions faster than what a single human can possibly accomplish.

Besides the misunderstanding of what it actually is, what keeps marketers from leveraging machine learning in email marketing? Here’s a few of the answers we hear across the country:

  1. Don’t have the right data to utilize.
  2. Data is “bad,” or in other words, it’s outdated, unclear, or flawed.
  3. No budget for machine learning technology to apply to tech stack.

If you’re experiencing any of these problems as well, you’re not alone!

One of the leading issues we hear marketers say about leveraging machine learning for email is that they have a data problem. No matter the size of the organization, small, medium or large, there’s a “data problem” in all of our businesses! We like to dig a little deeper and ask what the problem is. And we consistently hear there’s “bad” data, too much data, or not enough data to get started.  

Everyone — even Amazon — struggles with their data:

She’s a mom blogger, and a mother of 2 young boys. Apparently, she bought a toilet seat. And after completing her purchase, she started to get messages about buying more toilet seats or toilet seats that she may like! She bought a toilet seat out of necessity, not as a collector. So getting these types of messages from Amazon is not only annoying, but also just plain stupid.  

Others commented about their own woes with Amazon, getting messages about more burial urns, coffins, or even punch-down tools.

But it doesn’t have to be this way.

You can utilize machine learning for email without causing even more data woes, costing your budget an arm and a leg, or having to deal with infinitely complex tech stack integrations.

So where do you start?

It helps to think with the end in mind.

machine learning flow chart

Machine learning makes the complex, simple. The above illustration shows all the factors and components that go into applying machine learning to marketing.

But what’s important about this illustration is not all the factors and components, rather it’s the fact that machine learning does all the work for you. Machine learning helps ingest, process, and make sense of all your data. Whereas before you would spend time pulling and organizing raw data and then uploading to your marketing technology, machine learning completely eliminates that step for you, so you can focus on what’s most important.

This is the model we use at Cordial to help illustrate all the work that goes on behind the scenes that translate into actionable tactics you can put into place to become an email all-star.

Knowing what’s possible, here’s three ways you can use machine learning technology in real-world, applicable ways for your business.

1. Using machine learning for testing & optimization

Testing and optimization is one of those topics that everyone talks about, but no one actually does.

Why don’t marketers test and optimize messages more frequently? It can be time-consuming, inconclusive, and or near impossible with the technology you use today.

Testing messages doesn’t usually produce enough revenue results to justify the amount of effort that is put into creating the new content and campaigns. It’s all about results at the end of the day for each one of us. So, we thought about this process that marketers go through when initially rolling out machine learning to optimize messages to yield statistical significance — or in other words — results!

machine learning data

At Cordial, we take testing and optimization seriously. Which is why we worked to make it as easy as possible to leverage machine learning across subject lines, content, hero images, and promotional offers to continuously optimize towards the desired goal in your campaigns. The machine learning algorithm utilizes a method of testing called Thompson Sampling, which is based on an algorithm called Multi-Armed Bandit Theory.

But you don’t need to remember any of that — all you need to know is that the algorithm works to automatically optimize a message based on the best performing combination of factors.

2. Using machine learning for triggers & automations

Using machine learning for testing and optimization also directly applies to triggered and automated messages. You may have triggered automations like your welcome series, abandoned cart, or upsell series that haven’t been touched in months.

Because of the automated nature of these kind of messages, they make for the perfect message to use the testing and optimization machine learning technology above. Since these messages constantly go out, it’s paramount that these messages are optimized to perform as best as they can.

Not optimizing triggered automations is almost like leaving money on the table. Thanks to the application of machine learning to programmatically test and find the best performing variation of a message, you can easily test and optimize your triggered email automations to ensure they’re performing as best as they possibly can.

3. Using machine learning for product recommendations

Finally, product recommendations are one of the best ways to utilize machine learning. Product recommendations are a magical feature that can be a game-changer for your personalization efforts.

Cordial Recommendations uses machine-learning technology and predictive modeling to deliver product suggestions based on real-time customer interactions and behavior. Recommendations improve and adapt over time to increase opens, clicks, and purchases as more is learned about your customers.

Related: Machine learning is just one of several game-changing opportunities for email marketers. Read more on Four Steps To Becoming An Email All-Star

An Example: REVOLVE

REVOLVE migrated to Cordial after using a legacy ESP for years and uses the platform to send promotional and triggered messages to their customer base. Because of the gaps in their legacy tech they were unable to provide their customers with personalized or triggered messages, severely limiting their marketing efforts. It simply was impossible to scale personalization using the segmentation model they followed previously

Cordial enabled REVOLVE to completely rethink how they communicate with their customer base, relying heavily on triggered communications that engage customers in the moment they are primed for action. They now use programmatic templates to personalize millions of messages each day.

Since signing with Cordial, Revolve has pushed live 15 different personalized triggered campaigns which now account for over 20% of their overall revenue. These campaigns have a 2X engagement rate over traditional promotional campaigns and have resulted in massive gains in efficiency for the team. Instead of building promotional campaigns one by one, they can rely on Cordial to automate and deliver messages for them, freeing up time for the team to be more strategic and effective.

They also leverage Cordial Experiments to optimize all the triggered automations they implemented and can now be confident that they’re generating as much revenue as possible. It all wouldn’t have been possible without the use of machine learning, which has streamlined their efforts to optimize and personalize messages in a repeatable, scalable way.

In Summary

To become an email all-star, it’s time to move past the old way of doing things and adopt the new, namely, machine learning technology. Think differently about testing and optimization using machine learning to finally move beyond A/B testing. Leverage your data to learn what your customers want to buy next. Machine learning doesn’t have to be scary, confusing, or out-of-reach.

Let the machines do the work!

alison-machine learning

Allison serves as Cordial’s founding member of the partnerships channel and growth ecosystem. She entered into the world of email in 2013, after spending time being a creative designer for print media, hopping into technology sales, and being an entrepreneur of a local fitness club. Allison works closely with the leading technology in various industries, giving her an unparalleled perspective in the space. 

Cordial is a next-gen messaging platform that helps marketers leverage their data to create timely, personalized experiences for their customers across channels. Instead of relying on multiple technologies and messaging providers, Cordial enables brands to simplify their processes by consolidating promotional, triggered, transactional, and lifecycle messaging to create unified brand experiences that make the customer the center of every interaction.

You can find more content like this on the Cordial blog.


Your customers demand it, your marketing team wants to do it — so how do you actually make it happen?

Retail Has a Personalization Problem

The fact of the matter is: Retail has a personalization problem.

We often hear about consumers’ desire for more personalized experiences and marketers’ efforts to deliver, but just as often we hear about how those efforts fall short.

Consider the following headlines that have surfaced this past year: “Personalization Helps Retailers; Too Bad They’re Terrible At It” (Bloomberg) and “Study: Retailers Failing to Meet Consumer Expectations” (WWD) are just two of many in this vein.


While there are numerous factors that impact this disconnect, it’s not that retailers aren’t trying. It’s that personalization is hard.

But it doesn’t have to be.

What Does Effective Personalized Marketing Look Like?

One of the most common challenges we see to getting personalized marketing right is the lack of a clear definition of what personalization entails. And that’s a problem, because without a clear definition, you can’t develop a strategy or get the buy-in you need to move forward.

So what does effective personalized marketing look like?

Working with the definition that personalization in retail is about matching customers to the products that excite them, there are three key angles to delivering a personalized experience:

  1. Product recommendations
  2. Audience
  3. Timing

Essentially, you need to deliver targeted product recommendations to a specific customer at the optimal time. Now that’s a lot to get right, especially at scale — hence why personalization can be so challenging. So how do you do it?

Mastering Personalized Marketing at Scale

While there’s no one way to get personalized marketing right, we recommend the following tips to master the three angles of personalized marketing at scale:

1. Get Detailed About Your Products to Deliver Targeted Recommendations

First comes a part of the personalization equation that it’s easy to overlook: Product data.

However, tracking product data can make or break your personalization efforts. That’s because a deep understanding of product data can help you create truly relevant experiences for customers by making Netflix-like recommendations. For example, when you tie very detailed attributes to each of your products, you can go beyond “Shopper A likes sweaters” and instead think in terms of “Shopper A likes blue, v-neck, cashmere products” — and that level of detail changes the game.

Tracking product data can also help you identify new opportunities to engage customers, for instance by notifying customers when products in which they’re interested drop in price, are running low in inventory or come back in stock.

2. Define a Specific Audience By Marrying Behavior, Customer and Product Data

Second, you need to tie your product data to website behavior and customer data.

A deep understanding of your products will only get you so far — you also have to tie that knowledge to information about your customers in order to deliver the optimal product recommendations to each shopper.

Specifically, this includes tracking customers’ behaviors onsite and their engagement with your marketing communications, such as email. To take this one step further, you can even evaluate customer data based on predictive measures, like a shopper’s predicted affinity for certain product categories. Together, this data will help you determine the best audience with whom to share various product recommendations.

3. React in Real Time with Dynamic Content

Lastly, you need to weave in timing to allow for true real-time personalization.

After all, there’s nothing worse than sending a message only for it to be outdated when customers view it. Along the same lines, you don’t want to miss an opportunity to engage with shoppers at the optimal time in their buying journey.

By bringing real-time personalization into your emails through dynamic content, you can ensure that every email you send will be just as relevant tomorrow as it is today. Furthermore, by combining native open-time data with live business-context data, you can ensure that all of the information in your emails is always up to date and that you reach customers in their time of need.

Effective Personalized Marketing in Action

Once you master the three angles of personalized marketing, you’re ready to put your efforts into action. What exactly does that look like?

Picture this: Your brand is running a sale on jeans this week. You want to get the word out and decide to promote the sale specifically to customers who have an interest in jeans (based on past browse and purchase behavior) and have a predicted affinity for discounts.

You start emailing customers on Monday morning at the start of the sale and include a countdown timer in the email to create a heightened sense of urgency. This timer also ensures that no matter when people open the email, it will always remain relevant — even if they open it on Friday when there are hours left in the sale that was promoted as a week-long event.


And even when the clock runs out, if you’ve included “live images” the content can automatically change so that instead of the sale/promotion image, viewers see a message that reads “Sorry this offer expired, but visit the website to check out today’s amazing deals instead.”


Switching gears, let’s say you’re using some user generated content (UGC) to nurture customers who have shown an interest in certain products but are not quite ready to buy yet. What better way to do so and keep things fresh than to pull in a live social feed to your emails so that recipients can always see the latest chatter about your brand and the products they’re most interested in?

AEO Social

It’s Time to Master Personalization

Personalization has proven difficult for retailers in the past, but if you can piece together product recommendations and targeted audiences with real-time information, you’ll be well on your way to delivering truly personalized experiences at scale.

To learn more about how retailers are already putting this advice into action, click here for the inside scoop on how Liveclicker helped Torrid to the highest revenue hour in company history. For Liveclicker’s take on triggered personalization, check out our guest blog, Email at the Speed of Time: Triggers, Open-Time Data, and Beyond.


Evan Britten-Bozzone is Director of Strategy & Partnerships at Bluecore with a successful history creating and growing leading SaaS Marketing Technology products. Prior to Bluecore, Evan founded a consumer services company, worked as a private equity analyst at The Blackstone Group and worked as an investment banking analyst at Lazard.