Will Boyd on smarter deliverability and winning email strategies — Stripo.email

What’s the secret to getting your emails opened, clicked, and actually driving revenue? Will Boyd has been chasing (and hitting) those inbox goals for over a decade. As the senior marketing automation specialist at the Memphis Grizzlies, and with a background spanning major ESPs and CDPs, he knows exactly how to blend data, strategy, and human insight for high-performing email campaigns.

In this interview, Will shares the hard truths about opens and clicks, the automation mistakes even pros make, and how to build deliverability strategies that actually move the needle. He walked us through the nuances of balancing infrastructure and content, building smarter automation flows, and prioritizing real outcomes over vanity metrics.

Will Boyd has been deep in the email marketing trenches since 2011, helping brands not just to reach inboxes but to make the most of that moment when they do. Now the senior marketing automation specialist at the Memphis Grizzlies, Will brings a rare mix of technical deliverability expertise and strategic marketing insight. Over the years, he’s worked directly with some of the world’s largest email senders across both ESPs and CDPs to make sure that their marketing strategy and email deliverability goals were aligned for maximum inboxing reach and measurable revenue.

Inbox truths: Debunking deliverability myths and knowing when to let go

Stripo: What first drew you to email marketing, and what continues to motivate you to stay deep in the world of deliverability after all these years?

Will: What’s always attracted me to email — and what keeps me in it — is the way it’s rooted in relationships. Unlike social media, which often feels like a one-way stream of endless posts driven by algorithms, email is permission based. If you’re sending to someone who didn’t ask for it, you’re sending spam, and your message will likely go to the spam folder.

That element of permission is powerful. It puts the recipient in control. The spam button, for example, gives recipients more direct feedback power than any other channel. It reinforces the need for senders to respect the inbox, to honor the relationship. That dynamic, where trust and engagement determine your access, is what continues to fascinate me.

S: You’ve worked with brands and platforms, from the Memphis Grizzlies to Twilio and Simon Data. What’s one misconception about email delivery that persists across both the platform and sender sides?

W: One big misconception I see on both the platform and sender sides is around best practices. Many people still treat best practices like a checklist or a guarantee, as if doing those five or ten “magic” things will automatically get your mail into the inbox. But that’s just not how it works.

Best practices are helpful, and you should absolutely follow them. But their true purpose is to help you serve the recipient better. In the end, it’s not about tricking filters — it’s about consistently delivering the content you promised when the recipient signed up. If you’re doing that well, you’ll continue to reach the inbox, regardless of the technical shifts that come along.

S: How should teams today approach sunset policies? What data should inform decisions about when to suppress or remove subscribers?

W: When I think about a sunset policy, my goal is always to build a system that listens for human activity. And that’s tricky in email, because metrics like opens and clicks don’t always mean what we think they mean. An open doesn’t guarantee someone will read the message. A click doesn’t always mean real interest.

That’s why I encourage marketers to design campaigns that drive measurable actions beyond the inbox — for example, clicking through to your website, spending time there, or completing a specific action. Those are better indicators that you’re reaching real, engaged people.

At the Memphis Grizzlies, we used a mix of signals to determine such moments: 

• when we want to pause sending to a subscriber so that we slow down their receiving cadence;
• when we want to send them specific messaging to try to get them reengaged;
• when we want to stop sending to them altogether. 

We looked at how many emails someone received without opening or clicking and factored in behavior outside email, such as ticket purchases, merchandise orders, and form submissions. When we could see that someone was still active in other ways, we felt more confident continuing to send, even if their email engagement was low.

So, in short: use as many data points as you can to answer one key question — Do I believe this person is still there and still wants my emails? And, as a general rule, don’t send to people who haven’t opened or clicked anything in over a year. That alone helps avoid spam traps and blocklist issues.

That said, most inbox providers like Gmail and Microsoft care more about recent engagement — what’s happened in the past 90 days, or even the last six months. So, make sure your sunset policy aligns with that reality and not just the old 12-month model.

Mastering signals: How to use your CDP without tanking your reputation

S: From your perspective, how does a CDP improve or complicate a deliverability strategy? What’s key to getting it right?

W: A CDP really opens up the ability to use the kinds of data points I mentioned when we talked about sunset policies — those that go beyond just opens, clicks, and unsubscribes. When you connect a CDP across your entire organization, it brings all your available data together. That means you can know, for instance, that this recipient completed these three actions and exactly when they did.

The real value of a CDP is that it surfaces this kind of data for marketers who might not know SQL or have a data team generating highly targeted lists. A good CDP handles all of that at the back end, letting you do things with data you couldn’t do before.

One of my favorite email-specific metrics we tracked in a CDP was the number of messages a recipient received in a row without engaging. That simple stat helps you decide whether it’s time to sunset a contact or send them different messaging.

And that’s another key benefit: a CDP doesn’t just help you analyze email — it helps you connect to other channels too. Sometimes, email isn’t the best medium. Maybe that message works better via SMS or through a Facebook-lookalike audience to grow your list. CDPs make this kind of cross-channel coordination simpler.

Ultimately, getting your CDP strategy right means asking: How can this tool help us improve the recipient experience overall? It’s not about blasting messages across every channel. It’s about using data to make informed decisions that improve engagement and measurable results.

S: As sender reputation becomes increasingly nuanced, what signals matter most in 2025, and which ones do marketers tend to overestimate?

W: Instead of analyzing these metrics in isolation, compare them across mailbox providers. For instance, an open rate might not definitively tell you a message was read, but if Gmail shows a 40% open rate and Hotmail only 5%, you likely have a deliverability problem at Hotmail. This contrast is a powerful diagnostic tool.

One mistake I see is marketers comparing their performance to industry benchmarks instead of their own metrics across domains. Look at your results at Gmail, Yahoo, Outlook, and so on. That’s how you spot where things are working and where they’re not.

Another often-overlooked but incredibly useful signal is the unsubscribe rate. It’s a true indicator of human interaction — someone had to open your message and click to unsubscribe. If your unsubscribe rate is consistent and stays below 1%, you’re likely doing a good job. But if it rises above that, it may be a sign that your content isn’t resonating anymore or that you’re sending too often.

On the flip side, a 0% unsubscribe rate might seem ideal, but it could also mean your emails are going straight to the spam folder, where people aren’t even seeing them.

So, the unsubscribe rate, though sometimes seen as negative, can be one of the most honest signals about how your audience feels. Use it to guide improvements in content, cadence, and targeting.

S: You’ve often emphasized data-driven email practices. But with so much data available, how can teams prioritize which metrics truly guide smarter deliverability decisions versus just adding noise?

W: Start by leveling up your questions before diving into the data. What are you trying to learn or improve? Metrics like opens and clicks might feel like indicators of success, but they mainly tell you whether your email is reaching real people or landing in spam.

If you’re seeing consistently strong open rates across mailbox providers, that likely means your emails are hitting inboxes. If clicks are increasing, something in your messaging is resonating. But these signals only go so far.

The real power comes from tying those engagement signals to measurable outcomes. For example, if your goal is to drive traffic to your website, check Google Analytics to see how many users came from the campaign and how long they stayed. Or if you’re aiming to sell a product, track conversions. When you combine these outcome-based metrics with open and click rates, you start to see the full picture.

Sometimes, a well-crafted campaign with great content won’t perform, simply because it’s stuck in spam. Other times, your email lands in the inbox and gets plenty of opens but fails to convert. That tells you the content or offer might need work.

Solving the deliverability puzzle: Infrastructure, content, and smart automation at scale

S: When teams debate whether deliverability issues are content based or infrastructure based, how do you guide them toward diagnosing the real problem?

W: That’s a great question, because mailbox providers rarely tell you what’s wrong or how to fix it. So, I always start by ruling out simple infrastructure issues.

1. First, I check the technical foundations: Is authentication working as expected? Are SPF, DKIM, and DMARC properly configured and passing? Google is your friend here — there are plenty of great guides out there to help you double-check these settings.
2. Next, I make sure that the sending IP and domain aren’t blocked. Tools like mxtoolbox.com are great for scanning common blacklists.
3. Once I’ve confirmed that the infrastructure is sound, I turn to content. I run the email through checks — tools such as Email on Acid or Litmus, or even free HTML validators — to spot red flags in the code or links. I look closely at every URL in the message to ensure I’m not linking to a site with a bad reputation.
4. After clearing the technical and obvious content issues, I dig deeper. This means testing different content variations and removing or replacing elements to isolate what might be triggering spam filters. It’s not glamorous work, but it’s effective.
5. Finally, I assess whether the issue is systemic or isolated. If it’s just one or two campaigns, you’re likely looking at a short-term problem — maybe a content hiccup or an authentication blip. But if the issue is persistent, it’s often a reputation problem that will require improving the experience for your recipients over time.

S: With your experience in marketing automation across platforms like Simon Data and SendGrid, what are the most common automation mistakes that impact email marketing results? And how can teams avoid them?

W: One of the biggest mistakes I see is the urge to automate everything — and I get it. Automation is powerful. But when you go all in too quickly, it’s easy to overwhelm recipients with confusing message cadences or over-messaging that damages trust in your brand.

Suddenly, your audience is thinking, “Wait, why am I getting three different emails from this brand in one day?” That’s not a great look.

The goal is to feel confident enough to sleep at night, knowing your automation is doing exactly what you intended. It’s also important to map out how you want your audience to experience your brand — and then design your automations to support that cadence, not just to crank out as many messages as possible across different channels.

S: How do you approach building automation workflows that balance personalization with scale, especially when working with dynamic data inside a CDP?

W: This is a big, ongoing challenge — and one I’m actively working on with the Memphis Grizzlies. The heart of it is content prioritization: figuring out what content matters most to which recipients and then making sure you’re not flooding people with irrelevant messages.

It starts with deeply understanding your audience — where they are, how they’ve interacted with your brand, and what the next logical step is in their journey.

For instance, we have fans all over the world. But NBA rules mean we can only market certain offers within a specific radius of our venue. A fan in California who loves the Grizzlies probably won’t fly in tomorrow for a game, but we can engage them with content like fan polls or a prompt to download our app.

Meanwhile, someone who lives nearby and has never been to a game? That person gets a targeted campaign inviting them to their first in-arena experience. Someone who’s already been to 15 games in two years? They’ll see content about season ticket packages or exclusive experiences.

So, the key is this: know who you’re talking to, know why you’re messaging them, and prioritize accordingly. Ask yourself, “What is the most important message for this person today?” That’s how you scale personalization without sacrificing relevance.

Wrapping up

Big thanks to Will Boyd for sharing his expertise and real-world insights with us. With over a decade of experience spanning email service providers, customer data platforms, and now the Memphis Grizzlies, Will brought both technical depth and a strategic lens to this conversation.

Here are some insights from this interview:

1. Don’t chase opens and clicks alone — treat them as signal data, but focus on real business outcomes like conversions and site engagement to measure success.
2. Start with infrastructure when diagnosing deliverability issues — rule out technical problems (such as authentication errors or blacklists) before shifting focus to content.
3. Avoid automation overload — test thoroughly and build workflows that respect user cadence instead of overwhelming subscribers.
4. Balance personalization with scale — prioritize content based on recipient behavior, location, and intent to deliver relevant messages, without over-messaging.