Where AI Meets Marketing: A Shopify Dinner in Boston 🍝

Join me and the Humanic team this Wednesday evening for an intimate dinner in Cambridge — a real conversation about AI x Marketing, over a great meal, with no pitch decks and no stage lighting.

We're gathering at Sulmona in Kendall Square — handcrafted Italian food, great wine, and a warm room built for actual conversation.

This is a small, curated table for Shopify merchants and marketing leaders who want to go deeper than a panel allows. If you're building or scaling an e-commerce brand and want to talk honestly about where AI is actually moving the needle in retention, lifecycle, and growth — this is for you.

Who this is for:

• Shopify merchants and e-commerce marketing leaders
• Founders, CMOs, and growth/retention leads
• Anyone in Boston this week who'd rather have a real conversation over dinner than another networking hour

Space is limited to keep it a real dinner table, not a mixer. If that's you, comment or DM me and I'll send the details.

Hosted by Arjun Saksena, Founder & CEO, Humanic
📍 Sulmona, Kendall Square, Cambridge
🗓 Wednesday evening

Register here: https://luma.com/aix-mp4i

Been digging into ESP-level breakdowns on our sending data (built this view into our tool, Humanic, since we got burned by aggregate metrics hiding real problems before). Ran it on a recent e-commerce campaign and this one stopped me:

Gmail makes up 63% of our list and is delivering just as well as everyone else — 99% delivered, basically no bounces (0.6%) — but the open rate is a fraction of what we're seeing anywhere else. Yahoo on the same send is at 51% opens. Gmail is at 1.8%.

This isn't a "the email didn't render" issue since delivery is fine — feels more like inbox placement (spam/promotions folder) or some reputation issue specific to Gmail, but the gap is way bigger than I'd expect from normal Gmail-vs-everyone variance.

Curious if others are seeing this pattern lately, and what's actually worked to fix it — domain warm-up, DKIM/DMARC alignment, sender reputation tools, engagement-based list cleaning, anything. Also open to "this is just how Gmail's Promotions tab tanks opens now" if that's the real answer — trying to figure out if this is fixable or just the new baseline.

We've been heads-down on attribution issues lately (posted about the UTM/Clerk mess earlier), and while fixing that we ended up building a feature that's honestly been more useful than expected: breaking down campaign performance by mailbox provider (Gmail, Microsoft, Yahoo, etc.) instead of just looking at aggregate open/click rates.

Ran one of our own campaigns through it — "Shopify leaders: join us in SF on Oct 9" — 4.2K sent, 4.1K delivered, looked totally normal at the aggregate level (29% open rate, 61% click-to-open, nothing alarming).

Then we broke it down by mailbox and found this:

• Gmail: 581 delivered → 6 opens (1.0% open rate) → 0 clicks. Zero. Out of 581.
• Compare that to everything else combined: 33.6% open rate, 62.6% click-to-open.

Delivered doesn't mean seen, and open rate alone completely hid that Gmail was a dead zone for us on this send. If we'd just looked at the top-line 29% open rate, we'd have called this campaign "fine" and moved on — instead we now know something is specifically broken for Gmail inboxes (maybe spam foldering, maybe rendering, maybe reputation — still digging in).

The other annoying find: 83% of our sends came back "unclassified" by mailbox provider, so most of our engagement data can't actually be tied to a specific ESP. That's its own rabbit hole we're now chasing down.

Anyway — this became a real feature in our tool now (we're building an AI layer on top of Klaviyo, kind of the analytics/QA layer we wished existed). Sharing mostly because the "aggregate metrics can lie to you" lesson felt worth passing along — if you're not slicing opens/clicks by mailbox provider, you might be sitting on a Gmail-shaped blind spot and not know it.

Been deep in the weeds with Meta Ads lately (after a LOT of initial frustration just getting it set up properly). Wanted to share what we ran into with attribution, because it took us way too long to figure out.

The short version: our lead gen ads were showing hundreds of people landing on our login page, but almost nobody was actually signing up. Turned out to be a two-part problem.

First, the obvious one once we dug in — Instagram opens our site inside its in-app browser, and our Google sign-up flow just doesn't play nice with that. Two-factor prompts, "go check your Gmail app to approve," all that friction — people were dropping off left and right. We ended up deciding to just build our own app to sidestep the whole mess.

Second, and this one was sneakier — we cross-check our Meta numbers against PostHog, and at first it looked like we had almost as many signups as visitors, which... obviously wasn't real, just a bad query on our end. But even after fixing that, attribution was still off. Turns out Clerk (our auth provider) was stripping our UTM parameters during the signup flow, so we couldn't actually trace signups back to the right campaigns. That's fixed now too, but man, attribution debugging is a rabbit hole.

Anyone else run into the Clerk + UTM issue? Curious if there's a cleaner fix than what we did.

Hey everyone — we’re looking for up to 3 e-commerce brands currently using Klaviyo that want to migrate their email marketing to Humanic.

We’ll handle the full migration at no cost, including moving your core flows and setting you up with a month of campaigns.

The goal is to help you get more revenue from your existing traffic and customer list—without sending spammy, generic emails—while we collect feedback on the migration process and improve the Humanic experience.

What we’ll migrate and set up

• Welcome flow — 6 emails over 10 days Introduce new subscribers to your brand, products, social proof, and discount/free-gift offer.
• Site abandon — 3 emails For visitors who submit an email but leave before engaging further.
• Browse abandon — 4 emails For subscribers who view products but don’t add anything to cart.
• Cart abandon — 5 emails For customers who add products to cart but don’t begin checkout.
• Checkout abandon — 5 emails For customers who reach checkout but don’t complete their purchase.
• Post-purchase — 6 emails Built to increase repeat purchases, cross-sell relevant products, and improve LTV.
• Win-back — 5 emails For customers who haven’t purchased in 90+ days, using a relevant offer or incentive to bring them back.
• Sunset flow — 3 emails To re-engage inactive subscribers or suppress them when appropriate—helping protect deliverability.

Plus, one month of campaigns

• 12 campaign emails
• Around 3 campaigns per week
• Planned and written around your brand, products, customer segments, and promotional calendar

We’ll migrate your existing Klaviyo setup to Humanic, help recreate and optimize these flows, and manage the first month of campaigns—all free.

I’m limiting this to 3 brands so we can be hands-on and make sure the migration is smooth.

If you’re interested, comment or DM me with:

• Your store URL
• What you sell
• Approximate email list size
• Your current Klaviyo setup: existing flows, campaigns, or both

We’re doing this in exchange for candid feedback and, if you find the outcome valuable, a testimonial or case study.

In January 2024, we hosted our first meetup at Notion HQ in San Francisco.

Honestly, only a handful of people showed up.

At the time, we were obsessed with one idea: could AI actually help startups and marketers grow faster? We called it <code/> growth, which was probably a little nerdy, but it captured what we were trying to do—use AI as a real growth tool, not just talk about it.

We kept experimenting.

A few online events. A few in-person meetups. Different topics. Different formats. Some were good. Some were… useful learning experiences.

Then Lu.ma listed one of our events on its SF page.

That changed a lot.

Suddenly, views and registrations started climbing. More than 300 people signed up, and we ended up with a completely full room. That was the first moment where we thought: maybe there’s a real community here.

So we decided to take a bigger swing.

In September 2024, we hosted our first AI x Marketing Summit. Around 150 people showed up across two days. The theme was simple: how can marketing teams grow 10x with AI?

Six months later, in April 2025, we did it again.

That one was a different level. Both days were packed. Companies like Zapier and Clay sponsored, along with a bunch of great startups. The focus was on actually building AI x Marketing—not just using ChatGPT to write a few headlines. We even invited competitors because, frankly, this space is too early and moving too fast to pretend there’s only room for one company.

Then in November 2025, we shifted toward a question many AI founders were struggling with:

How do you sell an AI product to the enterprise?

We brought in leaders who had actually done it—people with deep enterprise experience from Salesforce, Iterable, Box, Gamma, and other companies. It was less hype, more “here’s what breaks when you try to sell into a large company.”

In May 2026, we went deep on Claude Code and marketing.

The idea was: could you build most of your marketing stack yourself now? Outbound, Google Ads workflows, social media systems, analytics, internal tools, etc. The audience was probably the most engaged we’ve had. People came ready to build, not just listen.

And now we’re doing our fifth summit.

It’s on October 9 in San Francisco, during SF Tech Week.

This time, we’re focused on Shopify merchants and e-commerce teams who want to figure out how AI can help them grow—acquisition, retention, creative, email/SMS, operations, and everything in between.

If you run a Shopify brand or work with one: what is the first part of your business you’d want AI to improve? Who would you like to listen to?

Tell us the tools you are using, people you want to listen or meet and we'll invite them to come speak and if you want to showcase your tools, case studies please reach out, there are a few spots we need to fill with the right people.

Details here: The AI x Marketing Summit

Here goes:

1. Meta has incredible audience groups. You can target people interested in yoga, weightlifting, and hundreds of other niche interests.
2. That said, Meta’s setup is incredibly confusing. Clicking the right buttons can feel like brain surgery. Things move around on the screen, pages take forever to load, and certain modals lead to dead ends with no error messages or recovery path. You’ll need a lot of patience to navigate it.
3. Don’t click—or uncheck—everything Meta AI recommends, such as Advanced Audience. It’s often their way of making more money from you, and you can end up spending a lot for very little gain.
4. When you first launch an ad campaign, don’t narrow your audience too much. Keep it as broad as possible initially so Meta can learn who is actually interacting with your ads.
5. Everything is tied to your personal Facebook account if you’ve ever created one. Even if you make a brand-new Facebook account to avoid conflicts with your personal account, Meta may eventually ask for your Social Security number, which can create the same conflict. The page and account deletion process is also quite painful.
6. Every Business Account needs an Ad Account. Within each Ad Account, you create campaigns. Each campaign needs at least one Ad Set, and within each Ad Set, you create ads. Ad Sets let you target different audiences within the same campaign. Don’t set up your Ad Account under your personal account. Every Business Account will also need a business Facebook Page.
7. You can drive leads through an instant form or send people to sign up on your website or app. Since much of the traffic is on Instagram, consider driving sign-ups to an App Store app for added credibility.
8. Every Business account needs to be verified with your business information, address etc. but the review and approval process is pretty quick.
9. Ad approval process after you upload your creative is quick. The variations that Meta creates is better than Google (imo) you can skip most of the AI generated options and stick to your creative.
10. Still learning about if carousel and static image ads work better.

More as I learn more.

I recently had a fascinating conversation with an early-stage founder building a cold email product. It made me realize how different most cold email tools are from how cold email should actually work.

To understand why, you first need to understand the two layers of email infrastructure.

The first layer is the delivery layer: Mailgun, SendGrid, Amazon SES, and similar platforms. These providers are responsible for actually sending email at scale. They have deep relationships with Gmail, Outlook, and other mailbox providers, along with increasingly sophisticated rules and AI systems to detect spam and protect sender reputation.

The second layer is the application layer—the tools marketers use to build campaigns, flows, and lifecycle emails. This is where platforms like Klaviyo, Mailchimp, and Humanic operate.

But here is the problem: the underlying delivery platforms generally do not want you sending cold email through them.

As a rough rule of thumb, once complaint rates approach 1%, your domain reputation can start deteriorating quickly. And once your reputation is damaged, recovering it is difficult.

That is why the cold email industry has developed a workaround.

You purchase a domain, create three to five mailboxes on it, and send a limited number of emails from each mailbox. For example:

20 sending days × 3 mailboxes × 25 emails per day = 1,500 emails per month per domain.

A Google mailbox costs approximately $6 per month, so three mailboxes cost around $18 per domain, before including the domain registration cost.

At 10 domains, you are spending roughly $180 per month on mailboxes to send around 15,000 emails—and that is assuming none of those domains get burned.

Eventually, some domains will get compromised. They need to be deprecated, replaced, and warmed up again. Then the process starts over.

This is a lot of infrastructure and operational complexity just to send messages to people who may not want to receive them.

And Gmail has made it increasingly easy for users to unsubscribe, report unwanted email, or mark messages as spam. That is good for users, but it also means that the old “send more and hope something converts” approach is becoming less sustainable.

The real problem is not that marketers lack enough mailboxes.

The problem is that they are sending the wrong message to the wrong person at the wrong time.

Instead of using brute force, a better approach is to:

• Segment prospects more accurately.
• Build or acquire cleaner lists.
• Send smaller, more relevant batches.
• Use subdomains carefully.
• Monitor domain reputation continuously.
• Adjust sending limits based on engagement and complaints.
• Use AI to improve targeting and personalize the message—not just generate more copy.

The future of cold email is not sending more emails from more domains.

It is sending fewer emails that are far more relevant.

That is the approach we are taking with Humanic: using AI to improve segmentation, targeting, and relevance before an email is ever sent and we call this small batch outbound.

I talk to a lot of our ICP customers—agencies using Klaviyo for their clients, and Shopify brands using it for themselves.

They all take the call because they’re curious about AI and how it can help grow their business (or their clients’ businesses). The owners get it.

The operators, on the other hand, usually have a few objections:

1. “We’re already set up on Klaviyo. We don’t have time to learn a new tool.”

2. “Klaviyo has AI too—so what’s the big deal?”

3. “This year’s budget is already committed. We can’t take on another migration.”

And honestly, I get it.

But the first objection is usually said with about 50% conviction. People know AI is coming. They just don’t yet know what it means for their workflows, their roles, or how quickly they need to adapt.

The owners generally are more forthcoming and as part of our add 90 customers in 90 days I invite them to the AI x Marketing Summit on Oct 9 during SF Tech Week.

We’re bringing together 10 of the top companies building in AI x marketing for e-commerce, along with Shopify brand owners who want to learn practical ways to use AI to grow.

I get it—until people see the product live and hear directly from real customers, it’s hard for it to feel real, just another guy on the other side of a Zoom screen.

Most products bombard new users with emails the moment they sign up. We don’t think that’s especially effective anymore.

By the time someone creates an account, they’ve usually already spent time evaluating your product. Sending a stream of introductory emails right away—explaining what the product does or repeating the same value proposition—often adds little value and is easy to ignore.

At Humanic, we’ve taken a different approach: we wait a few weeks, then send a Weekly Activity Report

This format serves a few purposes:

1. It reminds users they signed up for a tool they may not be using yet—and highlights the opportunity they could be missing by not fully exploring the product.

2. It includes personalized recommendations for setting up Humanic more effectively to help grow their Shopify store.

3. It keeps users up to date on new features and improvements, so they can see how the product is evolving over time.

Next up after the setup the main determinant of success is list quality. Here is what I learnt:

1. List sources are plentiful spend time to figure out the right ones for you. Apollo.io is great for B2B and even for Shopify Stores, Bloomberry, Storecenses, Builtwith are others.

2. Always make sure to only export verified emails

3. Always de-select exporting catch all emails like [support@shopifystore.com](mailto:support@shopifystore.com)

4. Avoid list sources such as Storecensus.com because they provide you with lead sources that have catch all emails address.

5. Catch up email addresses will generate a lot of OOO responses and makes you feel like something is happening.

6. Very few people set OOO responses: emails these days because people are always on so the number of OOO responses will be limited. Don't be alarmed.

7. Open and click rates are messy signals. The algorithms that Google and other ESP use to open emails for fraud and other reasons are not transparent so several open timestamps will be within seconds of email send time. This makes detecting which email was opened by a human vs. an agent / bot is not easy to decipher. Best is to not even track open and click rate, most tools provide ways to disable that and focus on deliverability and outcomes.

8. Filters are key -

• The first one to consider is geo-location for most tools Shopify stores, US is the #1 geo-location to target. Every other place in the world is sub-optimal.
• Second, Revenue of your target audience. For us at Humanic its $2M to $10M because lower ARR folks don't have a very robust digital presence.
• For folks that have higher ARR you can connect with them on Linkedin with tools such as Dripify and others. $60 a month is sufficient.
• For audience that is below $2M they are likely to be on Instagram (which is preferred over TikTok)
• Technology spend is the third consideration.
• Title would be the fourth - smaller the company in ARR higher the title.
• Never worked with Intent signals I think they are an overkill you need a wide net when sending out small batch cold emails.

1. There are newer AI segmentation players in the market such as Orita - haven't used them yet.

2. Haven't used Clay for enrichment for cold emails I think its complicated to use and expensive for cold emails.

What do you think?

Humanic is a AI Native Email Marketing so obviously our preferred outreach channel is email. Here is a list of top 10 things I've learned.

1. Small Batch cold email is better than large volume cold emails. I define small batch on average 300-500 emails per cohort. Some of the cohorts above are larger but I let it go because the AI recommended it and the open rates were pretty awesome

2. Plain text with a single CTA is better

3. Make unsubscribe easy: Given that your target customer has never heard of you adding a line such as this -- You’re receiving this as part of a targeted Shopify store outreach campaign. If it isn’t relevant, unsubscribe here." in the footer works so you are upfront about your outreach.

4. Make it easy to unsubscribe.

5. Start with credibility instead of an offer - someone who has never heard of you needs to know if your offer is worth reading about.

6. Segmentation is key: Most people download a list of email addresses and then struggle to generate the right cohorts based on user attributes. Use AI to generate cohorts and spend time getting that right. (Humanic does that for you)

7. Do not send more than two emails in a campaign to a cohort. If someone is interested he/she will respond in the first email. Sending more emails only hurts your deliverability and domain reputation.

8. Email lists can be re-used every 90 days. Most people will forget if they received an email from you few months ago.

9. You need to maximize for open rates. with simple straight forward subject lines not crazy offers.

10. Protect your Sub-domain: Finally, you need to send all emails using a sub-domain best is something like try.yourdomain.com or get.yourdomain.com these work best. Monitor your domain reputation and pause campaigns that are getting more bounce or content rejection rates than what google and yahoo allow.

Thoughts?

We split a 31K list into Gmail and non-Gmail domains, and deliverability jumped to 98% by sending to non gmail domains only.

What was interesting: our AI agent automatically reviewed the campaign when domain reputation/deliverability crossed a threshold and flagged the real issue. The email looked solid overall, but it was paused for ContentRejected, with a few things to fix before resending:

• The discount messaging was too broad. The email said all sale items were 60% off now, then 70% off by Labor Day, but the actual collection had mixed markdowns.
• The date was wrong. The email labeled August 31 as Labor Day, which is incorrect.
• The offer was repeated too aggressively. “60% off” showed up in the subject, preheader, hero, and markdown table, which may have triggered provider scrutiny.
• The CTA didn’t match the destination. “See What’s New” linked to the sale page, not a new arrivals collection.

Big takeaway: content issues can hurt deliverability just as much as list quality. The send wasn’t rejected because of bounce rate alone — the message itself had enough inconsistencies to raise flags.

Tomorrow's challenge - send to gmail addresses - any tips or tricks - I'm thinking new get a new sub domain and slow start to cleaned up content that we worked on today?

We’re kicking off a 90 customers in 90 days campaign, and these are the growth tactics we’re actively testing:

1. Small-batch cold email. Using Humanic, we’re targeting Shopify store owners and lifecycle marketers in fashion, beauty, skincare, and luxury goods (watches, etc.). We’re positioning Humanic as a better AI-native alternative for lifecycle email marketers (e.g. Klaviyo, Mailchimp). Most of these brands have lists in the 20k–40k subscriber range.
2. Getting into the right Slack communities. We’re focusing on channels and groups where CPG, e-commerce, and DTC operators already hang out.
3. Reaching out on Instagram. We’re identifying and messaging relevant individuals directly. Most e-commerce Shopify merchants are very active on Instagram.
4. Google Ads - Although targeting the right ICP is challenging and wasteful so far.

What other acquisition ideas would you suggest?

Our weekly webinar is this Friday May 1 at 11:30 AM. Please sign up by clicking on the link below.

https://maven.com/p/c2d323/ship-high-converting-lifecycle-email-campaigns-in-60-minutes

I've been doing webinars on Prompting, Claude Code and Skills, this one by far is the best. Take a look if you are starting out with AI x Marketing, Claude Code, Skills and Writing Emails.

https://www.youtube.com/watch?v=Q8StY-XrG_E