The post-BFCM tool evaluation has begun. Brands are reviewing what worked, what didn’t, and what needs to change before Q1 kicks into gear.
Most of these evaluations focus on the wrong question. They ask: which tools performed best? The better question: which tools are actually talking to each other?
Because the brands winning in 2025 aren’t winning because they have the best ESP or the best SMS platform or the best referral program. They’re winning because their stack works as a system, not a collection of disconnected point solutions.
The Integration Problem
Here’s what a typical ecommerce tech stack looks like: an ESP handling email, a separate platform for SMS, a referral program bolted on somewhere, retargeting pixels firing independently, a CDP trying to stitch it all together, and an analytics platform attempting to make sense of the chaos.
Each tool has its own dashboard. Each tool claims credit for conversions. Each tool optimizes for its own metrics without awareness of what the others are doing.
The result? Customers get hit with an email, then an SMS, then a retargeting ad, then another email, all within 24 hours, none of them aware the others exist. Meanwhile, attribution is a mess because every tool is counting the same conversion as its own win.
This isn’t a technology problem. It’s an architecture problem. And it’s costing brands revenue they don’t even know they’re losing.
The Stack That’s Actually Working
The brands seeing the best Q1 results share a common characteristic: their tools communicate.
When a customer makes a purchase, the ESP knows, the SMS platform knows, the referral program knows, and the retargeting pixels know. Not hours later through a batch sync. Immediately. In real time.
This enables something powerful: coordinated customer journeys instead of channel chaos.
A customer buys during BFCM. The order confirmation email (handled by the ESP) includes personalized product recommendations AND a referral link (pulled from the referral platform). The customer clicks the referral link but doesn’t share yet. The SMS platform knows this and sends a gentle prompt two days later. The retargeting platform knows they’re already engaged and excludes them from generic prospecting campaigns.
Every tool is aware of what the others have done. Every touchpoint builds on the last. Nothing contradicts or duplicates.
This is what integrated means. Not “we have an API” but “we actually use it to create unified customer experiences.”
The 70% Open Rate You’re Wasting
Let’s talk about the most underutilized real estate in ecommerce: transactional emails.
Order confirmations. Shipping notifications. Delivery confirmations. These emails have open rates above 70%. Sometimes above 80%. Nothing else in your marketing arsenal comes close.
And what do most brands put in them? A receipt. Maybe a tracking number. Perhaps a generic “shop more” button that no one clicks.
This is a massive missed opportunity.
Transactional emails are the moment when customer attention is guaranteed. They’re actively looking for these emails. They’re opening them immediately. They’re reading every word.
The brands maximizing Q1 are treating transactional emails as prime conversion real estate. Order confirmation includes personalized recommendations based on what they just bought. Shipping notification includes a referral prompt while anticipation is high. Delivery confirmation asks for a review AND includes a referral link for sharing their new purchase with friends.
Every transactional touchpoint becomes a chance to drive the next action. Not in an aggressive, salesy way. In a helpful, “while you’re here” way.
If your ESP and referral platform don’t talk to each other, this is nearly impossible to execute well. You end up with clunky workarounds, inconsistent experiences, and missed opportunities.
The Dark Referral Problem
Here’s an uncomfortable truth about attribution: a significant portion of your revenue comes from word-of-mouth you can’t track.
Someone tells their friend about your brand at dinner. The friend Googles you later that night and makes a purchase. Your attribution model credits Google. The actual driver? An untrackable conversation.
Someone shares your product in a group text. Their friend clicks through but the referral parameters get stripped somewhere along the way. They land on your site as “direct traffic.” The actual driver? A recommendation you’ll never see in your dashboard.
These are dark referrals. Word-of-mouth that drives real revenue but lives outside your tracking infrastructure.
The problem isn’t that dark referrals exist. They’ve always existed. The problem is that most brands have no idea how much revenue they represent, which means they have no idea how much they’re underinvesting in referral as a channel.
Studies suggest that word-of-mouth influences up to 50% of purchasing decisions. But most attribution models credit it with low single digits. The gap between reality and measurement is enormous.
The brands getting this right are using tools that surface dark referral patterns. Post-purchase surveys asking “how did you hear about us?” with options beyond standard UTM-trackable channels. Referral program analytics that identify customers who share but whose friends convert through other paths. Attribution models that account for the influence gap, not just last-click credit.
If your tools can’t surface dark referral activity, you’re flying blind. You’re making investment decisions based on incomplete data. And you’re almost certainly undervaluing the program that’s quietly driving more revenue than you realize.
The Math That Should Keep You Up at Night
Let’s make this concrete.
You spent $50 to acquire a customer during BFCM. Meta ads. Maybe some Google Shopping. That $50 is gone regardless of what happens next.
That customer makes their purchase. Great. But then they never engage with an owned channel. They don’t open your emails. They don’t opt into SMS. They definitely don’t make a referral.
Six weeks later, you want to reach them again. How do you do it?
You pay. Another retargeting campaign. Another $30, $40, $50 to get their attention. And this time they’re less likely to convert because they’re not in buying mode.
Now multiply that across thousands of BFCM customers. The cost to re-acquire customers you already “acquired” becomes staggering.
Referral breaks this cycle.
When a customer makes a referral, two things happen. First, they’ve taken an owned channel action. They’re engaged. They’re invested. The likelihood they’ll respond to future owned channel outreach increases dramatically. Second, they’ve potentially acquired a new customer for you. A customer who costs nothing in media spend.
One referral can offset the CAC of the original customer entirely. Two referrals and that customer is now profitable on acquisition alone, before they even make a second purchase.
This is the economic argument for prioritizing referral in Q1. Not as a nice-to-have program. As a core strategy for fixing the unit economics that BFCM strained.
Your BFCM Customers Will Become Something
Here’s the reality of your BFCM customer file right now: those customers are in motion. They’re not static. They’re actively becoming something.
Some will become repeat customers. They’ll buy again, increase their LTV, and justify the acquisition cost you paid.
Some will become advocates. They’ll refer friends, leave reviews, and share on social. They’ll transition from cost center to growth driver.
And some will become someone else’s paid target. They’ll drift away, their email addresses eventually sold or scraped, and your competitors will pay to acquire them. The customer you spent $50 to get will cost someone else $50 to take.
Your tools and your strategy determine which path each customer takes.
A connected stack that coordinates email, SMS, and referral gives you the best shot at converting customers to owned channels. Disconnected point solutions that blast messages without coordination push customers toward disengagement.
The window to influence this is short. Forty-five days, give or take. After that, the patterns are set. The customers who were going to engage have engaged. The ones who were going to drift have drifted.
Building the Q1 Stack
The evaluation criteria for your Q1 tools should shift.
Stop asking: “What are the features?” Start asking: “How does this integrate with everything else?”
Stop asking: “What’s the reporting dashboard look like?” Start asking: “Can this tool see what my other tools are doing in real time?”
Stop asking: “What’s the cost per message?” Start asking: “Can this tool help me identify dark referral patterns and owned channel conversion rates?”
The individual capabilities of your ESP or SMS platform or referral program matter far less than how well they work together. A mediocre tool that integrates perfectly will outperform an excellent tool that operates in isolation.
For referral specifically, look for platforms that embed naturally into transactional flows, that share data bidirectionally with your ESP and SMS tools, and that provide attribution visibility beyond just tracked link clicks.
The Q1 Priority
The brands that win Q1 won’t be the ones with the biggest ad budgets or the flashiest creative. They’ll be the ones who successfully converted their BFCM customers from rented transactions to owned relationships.
That conversion depends entirely on whether your tools can work together to create coordinated, high-value customer experiences. Transactional emails that include referral prompts. SMS that knows what email has already done. Attribution that surfaces the word-of-mouth you can’t directly track.
Your BFCM customers are either going to become your acquisition channel or someone else’s paid target. The tech stack you deploy in Q1 determines which.
Choose tools that talk to each other. The alternative is paying rent forever.
About the Author:
Jeremy Foreshew is a full-stack marketer with deep expertise in customer-led growth. As Head of Marketing at Talkable, he helps DTC and eCommerce brands turn their customers into their most powerful acquisition channel. Jeremy writes about referral strategy, retention, and the future of word-of-mouth marketing. He has been featured in Forbes, TechCrunch, and HuffPost.
