The brand was facing:
Leadership suspected email was leaving significant revenue on the table, but had no data-driven way to confirm it or prioritize where to start. The marketing team was small, and most of their time went into designing and sending the weekly newsletter -- leaving effectively no capacity for the behavior-triggered automation that typically drives the majority of e-commerce email revenue. Every week became a scramble to fill the newsletter with content, rather than a deliberate, data-informed marketing calendar. The team knew, in general terms, that competitors were doing more sophisticated things with their email and SMS programs, but lacked both the internal expertise and the bandwidth to figure out where to begin.
We designed and implemented a full-lifecycle Klaviyo program built around behavior, not blast sends, addressing both the missing revenue capture and the underlying list health problem simultaneously:
Each of these five workstreams was sequenced deliberately rather than launched simultaneously. Data foundation work came first because every flow and campaign built afterward depended on accurate segmentation being in place. Core automated flows came next, since behavior-triggered messaging typically delivers the highest return relative to effort in any e-commerce Klaviyo program. Campaign strategy and SMS rollout followed once the underlying data and automation foundation could actually support them well, and deliverability monitoring ran continuously throughout rather than as a final step -- treating list health as an ongoing discipline, not a one-time cleanup.
Within four months of full implementation, once segmentation, flows, and the deliverability foundation had time to mature and compound, the results became clearly measurable:
Before this engagement, the brand's only behavior-triggered flow was a basic abandoned cart sequence -- and even that was a single generic email, not a multi-touch series. Browse abandonment, which targets visitors who viewed products but never added anything to a cart, was entirely missing. This is a genuinely large addressable audience for most e-commerce brands, since far more visitors browse and leave than ever reach the cart stage. Once built, this flow alone became one of the highest-converting automations in the entire program, precisely because it was reaching people at a moment of genuine, recent interest rather than waiting for a cart action that a large share of browsers never take.
A genuinely important part of this engagement was resisting the instinct to simply send more. The brand's prior approach -- a single generic weekly blast to the full list regardless of engagement -- was already showing early signs of deliverability strain, with rising unsubscribe rates and softening open rates. Rather than layering more campaigns on top of an already-strained list, the first real step was cleaning and re-segmenting existing subscribers, suppressing chronically unengaged addresses before sending anything new. This meant a smaller addressable list in the short term, but a foundation that could actually support sustained, healthy growth rather than a short-term revenue spike followed by a deliverability collapse.
It would have been tempting to build the abandoned cart and browse abandonment flows first, since these are typically the fastest-visible wins in any Klaviyo implementation. Instead, the engagement deliberately started with data foundation and segmentation work -- connecting the full Shopify catalog and purchase history, and building genuinely dynamic segments based on real behavior rather than static list membership. This ordering mattered: every automated flow built afterward could immediately leverage accurate segment data, rather than needing to be rebuilt later once better segmentation existed. Teams that skip this step often end up retrofitting personalization into flows that were originally built generically, which is considerably more work than building it in from the start.
Rather than treating SMS as simply "email, but shorter," the program treated it as a genuinely distinct channel with its own opt-in flow and its own specific use cases. SMS was reserved deliberately for moments where the immediacy actually mattered -- flash sale announcements, back-in-stock alerts for items a customer had specifically shown interest in, and shipping status updates. This restraint mattered for two reasons: it kept SMS opt-out rates low by ensuring every message felt genuinely relevant and timely, and it avoided the common trap of duplicating the same content across both channels, which tends to annoy subscribers on whichever channel receives the message second. Within 90 days, SMS was already contributing a meaningful share of total messaging revenue -- a result that depended directly on this disciplined, use-case-specific approach rather than blanket adoption.
A common pattern in email marketing engagements is a burst of optimization activity followed by the program reverting to static, unexamined habits once the consulting engagement ends. To avoid this, a real priority of the work was establishing an ongoing testing calendar and a reporting rhythm the in-house team could sustain independently -- not a one-time list of recommendations, but a repeatable process. Revenue-per-recipient reporting by segment, reviewed monthly rather than only at campaign send time, gave the team a genuine feedback loop for continuously refining segmentation and flow logic long after the initial build was complete. Six months post-launch, the brand's own team was independently identifying and testing new flow variations, using the same reporting framework established during the engagement -- a sign the capability had genuinely transferred, not just the immediate results.
This handoff mattered as much as the initial build itself. A Klaviyo program that only performs well while an outside consultant is actively managing it hasn't genuinely solved the brand's underlying capability gap -- it's simply moved the dependency from a fragmented internal process to an external one. Structuring the engagement around teaching the in-house team to read and act on the same reporting used during the build meant the improvements were built to last well beyond the initial engagement window, not just through the period of direct consulting involvement. A year later, the brand's flows and segmentation strategy had continued to evolve under their own team's ownership, a genuine sign the underlying capability -- not just a fixed set of automations -- had transferred successfully.
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