Technovier professional engagement
Use this when the constraint is not just traffic, but several connected parts of the commerce journey: conversion, tracking, checkout, recovery, retention, and financial visibility.
Investment
$9,000-$15,000 one-time
Timeline
30-45 days
Engagement
Connected ecommerce growth system
Best fit
Brands with proven products, existing traffic or ad spend, and unclear visibility into what is driving profitable sales
What's inside
Each engagement defines what Technovier will implement, what is separately scoped, how long the work should take, and how the result will be handed over or operated.
Included
Separately scoped
Related capabilities
These are not automatic entitlements. They are included only when they are necessary to solve the agreed system problem.
Engagement flow
We move through three tightly managed phases: alignment, build, and launch support. You get async Loom updates, shared dashboards, and one accountable Technovier team throughout.
Map traffic sources, catalog setup, Shopify events, pixels, CAPI, GA4, conversion paths, and reporting gaps.
Rebuild campaign structure, retargeting, abandoned cart recovery, email/SMS flows, and core creative-testing loops.
Go live with reporting, product-level performance review, an experiment cadence, and an ongoing-operations recommendation if scale is justified.
Overview
Ecommerce System Build is for brands where ROAS looks acceptable but profit still feels uncertain. The problem is often that acquisition, product conversion, checkout, cart recovery, lifecycle, and product-level reporting are not speaking the same language. We connect the required storefront, media, tracking, recovery, retention, and reporting layers so the brand can see what actually drives margin, repeat purchase, and recovery. The goal is not more spend. It is a measurable commerce system with clearer attribution and better retention decisions.
Fit Check
System Scope
Delivery Flow
Step 1
We map the checkout, events, ad accounts, and reporting stack so every revenue source can be trusted.
Step 2
We set up campaign structure, catalog flows, cart recovery, and lifecycle messaging around the products that matter most.
Step 3
We validate events, product feeds, automation timing, and reporting before scaling spend or content velocity.
Step 4
We use the dashboard and creative feedback loop to improve margin, conversion, and repeat purchase behavior.
Quick Answers
Ecommerce System Build is Technovier’s connected implementation for ecommerce brands. It can connect acquisition infrastructure, product conversion, checkout tracking, cart recovery, lifecycle retention, and reporting within an agreed scope.
It is best for brands with real product demand, active traffic, and enough complexity that ROAS alone is not giving a clear picture. It works well when profit depends on retention and recovery, not just new customer acquisition.
It fixes tracking gaps, weak cart recovery, over-broad segmentation, creative fatigue, and disconnected product reporting. The goal is to make the store easier to scale without guessing where the margin is coming from.
Technovier builds the tracking map, campaign structure, recovery flows, segmentation rules, and product-level reporting layer. That gives the team one view of acquisition, checkout, and lifecycle performance.
We measure attributed revenue, recovery performance, repeat purchase behavior, product performance, and the efficiency of the media spend. The store should become easier to understand and easier to improve.
It ties media signals to Shopify behavior, lifecycle segments, recovery flows, and post-purchase data so the team can see which campaigns bring customers who buy again. That matters because ecommerce scale is usually won in the combination of acquisition and retention, not one or the other.
A standard plan often isolates media, creative, and email. This engagement connects checkout, customer segments, retention workflows, and reporting so the store can see the full path from first click to repeat order and make better profit decisions.
Deliverables
Outcomes
The team can see which campaigns and products are actually creating profitable sales.
Lifecycle automation and segmentation support more efficient customer reactivation.
Cart and browse abandon flows bring back more ready-to-buy shoppers.
Campaign structure and creative testing improve signal quality and reduce waste.
The brand can make merchandising and inventory decisions with better performance data.
Proof
$38,944
Total Revenue
LOCKSTOCK
$32.8K
Net Sales After Returns
16%
Return Rate
58%↑
Increase in Monthly Online Orders
Confidential Marketplace Partner
$120
Average Order Value (AOV)
4.2X
Return on Ad Spend (ROAS)
4.2M+
Total Impressions
Fresh Food Ecommerce Brand
55K+
Link Clicks
8,470+
Orders via Paid Ads
FAQ
It is ecommerce-first, but the exact stack can be adapted if your store uses other supported tools. The important part is the connection between media, checkout, lifecycle, and reporting.
We care about ROAS, MER, CAC, AOV, LTV, cart recovery, repeat purchase behavior, and product-level performance. Those numbers show whether growth is profitable, not just busy.
We audit it and fix only what is missing, misfiring, or distorting the data. Good systems are kept; broken or incomplete ones are cleaned up.
Yes. We use a creative-testing loop and catalog performance review so the store can learn which messages and products actually move the business forward.
We need product clarity, analytics access, and access to the ad, email, SMS, and ecommerce tools that power the store. That lets us connect the full path from click to repeat order.
ROAS can hide a lot of business reality. This system adds margin-aware reporting, repeat purchase context, cart recovery visibility, and product-level signal so you can judge whether growth is actually healthy instead of merely busy.
We need clean access to Shopify, analytics, media accounts, email and SMS tools, and a clear view of the offer stack. That gives us enough to connect checkout events, lifecycle flows, and reporting without building around missing inputs.
Next step