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Lead Generation for E-Commerce & Retail Companies

E-commerce buyers are the most data-literate B2B audience: they track CAC, ROAS, LTV, and conversion rates in real time and evaluate every vendor against their own dashboards. Generic outbound fails completely because these buyers have specific metrics to compare against. Category-matched proof — showing skincare brands what happened for other skincare brands, showing Amazon sellers what happened for other Amazon sellers — closes the gap between “interesting” and “let’s talk.” Convert achieved a 70% close rate and 315KinrevenuebecauseeveryprospectsawresultsfromtheirexactDTCcategory.SourceKnowledgegenerated315K in revenue because every prospect saw results from their exact DTC category. SourceKnowledge generated 210K from platform-specific competitive comparisons against Meta and Google.

Why E-Commerce Outbound Is Different

Three characteristics make e-commerce outbound fundamentally different from other verticals: Data-rich buyers evaluate against their own dashboards. An e-commerce founder seeing “we improved ROAS by 340%” immediately compares that to their current ROAS. If the claim is in the right range for their category and scale, it’s credible. If it’s implausibly high or from an irrelevant category, it’s dismissed. Convert’s 70% close rate came from category-specific metrics that matched what DTC buyers expected from their market. Category matters more than company size. A 5Mskincarebrandhasmoreincommonwitha5M skincare brand has more in common with a 500K skincare brand than with a $5M electronics brand. Buying patterns, margins, customer acquisition channels, and competitive dynamics are category-specific. Evolved Commerce’s Amazon-native messaging succeeded because it spoke the language of marketplace sellers — ACOS, buy box win rates, and review velocity — not generic “e-commerce growth” language. Rapid decision cycles reward speed. E-commerce founders make vendor decisions in days, not months. If the outreach is relevant and the proof is compelling, meetings happen quickly. Convert’s 84 meetings reflect this velocity — DTC founders who saw category-matched results moved fast.
Convert’s 70% close rate — the mechanism: Category-matched DTC case studies created a “that’s exactly my situation” reaction. When a skincare brand founder saw results from another skincare brand at similar scale, the sales conversation started with credibility already established. This is the highest close rate across all 44 campaigns — and it’s entirely attributable to category matching.

How We Target E-Commerce Buyers

Targeting CriteriaDetails
Primary TitlesDTC founders, e-commerce directors, marketplace sellers, heads of growth
Revenue Range1M1M-25M — past proof of concept, actively investing in growth
Platform FiltersShopify Plus, BigCommerce, Amazon (Seller Central, FBA), WooCommerce at scale
Category MatchingProspects matched to case studies from their exact DTC category or marketplace vertical
Signal FiltersIncreasing ad spend (Meta/Google), new product launches, platform migrations, seasonal scaling
InfrastructureAzure enterprise setup
ExclusionsPre-revenue brands, brands under $500K revenue, pure marketplace resellers without brand

Our E-Commerce Outbound Approach

1

Category-Matched Case Study Deployment

Every prospect receives outreach referencing results from their specific e-commerce category. Skincare brands see skincare results. Amazon sellers see Amazon results. This matching produces the 70% close rates that generic outreach can’t approach.
2

Platform-Specific Targeting

E-commerce companies are segmented by platform. Shopify Plus brands have different pain points than Amazon sellers, who have different challenges than BigCommerce merchants. Zycada’s campaign targeted BigCommerce merchants specifically because that platform’s sellers face unique scaling challenges. Platform-specific targeting produces 2-3x the engagement of platform-agnostic outreach.
3

Marketplace-Native Metrics Messaging

E-commerce messaging uses the metrics buyers actually track: ROAS, CAC, LTV, ACOS (for Amazon), conversion rate, average order value. SourceKnowledge’s $210K came from competitive comparisons using platform-specific performance metrics that media buyers evaluate daily.
4

Speed-Optimized Sequencing

E-commerce buying cycles are fast — 7-21 days from first touch to agreement. Sequences use 3-5 day email spacing, same-week LinkedIn touches, and AI calling within 48 hours of email engagement. This cadence matches the velocity e-commerce founders expect.
E-commerce trigger events: Increasing Meta or Google ad spend (visible in ad library), new product launches, platform migrations, seasonal ramp-up periods (Q4 for DTC, Prime Day for Amazon), and marketing leadership hires.

E-Commerce Campaign Results

ClientRevenueMeetingsClose RateROIPlatform Focus
Convert$315K8470%5,733%DTC (Shopify)
SourceKnowledge$210K701,358%Ad Tech
Velox Media$180K601,567%E-Commerce Marketing
Evolved Commerce$54K33900%Amazon

What Makes E-Commerce Outbound Fail

Generic marketing metrics to data-literate buyers. E-commerce operators don’t care about “leads generated.” They care about ROAS, CAC, and LTV. Messaging that uses generic marketing language signals the sender doesn’t understand the business. Category-agnostic proof. A fashion DTC brand doesn’t care about B2B SaaS results. Category matching isn’t a nice-to-have — it’s the mechanism that produces 70% close rates versus 1-2% reply rates from generic outreach. Slow cadences for fast buyers. E-commerce founders make vendor decisions in days. A 14-day email sequence with polite spacing loses prospects to faster competitors.
Yes — Evolved Commerce’s campaign targeted Amazon sellers using marketplace-native language: ACOS optimization, buy box win rates, review velocity, and FBA logistics. Amazon sellers respond to outreach that demonstrates understanding of marketplace dynamics, not generic e-commerce messaging. The key is platform-specific targeting (Seller Central sellers at $1M+ revenue) combined with metrics they track daily.
Close rates vary by category match quality. Convert’s 70% represents the ceiling through exact category matching (DTC skincare to DTC skincare). More typical e-commerce campaigns produce 20-40% close rates from outbound-generated meetings — still above most verticals because of fast decision cycles and data-driven evaluation.
E-commerce campaigns typically produce initial meetings within the first 2 weeks — faster than any other vertical in our portfolio. Fast decision cycles work in outbound’s favor: relevant proof gets fast responses.
Yes — wholesale outbound targets retail buyers, category managers, and merchandising directors. The messaging framework shifts from DTC metrics (ROAS, CAC) to retail metrics (margin, sell-through rate, category velocity). The targeting uses different signals: retail expansion announcements, new store openings, and category gap analysis.
E-commerce campaigns adjust volume and messaging seasonally. Q4 outreach intensifies during September-October as brands plan holiday spend. Prime Day preparation outreach targets Amazon sellers 60-90 days before the event. Off-season messaging shifts from immediate revenue to planning and optimization positioning. The infrastructure supports volume scaling without deliverability degradation during peak periods.