> ## Documentation Index > Fetch the complete documentation index at: https://learn.outboundsystem.com/llms.txt > Use this file to discover all available pages before exploring further. # SourceKnowledge > SourceKnowledge spent $14,400 over 8 months and generated $210,000 in revenue — a 13.6x return. Ad tech platform for retail. Vertical-specific platform comparisons vs Meta and Google. 70 meetings booked, 31 responses per month. # SourceKnowledge — 13.6x ROI SourceKnowledge went from lost in the "better ROAS" noise to 70 booked meetings and an inbox so full of leads that follow-up capacity became the bottleneck — not lead generation. Vertical-specific platform comparisons against Meta and Google did the heavy lifting: fashion buyers saw fashion ROAS data, DTC consumables buyers saw consumables data. Generic "better performance" claims got replaced with numbers media buyers could evaluate against their own dashboards. \$14,400 \$210,000 13.6x 70 \$206 \$26,250 | Detail | Info | | ------------- | ----------------------------- | | Industry | Advertising Platform | | Company Size | 50-200 employees | | Services Used | Email + AI Calling + LinkedIn | | Duration | 8 months | ## The Challenge Retail marketing leaders are bombarded with "better ROAS" promises from every ad platform. SourceKnowledge needed proof specific enough to make a media buyer stop scrolling — not generic benchmarks, but vertical-specific ROAS comparisons showing exactly where SourceKnowledge outperformed Meta and Google in specific retail categories. Generic ad platform positioning without vertical-specific performance comparisons against the incumbent platforms prospects already used was getting buried in ad tech noise. **Before Outbound System:** * Generic "better ROAS" positioning lost in ad tech noise * No vertical-specific performance comparisons vs. Meta/Google * No systematic outbound to retail media buyers * Single-channel outreach missing decision-makers **After Outbound System:** * 70 meetings booked in 8 months * 31 qualified responses per month on average * Vertical-specific ROAS data displacing incumbent platforms * Follow-up capacity became the bottleneck, not lead gen ## The Solution Prospect lists targeted retail brands with aggressive paid acquisition budgets actively scaling spend on Meta and Google. Messaging led with vertical-specific ROAS figures showing where SourceKnowledge outperformed incumbents in fashion, home goods, and DTC consumables — numbers media buyers could evaluate against their own performance dashboards. ### Cold Email Sequences with platform comparison data: not generic benchmarks but vertical-specific ROAS figures against Meta and Google. Fashion brands saw fashion data. DTC consumables brands saw consumables data. Each email gave media buyers something to check against their own numbers. ### LinkedIn Outreach Targeted media buyers and heads of growth with personalized connection requests referencing the prospect's specific ad activity and vertical, creating familiarity before the platform comparison email arrived. ### AI Cold Calling Direct channel for high-spend retail brands, using brief scripts leading with the specific ROAS delta in the prospect's retail vertical. A 60-second call about category-specific performance converted interest into meetings. ### Beyond the Meetings * **Market Intelligence:** Campaign data mapped which retail verticals had the highest dissatisfaction with incumbent platforms, giving SourceKnowledge competitive intelligence for product positioning. * **Pipeline Insurance:** Multi-channel meant even if an email got buried, LinkedIn kept SourceKnowledge visible in the prospect's feed, preventing lost opportunities. * **ICP Refinement:** DTC consumables brands showed the highest response to platform comparison data, while fashion brands responded more to creative capability messaging, enabling per-vertical optimization. * **Capacity-Driven Growth:** 31 replies/month generated a high-quality problem: the bigger challenge became follow-up capacity, not lead generation. ## Campaign Timeline Retail brand targeting by paid acquisition budget. Vertical-specific ROAS comparison data compiled against Meta and Google benchmarks for fashion, home goods, and DTC consumables. Email, LinkedIn, and calling launched simultaneously. First responses within 6 days. Platform comparison data resonating immediately with media buyers. 31 replies/month pace established and sustained. Vertical messaging optimized based on response data by category. DTC consumables flagged as highest-response segment. 70 total meetings booked. Follow-up capacity became the primary constraint, not lead volume. Pipeline quality consistent throughout. ## Full Metrics Breakdown | Metric | Result | | ---------------------------------- | --------- | | Total Spend with Outbound System | \$14,400 | | Campaign Duration | 8 months | | Qualified Leads Generated | 248 | | Cost Per Qualified Lead | \$58 | | Meetings / Calls Booked | 70 | | Cost Per Booked Meeting | \$206 | | Show Up Rate | 77% | | Revenue Generated (cash collected) | \$210,000 | | New MRR Added | \$26,250 | | ROAS (on cash collected) | 14.58x | | **Total ROI** | **13.6x** | *All revenue figures reflect cash collected, not contract value.* > "I've got an inbox FULL of leads. My challenge is getting back to all of these leads." > > — **Naema Boisson**, Manager, Strategic Partnerships at SourceKnowledge ## Get Results Like SourceKnowledge SourceKnowledge proved that platform comparison data in specific retail categories cuts through ad tech noise where generic ROAS claims fail. If you sell into [e-commerce and retail](/industries/e-commerce) buyers, vertical-specific proof against incumbent platforms is the fastest way to earn a media buyer's attention. See how our [cold email service](/services/cold-email) handles enterprise deliverability and our [multi-channel outbound](/services/multi-channel) creates consistent 31+ response/month pipelines. See how vertical-specific platform comparisons and multi-channel outbound would work for your ad tech pipeline.