$1.6M in Measurable Impact: How Saras Built Faherty's Decision-Grade Data Foundation Across Carrier Strategy, Inventory, CX Staffing, and Annual Planning

Faherty is an omnichannel apparel and lifestyle brand operating across ecommerce and approximately 75-78 physical retail stores nationwide, supported by a central warehouse and multiple third-party logistics partners. The brand runs high promotional intensity during Black Friday Cyber Monday and holiday windows, concentrating its highest order volumes, customer expectations, and operational demand into a compressed multi-week period.

Beginning in late 2023, Saras Analytics partnered with Faherty across operations, marketing, finance, retention, and customer experience to build a unified data foundation on Saras Pulse that enabled decision-grade analytics at every level of the organization.

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As Faherty scaled across channels, stores, and seasons, the scope and consequence of decisions expanded across six interrelated areas. The constraint was not lack of data. The challenge was making high-confidence decisions fast enough, particularly during peak periods.

• Reactive CX staffing: Holiday support was planned from historical averages and judgment. SLA compliance fell to 50-60% during peak weeks. Ticket backlogs exceeded 1,000 open items with no early warning signal.

• Carrier decisions at aggregate level: Carrier performance varied by state and season but was evaluated on blended averages. This created delivery risk and six-figure cost exposure during peak periods without granular visibility.

• Inventory locked in manual processes: Store-by-SKU inventory data spanned millions of rows. Manual extraction took up to 24 hours, making proactive safety-stock decisions impractical during high-velocity periods.

• Warehouse overtime with no accountability: Faherty incurred approximately $150K annually in overtime charges from its third-party logistics partner. The operations team suspected underutilization but lacked data to challenge the claims.

• Segmentation without activation: Customer data existed but segmentation was not connected to campaign execution. Retention efforts were broad rather than lifecycle-driven, leaving incremental revenue unrealized.

• Aspirational annual targets: Revenue planning was top-down with no mechanism to stress-test targets against real spend constraints, cohort behavior, or retention dynamics.

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Saras Analytics unified Faherty's customer, order, marketing, carrier, warehouse, and behavioral data into a single connected foundation built on Saras Pulse. On top of that foundation, Saras built domain-specific analytics capabilities delivering decision-grade intelligence across five areas simultaneously.

• ML-based CX staffing model: Connected orders, promotions, returns, carrier performance, and historical CX volume to produce day-level staffing recommendations weeks before peak demand. Weekly forecast-versus-actual recalibration reached 2-8% monthly variance during the live holiday period.

• State-level carrier performance dashboard: Shipment data refreshed twice daily via an automated pipeline. A 95th percentile delivery analysis identified exactly which states required premium carrier switching versus those where economy service remained safe, enabling targeted cost management.

• Store safety-stock recommendation engine: Automated daily ingestion of store-level inventory replaced a 24-hour manual extraction process. A weekly recommendation engine ranked store-by-SKU release opportunities by revenue upside, transforming store inventory from a static buffer into a monetizable asset.

• Warehouse performance transparency: Existing warehouse logs converted into a capacity-versus-actual throughput dashboard, separating inbound and outbound flows to surface where overtime was being charged against unused baseline capacity.

• Customer segmentation and activation framework: Value- and lifecycle-based segmentation directly activated in retargeting and retention campaigns across direct mail, handwritten notes, VIP gifting, email, and SMS channels.

• Scenario-based annual forecasting: Constraint-aware revenue model built on ARIMA and SARIMA statistical methods, historical customer cohort behavior, and marketing spend correlations, translated into an Excel-first output for FP&A usability.

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Teams moved from reactive adjustments to proactive decisions across every function. Analytics shaped carrier strategy, inventory releases, CX staffing, vendor negotiations, marketing campaigns, and annual budgets.

• $1.1M incremental revenue from segment-driven campaigns across direct mail, handwritten notes, VIP gifting, anniversary email, and Email over Summer Sale campaigns.

• $375K annualized revenue opportunity identified via store safety-stock monetization, with $35K realized in the first four weeks of implementation.

• $150K shipping cost savings in two weeks through state-level carrier analysis during the 2024 holiday period, keeping 30,000 shipments on economy service without compromising delivery promises.

• 90% SLA compliance during BFCM up from 50-60% the prior year. Peak backlog dropped 85%, from over 1,000 open tickets to approximately 150.

• 28% faster delivery times during the holiday period through carrier performance insights and proactive switching.

• 30% reduction in delivery-related CX tickets through proactive carrier adjustments and pre-emptive customer communication.

• $150K annual warehouse overtime exposure addressed through performance transparency and data-backed vendor discussions.

• 8-10% annual revenue forecast error under real spend constraints, enabling aligned financial planning and confident resource commitment.

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