Introduction & Context:
Bio Vita is a fast-growing health supplements brand focused on natural wellness products. Serving a health-conscious audience across multiple digital platforms, Bio Vita offers everything from immune-boosting vitamins to fitness supplements. However, as the brand scaled its product lines and digital presence, it became increasingly difficult to measure performance across sales, inventory, customer engagement, and marketing in a consistent and actionable way.
Initial Challenges:
– Siloed Data Systems: Multiple tools for sales, email marketing, and e-commerce made data aggregation a slow, manual process.
– Delayed Decision-Making: Critical KPIs (e.g. best-selling SKUs, stock levels, campaign performance) were often outdated or inconsistent.
– Missed Revenue Opportunities: Without predictive forecasting or deep customer segmentation, upsell and retargeting campaigns underperformed.
The Challenge (Pain Point & Problem Statement):
Primary Issues:
1. Fragmented Reporting: No single source of truth for marketing, sales, and customer data.
2. Inefficient Tracking: KPI reports were updated manually, often days after the fact.
3. Lack of Customer Insight: Personalization efforts were generic, hurting LTV and repeat purchase rate.
Quantifiable Pain Points:
– Average reporting delay: 72 hours
– Campaign ROAS: Dropped from 2.1x to 1.4x in 3 months
– Repeat purchase rate: 17%, well below industry benchmarks of 30%+
Category
Analytics/BI
Clients
Bio Vita
Location
Morocco
Led & Executed by:
Mohamed Chourouki
The Strategy & Execution (Step-by-Step Breakdown of Actions Taken):
A business intelligence transformation was launched to centralize data, visualize metrics, and improve strategic forecasting.
Phase 1: Data Consolidation & Warehouse Setup
– Integrated data from Shopify, Klaviyo, Google Ads, Meta Ads, and Google Analytics into a BigQuery warehouse.
– Established automated pipelines using Supermetrics and Zapier to maintain real-time sync.
Phase 2: BI Tool Deployment & Dashboarding
– Implemented Looker Studio to build role
-specific dashboards: Executive, Marketing, and Fulfillment.
– Created real-time trackers for key KPIs: ROAS, CTR, conversion rate, best
-selling SKUs, and inventory velocity.
Phase 3: Advanced Customer Segmentation
– Grouped customers based on behavior and LTV: first-time buyers, loyal repeat buyers, cart abandoners, and inactive leads.
– Fed segments into Meta Ads and email flows for more targeted campaigns.
Phase 4: Predictive Analytics Integration
– Built a SKU-level forecast model using historical sales and seasonality trends.
– Identified top 10 products with highest margin and reorder frequency for upsell focus.
The Challenges & Roadblocks:
1. Data Quality Conflicts: Different platforms defined KPIs (like conversions) inconsistently.
– Solution: Standardized metrics across platforms with shared definitions and validation rules.
2. Resistance to Tool Adoption: Teams preferred legacy spreadsheets.
– Solution: Offered side-by-side training and created dashboard templates to simplify the transition.
3. SKU Variability: High volume of products led to dashboard clutter.
– Solution: Introduced smart filters and category breakdowns to highlight what mattered most.
The Results & Impact (Before vs. After Data Comparison):
Key KPI Improvements:
– Reporting Speed:
– Before: 72 hours (manual)
– After: Real-time (automated pipelines)
– ROAS (Marketing Campaigns):
– Before: 1.4x
– After: 3.2x
– Repeat Purchase Rate:
– Before: 17%
– After: 34%
– Top SKU Forecast Accuracy:
– Before: No forecasting
– After: 91% accuracy, enabling better stock planning
– Revenue (3-month period):
– Before: $98,000
– After: $136,000 (+39%)
Key Takeaways & Lessons Learned:
1. Centralized Data = Faster Decisions: Aligning marketing, ops, and finance around real-time data changed how fast Bio Vita could act.
2. Segmentation Drives ROI: Tailored offers to customer types significantly increased repeat purchases and ROAS.
3. Forecasting Protects Revenue: Knowing which products would sell helped reduce overstock and boost ad performance.
4. Training Matters: Getting team buy-in required not just dashboards, but clarity and usability.
5. BI is Ongoing: Weekly reviews and dashboard refinements are key to staying proactive.
Conclusion & Final Thoughts:
Bio Vita’s Business Intelligence initiative enabled the brand to scale responsibly, increase profitability, and improve retention in a data-driven way. The project proved that when BI is paired with clear KPIs and accessible dashboards, teams can pivot faster, personalize better, and plan smarter.
Scalability Potential:
– Add predictive churn modeling to increase LTV.
– Build in influencer campaign attribution across platforms.
– Use cohort analysis to further refine product lifecycle strategies.
This case study demonstrates how BI is not just about dashboards—it’s about empowering teams with the insights they need to win.
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