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An ecommerce store experienced a significant drop in open rates. I identified the root causes and outlined the corrective actions needed to restore engagement and deliverability.
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Just concluded a project and I have come to the conclusion that open rates are vanity metrics!
If your email automation is working, you won’t care about opens.
You’ll care about what changed after the email fired.
Did they:
– complete the lesson
– return to checkout
– upgrade
– stop ghosting
Email marketing celebrates sends.
Email automation measures decisions.
That difference is why some inboxes print revenue
and others just look busy.
Exactly
An email isn’t successful because it was opened, it’s successful because it moved someone to act.
Stop selling "bottles" and start selling "outcomes.
you can see how a simple shift in bundle architecture turns a one-time purchaser into a recurring customer.
Higher AOV isn't about better design it’s about better conversion architecture.
Building high-performance Shopify pages for brands ready to scale. Let’s talk.
Project: Velocity SaaS – Revenue Turnaround Analysis
Type: Independent portfolio project
Dataset: Synthetic B2B SaaS, 2,000 accounts / 2.2M rows, benchmarked against ProfitWell/OpenView
What I did:
MRR waterfall analysis, churn segmentation by plan/industry/channel
Usage decay / silent churn risk modeling
Logistic regression churn predictor: 98% recall, 70% precision, 0.82 F1
Built executive Looker Studio dashboard + Streamlit churn predictor
Outcome: $411K silent MRR at risk identified, CS-ready prioritized account list
Stack: SQL, DuckDB, Python, Pandas, Scikit-learn, Looker Studio, Streamlit
Live app: velocity-saas-churn-predictor.streamlit.app
Repo: github.com/SURAJRAJPUT2006
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