My work for the last three years has heavily revolved around the campaign and paid media based revenue and digital media analysis. Alongside that I have taken a deep dive into building out customer loyalty and retention programs as well as data driven acquisition methods.

I have built out loyalty campaigns through referral programs that I have coded and set up myself at Shredz where we built a credit offer for refer a friend system. We have also built loyalty programs based on customer life time value and order amount over a course of 3 months where loyal members would get access to exclusive content etc.

Retention has been key at ALOHA since it was a subscription business where I helped build out a 16 email communication point between the first interaction of a new customer all the way till the win back after they churned. I helped increase retention from a poor 11% to 23% in 3 months at ALOHA.

In addition I have built segmentations utilizing both internal behavioral scores and external behavior scores that attributes to differentiate customer base

I was involved in the process of model development (response, acquisitions, risk of churn, optimize response/spend, customer lifetime value studies, etc.) which helped with understanding retention patterns.

I was also involved in sensitivity analysis - developed cohort analysis between engagement of a consumer or a non buyer and understand how to acquire or retain based on content engagement and behavior patterns.

I also built segmentations utilizing transactional level data, demographic variables, shopper data to differentiate customer base and to understand what makes a loyal customer versus a one time purchase.

Using campaign analytics (test design-design statistically valid tests (control/test), incremental ROI analysis to determine campaign success on direct mail, email, digital, etc. campaigns) I was able to understand consumer behavior for a new versus existing customer based on organic and paid digital media.

I was also building out the analysis around marketing/customer lifecycle initiatives (acquisition, retention, reactivation, loyalty)

Lastly I utilized transactional data for the following analysis: (market basket analytics, share of wallet, cross sell, pricing, channel/product preference, migration analytics, pre/post treatment analysis) which heavily influenced direction of marketing spend on a existing customer versus acquiring a new one.

Overall I have had the ability to connect offline transactional/behavioral data to online click stream data to come up with the entire flow of understanding user behavior, purchase behavior, repurchase behavior followed by response to win back campaigns of lost customers.