Page 1: Introduction

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The Story I have recently joined a different team at the company I work for after a year and a half. The reason is being, the old role doesn’t spark joy any more, and I am excited for some new challenges. Then, I found this perfect role which has all the things I hope for, including more analytical, more data science driven, etc.. But, I am not familiar with this team at all. What is it?

The Team The new gig I am joining is the Email Marketing Team. It’s apparently the most free revenue driver of the company. Why? Because it costs nothing to send emails to our subscribers, and it actually drives 20% of the company revenue. And, it’s growting at 20% YoY.

The Work My onboarding project is basically to learn everything about Email Marketing. Understand what’s the current state, how it has been growting at such a high rate, and hopefully learn where the opportunities are so I can continue growing the program. Therefore, I made this dashboard to show my onboarding learnings and findings.

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Objective

The alternative objective for the Email program is to maximize long term CLV of customers by serving the right content at the right time and frequency across the customers’ entire journey.

If we would break down the customer journey into stages, we have:

Onboard: the Welcome email is used to onboard any new acquired customers. The onboarding flow offers a 10% discount for the first purchase with the goal to encourage the first purchase.

Convert: converting customers is one of the most important goals of the Email program, which this process generates the most conversions and GRS for the company. The Email program uses daily sales emails, triggered flows, and promotional emails to convert customers throughout the shopping journey.

Repeat: maximizing the customers’ CLV not only means purchase, but means repeated purchases. Driving repeat purchases and increasing customers loyal is a key focus for the Email program in the near team.

Re-engage: the Email program uses tactics to re-engage customers and to build a health loop for customers in different shopping stages.

Re-active: for customers who stopped shopping with use, the Email program offers a discount to customers for re-active purposes.

Overall objective for Email

Page 2: Performance Health Check

Customer Count by Segment: the email list is segmented into 6 segments: engaged, in-market, never engaged, newly acquired, recent purchaser, and unengaged.

Summary: this bar chart displays customer count growth by segment from Jan 2018 to Mar 2020. The data is acquired directly from the company’s database.

Observations: total email active list is growing at ~15% YoY and it’s around 5M today.

Q1: what has been causing the list growth? Is it mostly ogrinc growth driven by customers creating accounts with us and placing orders, or is it mostly driven by costly acquisitions?

Q2: we saw a significant drop in active list size in December 2019, which is an unusual trend. What happened in that month that caused the list decrease?

Segmentataion Bar Chart: it is important to understand the composition of the total active list. This bar chart shows as of March, 2020, the composition of the active list by segments.

Summary: this pie chart displays the composition of the total email list by segment as of March 2020. Data is acquired directly from the company’s database.

Observations: the largest segment is unengaged, followed by never engaged and engaged.

Q3: it would be interesting to understand what’s the unit economics of each segment. Which segment has the highest unit economics? And combining with segment size, which segment generates the most revenue?

Q4: given unit economics and segment sizing, where are the opportunity areas to focus on to drive incremental revenue?

GRS: GRS is one of the most important down funnel metrics that the Email program uses to track the program health, and it’s the ultimate goal of the program.

Summary: this line chart shows total revenue generated by the Email program by segment from Jan 18 to Mar 20. Data is directly acquired from the company’s database.

Observations: overall, the in-market segment and the recent purchased segment are the two highest segments in generating revenue. These two segments’ revenue also see fluctuation overtime.

Q5: what causes the revenue fluctuation for the in-market segment and the recent purchased segment? There was a huge spike in revenue in early 2019. What caused the huge spike in revenue around that time?

Visits: visits are a good indicator of how effective the Email program is in terms of sending people to site.

Summary: this line chart shows total visits generated by the Email program by segment from Jan 18 to Mar 20. Data is directly acquired from the company’s database.

Observations: at the first glance, we saw the in-market segment drives the highest visits to the site. We also saw a step function change in October 2018 where visits increased for all segments and increased dramatically for the in-market segment.

Q6: what change happened in October 2018 that caused the dramatic increase in visits for all segments?

Q7: combining with the GRS chart, we see the recent purchaser segment generates the highest revenue but has relatively low visits compared to the other two high visits segments. Does this mean the recent purchaser segment customers purchase higher ticket items than other segments? Or converting at a higher conversion rate?