TellApart Data Assignment

Kevin Wheeler

10.30.2013

Impression and clicking activity fluctuate leading up to holidays

The number of users impressioned and number of users clicked shows similar behavior

- Total

- Users

- Total

- Users

The growth in total number of impressions/clicks outpaces the increase in

user growth

Click-through rate does not show obvious trend

Upcoming holidays and post-Thanksgiving sales may cause spike in conversion rate

Purchasing activity drops off a couple weeks prior to holidays

Sales may account for decrease in average order amount heading into holidays

Post-Thanksgiving drop off in purchasing activity accounts for revenue fluctuation

Conclusions

• Increased impressions per user and stable click-thru rate are driving traffic, order volume, and revenue growth

• Holiday shopping accounts for unusual user behavior– Holiday sales account for dip in average order size– People wait for sales/holidays to buy

• Overall, trends seem promising when holidays taken into consideration– Increased impressions don’t cause significant drop-off

in click-through rate and conversion rate– Revenue doubles after holidays

Extras

Click-thru rate measured on a per-user basis follows similar behavior

Observations• Click thru rate (users_clicked / users_impressioned) relatively stable after

holidays (slight decrease)– However, clicks per user (clicks / users_clicked) increases quite a bit– Clicks / users_impressioned decreases thru holidays (from 0.035 to 0.02) then

jumps and stabilizes (0.03)

• Conversion rate (num_orders / users_impressioned) also relatively constant whereas num_order per impression is amazingly flat/constant– Num_orders / users_clicked (clicks) spikes during holidays, slowly decreases

• Impressions per user on the rise after drop over holidays• Avg lag hrs spikes during holidays• Avg order value (revenue per order) decreases during holidays (sales) and

then linearly increases after• Revenue per user_clicked (sum(order_value) / users_clicked) slightly

decreases over time– Same with revenue per impression

• Number of orders per day increases, drops off in days after holidays, then begins to increase again. Similar behavior as revenue per day, users_clicked per day, and clicks per day