TellApart Data Assignment Kevin Wheeler 10.30.2013
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