India Plaza Case Study
SkyGlue helps Indiaplaza identify fraudulent clicks.
Company Bio
Founded in 1999, Indiaplaza is one of the pioneers in the online shopping space in India. Indiaplaza offers nearly eight million products online including books, CDs, cameras, mobile phones, apparel, jewelry, flowers, chocolates, watches and food items, and has nearly 1.5 million customers worldwide.
Problem
There are some categories (perfumes for instance) where a lot of people add products to their cart but never buy (99 percent people who add to cart did not buy). The apparel category is experiencing the same problem.
Overview
The following is the conversion funnel for visitors who added perfumes to their cart. We can see that most visitors did not reach the second step (login). The funnel steps can be observed easily from the SkyGlue user drill-down report of a successfully converted customer.
Analysis steps:
We created a segment for visitors who added perfumes to their cart but didn’t visit the login page in order to further examine them in SkyGlue.
In SkyGlue, we see many visitors from the United States.
This can be verified in a Google Analytics report (from individual to segment):
The first reaction was: Maybe they drop out since Indiaplaza cannot ship perfume to US. In some cases, this may be a good conclusion.
However, upon further examining the SkyGlue user report, we find the visitors from US are concentrated in a couple of cities. This is abnormal. We then drilled down to these visitors to see what they did and how they came. The following is an example report of a visitor from New York:
After looking at several visitor reports like this, we find almost all this traffic is directly from Amazon.com Inc. They do not click other links except “Add to Cart” and they navigate through the website without clicking links. They are most likely machine generated visits (bots).
Without SkyGlue, it would have been impossible to get such level of details of on-page activities. It would also have been impossible to see all the information about an individual visitor at a glance in Google Analytics, so it would have been very hard to come to the conclusion that all the traffic is from Amazon.com.
We could then easily verify the problem in Google Analytics and see almost all visitors from US are from Amazon (from individual to aggregate).
Conclusion:
The drop out is caused by traffic from Amazon.com. These visitors are machine generated (bots). Since Amazon is a competitor, this needs to be brought to the attention of the business team. On the analytics part, you can filter out traffic from Amazon.com using a Google Analytics filter.
The following is the traffic trend from Amazon.com. We can see the traffic started in May and has grown dramatically recently.
Fixed Conversion Funnel
This is the conversion funnel after filtering out Amazon traffic. This is much more reasonable. We can use Google Analytics and SkyGlue to further improve the conversion funnel.
This above process demonstrates the efficiency of using SkyGlue in combination with Google Analytics to learn quickly and get insight from our Google Analytics data.
