Utilizing the new ARAP Traffic Report
Updated: May 2, 2019
For the past month I have felt that there was more utility to be gleaned from the new traffic report in ARA Basic. I finally made a breakthrough in being able to turn the % of Total GV (Glance Views) into Actual GVs, which then let me calculate the conversion rate for each ASIN. If you would like to know my % GV trick just email me at firstname.lastname@example.org and I will email it to you.
A problem that always exists for people in Vendor Central is taking all the data thrown at you and turning it into a useful set of actions. The Traffic data report is giving you information on what people are looking at and how often that gets converted into sales by Amazon. In this blog post, I develop actionable insight by adding sales and cost data to conversion rate and glance views to distinguish opportunities meriting better marketing e.g. PPC, from those that merit more effort to improve conversion rate e.g. product page description, photos, or A+ page investment.
In this first example, I produce a 2x2 comparing Conversion Rate on the x-axis with what I am calling Glance View Revenue on the y-axis as a surrogate for potential market size. Glance View Revenue is the number of glance views multiplied by the sell-in to Amazon cost i.e. your revenue at 100% GV conversion rate for that product This y-axis could also be framed to represent profit, or remaining untapped market for further insights.
This 2x2 has the effect of segmenting ASINs into 4 groups that are: 1. your portfolio stars (upper right) that are doing well and do not need immediate attention
2. those that you should work to fix the conversion rate through product page improvements (upper left)
3. those that you could be marketed better to drive up the GVs (lower right)
4. the dogs and cats that are not worth worrying about at this time (lower left).
Note that if an ASIN is out of stock (or has been for a majority of the period you are looking at), then these will show up as needing conversion rate fixing. I also threw out some high conversion rate ASINs that just got lucky for the week. Monthly data will probably give you better results than weekly but it depends on your product mix.
Another provocative analysis is to rank all ASINs based on “Potential Glance Revenue”. This metric aims to estimate the untapped residual market value if conversion rate could be improved to 100%. This was calculated by multiplying GVs x (1 - conversion rate) x Unit Revenue and then sorting from largest to smallest to the following chart:
While I hid the actual ASINs, this gives me a quick visual way of seeing the ASINs for which spending time on the product pages or doing a lightning deal may lead to increased sell-out which should lead to more orders from Amazon. The top 6 or 7 ASINs were the predictable top ASINs, but the remainder of my top 20 surfaced some interesting ideas.
For me these two KPIs and associated charts gave me ideas for demand-side improvement actions. If you are interested in automating KPIs like this take a look at the Merchant AI Dashboarding section. I hope this sparks some ideas for people on how to use the traffic data Amazon is giving you in a better way. I would love to hear about any other analysis people are doing with information from the traffic report. Please leave a comment, message me, or send me an email to email@example.com.