EBATES: Web Portal and Promotion Analysis
EBATES: Analysis of an Online Coupon Web Portal
EBATES is an online coupon web portal website launched in 1998. Β Sold in 2014 to Rakuten, a Japanese shopping website for $1B, EBATES offers consumers cash back who useΒ the portal to find retail shopping discounts.
To date, EBATES has paid consumers $1B in cash back rewards since website inception. Β The average cash back value on purchases made with retail partners is 5%. Β EBATESΒ has 6 million users, over 2,000 retail partners and continues to grow and acquire other coupon website portals. Β Β Source: Motley Fool
Given EBATES' success as an online coupon aggregator, do the discounts offered on the website impact purchase behavior or increase cash back to consumers who make more purchases with retailers? Β This blog post will explore this theory using a web scraped dataset from EBATES and R code visualization analysis.
EBATES Business Model
EBATES partners with web retailers to offer discounts and cash rewards to online shopping consumers. Β As an aggregator of retail offers, EBATES requires consumer registration before using the websiteΒ to capture useful consumer data. Β Once registered, EBATES consumers will search for their shopping destination, click on a cash back offer and redirect to the retail partner website for online shopping. Β Any purchases made with the retail partner is passed back to EBATES and calculated in the consumer's account as their cash back shopping reward. Β Quarterly, EBATES will send rebate checks or deposit cash into the consumers Pay Pal account. Β
EBATES generates revenue through paid commissions based on their web referrals to retail partners.Β
Website Demographics
The EBATES core consumer is female and college educated who shops online both at home and work. Β Typically college educated females are employed, therefore, this specific demographic doesn't have a lot of time to go to brick-and-mortar stores to shop. Β Instead, they opt-to use EBATES to gain a cash back discounts on itemsΒ they would likely purchase anyway. Β
The following chart illuminates the EBATES' core consumer:
source: Alexa, Amazon
Scraped Data from EBATES
Using scrapy and selenium as web scraping tools to capture data from the EBATES website, the web spider crawled through a table of all currentΒ retailers to capture the following dataset: retailer name, total coupons/discounts offered, current coupon promotion and cash back since website inception. Β Once that data was captured and cleansed, additional variables were calculatedΒ as a function of % cash back and total retail purchasesΒ to enhance the data collected. Β
In total, a full dataset was developed on 1,500 retailers (2,200 in total) with the balance maintaining secrecy around total cash back. Β Without total cash back as a variable, it was difficult to makeΒ any conclusions about a retailer or consumer behavior other than highlight theΒ number of coupons offered since site inception. Β
The biggest retailerΒ holding back proprietary cash back data is Amazon. Β
Analysis: Top EBATES Retailers by Total Cash Back to Consumers
Prioritizing by total cash back to consumers, the top retailers in the dataset follow in the table below. Β Clearly, these retailers are aligned with the core demographic described previously with Macy's being the top shopping destination through the EBATES web portal.
Looking at a visualization of the top 50 retailers by total cash back and total purchase amount, the visualization indicates there is a relationship between the two variables as demonstrated by the regression line in the chart below Β However, one would assume there would be a strong relationship between these two variables anyway; thus you cannot necessarily derive a meaningful conclusion other than when sales increase, more cash paid back is paid to consumers through these top retailers.Β
Analysis: EBATES Consumer Coupon Promotion by Retailer
Taking the analysis to the next level, the relationship between total coupons and total cash back was reviewed and visualized. Β In theory, if the retailer offered more coupons, then there should be more sales and ultimately cash back paid to the consumer.
However, based on the visualization below, there is a relationship between the two variables however it is a weak one based on the slope of the regression line. Β In some cases adding coupons or discounts help generate cash back to consumers but isn't a strong indicator that this type of promotion will drive business to one retailer or another.
Looking further into the dataset, the same analysis was generated on retailers at the mean of total cash back. Β Two hundred observations were included +/- from the mean.
As the visualization indicates below and similar to the top 50 retailers visualization, there isn't a strong relationship between total coupons offered versus cash back paid to consumers.
Promotions Summary and Next Steps
Based on the data collected and derived, there were no strong relationships found based on coupon promotion and total sales when graphed against cash back paid to consumers. Β However, one point does stand out which is difficult to quantify and that relates to brand. Β With strong, established retail partners, EBATES has been able to attract and grow into one of the largest coupon sites on the webΒ and is ranked as the 383rd most visited site.Β source: Alexa, Amazon . Β For it's core consumer, EBATESΒ has become a pass through destination when web shopping.
More data and time would yield actionable promotional results for EBATES. Β Such analyses include: analyzing segmentation by retail category, length of retail relationship with the site, consumer profiling, promotional dataΒ performance on the home page and A/B testing of offer, promotion position and creative.
Further to this list, there are many more analyses to be reviewed to truly optimize the promotional value of the site and drive incremental revenueΒ for partners and EBATES as a whole.
Scrapy and Selenium Code
Following is the scrapy and selenium spider utilized toΒ capture the relevant data from the EBATES websiteΒ included in this analysis.
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Johnna Ayres
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