Business objectives revolve around consumerism. To keep a check on all the business activities becomes the core objective of an organization. Organizations are striving hard to keep their analysis on check to avoid any kind of discrepancies. This interesting case study of HomeShop18 reflects the power of Google Analytics and how it helped the organization to find out the discrepancies in the data collected.
Google Analytics has become one of the most widely used analytical tool. Google Analytics acts as a complete package in meeting all the analytical requirements of an organization. The plethora of features bundled in Google Analytics help the user to gather smallest of details about the website and other online channels. HomeShop18 used Google Analytics to identify the discrepancies in the data they had collected.
About HomeShop18
HomeShop18 was established in the year 2008 and it is an on-air retail channel of Network 18 Group. It is India’s first channel which enabled people to shop sitting at home. Demonstrations on various products and services are given which help people in deciding their purchase. With the advent of internet, HomeShop18 gradually penetrated the online market by launching their website www.homeshop18.com. HomeShop18 website gradually climbed the ladder of success and became one the most frequently accessed e-commerce portal.
Business Objective of HomeShop18
Like any other e-commerce website, HomeShop18 had their own in-house analytical system. In order to get an additional insight, HomeShop18 implemented Google Analytics. To their surprise, the data generated by in-house analytical system and Google Analytics had about 25% discrepancy and the difference was huge.
The business objective of HomeShop18 was to identify the reason behind such huge difference in data.
Strategies adopted by HomeShop18
In order to identify the root cause of such huge differences in data, HomeShop18 partnered with Nabler.
Nabler is a digital analytics solution company and a pioneer in helping organizations take successful data-driven decisions. Nabler helps organizations to manage and evaluate their presence on various online platforms like social networking sites, websites, blogs, mobile applications etc. Nabler provides custom solutions to organizations to get thorough insight about their data.
Nabler has a huge experience in handling such cases of e-commerce portals and that makes easier for them to carry out the process. According to Nabler, at an average there exists 32%-36% discrepancy between the numbers generated by in-house transactional reporting system and Google Analytics data. The general factors that may lead to such discrepancies could be:
- Various payment methods available on the website like PayPal, Cash on Delivery, Google checkout etc.
- No proper tracking system in place. The organization may not be tracking their shipping charges, Gift wrap cost, promotional discounts, taxes etc.
- Other ordering options. For example; people may use offline methods like phone or POS.
Nabler ran down a check in the above mentioned areas for HomeShop18 but all this system came out clear. So, as an alternative, Nabler came up with few hypothetical scenarios to determine all the possibilities. The following were the queries around which Nabler worked for resolving the issue:
Query 1: Is the difference between in-house transactional reporting system and Google Analytics data happening on a daily basis or there exists some inconsistency in that?
Solution: Nabler implemented and trended differential data while setting it up at day level. The results indicated that the difference was on a daily basis.
Query 2: Does the data generated by both the systems has a disparity during certain hour (s) of the day?
Solution: Nabler used differential data by tracking the time of a day and they could see that the disparity was throughout the day.
Query 3: Is Google Analytics implemented by HomeShop18 unable to track the transactions of certain seller(s)?
Solution: Nabler used differential data which was segmented based on seller names. The results indicated that all the seller(s) transactions were being tracked perfectly.
Query 4: Is Google Analytics not able to identify or track certain products or product types?
Solution: The results indicated that all the products ids were getting tracked by Google Analytics at some point of time. So, this angle was also ruled out.
When all these queries were analysed and clarity was achieved, Nabler took the analysis to the next level. They created certain advanced segments within the analytical tool. While doing so, one of the segments indicated some interesting pattern. The report generated under this segment was able to track the visits to the confirmation page but the transaction details were not getting tracked by Google Analytics. HomeShop18 were very sure that this cannot happen because their system architecture could not be faulted.
In order to prove the point, Nabler did some purchases on the website. Then it was evaluated whether these purchases were generating transaction codes. When Nabler checked the page report under this segment, they could identify that the system was not generating necessary ecommerce tags for one particular product. When closely analysed it was identified that there existed an Apostrophe (‘) in the product name. This special character was breaking the flow of JavaScript code as Google Analytics considers this symbol as a delimiter which was resulting in 47% discrepancies in data.
Results Achieved by HomeShop18
- A slight error in the coding part was identified and rectified. As a result the transactional discrepancies reduced by 11.6%.
- Various other products which were not getting tracked could also be identified.
Learnings
Organizations implement in-house analytical tools and systems which is very well appreciated. But taking a second opinion is always good. Google Analytics has helped many organizations to resolve their issues and these examples are available all over the internet. HomeShop18 would have never been able to find out the real cause of their data discrepancy, if they had not gone for Google Analytics. A simple reason like that of including a special character during the coding kept the entire organization wondering. The querying method of analyzing the issue is a remarkable strategy when the organization do not know where to start. This helped the organization to analyse and discard all the necessary possibilities or reasons for discrepancies. As a result, the organization could carry out a detailed analysis of each and each section of the website to remove any kind of glitch.
Image Credit: HomeShop18
Interesting case study. Minor error in code can make such big discrepancies in result. Sometimes we could not see any fault in our own system. To get proper analysis of system it is always better to take second opinion.