Horizontal vs. Vertical Analysis

Horizontal analysis and Vertical analysis

One is analyzing all the customers in the population 'at a given time in their lifecycle'
Other is analyzing all the customers in the population 'as-is'

The WFR Problem India vs. China
We ran into an interesting problem last week. The web failure rate or WFR (Refer for definition & meaning: WFR Meaning) of India was 3x that of China. Immediately the first thought is 'Is China support site better than India support site'?
Other hypotheses that come top of mind - 'China has local language support in their support site', 'Chinese customers are probably more net savvy'........
Or maybe 'we need to get more data :) and drill down to an LOB level'

Why we would have never found an answer
This was a classic example where no amount of analysis/drill-downs would get us to a solution. What we were looking at was essentially was an analysis 'as-is' level - at an 'aggregated' level.

Please note: all numbers are dummy and not real

Getting everybody to the same point
Analyzed the customers into 2 buckets:
Once that had a problem: 'Contacted Customers' or 'Contacted ASUs'
The full bucket: 'All Customers' or 'All ASUs'

The clue was that web failures/Contacted Customers was same in India and China.



whereas the web failures/all active customers was comparable


This pointed to higher proportion of installed base in India contacting


Looked at the systems by their age and found the culprit - India has a higher proportion of newer systems than China. This results in Indian customers having a higher WFR because newer systems tend to have a larger # of problems in the first half of their lifecycle



An excellent example of why it is important to look at horizontal analyses getting everyone to the same point

Analyzing Effectiveness of an e-support site

For an introduction to e-support sites:
http://webanalyticsnuggets.blogspot.com/2010/11/benefits-of-efficient-support-site.html

Web Failure rate
The single most important metric to analyze success of an e-support site is 'Web Failure Rate' or WFR.

It is defined as the proportion of support site visits that did not find a solution to their problem online. So if there were 100 visits to the support site and if 20 of them did not find a solution to their problem online, the web failure rate is 20%

How to calculate Web Failure Rate:
This is the tricky part.
That a visitor did not find a solution to their problem online is proven if he contacted a non-online channel to find a solution. This could be a call by the visitor to the toll free #.

In this scenario, there has to be a common field that links the visitor to the caller. It could be a 'service tag' or it could be a 'customer number'.......
In case of unique service tags or customer numbers, the visitor would enter it to find a solution on support site; and would also refer to it during his call with the customer service representative.



The shaded area above is web failures.

The key in e-support is to minimize the web failures and hence the web failure rate (WFR)

Will post on the other metrics that are used in e-support in a separate post

Benefits of an efficient Support Site

Most ecommerce sites provide support:
1. Support on product usage - To provide support on user queries on product usage. This maybe part of the package that the user bought like an 'add-on' or these maybe queries that the user is entitled to having bought the product
2. Support on product failure & product related problems - Products fail and can have problems during their in-warranty period. This is support that both the seller and the product manufacturer are required to support. Even if the product manufacturer is supposed to handle it, nothing stops the customer from contacting the seller - and forms an important component of customer experience

Support can be provided by:
1. Having a toll-free number where folks can call in
Cons:
* Need to have a dedicated staff to take on the calls - FTE Cost
* Cannot cross-use staff on other activities, during peak season there are likely to be a higher number of calls - FTE Slack time
* Low FTEs means high waiting time - Customer Satisfaction Effected
High FTEs means high idle time
* Core Competency logic may result in moving this to a 3rd party meaning lesser control
* Variability: Customer may have varying levels of satisfaction depending on the person he contacted - Bearing on Customer Satisfaction

Pros:
* Personalized Experience

2. Having a site where users can find solutions to their problems

Pros:
* Zero Ongoing FTE Cost
* Having clear paths for common problems can ensure that 70-80% of the problems have the same kind of resolution path with no variability
* Overall - cost of resolving a problem online is much lesser than resolving a problem offline (that is through a call)


So an efficient support site can reduce the overall cost of ownership of running an e-commerce business