Recently we finished a project with one of our customers worxogo.
Worxogo are in a very interesting field. The data for which we were working came from one of their solutions for gamification of sales. Amongst other means, they also use ‘nudge’ which was recently in news because Richard Thaler, the father of ‘nudge theory’, has been awarded the Nobel economics prize for year 2017. Richard Thaler came up with the concept of ‘nudging’ people through subtle changes in government policy to do things that are in their self-interest. As per Wikipedia, “Nudge Theory” is “Nudge theory (or nudge) is a concept in behavioural science, political theory and economics which proposes positive reinforcement and indirect suggestions to try to achieve non-forced compliance to influence the motives, incentives and decision making of groups and individuals”.
The data we got was for varied customers including –
1. a manufacturing and sales company and
2. financial services company.
The outcome of the project was –
1. Create a data model – This included creating a single view of the data from different sources.
2. Getting Insights from the data with respect to Sales achievement and the gamification components.
The data was from different tables and the diagram below details the process –
The data was from different tables –
1. User table
2. User Personality
3. Leader Board
6. KPI’s (daily, weekly and monthly)
7. Google Analytics files
We process data from all tables, mark duplicates and merge them all to create the data model. Based on requirements/analysis we then create as many data marts required for reporting and analysis.
We initially started with single day data and merged all data from different sources into a single data model. Then we did the same for one month’s data and then we included all data we were provided with. We did this stage wise process to validate the design process.
The challenge was that the the KPI’s were defined on daily, weekly and monthly basis and the google analytics data was on an hourly basis.
So, we had to create a single view of the data to capture the hourly google analytics data and also the daily, weekly and monthly KPI’s.
Once the data mart was there, it was exported to excel format for creating reports using pivot tables.
Below is the screen shot of one of the reports we created in excel –
Data Marts and Analysis
We also analysed the different gaming aspects with respect to the KPI’s achieved.
With the analysis using visualization, we got some valuable insights and something for the business to think about and take an action on.
Some of the analysis and insights we came across –
The viewing habits of the employees on different days of the week –
In this plot the X-axis is the hour when employees engage with the mobile application and Y-axis is the day of the week.
Similar to this we had also plotted Viewing habits of the employees by personality.
This would help the business to understand the time when the employee engages with the mobile application and hence can be suitably used to target the message/nudge from the application/process to the employee at the preferred time to be more effective.
In the plot below, we plotted two metrics besides each other to get more insights .
These gives an insight into the relationship between the two metrics.
In the plot below, we captured the metrics before and after an event to give more insight into the event management.
Here we plotted the vintage chart of the KPI’s achieved for a month. We grouped the employees and plotted the different groups to check the behaviour. This shows the pattern in the KPI achievement process for a month. The vertical lines are specific events, and the horizontal lines (solid and dashed) are the average for the groups.