Introduction to DataMa Compare for Consulting, a tool that simplifies how you explain gap of a KPI between two segments

1. This information is confidential and was prepared by DataMa solely for the use of our client; it is not to be relied on by any 3rd party without DataMa's prior written consent
DataMa Compare
Introduction for consulting usage

2. This information is confidential and was prepared by DataMa solely for the use of our client; it is not to be relied on by any 3rd party without DataMa's prior written consent
What is DataMa Compare?
DataMa Compare is a software
licensed and developed in R by DataMa Company,
designed to help you understand
why A is different than B on a given KPI.
Once installed on your machine or within your organization,
it consumes your client’s data to
provide a simple visualization that will make your life easier.
You can try it free of charge on any client’s use case by
contacting us on:
www.datama.org

3. This information is confidential and was prepared by DataMa solely for the use of our client; it is not to be relied on by any 3rd party without DataMa's prior written consent
Use Case 1: Week on Week website performance monitoring
Client’s input DataMa Compare output
This client, an e-commerce website, wants to understand what’s driving the gap of Revenue/ User from one week to
another (read full use case description on DataMa Compare demo article)
An access to the Google Analytics API
providing e-commerce metrics, split by key
ecommerce dimensions
“ Revenue/ User drops by -19% mainly due to
conversion issues, caused by SEO traffic changes”

4. This information is confidential and was prepared by DataMa solely for the use of our client; it is not to be relied on by any 3rd party without DataMa's prior written consent
Use Case 2: Actual Margin vs. Budget
Client’s input DataMa Compare output
This client, a consumer good producer, wants to understand why his current absolute margin is higher than initially
budgeted.
An access to IBM Watson financial forecast,
with volumes, revenue and margin split by
product and countries
“ +27% higher margin vs. budget thanks to much
higher volume in Germany and higher price point of
product B than expected”

5. This information is confidential and was prepared by DataMa solely for the use of our client; it is not to be relied on by any 3rd party without DataMa's prior written consent
Use Case 3: Insite Page Content benchmarking
Client’s input DataMa Compare output
This client, a media online player, wants to understand why Page A is performing better than Page B in terms of
conversion, and which specific section of the page is causing the gap
An access to Content Square data, splitting
performance metrics by page zones and
devices
“ Page A is doing 2 times better than page B thanks to
higher engagement on text zone, and higher views/
visits, particularly on desktop”

6. This information is confidential and was prepared by DataMa solely for the use of our client; it is not to be relied on by any 3rd party without DataMa's prior written consent
Use Case 4: Revenue comparison between two geographies
Client’s input DataMa Compare output
This client, a large hotel player, wants to understand what’s driving the difference in revenue between US regions and
EU region
An Excel (CSV) extract, splitting business
key indicators by region, brand and Area
type
“ We have less hotels in the US, and they are smaller
in number of rooms and room size, with slightly
lower occupancy rates.”

7. This information is confidential and was prepared by DataMa solely for the use of our client; it is not to be relied on by any 3rd party without DataMa's prior written consent
More broadly, when should I use DataMa Compare?
Start
(e.g. LY)
End
(e.g. TY)
?
How can I quickly explain this… … with this ?
Dim 1
(e.g.
Medium)
Dim 2
(e.g.
Device)
Start
End
Dimensions MetricsAny KPI
(e.g. $/Session)
A
(Session)
B
(PV)
C
(Bkg)
D
($)

8. This information is confidential and was prepared by DataMa solely for the use of our client; it is not to be relied on by any 3rd party without DataMa's prior written consent
DataMa Compare: A plug & play R model explain KPI gaps easily
FOR DISCUSSION
Why?
What?
• Compare any KPI between two segments and understand quickly what's driving the gap​, with large data sets
• Mix effects
• Segments performance changes on specific dimensions
• Underlying metrics changes
• Typical use cases (see next pages):
• Understand the performance (Revenue, Conversion, Traffic) variations from one period to another (Week
on Week, Year on Year, Budget vs. actual...)
• Compare two business units, or two products (e.g. two web pages) to understand how to improve one of
them
• Inputs: a flat table with metrics distributed on dimensions (typically, a CSV)
• Inside: an R code. R is open source, free and easy to install software on your current system
• Outputs: an other flat table with drivers identified. This can be plugged on your current visualization tool (e.g.
see Tableau template) or use R Shiny apps (see demo app here)
• Any executive in charge of explaining regularly variations in a KPI, and identify drivers in a complex flow.
Typically sales or marketing executives, e-commerce directors, BI heads...Who?

9. This information is confidential and was prepared by DataMa solely for the use of our client; it is not to be relied on by any 3rd party without DataMa's prior written consent
DataMa Compare approach: 3 main levels of analysis
Waterfall analysis
Dimension
analysis
Mix effect
Segment
Performance
Summary
• Once KPI equation properly written, identify
which underlying KPI is responsible for the change
• For each underlying KPI, analyze how much mix
effects on each dimension contributes to the
observed gap
• For each underlying KPI and each dimension,
identify which specific segment performance is
driving the observed gap
• For each underlying KPI, select most interesting
dimension to explain observed gap

10. This information is confidential and was prepared by DataMa solely for the use of our client; it is not to be relied on by any 3rd party without DataMa's prior written consent
DataMa Compare key advantages for consulting
✓ Big Data: R can easily tackle large Data Sets. Low limitations in number of metrics & dimensions
✓ Client ready: Charts can be easily inserted in slides
✓ No black box: Constant access to calculations and row data, hosted by your own machine
✓ Accessible: Even without knowing R, you can easily set up your own use case
✓ Business oriented: simple maths, easy to explain, for smart business decisions
✓ Flexible: With Shiny interface, you can easily drill down/ filter/ simplify the output
✓ Quick: Use cases can be set up in <5 minutes
✓ Reproductible: You can implement an automated dashboard to update analysis regularly

11. This information is confidential and was prepared by DataMa solely for the use of our client; it is not to be relied on by any 3rd party without DataMa's prior written consent
References:
DataMa website
DataMa Compare :
• GA use case
• Shiny live demo
• Tableau demo
Contact: guillaume@datama.org