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Achieving Marketing ROI with Analytics - A Case Study

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Olivier Maugain

on 16 February 2015

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Transcript of Achieving Marketing ROI with Analytics - A Case Study

Achieving Marketing ROI With Analytics
A Case Study

Results
(Using Analytics)
- Number of ads sent: 600
- Response rate: 13.5%







-> Number of positive responses: 81
-> Revenue generated: 81,000 RMB

- Cost of campaign: 60,000 RMB
-
ROI

of the campaign:
35.0%
- Cost savings:
40'000 RMB
Results
(Random Selection)
Response rate: 10.0%
-> Number of positive responses: 100
-> Revenue generated: 100'000 RMB

Cost of campaign: 100'000 RMB
->
ROI
of the campaign:

0.0%
ROI Case Study:
Campaign Optimisation
Objective:
Reduce
the number of ads (or targets) of a marketing campaign in order to improve its
efficiency
Assumptions:
- Number of ads sent: 1'000
- Cost of each ad: 100 RMB
- Value of a positive response: 1,000 RMB
- Random selection of targets
Agenda
1
Marketing and ROI
2
What is Analytics?
3
How to achieve ROI in marketing?
4
Looking into the future of Marketing
"The process of discovering meaningful knowledge (e.g. correlations, patterns and trends) by sifting through large amounts of data stored in repositories, using statistical and mathematical techniques."
Helps managers to predict what’s going to happen in the
future
(as opposed to conventional Business Intelligence, which is about explaining the past and the present)
Background - Challenges
Slowing growth rates
Poor customer retention
Dependence of revenue on 2 product categories (out of 6)
Lack of deep understanding of customer needs and behaviours
No re-sell or up-sell strategy
Meanwhile...
Objectives
Improve customer loyalty
Raise customer retention rate
Grow revenue per customer
Increase share of wallet
Build up basis of VIP customers
Optimise sales and marketing resources
Closing the gap
Strategy:

Personalisation of communication
In other words...
Providing the right message...
To the right
person
...
At the right time...
Through the right channel...
With the right
offer
.
Step 1: Segmentation
By value (RFM Analysis)...
By attitude and preference...
Step 2: Profiling
Selecting the right target
Decision tree
Rule sets
Step 3: Selecting the right product
Market basket analysis
Association rules
Results:
Calculating the ROI
- Number of targets: 3'000
- Cost for each target: 900 CNY
- Value of a positive response: 10,000 CNY
Assumptions:
Before: Random Selection
Response rate: 10%
-> Number of positive responses: 300
-> Profit generated: 3 million CNY

Cost of campaign: 2.7 million CNY
->

ROI
of the campaign:
11.1%
After:
Using optimisation models
- Number of ads sent: 2'000
- Response rate: 13.5%







-> Number of positive responses: 270
-> Profit generated: 2.7 million CNY

- Cost of campaign: 1.8 million CNY
-
ROI
of the campaign:
50.0%
-
Cost savings:
900'000 CNY
Newest trends in marketing...
360 degree view of the customer
Omni-channel retailing
O2O
Customer Experience Management (CXM)
So-Lo-Mo (Social, Local, Mobile)
Sentiment Analysis
Big Data
... Are all related to analytics
in one way or another
You don’t need
to become a winemaker
to become a wine connoisseur.
Professor Meng XiaoLi
(Harvard University)
CEO
AsiaAnalytics (formerly SPSS China)

Email: maugaino@asia-analytics.com
LinkedIn:
Retail, Marketing Customer and Analytics
Thank you for your attention.
Olivier Maugain
1. Initial situation
2. Objectives
3. Gap
4. Strategy
5. Results

Step 1a:
Segmentation
Disclaimer:

The case study shown in this presentation was
not
conducted at Chanel. There is no connection between AsiaAnalytics and Chanel.

The pictures used here were chosen for illustrative and decorative purposes only.
Full transcript