|
Size: 2791
Comment:
|
Size: 3723
Comment:
|
| Deletions are marked like this. | Additions are marked like this. |
| Line 15: | Line 15: |
==== Customer journey attribution with model based attributable risk ==== The efficiency of marketing investments is of high interest. However it is very difficult to be measured due to the split of marketing investments into multiple channels with different performance measures. Multi-touch attribution addresses performance based compensation to multiple channels with respect to the contribution to conversions. Click streams across multiple channels and conversion events, e.g. purchases, are called customer journeys. A logistic regression model that reflects both performance of touch points (e.g. clicks) and temporal relation to other touch points is fit to a sample of customer journeys. The probability estimates are used for the estimation of attributable risk for channels / a channel. That is:"the fraction of conversions that would not have been concluded if a channel / some channels did not serve ads". |
|
| Line 35: | Line 44: |
| * ''' Danny Panknin''' | |
| Line 70: | Line 80: |
| * ''' Danny Panknin''' |
Doktoranden-/Diplomandenseminar SS 14
In this seminar, master/phd students of the IDA group present their current work and research ideas.
When? |
usually on Wednesdays, 2:15pm to 3:15pm, or as announced (see below) |
Where? |
at TU Berlin , MAR 4005, or as announced (see below) |
How? |
More information for speakers and participants here. |
Next Talk
Wednesday, 30.04.14 14.15 MAR4033
Tillmann Fiehn
(Chair: Mikio Braun)
Customer journey attribution with model based attributable risk
The efficiency of marketing investments is of high interest. However it is very difficult to be measured due to the split of marketing investments into multiple channels with different performance measures. Multi-touch attribution addresses performance based compensation to multiple channels with respect to the contribution to conversions.
Click streams across multiple channels and conversion events, e.g. purchases, are called customer journeys. A logistic regression model that reflects both performance of touch points (e.g. clicks) and temporal relation to other touch points is fit to a sample of customer journeys. The probability estimates are used for the estimation of attributable risk for channels / a channel. That is:"the fraction of conversions that would not have been concluded if a channel / some channels did not serve ads".
Planned Talks
Wednesday, 07.05.14 14.15 MAR4033
Sven Dähne
Wiktor Pronobis
(Chair: Guido Schwenk)
Wednesday, 14.05.14 14.15 MAR4033
Forooz Shahbazi Avarvand
Jan Saputra Müller
(Chair: Sebastian Bach)
Wednesday, 21.05.14 14.15 MAR4033
Jacquelyn Shelton
Irene Winkler
(Chair: Wiktor Pronobis)
Wednesday, 28.05.14 14.15 MAR4033
Matthias Schultze-Kraft
Danny Panknin
(Chair: Felix Brockherde)
Wednesday, 04.06.14 14.15 MAR4033
Alexander Bauer
Kristof Schütt
(Chair: Nico Görnitz)
Wednesday, 11.06.14 14.15 MAR4033
Daniel Bartz
Bastian Venthur
(Chair: Matthias Schultze-Kraft)
Wednesday, 18.06.14 14.15 MAR4033
Fatemeh Ali Mardani
Anne Porbadnigk
(Chair: Laura Acqualagna)
Wednesday, 25.06.14 14.15 MAR4033
Markus Wenzel
Sebastian Bach
(Chair: Kristof Schütt)
Wednesday, 02.07.14 14.15 MAR4033
Laura Acqualagna
Johannes Höhne
(Chair: Daniel Bartz)
Wednesday, 09.07.14 14.15 MAR4033
Felix Brockherde
Irene Sturm
(Chair: Irene Winkler)
Wednesday, 16.07.14 14.15 MAR4033
Duncan Blythe
Nico Görnitz
(Chair: Johannes Höhne)
Previous Talks
-- Wojciech Samek -- Jul 2013