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iz podatkov
Simon Belak
@sbelak
Vodja analitike
Pomagal podjetjem postati data-driven
ex-
@sbelak
Kdo so moje stranke?
Kdo so moje stranke?
Tarčna Tipična
market analytics product analytics
clustering
segmentacija
Podatki
Domensko znanje
clustering
segmentacija
Od podatkov do
prostora
Spol: Ž
Starost: 21
Klobuk: ne
Spol: M
Starost: 25
Klobuk: ne
Spol: M
Starost: 42
Klobuk: da
Marko
Jana
Boris
Spol: Ž
Starost: 21
Klobuk: ne
Spol: M
Starost: 25
Klobuk: ne
Spol: M
Starost: 42
Klobuk: da
Marko
Jana
Boris
Podobnost
Spol: Ž
Starost: 21
Klobuk: ne
= točka v 3D
prostoru
Značilke
Lastnosti Obnašanje
Starost
Lokacija
Število zaposlenih
Letni prihodki
…
Zanimanja
Čas obiska
Frekvenca obiska
Trajanje obiska
Število nakupov
ARPU
Število akcij do nakupa
…
Kategorične vrednosti
(starost: 20-28) je lažje
tolmačit kot količinie
(starost: 25)
Primer: odkrivanje
problemov/zanimanj
1 0 0 0 1 …
1 1 1 0 1
0 1 0 1 1
…
S2 S1
S1
S2
x x
x x
0,6 0,1 0,3 0,2 0 …
0 0,4 0,6 0 0
0 0 0 0 1,0
…
Plemenitenje podakov
& seštevanje krompirjev
Lastnosti Obnašanje
Starost
Lokacija
Število zaposlenih
Letni prihodki
…
Zanimanja
Čas obiska
Frekvenca obiska
Trajanje obiska
Število nakupov
ARPU
Število akcij do nakupa
…
Primer: lead generation
Obstoječe stranke
Poencialne stranke
Popotnica
• Segmentacija ni nikoli samo ena
• Manj (značilk, podatkov) je lahko več
• Več ločenih preprostih modelov (= več perspektiv)
lahko pove več kot en kompleksen
• Karkoli je lahko značilka
• Pametna izbira značilk > pameten model

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inOrbit 2015: odkrivanje segmentov iz podatkov