From 1ec06922358ee559de94726a041fcd31735e6b7a Mon Sep 17 00:00:00 2001 From: AlxdrPolyakov <122611538+AlxdrPolyakov@users.noreply.github.com> Date: Fri, 30 Aug 2024 16:48:52 +0100 Subject: [PATCH 1/8] Add new case study, causaltune Signed-off-by: AlxdrPolyakov <122611538+AlxdrPolyakov@users.noreply.github.com> --- _case_studies/11_targeting_variants_for_maximum_impact.md | 7 +++++++ 1 file changed, 7 insertions(+) create mode 100644 _case_studies/11_targeting_variants_for_maximum_impact.md diff --git a/_case_studies/11_targeting_variants_for_maximum_impact.md b/_case_studies/11_targeting_variants_for_maximum_impact.md new file mode 100644 index 0000000..889607a --- /dev/null +++ b/_case_studies/11_targeting_variants_for_maximum_impact.md @@ -0,0 +1,7 @@ +--- +title: Targeting variants for maximum impact +description: "Causal inference for selecting the best option" +image: assets/causaltune-targeting.png +image-alt: Targeting variants for maximum impact +link: https://medium.com/@alexander.polyakov/targeting-variants-for-maximum-impact-bdf26213d7bc +--- From 66d69e778277ea8d72f56e8152c3d07cb3d3db4f Mon Sep 17 00:00:00 2001 From: AlxdrPolyakov <122611538+AlxdrPolyakov@users.noreply.github.com> Date: Fri, 30 Aug 2024 16:49:19 +0100 Subject: [PATCH 2/8] add a picture for new case study, causaltune Signed-off-by: AlxdrPolyakov <122611538+AlxdrPolyakov@users.noreply.github.com> --- assets/causaltune-targeting.png | Bin 0 -> 7790 bytes 1 file changed, 0 insertions(+), 0 deletions(-) create mode 100644 assets/causaltune-targeting.png diff --git a/assets/causaltune-targeting.png b/assets/causaltune-targeting.png new file mode 100644 index 0000000000000000000000000000000000000000..86e9359032a3620b17bf87ec69291f50da52910d GIT binary patch literal 7790 zcmc&(Vg4Scf? zbMQ^{joWV)CZEu7DbeI#$n~Pu<~P%FH(HrbyGrSUIUPzJr?QvDcNa4zO_qbTV8QT4 zX~EKYqnwzd?B?qX3g^m=#t*8hb+pcywvEa?g>RKZ@*`G9o`@a-ycIs;fJlKiov_`} z%{8amu8aDgpK4b+)|BN@P-1a$Fi_M`LQqg}fdCXBDh3(~^Jh7f&lmt4ltdIXRFoHT zKomK&|EEz1g$p_(xp(I0G*dH+Ouh8?jO-&*+r=e(+D{sl6-}G&Cub4pGxtN^-Bu`_ zVl8)aW}ZEqv1{qX{270XfC`@b)FN-+jKK|>gA})WFHwfeZJ;Yor!rV8x5iy-%Q42C|1D{2PjN>`lE>ocln;F1jmP$ zemuIJ0SOUDOr7ts%#71GCW0{V&j&bV0yn7%`t_nbXoj0|=9)UbR?|KdU&UD-2eusq zd)i+oq{(t}Wm~T62#%2r6U&~?8m`w%o1L}%WGPV=Zm23Ehuf@SycK8Kk=l2i><^G`2)&@;HC4&S!b?@a<(aXm0YH9!|G* zUXF8V#AO`P8JgRtJw6V$@87IJ=;J0dws&oK=De>&{y=U1;U(NtN0G4 z=U@uDZ+9TPfMA^+8XvYF4ei(59ft{@G^V?>ogljMoR0VqFBVis5Zo~jy%b0Y2yy7}=WR>S$2&LH*?E;bv*CWTiSz`R2zlG= zZP5o=g%;-j+y9M-a5UKu*#v$LU5WS!#A9r$=UeC zj||h6?gp)nXiw|EG)Z)_$a&vcRIv;Xz(l4IejdDYI4BtOkZajnFF4;?j~IDi#~YJ6 z##H#FYuPc*uHVRHzv6wJiGAG_{GqcYv$)X#bT;`u&+~!gibk?ae{SB7!$3q;a%PiI zc>3+m-zqV!f3z2NxVUj?707HWoKc^pW}xjoOAX@|SC zESm>r1ju5`J=GUh=e{!am_vwVacjQQx%yK)qh!#w+-H)P*efGUPU=G`Zo0B$g*QIF zz3Vj_tlvi77@_BL+Lw1zgWv5{7uE0+aWdQ0mpoYhyhVR~TitnjA8>*RmvA$p3F&vB z>%1O~nmY8~wOlB9iHNjsU(IrEFpXbv7BSu9jt@>IE$wn> zb@OUEo)O0X6zswl*MH7IMl&2YHXr|QXw2DmK}MQHpcY&vuLdC7ib5_{S~1zyE@OB& z4ud74EoRp>``%s=ZD_eqdkdzq<*|5l)N)?~m)>*R>vQ%H>Qz^>_?F2d69E`f5StmZ zo!LIj-p4x;FmCp4ggbtG)>~jP3}03OjF17M8k|f&PEu_wT8Ye!-nWnUIqNsd73ke% z2nM^6fOuL+k3PHif7W{jwH}>gsnmV{tT5jaRVEF!R$w3H0RKHcWLMXRkwI(E0T4D-!UP#(F9;j~yjqoLuV*`=)Kd19pue-KF1 z178M8gn@)#T|!`o*C9oVfRJ%dn#5`p}CZYJ9TV9dTG4=}iby@)4w zM^y~BlVw#Y*Xiq+FuYEjDrim)C_i9VcM1M|j@Xpy{qY+aee3mR4zjmkArNxm{vPSH zsocem=EDFk9jxd=b)m5nc3mUdf8nY^O;F;T-Vd1s_q=`1#(bkA*>}cxsm+vx52hTp zqVI59v{Nu06M=$4Vh+jU_adYd1RL2|BM4zO28e0v5gvtt?vSg4XM~42S|Pk3@yak_ z<$E~_8ZK)81rzljWYpDZ!v!gNTY2EMMoHNN-H2r?%MN^e(X^`opoVl9Q>HNi z>jB;FBMuv=d^&&SW%;|R6b7$$8`;#I^M)D6uUS`_A)msL|3yZe!6>G!SNc*j&_PII z*yh*Z09_<9?afzO7)dul5dgZ-lNn+}O@IS@% zW~bM__ogII@$1{ey25aNieK2c{9#0q3Op$_kUV@nr2tB<>+DlAVLz#PpC5quSa;L+ z%2iNwc~VZPMdxNZngSP*NOP4-Rk76pa-+(-+x-3-q84Y;-XnYEqFMYXk2tgEM%`Nc zyLUUi7#J^DtL*eSb9#RWq*r0HlSO}?*r9ku*#0!V6`hons;^iiXp|3<<+MdqzwCF` z&qoajCrOcqC-!K*E_hqMMD|)ZXVfZ&P-3EVy?LBIyfC&JnIvf=;&71D35+9%IdkBM z7wNws@~Ekm7voW`@e7Y5ppe{XaihL&xOZK6<)X{^P!!y4%_Ro}Mcjf$ZAD*0>8aeg z>zAoVb>eCU-_Qjcp;wd^&P|Qc=SPvFE;`T4#3~5aEoP_I+>uaC+5Dm>Y_aSf8Ob)K z<_tD^=G*p5EXGXW8sOssy?F0D2(eM5{@yr}Lz7`JW$Z`+NbnYNI%>2NTGk2F*HXs_hqb|kTdx6Q4`<)mSTlN_Vhc3BI+gnZq!73J)X=L@(D>U9&9w72K zo%hUSQ9h9?-#sDTUP1%Ygjh*j08z4cE~6KIFsT48{)6~pH)>Kmmn*MYR12Et*$*Kb{CWdb2Tgr`-KcIT9R1Dpx?$npHK|&{JLK=1YY(DKm0@Zl?J1=G;|f!5 zTen@4qzNNu3Q4!3$nxY9a-R$408xPADY5j zpQ^BE<4=B%J(m%+^BFQ40WpaF5C$O9B!hVVX#K2d<-Mf%f?cRyVl?KWsv=MMO)`+f zy7NC^+4&yQ@#mc_w(H}k5R;!U1;Cfv&sG| zs|lJ~t))8ax360)Dy(uNy_KDD5+>OvrFhNw4mk8pkt&d>J%mBXYRa9UfX4HrpX_pu z4NlBb%F~-@u_1g493*kJB% zVj`^kqi6)EyV>GH-FFu9ZQ19yx@+I-D<=Ofr>TA%N+{5Ex#l9e;edG8G}S&hu8K4u z$Hx$h__~I~?`O%Ll$v3`j&!sA5WznpGPv%hp#da)C3(*kYLI(k?vNiW`)dZBWy zuNWAMv>--v%S$?*`xuyhZ5ByC(#t6M2vW9WpMTNCtF`{{d+10FGh@;fj02?hySR$( z3Dr9NjwTL06II5aW=xb9y8ojkuSkY<4j7Re?{%C$A5)bQB!O*$V_u73Y5=49`fPC& zKc0A+kFV!fV=&*NO2pj*&Or5x;{TNj(~sArO7BBdtf4Pu5L@4VrVhG5O#Bn_*5=OS zk9Z8tccF1N$i`#cl2_J}g)6)3OBoOv;6~HZ+<7@K<3ks-C+@g0a7vC=ZYpQAkXrY?{g$h6%!nk*?p-f>J!VcG3^-lMPB8Cre)$PGwp3`01 zCHhUFlT-P1GrMa?IW@<3fv^cTPWGpSI=A`PMo*tK>AI)>Y}E@HxtOz5yV5Msei>2R zVmW4*ym)S~3PTlzX+e4SB2-_I@B+MtEV&4Zpq;Z2f|I7)2b=IzKbL-s|vxUC`la!UB&y?Ht$sZtkJwN5(+ z_CZ+e)IzVZ=Kk0}ZycD-M02OqD7Tu*Zt*7z82gqwEfa;8TmwJgCfhL>!#6{3IwNG$ z9}Fc@wDv8?M@UMP0)*E>1AKDn;_WU zFT{4)Kj)t~3M6>d)>Stz)O?GN&Ws0{7|ryZZ>Q9;wf%Tp*M&2|t~2B%nrRt&_PM!D z5=FszT)m-EK6x6{e3e#EC@GGphq}gEjO7UqMK%1uDHlt1Z)c)?405wX=OBJ7+dXrK zKkt%Rrj5HX_|Z;p2XU@rEPC|pP&kFhE*6a5mZ_S87d)Xu%Gb8v$5NxZ&KJ5JmXC{} zD)aq1P;NJ>t~m5O_ICi>*JdrI3;X<&SFN5;;44+?(ffC?5plAH)_Hq{a>H3boU$|E80 zKcJ4E{Pd517qYf#%X>918o1+XpHn7%PRG0A_h33q{m7Hx%jm1kC2=J$NuGLl|CX!ryp%>1!%5y!NF%n0YSi{Fp+?OXH7WC=LxHiCqX0+{z|}2qul+KG zd%X6jQcP+(pb0*&;fy|`8;~NH!ZP0W#c9}5Q$Eq+^i�k%Q@@LYeXG{aHrTGARKS z=lh4Y03Id}+p`^PS%hXzKG5}NfdrDxy6Nd&aFSlt-`DfgUo5z^uDLs`23_8MIiNq+p+;s;k|HmD zxzngg`a^0ovJtL~_BNpH=Zl>p$ED|ba#JlY+&&M;ne&Py>Ek7-HVaP_yPCWso-~8` zSFX_J0*tJ;n}sWyC)J5bhb59;m_h)xRbzHK+wW`#Cg_L=S5e=8R%7rFpi0qDxdVVvLG*nc(*)Xh0AE&cJV8I#D5 zsr>v`pJhXGKcpx4z^S3&=4V+dBzEhkVO688jOz5>BLOQnWb2<2+S8oAZiD#q#HUC7 zQYTmhG~r$$l4yV*vY`OPI8W)g_Kj2+1X!_7adMoc%C_Zipb9NF{V6+gU>To*b; z7c(5$RUKWC5lP>j5#g+_L-yEeFlG>j6AUz}OdZqZ{WXiA8HfeSoDtSWY2cTz?<*D2sw64|tn$yM-!6iS0M z#CSTQ?>xw1ZMQ$L&fOi|*HpcG2i7@?&azDXd=e!Y;?V6|+89OiW@HH<-S`sXb?K+v_OJ5->rSB^J$}OrzTz!4uZh6 zy`)~Gp-s00J>n{;?Pq*5_;IYeWf5w|U*RYG>wclDpph8qjy~|ud-F?U*lm$L)pS*6 z-G0n4KNVG7b*LpAUgfanBeSJ~g|W)i&PX@XrL+;zN`})L$He=LOHbtg*UoG`=p^7I zuIzcI-zO1dK=uZx12qq!49FBBs=oXywseSIEiB9+fD4t|Kq6Lwv`_QtCc-nML%FP8 zdt7LYajg{4n(CdO02v{>R_dccs`Lk_$A%e@LYsc3k?#D}tE9a=_AIABtUj!bNRC?e z0l+<$qS|&w#HPb95nx<&6Lv&pX}k_+)oqDSyEcdP$7AqJ(Yk$Wcl8#jp87rE#>Ho>C zN7({DJgbR0<6C0;fTU%R%|gI>9S&3o=~~}LwXE{UE2di!MX|LCn90S|sVSz?3kYZ8 zK(=khEQO(gU+H-F{ic(hFa{Nd#XyPNo)ka#1KV5xKS7+^-v)58cBZ~-xU;4(@Eocc zvh}pmON-nBx(_*UiKd3Js-qZadWW11z!8+T#wFNvEvitdL1|iJp&2C3e>iDlktSK|sbLfYYu6NjApSe*! z>kbsleMgK}nwJahNQ28(^9~jN&7&hKx((O}yKUtfNj$WhN=qf zmd>%25Cv@tNo@46lL^L5nC_>p&3r1lf%n^+UXpn9cYel4T7N?#^Bb*MC+uK)nV3S- zGI=YqKnDkas@mi_t3m4vw{i>bO?8^#$UbLtA=I2p$}c&re_6=4IBz)$y(J=r7pi9I z-}DfwxASle=;omOQcvJN7pdV$t>Ow+FcEu@KbcF$VaU?`ejBih-P9p*Gas^BPyboY z3Zrm{eOdRa=7*d27umZwfx&gs1nG|H)!G?Mc>5kE#tZZxvwGnr^xeU+OfPucOJCVW zH&o2W_je6bcK{T=eGTpWeOahX{oFOfYWjfvzx zog^f?sI~QSz#@aH?Wk+vtAp{eJya|F)!>S;V2=4kaUk6?cHIl6OK#N$~()Y_-3p6Mc` z2}PPIGgvzprHG0oFwp_4KO54eC9wTvRHlzv|DC%u-Z*YC7|F6Sw?q67DwZYKq|vq^ zyj*4H$hc(oLd4G!kW#>m>!*Z(ZPW(N2$T>deu}1RR(IiqogcFpr0+Z?kq9y>Aj*1^ zd$2eQTt|TP1X(B-#R5nEQ^;%!Z+2Z@KZyFwY9K48)L*P26ksB|3iAE8bXrnNd6grh z$1A0^PHo#-qC7MI1ks-0QzWOX#6ORkQ{K?-O-+?M&c1Bwm6-F5k>*5(@y+yPg~SHk zM(6J0zB3YGED~P`;P%Whk4<}D<)&3}b$?oPR!VLGPxyEAG8;B|y*p2pMJgsuEUqy3 z@T8Fm<^E%ixYU(gPs)if22mM26#GHS4~w8PN@M2EE;wWSrXDz`9~7Qw&ffQ1ayPBv zJIjRE?yKuRW|;BO*63(aB#U4)yXp7}+P=P}H+Lzpo7?>yBm(Iq*Z^W Date: Fri, 30 Aug 2024 17:26:39 +0100 Subject: [PATCH 3/8] Update 11_targeting_variants_for_maximum_impact.md Signed-off-by: AlxdrPolyakov <122611538+AlxdrPolyakov@users.noreply.github.com> --- _case_studies/11_targeting_variants_for_maximum_impact.md | 8 ++++++-- 1 file changed, 6 insertions(+), 2 deletions(-) diff --git a/_case_studies/11_targeting_variants_for_maximum_impact.md b/_case_studies/11_targeting_variants_for_maximum_impact.md index 889607a..82d653d 100644 --- a/_case_studies/11_targeting_variants_for_maximum_impact.md +++ b/_case_studies/11_targeting_variants_for_maximum_impact.md @@ -1,6 +1,10 @@ --- -title: Targeting variants for maximum impact -description: "Causal inference for selecting the best option" +title: Targeting variants for maximum impact using the CausalTune library +layout: page +description: >- + This tutorial provides an introduction to causal AI using the CausalTune library in Python. It shows a practical example and the use of the ERUPT metric. +summary: >- + This tutorial provides an introduction to causal AI using the CausalTune library in Python. It shows a practical example and the use of the ERUPT metric. It also shows how to use ERUPT to evaluate previous experiments, as well as how to evaluate the potential effect of a future experiment with different assignments using a real business example. image: assets/causaltune-targeting.png image-alt: Targeting variants for maximum impact link: https://medium.com/@alexander.polyakov/targeting-variants-for-maximum-impact-bdf26213d7bc From 485dccbe43f3649d5f4dedfe6760bf98eb7f38bb Mon Sep 17 00:00:00 2001 From: AlxdrPolyakov <122611538+AlxdrPolyakov@users.noreply.github.com> Date: Fri, 30 Aug 2024 17:29:11 +0100 Subject: [PATCH 4/8] Update 11_targeting_variants_for_maximum_impact.md Signed-off-by: AlxdrPolyakov <122611538+AlxdrPolyakov@users.noreply.github.com> --- _case_studies/11_targeting_variants_for_maximum_impact.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/_case_studies/11_targeting_variants_for_maximum_impact.md b/_case_studies/11_targeting_variants_for_maximum_impact.md index 82d653d..6afa0cc 100644 --- a/_case_studies/11_targeting_variants_for_maximum_impact.md +++ b/_case_studies/11_targeting_variants_for_maximum_impact.md @@ -4,7 +4,7 @@ layout: page description: >- This tutorial provides an introduction to causal AI using the CausalTune library in Python. It shows a practical example and the use of the ERUPT metric. summary: >- - This tutorial provides an introduction to causal AI using the CausalTune library in Python. It shows a practical example and the use of the ERUPT metric. It also shows how to use ERUPT to evaluate previous experiments, as well as how to evaluate the potential effect of a future experiment with different assignments using a real business example. + This tutorial provides an introduction to causal AI using the CausalTune library in Python. It shows a practical example and the use of the ERUPT metric. It also shows how to use ERUPT to evaluate previous experiments, as well as how to evaluate the potential effect of a future experiment with different assignments using a real business example. image: assets/causaltune-targeting.png image-alt: Targeting variants for maximum impact link: https://medium.com/@alexander.polyakov/targeting-variants-for-maximum-impact-bdf26213d7bc From b1a40d6c8e42a5665d5761eb1922aba128fcfba0 Mon Sep 17 00:00:00 2001 From: AlxdrPolyakov <122611538+AlxdrPolyakov@users.noreply.github.com> Date: Sun, 1 Sep 2024 18:36:00 +0100 Subject: [PATCH 5/8] Update 11_targeting_variants_for_maximum_impact.md Signed-off-by: AlxdrPolyakov <122611538+AlxdrPolyakov@users.noreply.github.com> --- _case_studies/11_targeting_variants_for_maximum_impact.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/_case_studies/11_targeting_variants_for_maximum_impact.md b/_case_studies/11_targeting_variants_for_maximum_impact.md index 6afa0cc..e44b814 100644 --- a/_case_studies/11_targeting_variants_for_maximum_impact.md +++ b/_case_studies/11_targeting_variants_for_maximum_impact.md @@ -7,5 +7,5 @@ summary: >- This tutorial provides an introduction to causal AI using the CausalTune library in Python. It shows a practical example and the use of the ERUPT metric. It also shows how to use ERUPT to evaluate previous experiments, as well as how to evaluate the potential effect of a future experiment with different assignments using a real business example. image: assets/causaltune-targeting.png image-alt: Targeting variants for maximum impact -link: https://medium.com/@alexander.polyakov/targeting-variants-for-maximum-impact-bdf26213d7bc +link: https://towardsdatascience.com/targeting-variants-for-maximum-impact-bdf26213d7bc --- From 076788f7316b687beb2b9c65a9d04c001e870576 Mon Sep 17 00:00:00 2001 From: AlxdrPolyakov <122611538+AlxdrPolyakov@users.noreply.github.com> Date: Tue, 3 Sep 2024 08:30:38 +0100 Subject: [PATCH 6/8] Update and rename 11_targeting_variants_for_maximum_impact.md to 11_improving_business_metrics_for_maximum_impact.md Signed-off-by: AlxdrPolyakov <122611538+AlxdrPolyakov@users.noreply.github.com> --- ...1_improving_business_metrics_for_maximum_impact.md | 11 +++++++++++ .../11_targeting_variants_for_maximum_impact.md | 11 ----------- 2 files changed, 11 insertions(+), 11 deletions(-) create mode 100644 _case_studies/11_improving_business_metrics_for_maximum_impact.md delete mode 100644 _case_studies/11_targeting_variants_for_maximum_impact.md diff --git a/_case_studies/11_improving_business_metrics_for_maximum_impact.md b/_case_studies/11_improving_business_metrics_for_maximum_impact.md new file mode 100644 index 0000000..ee63200 --- /dev/null +++ b/_case_studies/11_improving_business_metrics_for_maximum_impact.md @@ -0,0 +1,11 @@ +--- +title: Improving business metrics for maximum impact using the CausalTune library +layout: page +description: >- + This tutorial provides an introduction to improving business metrics using the ERUPT metric and the CausalTune library in Python. It shows a practical example and the use of the ERUPT metric for optimizing clickthrough rates. +summary: >- + This tutorial provides an introduction to improving business metrics using the ERUPT metric and the CausalTune library in Python. It shows a practical example and the use of the ERUPT metric for optimizing clickthrough rates. It also shows how to use ERUPT to evaluate previous experiments, as well as how to evaluate the potential effect of a future experiment with different assignments using a real business example. +image: assets/causaltune-targeting.png +image-alt: Targeting variants for maximum impact +link: https://towardsdatascience.com/targeting-variants-for-maximum-impact-bdf26213d7bc +--- diff --git a/_case_studies/11_targeting_variants_for_maximum_impact.md b/_case_studies/11_targeting_variants_for_maximum_impact.md deleted file mode 100644 index e44b814..0000000 --- a/_case_studies/11_targeting_variants_for_maximum_impact.md +++ /dev/null @@ -1,11 +0,0 @@ ---- -title: Targeting variants for maximum impact using the CausalTune library -layout: page -description: >- - This tutorial provides an introduction to causal AI using the CausalTune library in Python. It shows a practical example and the use of the ERUPT metric. -summary: >- - This tutorial provides an introduction to causal AI using the CausalTune library in Python. It shows a practical example and the use of the ERUPT metric. It also shows how to use ERUPT to evaluate previous experiments, as well as how to evaluate the potential effect of a future experiment with different assignments using a real business example. -image: assets/causaltune-targeting.png -image-alt: Targeting variants for maximum impact -link: https://towardsdatascience.com/targeting-variants-for-maximum-impact-bdf26213d7bc ---- From 2bbd2d151dbac875210d3c28128f494895af3d45 Mon Sep 17 00:00:00 2001 From: AlxdrPolyakov <122611538+AlxdrPolyakov@users.noreply.github.com> Date: Tue, 3 Sep 2024 08:31:11 +0100 Subject: [PATCH 7/8] Update 11_improving_business_metrics_for_maximum_impact.md Signed-off-by: AlxdrPolyakov <122611538+AlxdrPolyakov@users.noreply.github.com> --- .../11_improving_business_metrics_for_maximum_impact.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/_case_studies/11_improving_business_metrics_for_maximum_impact.md b/_case_studies/11_improving_business_metrics_for_maximum_impact.md index ee63200..e60bd98 100644 --- a/_case_studies/11_improving_business_metrics_for_maximum_impact.md +++ b/_case_studies/11_improving_business_metrics_for_maximum_impact.md @@ -6,6 +6,6 @@ description: >- summary: >- This tutorial provides an introduction to improving business metrics using the ERUPT metric and the CausalTune library in Python. It shows a practical example and the use of the ERUPT metric for optimizing clickthrough rates. It also shows how to use ERUPT to evaluate previous experiments, as well as how to evaluate the potential effect of a future experiment with different assignments using a real business example. image: assets/causaltune-targeting.png -image-alt: Targeting variants for maximum impact +image-alt: Improving business metrics for maximum impact link: https://towardsdatascience.com/targeting-variants-for-maximum-impact-bdf26213d7bc --- From 0ca41d4cf750fccd3f2dda7f97608691f69272ec Mon Sep 17 00:00:00 2001 From: AlxdrPolyakov <122611538+AlxdrPolyakov@users.noreply.github.com> Date: Tue, 3 Sep 2024 16:07:11 +0100 Subject: [PATCH 8/8] Update and rename 11_improving_business_metrics_for_maximum_impact.md to 11_improving_business_metrics_for_better_impact.md Signed-off-by: AlxdrPolyakov <122611538+AlxdrPolyakov@users.noreply.github.com> --- ....md => 11_improving_business_metrics_for_better_impact.md} | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) rename _case_studies/{11_improving_business_metrics_for_maximum_impact.md => 11_improving_business_metrics_for_better_impact.md} (85%) diff --git a/_case_studies/11_improving_business_metrics_for_maximum_impact.md b/_case_studies/11_improving_business_metrics_for_better_impact.md similarity index 85% rename from _case_studies/11_improving_business_metrics_for_maximum_impact.md rename to _case_studies/11_improving_business_metrics_for_better_impact.md index e60bd98..af304db 100644 --- a/_case_studies/11_improving_business_metrics_for_maximum_impact.md +++ b/_case_studies/11_improving_business_metrics_for_better_impact.md @@ -1,11 +1,11 @@ --- -title: Improving business metrics for maximum impact using the CausalTune library +title: Improving business metrics for better impact using the CausalTune library layout: page description: >- This tutorial provides an introduction to improving business metrics using the ERUPT metric and the CausalTune library in Python. It shows a practical example and the use of the ERUPT metric for optimizing clickthrough rates. summary: >- This tutorial provides an introduction to improving business metrics using the ERUPT metric and the CausalTune library in Python. It shows a practical example and the use of the ERUPT metric for optimizing clickthrough rates. It also shows how to use ERUPT to evaluate previous experiments, as well as how to evaluate the potential effect of a future experiment with different assignments using a real business example. image: assets/causaltune-targeting.png -image-alt: Improving business metrics for maximum impact +image-alt: Improving business metrics for better impact link: https://towardsdatascience.com/targeting-variants-for-maximum-impact-bdf26213d7bc ---