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Realtime Bid Optimization with Smooth Budget Delivery in Online Advertising
jujudubai
September 26, 2014
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20 slides
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1. Introduction 2. Background and Related Work 1. Problem Setup
3. Online Bid Optimization 1. Smooth Delivery of Budget 2. Selection of High Quality Ad Requests - Flat CPM Campaigns 3. Selection of High Quality Ad Requests - Dynamic CPM Campaigns 4. Estimation of CTR and AR (CVR) 4. Practical Issue 1. Cold Start Problem 2. Prevention of Overspending 5. Experimental Results 1. Comparison of Pacing Strategies 2. Evaluation of Real Campaign Performance 6. Conclusions Agenda -
1. Introduction • RTBʹ͓͚Δ࠷దԽϓϩηε “༧ࢉεέδϡʔϧͷ༧ࢉ੍Լʹ͓͍ͯɺCampaignͷύϑΥʔϚϯεͷ࠷େԽΛਤΔ”͜ͱ • ύϑΥʔϚϯεͷܭଌࢦඪ • CPCͱCPAͷ࠷খԽ •
CTRͱAR(CVR)ͷ࠷େԽ • ༧ࢉ৴੍ͷฏԽ • ઃఆ࣌ؒΑΓલʹɺڵຯͷ͋ΔimpͷҰ෦Ҏ্Λߪೖ͠ͳ͍Α͏ʹ͢Δ • εέδϡʔϧ్தʹ༧ࢉ͕ਚ͖Δ͜ͱɺաͳߪೖΛ͙ • ຊݚڀʹ͓͚ΔఏҊɾݕ౼ • ֤CampaignͷͨΊͷฏͳ৴੍Λຬͤ͞Δؒͷ ύϑΥʔϚϯεMetricsΛ࠷దԽ͢ΔͨΊͷΦϯϥΠϯΞϓϩʔνΛఏҊ • ฏԽ৴੍Λ՝ͨ͢ΊͷະདྷͷফඅΛ܁Γฦ͠ਪఆͨΊʹ ίϯτϩʔϧɾϑΟʔυόοΫɾϧʔϓΛݕ౼ -
2. Background and Related Work 1. Problem Setup time slot
ຖͷ༧ࢉͷ՝ goal ࢦඪͱ੍݅ ֫ಘͨ͠Ձ ೖࡳճ ࠂओͷίετ time slot ຖͷ༧ࢉ time slot t Ͱফඅ͞Εͨ༧ࢉ eCPMͷ্ݶ “ε-δ๏” -
3. Online Bid Optimization 1. Smooth Delivery of Budget ফඅ༧ࢉ
time slot ຖͷࢿͷߋ৽ time slot t ͷࠂϦΫΤετ૯ ࣍ͷtime slot t+1ͷad requestͱwinning rateͷ༧ଌ Feed Back Control ΛՄೳʹ͢Δ time slot t Ͱফඅ͞Εͨ༧ࢉ -
time slot t ͷ1ظઌͷ༧ࢉͷࢉग़ ༧ࢉ͕Ұ༷ͷ߹ ༧ࢉ͕Ұ༷Ͱͳ͍߹ - U ͕UʹΑͬͯ ҟͳΔ߹
- U ͕֤UͰ Ұ༷ͳ߹ time slot t ͷ࣌ؒతͳ͞ʢsecʣ Click or CVͷ༧ଌ֬ ༧ࢉͷֹ time slotͷ͞ͷൺ click or conversion͕֬ ߴ͍Campaignʹଟ͘ͷ༧ࢉΛׂ͘ ˎ ͜ͷϩδοΫ͚ͩͰɺclick or conversion͕֬θϩͷCampaignʹ༧ࢉׂ͕͔Εͳ͍ͨΊɺ2ͭͷઓུΛ྆ํѻ͏ * -
3. Online Bid Optimization 2. Selection of High Quality Ad
Requests - Flat CPM Campaigns goalɿ ݱࡏͷslotͷpacing rate Λߟྀ͠ɺࢿ͖͢ϦΫΤετΛબ͢Δ͜ͱ ݻఆ͞ΕͨೖࡳՁ֨ ʹ time slot ຖͷ c_i ͷ౷ܭྔΛࢉग़͢ΔͨΊʹ༻ σʔλͷͷฏۉ աڈͷ࣮σʔλ͔Βࢉग़ ʢࢀߟʣ -
େͳad requestྔ͔ΒɺClick or CV͠қ͍ad requestΛબ͢Δඞཁੑ CTR, CVRʹج͍ͮͨtime slot tʹ͓͚Δad requestͷ
CTR, CVRΛج४ͱͨ͠ϑΟϧλʔͰߟྀ͠ɺબ͢Δ q_t(s)͕աڈͷ࣮σʔλ͔Βࢉग़͞ΕΔͨΊɺਖ਼֬ͳσʔλͱݴ͍͍ ରࡦͱͯ͠ɺτ(t)ʹ৴པ۠ؒΛઃ͚Δ time slot t ʹ͓͚Δᮢ -
1.96 (95% confidence interval) • τ(t)ʹ৴པ۠ؒʢᮢʣ աڈͷ࣮σʔλ͔Β౷ܭྔΛܭࢉ͢ΔͨΊͷσʔλ Ad request ࠾্ݶ
Ad request ࠾Լݶ ৴པ۠ؒΛݩʹbid priceΛࢉग़ µ(t) + ⌧ (t) p d µ(t) ⌧ (t) p d τ(t)ΨεΛԾఆ τ(t)͕৴པ۠ؒͰ͋Εɺpacing_rate(t)ͷ֬Ͱೖࡳ ˎɹ৴པ۠ؒͷᮢܭࢉࣜ ҎԼͷࣜΛ༻͍ͯɺτ(t)Λܭࢉ ˎ “ t -1 ” ͱ͍͏աڈͷtime slotΛ༻͍ͯࢉग़ -
3. Online Bid Optimization 3. Selection of High Quality Ad
Requests - Dynamic CPM Campaigns 1. bid price c* ͷࢉग़ 2. base bid priceͷࢉग़ ui = AR ⇥ G base bid price ༧ଌ (CVR) ඪͱ͢ΔCPA 3. pacing_rate(t)ʹΑͬͯೖࡳՁ֨Λௐ ݻఆ͞ΕͨೖࡳՁ֨ ʹ time slot ຖͷ c_i ͷ౷ܭྔΛࢉग़͢ΔͨΊʹ༻ σʔλͷͷฏۉ CPA CampaignʹϑΥʔΧε pacing rate(t)ɺbiddingͷසΛίϯτϩʔϧ͢Δ -
ˆ ci = ✓⇤ui ✓ = ci ˆ ci bidprice
ˆ ci = ui ˆ ci = ⇢⇤ui (1) ɹSafe region : pacing rate(t) <= β1 ώετάϥϜθͷԼҐ1ʙ2ˋ མࡳՁ֨ σʔλΛੵ͠ɺ ώετάϥϜΛ࡞ (2) ɹCritical region : β1 <= pacing rate(t) <= β2 (3) ɹDanger region : β2 <= pacing rate(t) 1. ϦΫΤετΛϦδΣΫτ͍͗ͯ͢͠Δ 2. ೖࡳՁ͕֨͗͢Δ λʔήςΟϯάͷ੍͕ݫ͗͢͠Δ ҎԼͷࣜΛద༻ ೖࡳՁ֨ͷ্ݶ 3. దͳೖࡳՁ֨Ͱೖࡳ͢ΔͨΊɺpacing_rate(t)Λ3ྖҬʹ͚ͯɺೖࡳ ೖࡳՁ֨ -
4. Practical Issue 1. Cold Start Problem ✴ ղܾࡦ •
ྨࣅͨ͠CampaignσʔλΛ༻ -
4. Practical Issue 2. Prevention of Overspending ✴ ༧ࢉރׇͷࢭࡦ •
֤time slotͷ༧ࢉΛ͑ͨ߹࣍ͷtime slot·ͰೖࡳΛதࢭ -
ཧͱͷဃ ʢ༧ࢉͷҰ༷Λཧͱͨ͠߹ʣ dailyͷޡࠩ1% x : time slot y : total
budget spend 5. Experimental Results 1. Comparison of Pacing Strategies the ideal uniform spend and the actual spend using our uniform pacing strategy ͷ߹ -
x : time slot y : total budget spend x
: time slot y : relative performance in term of 1/eCPA dailyͷޡࠩ2.3% ཧͷࢿ ཧͱͷဃ ʢ֤time slotͰ ༧ࢉ͕ҟͳΔ߹ʣ the ideal spend and the actual spend using performance based pacing strategy ͷ߹ -
5. Experimental Results 2. Evaluation of Real Campaign Performance the
entire bid optimization framework 1. Flat CPM campaign • CTRͷ࠷େԽ 2. Dynamic CPM campaign • CPC, CPAͷ࠷খԽ -
• Compare with baseline model (in Flat CPM campaign) Baseline
modelͱɺtime slot tʹ͓͚Δpacing rateʹجͮ͘CTR(t)ͷᮢ͔Βࢉग़͢Δ ؆୯ͳదԠϑΟʔυόοΫ੍ޚΞϧΰϦζϜͰ͋Δɻ ฏۉͰ123%ͷύϑΥʔϚϯεվળ͕ݟΒΕΔ • Detail of Evaluation • ҟͳΔࠂओΧςΰϦʔ͔ΒϥϯμϜʹબͨ͠7ͭͷFlat CPM campaignΛ༻ • ͦΕΒ7ͭͷcampaignΛѻ͍ɺఏҊ͢ΔΞϓϩʔνͱطଘͷΞϓϩʔνΛධՁ • ֤Methodɺ1िؒՔಇͤͨ͞ޙɺ2िؒͷσʔλΛར༻ͯ͠ൺֱ -
• Compare with baseline model (in Dynamic CPM campaign) Baseline
modelͱɺpacing rateΛҰ༷ʹௐͨ͠طଘͷϞσϧ • Detail of Evaluation • ҟͳΔࠂओΧςΰϦʔ͔ΒϥϯμϜʹબͨ͠Dynamic CPM campaignΛ ඪઃఆຖʹஔʢCPC/CPAʣ͠ɺධՁ • ఏҊ͢ΔΞϓϩʔνͱطଘͷΞϓϩʔνͷLiftΛධՁ ฏۉͯ͠CPC19.02%ɺCPA30.87%ͷ ύϑΥʔϚϯεվળ͕ݟΒΕΔ -
6. Conclusion • ϦΞϧλΠϜͰͷ༧ࢉͷ࠷దԽख๏ΛఏҊ • “৴ޮՌͷվળ”ͱ”༧ࢉͷฏԽ”ͷ྆ํΛୡ • million of ad
request per secondͷσʔλྔΛϋϯυϧՄೳ • ༧ࢉͷunderpacingoverpacingΛߟྀͨ͠ΞϧΰϦζϜΛߟҊ • ࠓޙɺͬͱॲཧͰ͖ΔσʔλྔΛ૿͢