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1、Table Of ContentsTable Of Contents HYPERLINK l _bookmark0 Industryoverview HYPERLINK l _bookmark0 5 HYPERLINK l _bookmark1 FocusonNewRetailforgrowth HYPERLINK l _bookmark1 5 HYPERLINK l _bookmark2 Geographicexpansion HYPERLINK l _bookmark2 8 HYPERLINK l _bookmark3 Focalpointsfore-commercestocksin201
2、9 HYPERLINK l _bookmark3 14 HYPERLINK l _bookmark4 Profitmargintrendtostabilizein2019E;signsofarisingmarg HYPERLINK l _bookmark4 14 HYPERLINK l _bookmark5 Driverofprofitmargin#1:Useracquisitioncost HYPERLINK l _bookmark5 16 HYPERLINK l _bookmark6 Driver of profit margin #2: Compare unit economicsamo
3、ngmerchant HYPERLINK l _bookmark6 16 HYPERLINK l _bookmark7 Valuations HYPERLINK l _bookmark7 18 HYPERLINK l _bookmark8 Valuationframework HYPERLINK l _bookmark8 18 HYPERLINK l _bookmark9 Valuationdetails HYPERLINK l _bookmark9 18 HYPERLINK l _bookmark10 Valuationcomparisons HYPERLINK l _bookmark10
4、19 HYPERLINK l _bookmark11 Alibaba HYPERLINK l _bookmark11 23 HYPERLINK l _bookmark12 JD.com HYPERLINK l _bookmark12 25 HYPERLINK l _bookmark13 Outlook andfinancialforecasts HYPERLINK l _bookmark13 27 HYPERLINK l _bookmark14 Valuation andrisks HYPERLINK l _bookmark14 33 HYPERLINK l _bookmark15 Valua
5、tion HYPERLINK l _bookmark15 33 HYPERLINK l _bookmark16 risks HYPERLINK l _bookmark16 33 HYPERLINK l _bookmark17 Companyprofile HYPERLINK l _bookmark17 34 HYPERLINK l _bookmark18 Shareholdingstructure HYPERLINK l _bookmark18 34 HYPERLINK l _bookmark19 Managementprofile HYPERLINK l _bookmark19 35 HYP
6、ERLINK l _bookmark20 Pinduoduo HYPERLINK l _bookmark20 36 HYPERLINK l _bookmark21 Outlook andfinancialforecast HYPERLINK l _bookmark21 38 HYPERLINK l _bookmark22 Marketingcostisthevariableinturningprofitable HYPERLINK l _bookmark22 39 HYPERLINK l _bookmark23 Financialforecasts HYPERLINK l _bookmark2
7、3 40 HYPERLINK l _bookmark24 Valuation andrisks HYPERLINK l _bookmark24 45 HYPERLINK l _bookmark25 Valuationframework HYPERLINK l _bookmark25 45 HYPERLINK l _bookmark26 risks HYPERLINK l _bookmark26 45 HYPERLINK l _bookmark27 Companyprofile HYPERLINK l _bookmark27 46 HYPERLINK l _bookmark28 Sharehol
8、dingstructure HYPERLINK l _bookmark28 46 HYPERLINK l _bookmark29 Managementprofile HYPERLINK l _bookmark29 47 HYPERLINK l _bookmark30 Vipshop HYPERLINK l _bookmark30 48 HYPERLINK l _bookmark31 Outlook andfinancialforecasts HYPERLINK l _bookmark31 50 OfContents HYPERLINK l _bookmark32 Valuation andri
9、sks HYPERLINK l _bookmark32 55 HYPERLINK l _bookmark33 Valuationframework HYPERLINK l _bookmark33 55 HYPERLINK l _bookmark34 Earningssensitivity HYPERLINK l _bookmark34 55 HYPERLINK l _bookmark35 downsiderisks HYPERLINK l _bookmark35 56 HYPERLINK l _bookmark36 Companyprofile HYPERLINK l _bookmark36
10、57 HYPERLINK l _bookmark37 Shareholdingstructure HYPERLINK l _bookmark37 57 HYPERLINK l _bookmark38 Management profile HYPERLINK l _bookmark38 58Industry overviewsee two main industry trends driving the corporate strategy of major e-com- merceplayersinChina:1)acategoryshifttowardsFMCGandarepositioni
11、ngof coreexpertise,and2)diversedemographicandgeographicsegmentation,encouragescompaniestoseekalargeruserbase.Focus on New Retail for growthgrowth focus in underpenetrated FMCG segment Oneoftheunderlyingthemesine-commercecontinuestobethepushtowards FMCG (fast-moving consumer goods) segment penetratio
12、n, as e-commerce evolves from standardized products with a longer shelf life (e.g. 3C - computer, communication, consumer electronics) towards non-standard products with a shorter shelf life (e.g. groceries). believe China is still at an early stage of its investment cycle, which may continue for se
13、veral more years before we enter meaningful harvestingcycle.putthefiguresintoperspective,EuromonitordataindicatesthatChinase-com- merce penetration is 23% in 2018, one of the highest among other heFMCGcategory,andinparticular,thefood andbeveragesegment,Chinastillhasroomtoscaleup,withapenetrationrate
14、9%.Incomparison,SouthKoreahashighpenetrationinbothtotale-commerceFMCG,atleastprovidinganindicationthatFMCGpenetrationcanrisemeaningful- ly once infrastructure isdeveloped.Figure 1: E-commerce penetration comparison by countryFigure 1: E-commerce penetration comparison by country25%20%15%10%Source :
15、EuromonitorChinaKoreaJapanBraziISource : EuromonitorOnline penetration, 2018ChinaKoreaUSJapanBrazilFMCG9.0%21.1%4.1%3.6%0.4%Food and drink7.7%22.1%2.3%3.2%0.2%Consumer Health22.2%11.8%11.5%8.3%1.4%Home Care15.2%10.5%2.8%2.1%0.4%Pet Care36.9%36.0%16.8%11.7%2.2%Source : EuromonitorSource : Euromonitor
16、Food and drink, which contributes nearly 80% of FMCG category, has only7.7% online penetration, vs. Korea at 22.1%. Euromonitor estimates suggest foodand drinksonlinepenetrationcouldriseto10.4%in2022E,withinwhichwebelievethe upside will mostly come from the fresh food sub-category. Major market such
17、 as Miss Fresh an upcoming start-up in the fresh food delivery segmentin Chinaandinternetgiant-backedHemaandSuperSpeciesleveragetheironline- offline integrated experience and logistics capability to educate users and drive onlinefreshfoodgrowth(akaNewRetail).Forothersub-categories,wealsofurther upsi
18、de from a higher online penetration into consumer health (22.2% in 2018to30.0%in2022E),homecare(15.2%in2018to19.2%in2022E)andpetcare (36.9%in2018to45.2%in2022E),accordingtoEuromonitor.Intheory,ifChinacan tripletheFMCGsegmentsonlinepenetrationfrom9%in2018to27%overthenext few years, we believe the onl
19、ine e-commerce market size will grow from RMB4,315bnin2018toRMB8,603bnin2022E.Figure 3: Total retail market split by key categoriesFigure 4: Online retail market split by key categoriesFigure 3: Total retail market split by key categoriesFigure 4: Online retail market split by key categoriesRMB bn 2
20、,490 2,648 2,490 2,648 2,809 2,972 3,136 RMB bn 8,00025,00020,00015,00010,0005,000010,4113,6072,03211,2313,9192,14410,4113,6072,03211,2313,9192,14411,9914,2612,28212,7224,6242,42813,4105,0042,58620182019E2020E2021E2022ESource : EuromonitorAppareIFMCG - food and drinkFMCG - othersSource : Euromonitor
21、6,0004,0002,00001,8351,3702,3761,5472,8801,7283,3971,0021,9083,8961,1112,08820182019E1,8351,3702,3761,5472,8801,7283,3971,0021,9083,8961,1112,088Source : EuromonitorAppareIFMCG - food and drinkFMCG - othersSource : EuromonitorFigure 2: FMCG penetration and breakdown by sub-categoryFigure 2: FMCG pen
22、etration and breakdown by sub-categoryForacomparativemeasure,the3Candapparelsegmentsrepresent24%ofretailconsumptioninChina(onlinepenetrationof37%),andFMCGisonly9%pene- trateddigitallyinChina,sointheory,thereisalargerRMB1,120bnmarketopportu- nity for e-commerce players tocapture.Theinvestmenttosecure
23、thelarge(totaladdressablemarket)isalreadyunder- ChinasNationalBureauofStatistics(NBS)indicatesthatthefoodcategory andnon-foodFMCGcategoryhavebeengrowing34%and26%yoyrespectively, outpacingthegrowthof7%yoyforapparelin2018.Source : NBSFMCG - food and drinkSource : NBSFMCG - othersAppareIFigure 5: NBS-r
24、eported online FMCG retail sales growth is faster than that other categories in 2018Figure 5: NBS-reported online FMCG retail sales growth is faster than that other categories in 2018AccordingtoEuromonitorandourowncalculation,the3CsegmentisalreadydigitallypenetratedwithJDcapturing47%marketshareovera
25、llwhiletheapparel segmenthas55%penetrationwithAlibabaholding45%marketshare.Figure 6: Online penetration and market share by key verticalFigure 6: Online penetration and market share by key verticalApparel3CFMCGFMCG - Food and drinkOnline retail sales, RMBbn1,370749362279Online penetration, %55.0%36.
26、8%9.0%7.7%Market share, %BABA45%25%42%22%JD6%47%12%10%PDD6%2%31%20%VIPS3%1%6%1%Source : Euromonitor, company data, Deutsche Bank estimatesNote: Market share based on our estimation of fulfilled GMV ratio of company reported GMV.Source : Euromonitor, company data, Deutsche Bank estimatesNote: Market
27、share based on our estimation of fulfilled GMV ratio of company reported GMV.DominanceandprofitabilityintheFMCGsegmentisyetunclearOneofthecriticalchallengestogrowingintotheFMCGsegmentisthatthetradi- tionalcoreexpertisethathelpedthee-commerceplatformgrowislessofastrength in succeeding in the FMCG seg
28、ment. For example, competitive pricing may bea relativelyhighdecision-makingcriterionforaconsumerwhendecidingwhere/how to purchase a computer, but quality of goods or convenience/immediacy may greaterdecision-makingfactorswhenaconsumerdecideswheretoshopforceries.Theendresultisthate-commerceplatforms
29、areinvestingheavilyintople,operationsandinfrastructure(e.g.coldchainlogistics)tobolstertheirmarket position across brand positioning, product selection, delivery time and conve- niencetoconsumers.believeexistingofflineretailersarealsotakingthethreat frome-commerceplayersmoreseriouslyandnowtreatdigit
30、altransformationascritical part of their sustainabilitystrategy.Figure 7: No single offline FMCG retailer has more than 10% market share5.4%3.0%2.6%2.0% 1.9%1.4%10.0%Figure 7: No single offline FMCG retailer has more than 10% market share5.4%3.0%2.6%2.0% 1.9%1.4%8.0%6.0%4.0%2.0%0.0%Source :KantarAsa
31、result,webelieveinvestmentsandcompetitionwillcauseoverallprofitgins for e-commerce players to fall. In fact, New Retail dragged Alibabas non- GAAPmargindownby7%to28%inFY19andweexpectsimilarlevelof drag in FY20. While the opportunity is large, we do not see a clear path earningsrecoveryacrosstheentir
32、espaceinasystematicfashionasrelatingtoRetailSource :KantarGeographic expansionMeanwhile, Chinese consumers needs are quite diverse with meaningful differ- enceinconsumptionpatternsacrossincomebracketsandculturalbackgrounds. Given the diverse nature of consumers in China, online platforms have remain
33、 focused on growing users, particularly in lower tier cities where penetration has room to scalefurther.As shown below, the income disparity between Tier 3-5 cities and Tier 1 cities is morethan10yearsdifference,showinghowmuchroomthereisforconsumption upgradeastheChinesemiddleclassgrows.Tier3-5isals
34、osupposedtorepresent 50%oftotalChineseincomeby2022EatanestimatedRMB20.3tnindisposable income.RMB45,00040,00035,00030,00025,000Beijing ShanghaiRMB45,00040,00035,00030,00025,000Beijing ShanghaiGuangzhou ShenzhenNew Tier 1Tier 220,000Tier 3-515,00010,0005,0000Source : CEIC, Wind, NBS, Deutsche Bank est
35、imatesSource : CEIC, Wind, NBS, Deutsche Bank estimatesAsapointofreference,Chinahas65%ofitstotalpopulationinTier3andbelow cities, based on NBS data. Comparatively, our data analysis shows that e-commerceplayershave50%ofusersfromlowertiercitieswithPDDthemost skewedtowardsTier3andbelowcityconsumers,wh
36、ileJDhasthehighestportion ofTier1-2cityconsumers.Theseasonalpick-upinlowertiercityconsumersduring theChineseNew(typicallyinJanuaryandFebruary)spendingseason,also indicatesthatlowertiercityconsumersaredigitallyconnectedandwillingtospend online,butareyettomakeitarecurringandfrequentexperience.Source :
37、 CEIC, Wind, NBS, Deutsche Bank estimatesSource : CEIC, Wind, NBS, Deutsche Bank estimatesFigure10:Figure10:MAUmixacrossplatformsvs.Chinatotallation mix by different tiercitiesFigure 11: Users from tier 3 cities and below as % of total users by MAU70%VIPSTaobao60%VIPSTaobao50%40%China totaI popuIati
38、onTaobaoPDDTier 1-2 citiesTier 3 cities and beIow30%Source : NBS, Jiguang, Deutsche BankSource : Jiguang, Deutsche BankJan 18Apr 18JuI 18Oct 18Jan 19Apr 19Source : NBS, Jiguang, Deutsche BankSource : Jiguang, Deutsche BankFigure 8: Disposable income of tier 3-5 cities will account for 50% of total C
39、hinese income in 2022EFigure 9: Different Chinese cities positions on annual expenditure per capita S-curveFigure 8: Disposable income of tier 3-5 cities will account for 50% of total Chinese income in 2022EFigure 9: Different Chinese cities positions on annual expenditure per capita S-curveGiventhe
40、roomforuserexpansion,e-commerceplayershavebeenmarketingand investingaggressivelytosecuremoreusers.Overthepast12months,AlibabaPDDhavebeenmoresuccessfulingrowingusersthanJDandVIPS.BABAJDPDDVIPS# of active customers, mn2016443227na522017515293245582018636305419612019E72531852363Figure 12: Number of pay
41、ing customers by key platformSource : Company data, NBS, Deutsche Bank estimatesChina total population, mn1,395 as of 2018Figure 12: Number of paying customers by key platformSource : Company data, NBS, Deutsche Bank estimatesAlso,whilee-commerceplayershavebeenscalingupusersinlower-tiercities,PDD ap
42、pearstobeshiftingitsfocustogainingmorehigher-tiercityconsumersaswell, as evidenced by the sharp pick-up in total users as well as higher-tier city recently. Although PDDs mix between higher- and lower-tier cities does not appearstobeshiftingsignificantly,wedonotethatPDDappearstobegainingtrac- tionwi
43、thhigher-tiercityconsumersaswell.Basedoncommentsmadebytheman- agementsofleadinge-commerceplayerscominginto2019,weexpectthefightnew users will continue to be a major driver of revenue and profit outlook for the comingquarters.Figure 13: Indexed MAU in tier 1-2 cities (assuming bao MAU in Jan18 as 100
44、)Figure 14: Indexed MAU in tier 3 cities and below (assum- ing Taobao MAU in Jan18 as 100)Figure 13: Indexed MAU in tier 1-2 cities (assuming bao MAU in Jan18 as 100)Figure 14: Indexed MAU in tier 3 cities and below (assum- ing Taobao MAU in Jan18 as 100)1401201000TaobaoVIPSSource : Jiguang, Deutsch
45、e BankJan 18Apr 18JuI 18Oct 18Jan 19Apr 19Source : Jiguang, Deutsche Bank1201000TaobaoVIPSSource : Jiguang, Deutsche BankJan 18Apr 18JuI 18Oct 18Jan 19Apr 19Source : Jiguang, Deutsche BankFigure15:Indexedtier1-2citiesnewaddedFigure15:Indexedtier1-2citiesnewaddedusersbybaoandPDD(assumingMay18as100)Fi
46、gure16:Tier3citiesandbelownewaddedusersbybaoandPDD(assumingMay18as100)200150Jan 19100Jan 192001501000Source : Jiguang, Deutsche BankMay 18JuI 18Sep 18Nov 18Jan 19Mar 19May TaobaoSource : Jiguang, Deutsche Bank0May 18JuI 18Sep 18Nov 18Source : Jiguang, Deutsche BankTaobaoSource : Jiguang, Deutsche Ba
47、nkMar 19May 19Figure 17: New users added in tier 3 cities and below as % of total new users70%Figure 17: New users added in tier 3 cities and below as % of total new users60%50%40%Source : Jiguang, Deutsche BankMay 18JuI 18Sep 18Nov 18Jan 19Mar19May TaobaoSource : Jiguang, Deutsche BankDemographic b
48、alance is slightly better than geographic balance Demographic segmentation across age and gender is more balanced than graphicmix.Chinahasarelativelyequalgendermix(male:female:51%:49%),moste-commerceplayershavemorefemaleusersthanmaleusers.believethis phenomenonissomewhatexpectedgiventheculturalbackd
49、rop.JDisanexception with 54% male, given its product focus on electronics categories. VIPS has femaleusersasithasmoreapparel-relatedproductsonitsplatform.and PDDsusershavearelativelysimilargendermixwith59%femaleusersforand56%femaleusersforPDD.Regardinguseragedistribution,Taobao/PDDmoreyoungusersunde
50、r25(40%oftotalusers),comparedtoJD/VIPSwhichhave35%ofusersunder25years-old.Onarelativebasis,wedonotseee-commerce playersfocusingasmuchondemographicusershiftintheirnewuseracquisition strategies, relative to geographic shift. In general, we believe and cohortsareslightlybetterpositionedthanpeersinterms
51、ofabilitytoscaleandcon- sumemoreovertime,astheytendtohaveayoungeragedistributionvs.peers.China totaIpopuIationTaobaoVIPSChina totaI popuIationTaobaoPDDVIPSSource : NBS, Jiguang, Deutsche BankSource : NBS, Jiguang, Deutsche BankMaIeFemaIeSource : NBS, Jiguang, Deutsche BankSource : NBS, Jiguang, Deut
52、sche BankUnder 2526-3536-45Above 46Figure 18: Gender mix by MAU across platformFigure 19: Age distribution by MAU across platformFigure 18: Gender mix by MAU across platformFigure 19: Age distribution by MAU across platformThe difference in user profile results in a meaningful discrepancy between pl
53、at- forms,asindicatedbyfrequencyofpurchaseandaverageticketsizeofpurchases, as shownbelow.Figure 20: Summary of key operation metricsFigure 20: Summary of key operation metricsBABAJDPDDVIPS# of active customers, mn2016443227na522017515293245582018636305419612019E72531852363Net add in active customers
54、, mn20163672na1620177266na620181211317432019E89121053Orders per customer, mn201653.47.8na5.2201750.58.017.65.8201842.29.726.57.22019Ena11.1na8.5Annual ARPU per customer, RMB20164,4722,092na1,31820174,8802,3765771,51620184,8162,9181,1271,6772019E5,0753,4441,7302,214Average order size, RMB201684267na2
55、55201797296332622018114300422322019Ena310na261# of merchants20169,500,000107,500nana201710,000,000145,000152,000na201810,500,000187,5002,075,0001,000Source : Company data, Deutsche Bank estimatesNote:Source : Company data, Deutsche Bank estimatesNote:1)alldatabasedoncalendaryear.2)ARPUandaverageorde
56、rsizebasedonfulfilledGMV,whichweestimateis55%oftotalGMVreportedbyAlibabaand50%-54%forJD,60%forPDDand77%-81%forVIPS.Focal points for key e- commerce stocks in 2019Profit margin trend to stabilize in 2019E; signs of a rising margin a key criterion for stock rallyAsdiscussedaboveintheindustrysection,th
57、ee-commerceindustryinChinahas seen aggressive investment against a backdrop of robust and growth prospectsintermsofbothcategoryandusergeographicexpansion.Theendresult hasbeenadeclineinprofitmarginoverthepastfewyears.Whilemulti-yeargrowth prospectsarerich,webelievethetimevalueofmoneyisanimportantcrit
58、erionconsiderinrelationtoinvestingintheChinesee-commercesector.Identifyingturn- arounds in investment or a turn in profit trends will be to generating alpha in Chinesee-commerce.that extent, we believe 2019 represents a year in which we see profit margin potentiallystabilizefromheavyinvestmentin2018
59、.Noneofthee-commerceplay- ersappeartobedisavowingthelong-termgrowthprospects,buttheyhavestarted tomoderatespendingasweakermacroeconomicconditionsandreducedreturnon investmentaretemperingtheoutlook.Ingeneral,webelievestockshaverecovered fromtroughsearlierintheastherehavebeensignsofimprovingmarginsing
60、intoCY19.IfcompaniescansustainthemarginrecoveryoutlookintoCY20,believetheremaybefurtherroomforupside.ifthecompaniesengagein aggressivegrowthcampaignsagain,wefeelstocksmaynotperformasrichly.Figure 21: BABA non-GAAP EBITA marginFigure 22: JD non-GAAP net marginFigure 21: BABA non-GAAP EBITA marginFigu
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