DIGITAL CUSTOMER SERVICE TRENDS: CHALLENGES AND OPPORTUNITIES

35 35 ACC JOURNAL 2021, Volume 27, Issue 2 DOI: 10.15240/ ul/004/2021-2-003 DIGITAL CUSTOMER SERVICE TRENDS: CHALLENGES AND OPPORTUNITIES Michal Dos ál Technical Uni e si y o Libe ec, Facul y o Economics, Depa men o In o ma ics, S uden ská 1402/2, 461 17 Libe ec, Czech Republic e-mail: [email p o ec ed] Abs ac Cus ome se ice is an essen ial pa o many companies and hei p oduc and se ice po olio. In he cu en imes, cus ome se ice has shi ed mo e owa ds i s digi al o ms. In p e ious esea ch ou digi al cus ome se ice ends ha e been iden i ied: i ual assis an s, cus ome se ice pe sonaliza ion, mobile echnologies, and opinion mining. This a icle aims o compa e hese indings wi h eali y by employing a ocus g oup discussion wi h p o essionals and poin ou he oppo uni ies and challenges ha he companies implemen ing hese ends a e aced wi h. The esul s show ha he indings co espond wi h academic li e a u e. Keywo ds Cus ome se ice; Vi ual assis an ; Pe sonaliza ion; Mobile echnologies; Opinion mining. In oduc ion Due o he global pandemic, he digi al o m o cus ome se ice has become mo e impo an and is widely used. E en he companies ha did no use he digi al se ices a ailable o connec wi h cus ome s ha e become sa ie in his ma e . They mus adap o cu en cus ome needs and s anda ds, which a e apidly changing. Based on he li e a u e esea ch ha he au ho o his a icle has conduc ed o map cu en digi al ends in cus ome se ice, ou a eas o in e es we e selec ed. These a eas in digi al cus ome se ice a e i ual assis an s, cus ome se ice pe sonaliza ion, mobile echnologies, and opinion mining (also called sen imen analysis). This a icle ocuses on syn hesizing li e a u e indings and indings om ocus g oup discussion ocused on he ou digi al cus ome se ice ends lis ed abo e. The i s sec ion desc ibes used esea ch me hods, desc ibing he app oach o ocus g oup discussion. In he main sec ion o his a icle he main esul s o his esea ch a e p esen ed. 1 Me hods o Resea ch Based on au ho ’s p e ious esea ch, whe e he e iewed cu en digi al ends om di e en pe spec i es, he ends a e now analyzed o poin ou he challenges and oppo uni ies. To achie e his, he cu en s a is ics collec ed om cu en li e a u e on his opic and om ele an da a sou ces we e syn hesized. In o de o con i m he esul s om he li e a u e esea ch, a ocus g oup o ga he quali a i e da a on his ma e was c ea ed. The ocus g oup comp ised 15 p o essionals in he ield o cus ome se ice. The pa icipan s we e employees o companies local o he Czech Republic; howe e , some also ope a ed on he in e na ional ma ke o we e pa o in e na ional conce n. 36 36 The main opic o he ocus g oup was he challenges and oppo uni ies in digi al cus ome se ice, speci ically in he ou a eas o cu en ends. Following a e he leading en ques ions ha he mode a o asked du ing he discussion: 1. How do you pe cei e he usage o i ual assis an s (o cha bo s) in you company? 2. Wha a e he main d awbacks o using i ual assis an s? 3. Whe e do you see he oppo uni ies o i ual assis an s? 4. Wha o ms o pe sonaliza ion o you cus ome se ice do you use? 5. F om he se ice p o ide ’s poin , whe e do you see d awbacks o using cus ome se ice pe sonaliza ion echniques? 6. In which di ec ions do you see oppo uni ies in cus ome se ice pe sonaliza ion? 7. How do you use mobile echnologies in you se ices o cus ome s? 8. Wha d awbacks and oppo uni ies do you see in implemen ing mobile solu ions in you cus ome se ice? 9. Wha is you expe ience wi h opinion mining echniques? 10. Whe e do you see oppo uni ies o such echnology? Wha a e he d awbacks? W i e-up o no es aken du ing he ocus g oup in e iew was epea edly discussed a e wa d wi h he pa icipan s o ensu e no impo an in o ma ion was le ou . 2 Resul s and Discussion The ollowing chap e discusses he esul s ob ained du ing ocus g oup discussion and compa es hem wi h academic li e a u e indings. 2.1 Vi ual Assis an Technologies In o his ca ego y, bo h ex -based and speech-based i ual assis an s a e included. A ex - based i ual assis an can be a cha bo o a dialogue sys em. A speech-based assis an can be a i ual pe sonal assis an (e.g., Si i, Alexa) o in elligen /sma agen [1]. Acco ding o Eu os a [2], only 2% o Eu opean companies use a cha bo in a use case, whe e he cha bo communica es wi h cus ome s. The op h ee coun ies ha use his echnology he mos a e Denma k wi h 5% o i s companies, Spain and F ance wi h 3%. The s a is ic is conce ned wi h en e p ises wi h mo e han en employees. Cus ome se ices suppo ed by a i icial in elligence a e gene ally mo e accep ed among cus ome s wi h p io AI knowledge and who a e no hesi an o sha e pe sonal in o ma ion [3]. Dubiel e al. [4] in es iga ed he usage o i ual agen s (VA), and he esul s show he ollowing:  Use s use he VA echnology mos ly a home o in a ca du ing d i ing.  Bo h equen use s and in equen use s a e conce ned on a simila le el abou he p i acy aspec s o using such echnology; howe e , he equen use s a e mo e com o able using VA in on o amily membe s.  Mos o he use s use VA o ac -checking, upda es on wea he , and playing music.  Use s a e mos conce ned abou he VA misunde s anding hem o s uggling o co ec ly ecognize speech wi h an accen . 37 37 Resea ch by Tulshan and Dhage [5] shows ha among he ou mos used i ual assis an s (speci ically oice assis an s: Google Assis an , Si i, Co ana, and Alexa), he Google Assis an has he bes pe o mance in oice-based ecogni ion and human ee in e ac ion; while he Si i assis an ound in Apple de ices is on he second place. Thei esul s show ha all ou assis an s could answe up o 17.35% o daily ques ions; howe e , he Google Assis an was ound o be he mos e icien wi h 59.80%. Acco ding o [5], he main challenge o oice ecogni ion echnologies is ha he oices o people a y, and hey speak in di e en ways. This also co esponds wi h he esul s o [4], speci ically, ha people a e conce ned he mos wi h VA echnology no unde s anding hem co ec ly. The i s h ee ques ions laid ou in he Me hods o Resea ch sec ion we e hema ically connec ed wi h he opic o his sec ion. The discussion showed ha he pe cep ion o i ual assis an echnology in en e p ises is o e all posi i e. The ocus g oup pa icipan s poin ed ou ha employing cha bo solu ions in hei cus ome se ice inc eased he quali y and a ailabili y o hei se ice, which led o highe cus ome sa is ac ion. This e y well co esponds wi h a s a is ic om [6] showing ha 69% o cus ome s p e e cha bo s because hey can p o ide quick eplies o simple ques ions. Acco ding o [7], 56% o cus ome s p e e o message a business a he han make a phone call o cus ome se ice. Based on he eedback he ocus g oup pa icipan s ecei ed om hei cus ome s, i is e iden hey a e mo e inclined o use he cha bo echnology when hei inqui y o eques is o a simple kind (e.g., inqui y abou he o de s a us o a so wa e ea u e). When discussing he main d awbacks o implemen ing he VA echnology in he pa icipan ’s companies, hey poin ed ou some in e es ing ema ks. The pa icipan s collec i ely ag eed ha he main d awback o implan a ion cha bo echnology in hei company was ha i was e y ime-consuming. The p ocess comp ises, e.g., he p epa a ion (ini ial p ojec planning, selec ing he sui able supplie o he echnology, ca e ully selec ing he use cases), implemen a ion, and con inuous adjus men s based on eedback. Few o he pa icipan s also poin ed ou ha he implemen a ion cos s a e qui e high. The ques ion ega ding wha he pa icipan s pe cei e as oppo uni ies in using VA b ough ou in e es ing poin s and subsequen discussion. One o he discussed opics was he paymen p ocess h ough a i ual assis an . Only wo o he p o essionals in he ocus g oup had di ec expe ience wi h implemen ing a paymen ea u e in o hei VA. The con e sa ion showed an in e es ing and p omising ea u e o companies whose business model allows paymen h ough VA. Ano he g ea oppo uni y, as pe cei ed by he ocus g oup pa icipan s, is he abili y o au oma e a la ge numbe o epe i i e asks and, in he case o cha bo s, use some ich o ma s as ideos and pic u es o suppo he communica ion. 2.2 Cus ome Se ice Pe sonaliza ion Acco ding o [8], mo e han 50% o cus ome s a e willing o sha e he in o ma ion abou he p oduc hey like o ge pe sonalized discoun s, and 83% o cus ome s a e willing o sha e hei da a o c ea e a mo e pe sonalized se ice o hem. The co e o cus ome se ice pe sonaliza ion is ga he ing da a abou he cus ome s and c ea ing a so-called use model. The se ices and con en s a e ailo ed o speci ic use s and cus ome s. Pe sonaliza ion o cus ome se ice is a powe ul ool o building long- e m appo and ela ionships wi h a company’s cus ome s [9]. I g ea ly impac s he quali y o he company- cus ome ela ionship and how he cus ome pe cei es he company. The e o e, cus ome s a e mo e likely o shop a companies ha p o ide pe sonalized ecommenda ions and a mo e pe sonal shopping expe ience [8]. 38 38 Discussion o his opic in he ocus g oup esul ed in some in e es ing ema ks. The pa icipan ag eed ha as people a e mo e open o new echnologies, hey a e also willing o sha e hei da a and in o ma ion abou hei buying habi s. The e o e, i is qui e easy o implemen pe sonalized se ice p ac ices. As he di icul y o implemen a ion is qui e low, hey iden i ied his as he main oppo uni y om he cus ome ’s poin o iew. F om he company’s poin o iew, he main oppo uni y lies in de eloping use ul skills in ma ke and cus ome esea ch and knowledge disco e y in he use da a. The pa icipan s o he ocus g oup also discussed some d awbacks and challenges ha hei companies a e aced wi h when implemen ing and using se ice pe sonaliza ion. Acco ding o he majo i y o he pa icipan s, he mos challenging aspec is secu i y and da a handling. I is e y impo an o keep use and cus ome da a sa e and elimina e all secu i y isks esul ing in da a leakage o , wo se, publica ion o cus ome da a on malicious websi es and da abases. Few pa icipan s also no ed ha many o hei cus ome s a e no willing o sha e hei da a. The discussion showed ha his migh be age- ela ed, as he younge age g oups a e mo e suscep ible o da a collec ion and consequen ailo ed se ices. The majo i y o cus ome s o he ew pa icipan s a e cus ome s o highe age – as his is hei a ge g oup o cus ome s. 2.3 Mobile Technologies The e a e se e al ools and me hods ha companies can use in o de o upg ade and mode nize hei cus ome se ice. One o hem is o employ mobile echnologies in hei p ocesses. I can be as simple as c ea ing a mobile- iendly layou o e sion o he company websi e o e-shop. These s eps adically upg ade he accessibili y o se ices o he a ge cus ome s. In cu en imes he mobile de ices a e a i al pa o li e o many people. I is an ins umen o connec ing hem wi h hei iends. Mobile de ices p o ide people wi h en e ainmen and a sense o communi y h ough social media apps. In he las yea s, mobile de ices also gained a e y impo an ole in he business en i onmen , and he e o e i becomes i al in he wo k en i onmen . Many businesses and companies ook ad an age o ha and cus omized hei business model o accommoda e he mode n equi emen s o hei cus ome s. The ocus g oup pa icipan s seemed o ha e discussed his opic he mos , as he e a e nume ous ways o ake ad an age o mobile echnologies a ailable o us. They we e asked abou he ways hei businesses and companies used mobile echnologies. Tab. 1: shows he main a eas o use cases whe e he mobile echnologies a e used in cus ome se ices he pa icipan s o e . Tab. 1: A eas o use cases o mobile echnologies A ea o use cases Desc ip ion P oduc ma ke ing Use o p oduc ca alogs in he o m o mobile apps; abili y o iew and add p oduc e iews Ad e isemen Use o QR codes in p omo ional ma e ials (bo h in p in and online) Cus ome suppo Use o mobile applica ion o mobile web page o connec wi h cus ome suppo depa men , possible usage o cha bo echnology. Sales P oduc ca alogs in mobile apps o web pages wi h embedded e- comme ce capabili ies. Mobile applica ions o discoun s. Sou ce: Own 39 39 The discussion led o a collec i e ag eemen ha implemen ing mobile echnologies as an upg ade o cus ome se ice is he easies in e ms o solu ions a ailable o companies. The pa icipan s ag eed ha he basic usage o mobile echnologies is he de elopmen o web pages ha a e compa ible wi h mobile de ices (meaning hey a e op imized o iewing and b owsing on small de ices) and ouch de ices such as able s o lap ops wi h ouch displays. Mo e han hal o he ocus g oup pa icipan s s a ed ha hey use o plan on implemen ing he QR code echnology. Acco ding o hem and he li e a u e, e.g., [10], his echnology is qui e popula among hei cus ome s. In o de o be able o use he QR codes, he cus ome s only need o ha e ei he a special applica ion ins alled on hei mobile de ice o i hey ha e a ecen model o mobile de ices, hey do no ha e o ins all any applica ion as he abili y o ead QR codes is embedded he came a app. E en ually, he needed applica ion may al eady be ins alled on hei de ices as i is qui e a commonly used ea u e. As one o he possible d awbacks o using QR codes, he pa icipan s iden i ied he ea o cus ome s ega ding he secu i y o he QR codes. I is impo an o he cus ome whe e he QR code is loca ed. A s a is ic [11] ega ding he place whe e he cus ome s eel mos secu e scanning he QR codes showed ha cus ome s eel sa e using his echnology a e aile s (such as supe ma ke s, shops) he mos wi h 45.48 %. In he second place, he e a e ba s and es au an s wi h 42.55 %. The es o he places deemed as secu e by he cus ome s is shown in Fig. 1. Sou ce: Own adap ed om [11] Fig. 1: Secu e loca ions o scanning QR codes 2.4 Opinion Mining Among he ocus g oup pa icipan s, opinion mining was ex ensi ely discussed; howe e , no many pa icipan s ha e hei own expe ience wi h he echnology. When he pa icipan s we e asked ques ion #9 ega ding hei expe ience wi h opinion mining, hei esponses inclined mo e owa ds he heo e ical le el, meaning ha many o hem did some so o esea ch o his cus ome se ice ool; howe e , hey did no decide o implemen i ye . When asked abou hei easoning behind his decision, a numbe o he pa icipan s ag eed on he cu en inabili y o he sys ems o wo k wi h he Czech language, as some o he pa icipan s wo k mos ly wi h Czech cus ome s. 42.55% 45.48% 24.59% 35.27% 19.40% 24.87% 33.55% 20.56% 33.64% 5.61% 0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50% Res au an Re aile Rec ea ion Financial Exce cise O ice/Place o Wo k Medical T a el Packaging O he 40 40 Sou ce: Own Fig. 2: Numbe o answe s o ocus g oup pa icipan s when discussing he in en ions o implemen opinion mining One o he ema ks eco ded h oughou he discussion was ha smalle local companies do no ind he cus ome opinion mining echnology use ul o hem a his ime. On he o he hand, he pa icipan s om companies ha a e pa o in e na ional conce ns o ha e s akeholde s om bigge i ms s a ed ha his pa o cus ome se ice is o big in e es o hei u u e se ice imp o emen . The pa icipan s we e also asked wha hey pe cei e as oppo uni ies and d awbacks o using he opinion mining echnology. The bigges oppo uni y o employing opinion mining in o he cus ome se ice p ocess is o gain use ul in o ma ion abou he cus ome ’s sa is ac ion wi h he p oduc o se ice p o ided. This way, he company can adjus i s cus ome se ice s a egies o imp o e he a e o happy, loyal, and e u ning cus ome s. Pa icipan s widely discussed he possible use cases hey would see i . Men ioned we e p oduc e iews om cus ome s, eal- ime sen imen analysis o cus ome s du ing calls o cha s wi h cus ome suppo , pos -call analysis o he ansc ip o cus ome -ope a o communica ion, analysis o he commen /discussion boa d on hei e-shop p oduc pages. This well co esponds wi h academic li e a u e [12, 13]. The e we e h ee pa icipan s (see Fig. 2) whose i ms and en e p ises al eady use he opinion mining capabili ies. They desc ibed hei use cases and some o hei bes p ac ices om implemen ing hem. Acco ding o hem, he bigges ad an age in using such echnology is in he amoun o da a abou he sa is ac ion o hei cus ome s as hey can quickly cus omize and al e hei se ices o i he needs o hei cus ome s. The e we e also wo pa icipan s who we e in he p ocess o implemen ing he opinion mining echnology. Se en pa icipan s we e hinking abou applying his echnology, and h ee did no plan o implemen opinion mining. Many o he p o essionals pa icipa ing in he ocus g oup s a ed ha he cos o implemen a ion is one o he bigges d awbacks in adop ing his echnology in hei businesses. In his sense, he implemen a ion o opinion mining ea u es is mo e in e es ing o companies ha can use he po en ial o he ulles , gene a e some iable ou comes bu mainly a o d i in he long un. Many pa icipan s concluded ha opinion mining is e y in e es ing and, when used e icien ly, a powe ul ool. 3 2 7 3 A e you hinking abou implemen ing opinion mining? Al eady implemen ed In he p ocess Yes No 41 41 Conclusion In his a icle he oppo uni ies and challenges o cu en digi al cus ome se ice ends iden i ied in au ho ’s p e ious wo k we e analyzed. A ocus g oup was o med comp ising se e al p o essionals who discussed hose ends. The indings we e compa ed wi h li e a u e and co esponding s a is ics. Tab. 2 summa izes he main oppo uni ies and challenges iden i ied by he ocus g oup pa icipan s, and he e o e he esul s o his esea ch. Tab. 2: Summa y o main oppo uni ies and challenges when implemen ing digi al cus ome se ice ends T end Oppo uni ies Challenges Vi ual Assis an s Paymen h ough VA. Au oma ion o epe i i e asks. Time-consuming implemen a ion. Implemen a ion cos s. Pe sonaliza ion Knowledge disco e y in use da a. Secu i y. Da a handling. Consen o da a sha ing. Mobile Technologies QR codes. Mobile applica ions. Possible secu i y issues (QR code scams) Opinion Mining Use ul cus ome sa is ac ion da a. Cos o implemen a ion. Sou ce: Own Acknowledgmen s This wo k was suppo ed by he S uden G an Compe i ion o he Technical Uni e si y o Libe ec unde p ojec No. SGS-2021-1014. Li e a u e [1] GNEWUCH, U.; MORANA S.; MAEDCHE A.: Towa ds Designing Coope a i e and Social Con e sa ional Agen s o Cus ome Se ice. In: P oceedings o he In e na ional Con e nce on In o ma ion Sys ems 2017. Seoul, Sou h Ko ea, 2017. [2] EUROSTAT: ISOC_EB_AI da ase . [online]. 2021. A ailable om WWW: h ps://ec.eu opa.eu/eu os a /da ab owse /p oduc / iew/ISOC_EB_AI?lang=en [3] ISIDORE, R.; ARUN, J.: A e Indian Consume s Happy wi h A i icial In elligence Enabled Pe sonalized Cus ome Se ice. Academy o Ma ke ing S udies Jou nal. 2021, Vol. 25, pp. 1–16. ISSN 10956298. [4] DUBIEL, M.; HALVEY, M.; AZZOPARDI, L.: A Su ey In es iga ing Usage o Vi ual Pe sonal Assis an s. a Xi :1807.04606. [online]. 2018. A ailable om WWW: h p://a xi .o g/abs/1807.04606 [5] TULSHAN, A.; DHAGE, N.: Su ey on Vi ual Assis an : Google Assis an , Si i, Co ana, Alexa. 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Michal Dos ál 43 43 TRENDY DIGITÁLNÍCH ZÁKAZNICKÝCH SLUŽEB: VÝZVY A PŘÍLEŽITOSTI Služby zákazníkům jsou elmi důleži ou součás í mnoha i em a jejich po olia p oduk ů a služeb. V současnos i se služby zákazníkům zaměřují přede ším na jejich digi ální podobu. V ámci p o edeného předchozího ýzkumu byly iden i iko ány č yři současné endy digi álních službách zákazníkům: i uální asis en i, pe sonalizace služeb, mobilní echnologie a opinion mining. Cílem oho o článku je po o na a o zjiš ění s eali ou, a o pomocí diskuse s odbo níky ámci uspořádané ocus g oup a éž yzd ihnou hla ní příleži os i a ýz y při implemen aci ěch o echnologií. Výsledky ko espondují se zjiš ěními akademické li e a uře. TRENDS IM DIGITALEN KUNDENSERVICE: HERAUSFORDERUNGEN UND MÖGLICHKEITEN Kundense ice is ein seh wich ige Bes and eil iele Un e nehmen und ih es P oduk - und Diens leis ungspo olios. In de ak uellen Zei ha sich de Kundense ice meh in Rich ung seine digi alen Fo men e lage . In meine o he igen Fo schung wu den ie digi ale Kundense ice-T ends iden i izie : i uelle Assis en en, Kundense ice-Pe sonalisie ung, mobile Technologien und Meinungs o schung. Das Ziel dieses Papie s is es, diese E gebnisse mi de Reali ä zu e gleichen, indem eine Fokusg uppendiskussion mi Fachleu en du chge üh wi d, und zeigen die Chancen und He aus o de ungen au , mi denen die Un e nehmen kon on ie sind, die diese T ends umse zen. Die E gebnisse zeigen, dass die E gebnisse mi de wissenscha lichen Li e a u übe eins immen. TRENDY W CYFROWEJ OBSŁUDZE KLIENTA: WYZWANIA I SZANSE Obsługa klien a jes is o nym elemen em wielu i m i ich po ela p oduk ów i usług. W obecnych czasach obsługa klien a skupia się p zede wszys kim na jej cy owej o mie. Moje pop zednie badania ziden y ikowały cz e y ak ualne endy w cy owej obsłudze klien a: wi ualni asys enci, pe sonalizacja usług, echnologie mobilne o az eksplo acja opinii. Niniejszy a ykuł ma na celu po ównanie ych us aleń z zeczywis ością pop zez zas osowanie dyskusji w g upie okusowej z udziałem specjalis ów o az wskazanie pods awowych szans i wyzwań, p zed k ó ymi s oją i my wd ażające e echnologie. Wnioski są zgodne z li e a u ą naukową.