{"id":12168,"date":"2022-11-18T11:39:12","date_gmt":"2022-11-18T11:39:12","guid":{"rendered":"https:\/\/projectsofar.info\/aisuperior\/?post_type=blog&p=12168"},"modified":"2023-12-04T13:03:48","modified_gmt":"2023-12-04T13:03:48","slug":"how-nlp-can-be-used-to-improve-customer-service-the-benefits-of-an-ai-based-customer-service","status":"publish","type":"blog","link":"https:\/\/aisuperior.com\/nl\/blog\/how-nlp-can-be-used-to-improve-customer-service-the-benefits-of-an-ai-based-customer-service\/","title":{"rendered":"Hoe NLP kan worden gebruikt om de klantenservice te verbeteren: de voordelen van een op AI gebaseerde klantenservice"},"content":{"rendered":"

Doorbraken in de technologie waarbij taalkunde wordt gecombineerd met kunstmatige intelligentie (AI) hebben de weg vrijgemaakt voor een betere communicatie tussen mens en machine. Bedenk hoe virtuele assistenten, zoals Apple's Siri en Google Assistant, in de loop der jaren zijn verbeterd: van het starten met het volgen van eenvoudige opdrachten tot het bellen van bedrijven om afspraken te maken. Deze prestaties worden mogelijk gemaakt door modellen voor natuurlijke taalverwerking (NLP), en hun potentieel evolueert nog steeds.<\/p>\n

Wat is natuurlijke taalverwerking (NLP)?<\/span><\/h3>\n

NLP is de subgroep van de computerwetenschap die machines traint om menselijke taal \u2013 gesproken en geschreven \u2013 te begrijpen zoals mensen dat doen. De gesprekken van mensen zijn weliswaar niet altijd eenvoudig, maar klinken natuurlijk omdat mensen intu\u00eftief op elkaar kunnen reageren. De meeste mensen begrijpen taalsignalen, pauzes, culturele nuances en de verschillende betekenissen achter woorden en zinsneden.<\/p>\n

In de begindagen van de computerlingu\u00efstische modellering kon AI de door mensen gegenereerde tekst niet bijhouden. Maar hoe meer de trainingsgegevens werden verfijnd, hoe beter de algoritmen begrepen hoe menselijke gesprekken werken. In 2020,\u00a0Open AI<\/a>\u00a0ontwikkelde de revolutionaire Generatieve Voorgetrainde Transformer 3\u00a0(GPT-3)<\/a>, een NLP-model dat gebruik maakt van diepe neurale netwerken om bijna menselijke niveaus van categorisering van taalkundige informatie te bereiken.<\/p>\n

Dankzij deze functie kon AI informatie verwerken zoals mensen dat doen, wat leidde tot natuurlijker klinkende chatbots en digitale assistenten. Dankzij de steeds verder ontwikkelende NLP-modellen kunnen AI-tools nu artikelen schrijven om menselijke journalisten na te bootsen en complexe vragen of verzoeken van klanten op te lossen.<\/p>\n

Voordelen van het gebruik van NLP voor klantenservice<\/span><\/h3>\n

NLP-gebaseerde chatbots<\/h3>\n

Klanten verwachten nu 24\/7 hulp in alle sectoren, van het bankwezen tot e-commerce en de gezondheidszorg. Om aan deze groeiende vraag te voldoen, ontwikkelen bedrijven snel klantenservice-chatbots die herprogrammeerbaar zijn. Deze tools kunnen basisvragen beantwoorden en opdrachten uitvoeren, zoals het boeken van afspraken of vluchten. Bovendien kunnen deze chatbots worden getraind om branchejargon te begrijpen en te reageren op sectorspecifieke vragen en verzoeken.<\/p>\n

Deze functies stellen bedrijven in staat te besparen op arbeidskosten en hun menselijke agenten om te scholen zodat ze zich kunnen concentreren op het waardevollere klantrelatiebeheer, waardoor de burn-out van werknemers kan worden teruggedrongen. Volgens marktonderzoeksbureau Juniper Research zullen de consumenteninvesteringen in de mondiale chatbotmarkt naar verwachting in 2014 een waarde van $142 miljard bereiken.\u00a02024<\/a>\u00a0van slechts $2,8 miljard dollar in 2019.<\/p>\n

Tijdige analyse van het klantsentiment<\/h3>\n

Sentimentanalyse of opinieanalyse is het proces waarbij emoties achter teksten worden ge\u00efdentificeerd en gecategoriseerd om de klanttevredenheid en feedback te meten. Een voedselproductiebedrijf zou bijvoorbeeld NLP-algoritmen willen inzetten om sociale-mediasites, zoals Facebook en Twitter, te scannen om de gevoelens van mensen ten aanzien van hun nieuw uitgebrachte producten te begrijpen.<\/p>\n

Sommige algoritmen kunnen zelfs gerelateerde producten aanbevelen op basis van de feedback van een persoon, en bots kunnen worden getraind om in realtime te reageren op negatieve opmerkingen of klachten. Door klantsentimenten succesvol te kunnen beheren, kunnen bedrijven reputatieverliezen vermijden, die vaak moeilijker te overwinnen zijn dan financi\u00eble verliezen.<\/p>\n

Gepersonaliseerde marketing die het beheer van de klantrelatie verbetert<\/h3>\n

NLP-mogelijkheden kunnen ook worden ingezet om de klantervaring te verbeteren. De meeste mensen waarderen op maat gemaakte ervaringen die op hun behoeften zijn gericht. Online shoppers willen bijvoorbeeld graag een digitale shopping-chatbot die hen kan helpen beslissen welk product of welke dienst ze willen kopen. Bovendien kunnen marketeers, door sociale media, zoekwoorden en surfgedrag te analyseren, zeer gerichte campagnes cre\u00ebren die herkenbaar en aantrekkelijk zijn voor hun doelgroep.<\/p>\n

Het analyseren van merkvermeldingen kan marketeers ook helpen prospects te targeten en opkomende trends te begrijpen. Op deze manier kunnen klanten gepersonaliseerde landingspagina's of samengestelde producten in hun feeds hebben die het beste aansluiten bij wat ze zoeken en bij hun demografische gegevens. Gebaseerd op een\u00a02022<\/a>\u00a0Uit onderzoek van marketingbureau Epsilon verwacht 80 procent van de consumenten gepersonaliseerde ervaringen van retailers.
\nUitdagingen en toekomst van NLP<\/span>
\nHoewel NLP de afgelopen vijf jaar dramatisch is verbeterd, zijn er nog steeds enkele beperkingen. Het voornaamste probleem is dat machines nog steeds niet in staat zijn menselijke sociale signalen, zoals sarcasme, ironie of frustratie, te perfectioneren. Accenten en culturele nuances vormen nog een andere uitdaging, omdat algoritmen nog steeds proberen uit te vinden hoe \u00e9\u00e9n woord meerdere betekenissen kan hebben voor verschillende gemeenschappen.<\/p>\n

Desalniettemin werken experts er hard aan om de trainingsgegevens voor NLP-modellen te verbeteren, onder meer om ervoor te zorgen dat machines haatzaaiende uitlatingen nauwkeurig kunnen identificeren om ze niet te gebruiken. Bovendien worden algoritmen geleerd om concepten op hoog niveau en abstract denken te begrijpen om gesprekken met een open einde bij te houden.<\/p>\n

Hoe AI Superior kan helpen<\/span><\/h3>\n

Bij AI Superior stellen we bedrijven in staat end-to-end NLP- en kunstmatige intelligentie-oplossingen te ontwikkelen en te implementeren, inclusief\u00a0NLP-gebaseerde chatbots<\/a>, En\u00a0tools voor data-analyse van sociale media<\/a>\u00a0om klantenserviceprocessen te verbeteren en marketingactiviteiten te vergemakkelijken.<\/p>\n

Neem contact op<\/a>\u00a0Neem contact met ons op om erachter te komen hoe we een oplossing op maat kunnen cre\u00ebren die tegemoetkomt aan uw zakelijke behoeften<\/p>","protected":false},"excerpt":{"rendered":"

Breakthroughs in technology that incorporate linguistics with artificial intelligence (AI) have paved the way for better human-machine communication. Think of how virtual assistants, like Apple\u2019s Siri and Google Assistant, have improved over the years \u2013 from starting out with following simple commands to calling businesses to set appointments. 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