{"id":7773,"date":"2021-06-29T13:18:20","date_gmt":"2021-06-29T11:18:20","guid":{"rendered":"https:\/\/golem.ai\/blog\/nlp-relation-client\/"},"modified":"2022-04-22T12:02:11","modified_gmt":"2022-04-22T10:02:11","slug":"nlp-relation-client","status":"publish","type":"post","link":"https:\/\/miralia.ai\/en\/blog\/relation-client\/nlp-relation-client","title":{"rendered":"4 cas d\u2019usage du NLP dans la relation client"},"content":{"rendered":"

Le Natural Language Processing (NLP) ou traitement automatique du langage naturel (TALN) est une technologie qui permet aux machines de comprendre notre langage, d\u2019en comprendre le sens. Depuis les premiers travaux d\u2019Alan Turing en 1950 sur la communication avec la machine, \u00e9voqu\u00e9 dans son article \u00ab Computing Machinery and Intelligence \u00bb, les cas d\u2019usages ne cessent de cro\u00eetre dans un monde o\u00f9 les interactions humaines se multiplient. <\/h3>\n

<\/p>\n

Le NLP dans La relation client <\/h2>\n

L\u2019acc\u00e9l\u00e9ration num\u00e9rique impose un rythme soutenu en entreprise pour traiter et r\u00e9pondre \u00e0 l\u2019ensemble des demandes clients. Bien que 83% des fran\u00e7ais*<\/strong> soient pr\u00eats \u00e0 partager leurs donn\u00e9es avec une entreprise pour une exp\u00e9rience personnalis\u00e9e, cet avantage reste peu exploit\u00e9 tant le temps manque pour cat\u00e9goriser les demandes, r\u00e9pondre rapidement et de mani\u00e8re personnalis\u00e9e. Ci apr\u00e8s une s\u00e9lection de 4 cas d’usages connus.<\/p>\n

1. Le traitement des r\u00e9clamations<\/strong><\/p>\n

La multitude de canaux de communication complexifie le traitement et l\u2019analyse de tous les messages<\/strong>. L\u2019analyse s\u00e9mantique des demandes, souvent propres \u00e0 chaque m\u00e9tier avec un vocabulaire sp\u00e9cifique, permet en amont de gagner du temps dans l\u2019analyse des intentions pour r\u00e9pondre plus rapidement.<\/p>\n

<\/p>\n

\"\"
Analyse de plusieurs intentions dans un email<\/span><\/em><\/p>\n

<\/p>\n

2. L’analyse des emails<\/strong><\/p>\n

L’analyse fine des emails<\/span><\/a><\/strong> est un sujet complexe d\u00e9pendant de l\u2019organisation des entreprises et de leur capacit\u00e9 \u00e0 traiter rapidement les messages<\/strong>. L\u2019analyse du langage permet, ici, de gagner du temps dans la cat\u00e9gorisation des contenus (pr\u00e9 qualification), permettant aux collaborateurs de gagner du temps et de personnaliser leurs envois notamment gr\u00e2ce \u00e0 une g\u00e9n\u00e9ration automatique du message de r\u00e9ponse. <\/p>\n

\"\"<\/a><\/p>\n

3. Le social listening<\/strong><\/p>\n

L\u2019analyse des r\u00e9seaux sociaux, notamment pour suivre la r\u00e9putation d\u2019une marque, est courante. Mais le cas d\u2019usage le plus fr\u00e9quent reste la d\u00e9tection du m\u00e9contentement. Fr\u00e9quent notamment en BtoC, l\u2019analyse des messages<\/strong> des r\u00e9seaux sociaux est strat\u00e9gique pour identifier rapidement les probl\u00e9matiques clients. Rep\u00e9rer ses intentions gr\u00e2ce au NLP<\/strong>, permet d\u2019\u00eatre plus r\u00e9actif. Un temps \u00e9conomis\u00e9 qui permet de personnaliser le traitement des requ\u00eates.<\/p>\n

4. Les agents conversationnels<\/strong><\/p>\n

Les agents conversationnels, aussi appel\u00e9s chatbots, permettent d\u2019engager plus directement une conversation avec les clients et prospects. Disponibles sans contraintes de temps, ils apportent une premi\u00e8re r\u00e9ponse, dont la performance d\u00e9pend de beaucoup de la qualit\u00e9 de la compr\u00e9hension du langage<\/strong>, et donc du choix technologique<\/strong>.<\/p>\n

<\/p>\n

\"\"
Exemple d’analyse du langage avec Golem.ai<\/em><\/span><\/p>\n

<\/p>\n

Vous l\u2019aurez compris, les cas d\u2019usages se multiplient et s’\u00e9tendent au-del\u00e0 du secteur de la customer relationships<\/strong>. Qu\u2019il s\u2019agisse d\u2019analyser une grande quantit\u00e9 de documents, ou d\u2019automatiser la cat\u00e9gorisation des messages entrants, la finalit\u00e9 reste la m\u00eame : to save time<\/span><\/a><\/strong> pour se concentrer sur des t\u00e2ches \u00e0 forte valeur ajout\u00e9e.<\/p>\n

<\/p>\n

Vous avez une question sur la gestion de relation client<\/strong><\/a> ? D\u00e9couvrez notre solution InboxCare<\/strong><\/a> permettant de simplifier ce processus complexe. N\u2019h\u00e9sitez pas \u00e0 contacter directement nos \u00e9quipes<\/strong><\/a> pour plus d\u2019information.<\/p>\n

* https:\/\/www.kissthebride.fr\/experience-relation-client\/infographie-les-chiffres-cles-de-lannee-2020-du-marketing-client\/<\/span><\/p>\n\n\n

<\/p>\n","protected":false},"excerpt":{"rendered":"

Qu’apporte l’intelligence artificielle de compr\u00e9hension du langage dans le secteur de la relation client ?<\/p>","protected":false},"author":3,"featured_media":7775,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"content-type":"","footnotes":""},"categories":[68,111,74],"tags":[],"class_list":["post-7773","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-blog","category-relation-client","category-technologie"],"acf":[],"yoast_head":"\nIA et NLP dans la relation client<\/title>\n<meta name=\"description\" content=\"Analyse de documents, cat\u00e9gorisation des messages... 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