{"id":10621,"date":"2026-06-29T17:43:26","date_gmt":"2026-06-29T15:43:26","guid":{"rendered":"https:\/\/mio.one\/casos-de-exito\/flexicar\/"},"modified":"2026-07-08T12:47:22","modified_gmt":"2026-07-08T10:47:22","slug":"flexicar","status":"publish","type":"casos","link":"https:\/\/mio.one\/en\/casos-de-exito\/flexicar\/","title":{"rendered":"Flexicar"},"content":{"rendered":"\n

Customer<\/strong><\/h3>\n\n

FlexicarProject: NationalIndustry: Automotive<\/p>\n\n

<\/div>\n\n

Services<\/strong><\/h3>\n\n
\n

Customer Experience<\/p>\n\n\n\n

Artificial Intelligence <\/p>\n\n\n\n

Conversational Automation <\/p>\n\n\n\n

Technology Integration<\/p>\n\n\n\n

Contact Center<\/p>\n<\/div>\n\n

<\/div>\n\n

From Calls to Action: How Flexicar Scaled Its After-Sales Service with a 24\/7 Chatbot<\/strong><\/h1>\n\n
<\/div>\n\n

The Challenge<\/h3>\n\n

Flexicar, one of Spain\u2019s largest networks of used-car dealerships, needed to improve the phone support provided by its after-sales service in the face of high demand, call spikes, and limited availability outside of business hours.<\/p>\n\n

The company was experiencing between 20% and 30% of calls that were abandoned or went unanswered<\/strong>, and about 10% of calls came outside of business hours<\/strong>. This situation created friction in the customer experience: long wait times, repeated contact attempts, a lack of response at critical moments, and increased pressure on customer service teams. <\/p>\n\n

The challenge was clear: to transform the after-sales call center into a system that was always available, effective, measurable, and scalable<\/strong>\u2014one capable of turning every call into an operational action.<\/p>\n\n

<\/div>\n\n

The Solution<\/h3>\n\n

At MIO One, we designed and implemented a 24\/7 voice chatbot<\/strong> connected to Flexicar\u2019s systems: workshop scheduling, CRM\/ticketing, and call center. This solution was not conceived as an informational bot, but rather as an operational layer<\/strong> capable of answering calls, identifying the reason for contact, performing intelligent triage, and taking the appropriate action in each case. <\/p>\n\n

The assistant handles three possible outcomes per call:<\/p>\n\n

    \n
  • Appointment confirmed<\/strong>, when the request meets the requirements for scheduling a visit.<\/li>\n\n\n\n
  • Case created and flagged<\/strong> when the issue requires further attention.<\/li>\n\n\n\n
  • Referral to a human agent<\/strong> when the case requires specialized intervention.<\/li>\n<\/ul>\n\n

    To do this, the system validates critical data such as the vehicle, contact phone number, warranty, insurance company, repair shop, and availability. Furthermore, it has been built on a model of continuous improvement, incorporating iterations on key aspects such as license plate recognition, standardization of repair shops and schedules, and triage of specific situations such as towing, warranties, or incidents not covered by insurance. Best of all, it also operates during business hours as just another agent within the pool of operators, providing operational flexibility and maintaining a human-in-the-loop model for cases requiring intervention. <\/p>\n\n

    <\/div>\n\n

    Results<\/h3>\n\n

    The assistant handles an average of 30,000 calls<\/strong> per month. It currently handles around 10,000 calls per month<\/strong>, with an average call duration of about 3 minutes<\/strong>, which continues to decrease month by month thanks to the optimization of the conversation flow. <\/p>\n\n

    The solution has made it possible to turn the phone into a channel for taking action, not just for customer service. Every call can result in a recorded action: a scheduled appointment, a documented case, or a justified referral. <\/p>\n\n

    In addition, the system\u2019s performance shows a gradual improvement: since the option to transfer to a human agent was enabled, the number of open cases has begun to decline while the number of appointments has remained stable\u2014a sign that the assistant is learning to resolve issues more effectively without generating unnecessary tickets.<\/p>\n\n

    <\/div>\n\n

    Impact<\/h3>\n\n

    The project has transformed Flexicar’s after-sales phone support into a more agile, accessible, and scalable model.<\/p>\n\n

    A solution that combines artificial intelligence, technology integration, and customer experience to provide 24\/7 support, reduce friction, handle spikes in demand, and free up contact center capacity without losing operational control.<\/p>\n\n

    Useful, integrated, and measurable automation designed to turn calls into actions and improve the customer experience from the very first interaction.<\/strong><\/p>\n","protected":false},"excerpt":{"rendered":"

    From Calls to Action: How Flexicar Scaled Its After-Sales Service with a 24\/7 Chatbot<\/p>\n","protected":false},"featured_media":10513,"parent":0,"template":"","meta":{"_acf_changed":false,"footnotes":""},"servicio":[],"industria":[],"class_list":["post-10621","casos","type-casos","status-publish","has-post-thumbnail","hentry"],"acf":[],"yoast_head":"\nFlexicar - MIO One<\/title>\n<meta name=\"description\" content=\"Flexicar aims to improve the telephone support provided by its after-sales service, given the high demand, call spikes, and limited availability outside of business hours.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/mio.one\/en\/casos-de-exito\/flexicar\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Flexicar - MIO One\" \/>\n<meta property=\"og:description\" content=\"Flexicar aims to improve the telephone support provided by its after-sales service, given the high demand, call spikes, and limited availability outside of business hours.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/mio.one\/en\/casos-de-exito\/flexicar\/\" \/>\n<meta property=\"og:site_name\" content=\"MIO One\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/SomosMIOGROUP\/\" \/>\n<meta property=\"article:modified_time\" content=\"2026-07-08T10:47:22+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/mio.one\/wp-content\/uploads\/sites\/2\/2026\/06\/horizontal-flexicar-1.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"2500\" \/>\n\t<meta property=\"og:image:height\" content=\"1102\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:site\" content=\"@SomosMiogroup\" \/>\n<meta name=\"twitter:label1\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data1\" content=\"3 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/mio.one\\\/en\\\/casos-de-exito\\\/flexicar\\\/\",\"url\":\"https:\\\/\\\/mio.one\\\/en\\\/casos-de-exito\\\/flexicar\\\/\",\"name\":\"Flexicar - 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