{"id":4609,"date":"2026-04-28T09:30:00","date_gmt":"2026-04-28T07:30:00","guid":{"rendered":"https:\/\/www.nethexcare.ro\/?p=4609"},"modified":"2026-04-28T09:38:44","modified_gmt":"2026-04-28T07:38:44","slug":"quality-automation-in-contact-centers","status":"publish","type":"post","link":"https:\/\/www.nethexcare.ro\/en\/quality-automation-in-contact-centers\/","title":{"rendered":"Quality Automation in Contact Centers"},"content":{"rendered":"\n

From Sampling to 100% AI Monitoring: How Artificial Intelligence Is Transforming Quality Management. <\/h2>\n\n

Is<\/span>\u00a0<\/span>quality<\/span>\u00a0<\/span>automation<\/span>\u00a0in contact centers\u00a0<\/span>possible<\/span>? For\u00a0<\/span>decades<\/span>, Quality Management in contact centers\u00a0<\/span>has<\/span>\u00a0<\/span>operated<\/span>\u00a0<\/span>according<\/span>\u00a0to a\u00a0<\/span>well-established<\/span>\u00a0<\/span>logic<\/span>:\u00a0<\/span>listening<\/span>\u00a0to a small\u00a0<\/span>percentage<\/span>\u00a0of calls \u2014\u00a0<\/span>typically<\/span>\u00a0<\/span>between<\/span>\u00a02% and 5% of the\u00a0<\/span>total<\/span>\u00a0\u2014 and\u00a0<\/span>drawing<\/span>\u00a0<\/span>conclusions<\/span>\u00a0<\/span>about<\/span>\u00a0overall performance.\u00a0<\/span>This<\/span>\u00a0<\/span>approach<\/span>\u00a0<\/span>was<\/span>\u00a0<\/span>driven<\/span>\u00a0by\u00a0<\/span>objective<\/span>\u00a0<\/span>constraints<\/span>\u00a0in time, human\u00a0<\/span>resources<\/span>, and\u00a0<\/span>available<\/span>\u00a0tools. Today, thanks to\u00a0<\/span>artificial<\/span>\u00a0intelligence and speech\u00a0<\/span>analytics<\/span>\u00a0and text\u00a0<\/span>analytics<\/span>\u00a0<\/span>technologies<\/span>,\u00a0<\/span>this<\/span>\u00a0<\/span>paradigm<\/span>\u00a0<\/span>has<\/span>\u00a0<\/span>become<\/span>\u00a0obsolete.\u00a0<\/span>We<\/span>\u00a0<\/span>have<\/span>\u00a0<\/span>entered<\/span>\u00a0the era of 100% Quality Monitoring:\u00a0<\/span>every<\/span>\u00a0voice, chat,\u00a0<\/span>email<\/span>, and social<\/span>\u00a0media<\/span>\u00a0interaction\u00a0<\/span>is<\/span>\u00a0<\/span>automatically<\/span>\u00a0<\/span>analyzed<\/span>,\u00a0<\/span>evaluated<\/span>, and\u00a0<\/span>tracked<\/span>.<\/span><\/span>\u00a0<\/span><\/p>\n\n

The Sampling Problem:\u00a0<\/span>Why<\/span>\u00a05%\u00a0<\/span>Is<\/span>\u00a0No\u00a0<\/span>Longer<\/span>\u00a0<\/span>Enough<\/span><\/span>\u00a0<\/span><\/h3><\/h3>\n\n

The traditional Quality Assurance (QA) model rested on an implicit assumption: a representative sample of interactions was sufficient to assess agent performance, identify operational issues, and ensure regulatory compliance. In practice, however, this approach has structural limitations that the most advanced organizations are recognizing with increasing urgency. <\/p>\n\n

First,\u00a0<\/span>selection<\/span>\u00a0<\/span>bias<\/span>. QA teams\u00a0<\/span>tend<\/span>\u00a0\u2014\u00a0<\/span>often<\/span>\u00a0<\/span>unconsciously<\/span>\u00a0\u2014 to\u00a0<\/span>evaluate<\/span>\u00a0the interactions\u00a0<\/span>that<\/span>\u00a0are\u00a0<\/span>easiest<\/span>\u00a0to review or\u00a0<\/span>that<\/span>\u00a0<\/span>have<\/span>\u00a0<\/span>already<\/span>\u00a0<\/span>been<\/span>\u00a0<\/span>flagged<\/span>\u00a0<\/span>as<\/span>\u00a0<\/span>problematic<\/span>. In\u00a0<\/span>doing<\/span>\u00a0so,\u00a0<\/span>they<\/span>\u00a0<\/span>overlook<\/span>\u00a0a large\u00a0<\/span>portion<\/span>\u00a0of\u00a0<\/span>neutral<\/span>\u00a0or borderline\u00a0<\/span>conversations<\/span>\u00a0<\/span>that<\/span>\u00a0<\/span>may<\/span>\u00a0<\/span>conceal<\/span>\u00a0<\/span>latent<\/span>\u00a0<\/span>issues<\/span>.<\/span><\/span>\u00a0<\/span><\/p>\n\n

Second,\u00a0<\/span>regulatory<\/span>\u00a0coverage.\u00a0<\/span>Sectors<\/span>\u00a0<\/span>such<\/span>\u00a0<\/span>as<\/span>\u00a0banking, insurance,\u00a0<\/span>telecommunications<\/span>, and energy are\u00a0<\/span>subject<\/span>\u00a0to\u00a0<\/span>increasingly<\/span>\u00a0<\/span>stringent<\/span>\u00a0recording and\u00a0<\/span>verification<\/span>\u00a0<\/span>obligations<\/span>. With sampling, the\u00a0<\/span>statistical<\/span>\u00a0risk of\u00a0<\/span>missing<\/span>\u00a0a\u00a0<\/span>violation<\/span>\u00a0\u2014\u00a0<\/span>such<\/span>\u00a0<\/span>as<\/span>\u00a0an\u00a0<\/span>incorrect<\/span>\u00a0statement, a\u00a0<\/span>missing<\/span>\u00a0<\/span>piece<\/span>\u00a0of information, or a\u00a0<\/span>failure<\/span>\u00a0to\u00a0<\/span>disclose<\/span>\u00a0\u2014\u00a0<\/span>is<\/span>\u00a0<\/span>significantly<\/span>\u00a0high.<\/span><\/span>\u00a0<\/span><\/p>\n\n

Third, feedback\u00a0<\/span>latency<\/span>:\u00a0<\/span>traditional<\/span>\u00a0QA\u00a0<\/span>provides<\/span>\u00a0information after the problem\u00a0<\/span>has<\/span>\u00a0<\/span>already<\/span>\u00a0<\/span>occurred<\/span>. AI, by\u00a0<\/span>contrast<\/span>, can flag an\u00a0<\/span>anomaly<\/span>\u00a0in real time or\u00a0<\/span>within<\/span>\u00a0a\u00a0<\/span>few<\/span>\u00a0hours of the interaction closing.<\/span><\/span>\u00a0<\/span><\/p>\n\n

Quality Automation in the Contact Center: How 100% AI Monitoring Works<\/span><\/span>\u00a0<\/span><\/h3>\n\n

The core of this transformation is the combination of multiple complementary technologies, integrated into a unified intelligent Quality Management platform. <\/p>\n\n

Automatic<\/span>\u00a0Speech\u00a0<\/span>Recognition<\/span>\u00a0(ASR):<\/span><\/span>\u00a0<\/span>every<\/span>\u00a0call\u00a0<\/span>is<\/span>\u00a0<\/span>automatically<\/span>\u00a0<\/span>transcribed<\/span>\u00a0<\/span>into<\/span>\u00a0text, with growing\u00a0<\/span>accuracy<\/span>\u00a0<\/span>even<\/span>\u00a0in the\u00a0<\/span>presence<\/span>\u00a0of\u00a0<\/span>regional<\/span>\u00a0<\/span>accents<\/span>.\u00a0<\/span>Transcriptions<\/span>\u00a0<\/span>become<\/span>\u00a0the\u00a0<\/span>foundation<\/span>\u00a0for\u00a0<\/span>all<\/span>\u00a0<\/span>subsequent<\/span>\u00a0<\/span>analyses<\/span>.<\/span><\/span>\u00a0<\/span><\/p>\n\n

Natural Language Processing (NLP):<\/span><\/span>\u00a0<\/span>language<\/span>\u00a0models\u00a0<\/span>extract<\/span>\u00a0from\u00a0<\/span>each<\/span>\u00a0<\/span>transcript<\/span>\u00a0the key\u00a0<\/span>entities<\/span>, customer sentiment,\u00a0<\/span>conversation<\/span>\u00a0<\/span>topics<\/span>, the\u00a0<\/span>presence<\/span>\u00a0of mandatory\u00a0<\/span>phrases<\/span>, and\u00a0<\/span>prohibited<\/span>\u00a0words or\u00a0<\/span>expressions<\/span>.<\/span><\/span>\u00a0<\/span><\/p>\n\n

Sentiment and\u00a0<\/span>Emotion<\/span>\u00a0Analysis:<\/span><\/span>\u00a0AI can\u00a0<\/span>detect<\/span>\u00a0<\/span>not<\/span>\u00a0<\/span>only<\/span>\u00a0<\/span>verbal<\/span>\u00a0content,\u00a0<\/span>but<\/span>\u00a0<\/span>also<\/span>\u00a0the\u00a0<\/span>emotional<\/span>\u00a0<\/span>tone<\/span>\u00a0of the\u00a0<\/span>conversation<\/span>\u00a0\u2014\u00a0<\/span>frustration<\/span>, satisfaction,\u00a0<\/span>urgency<\/span>\u00a0\u2014 on\u00a0<\/span>both<\/span>\u00a0the customer and the agent side.\u00a0<\/span>This<\/span>\u00a0makes\u00a0<\/span>it<\/span>\u00a0<\/span>possible<\/span>\u00a0to\u00a0<\/span>identify<\/span>\u00a0interactions\u00a0<\/span>at<\/span>\u00a0high risk of escalation or\u00a0<\/span>abandonment<\/span>.<\/span><\/span>\u00a0<\/span><\/p>\n\n

Automated<\/span>\u00a0Scorecards:<\/span><\/span>\u00a0<\/span>each<\/span>\u00a0interaction\u00a0<\/span>automatically<\/span>\u00a0<\/span>receives<\/span>\u00a0a score on a\u00a0<\/span>customizable<\/span>\u00a0<\/span>evaluation<\/span>\u00a0form,\u00a0<\/span>aligned<\/span>\u00a0with the\u00a0<\/span>organization’s<\/span>\u00a0business\u00a0<\/span>objectives<\/span>\u00a0and\u00a0<\/span>regulatory<\/span>\u00a0<\/span>requirements<\/span>. The QA team (Quality Assurance \u2014 the\u00a0<\/span>specialized<\/span>\u00a0group\u00a0<\/span>responsible<\/span>\u00a0for\u00a0<\/span>ensuring<\/span>\u00a0<\/span>that<\/span>\u00a0products, software, or services\u00a0<\/span>meet<\/span>\u00a0high\u00a0<\/span>quality<\/span>\u00a0and compliance standards) can focus on coaching,\u00a0<\/span>exception<\/span>\u00a0<\/span>validation<\/span>, and\u00a0<\/span>continuous<\/span>\u00a0model\u00a0<\/span>calibration<\/span>.<\/span><\/span>\u00a0<\/span><\/p>\n\n

Quality Automation in the Contact Center: Concrete Benefits for Operations<\/span><\/span>\u00a0<\/span><\/h3><\/h3>\n\n

Adopting 100% monitoring is not just a technological advancement \u2014 it has direct and measurable impacts across all operational dimensions of the contact center: <\/p>\n\n

    \n
  • Objectivity<\/span>\u00a0and\u00a0<\/span>consistency<\/span>:<\/span><\/span>\u00a0AI\u00a0<\/span>applies<\/span>\u00a0the\u00a0<\/span>same<\/span>\u00a0<\/span>evaluation<\/span>\u00a0<\/span>criteria<\/span>\u00a0to\u00a0<\/span>every<\/span>\u00a0interaction,\u00a0<\/span>eliminating<\/span>\u00a0the inter-<\/span>rater<\/span>\u00a0<\/span>variability<\/span>\u00a0<\/span>typical<\/span>\u00a0of\u00a0<\/span>manual<\/span>\u00a0QA.<\/span><\/span>\u00a0<\/span><\/li>\n\n\n\n
  • Scalability<\/span>:<\/span><\/span>\u00a0<\/span>whether<\/span>\u00a0the contact center handles 1,000 or 1,000,000 calls per month, coverage\u00a0<\/span>remains<\/span>\u00a0<\/span>at<\/span>\u00a0100% with\u00a0<\/span>no<\/span>\u00a0linear\u00a0<\/span>increase<\/span>\u00a0in cost.<\/span><\/span>\u00a0<\/span><\/li>\n\n\n\n
  • Proactive<\/span>\u00a0risk\u00a0<\/span>identification<\/span>:<\/span><\/span>\u00a0interactions\u00a0<\/span>that<\/span>\u00a0<\/span>exceed<\/span>\u00a0<\/span>certain<\/span>\u00a0risk\u00a0<\/span>thresholds<\/span>\u00a0\u2014 for\u00a0<\/span>instance<\/span>, due to\u00a0<\/span>extreme<\/span>\u00a0negative sentiment or\u00a0<\/span>failure<\/span>\u00a0to\u00a0<\/span>disclose<\/span>\u00a0\u2014 are\u00a0<\/span>prioritized<\/span>\u00a0for immediate human review.<\/span><\/span>\u00a0<\/span><\/li>\n\n\n\n
  • Targeted<\/span>\u00a0and\u00a0<\/span>personalized<\/span>\u00a0coaching:<\/span><\/span>\u00a0team leaders\u00a0<\/span>receive<\/span>\u00a0<\/span>specific<\/span>\u00a0insights for\u00a0<\/span>each<\/span>\u00a0agent,\u00a0<\/span>based<\/span>\u00a0on the\u00a0<\/span>analysis<\/span>\u00a0of\u00a0<\/span>their<\/span>\u00a0<\/span>entire<\/span>\u00a0interaction history,\u00a0<\/span>not<\/span>\u00a0just a sample of 5\u201310 calls per month.<\/span><\/span>\u00a0<\/span><\/li>\n\n\n\n
  • Churn<\/span>\u00a0reduction and CSAT\u00a0<\/span>improvement<\/span>:<\/span><\/span>\u00a0<\/span>intercepting<\/span>\u00a0<\/span>weak<\/span>\u00a0<\/span>signals<\/span>\u00a0of\u00a0<\/span>dissatisfaction<\/span>\u00a0<\/span>before<\/span>\u00a0<\/span>they<\/span>\u00a0turn\u00a0<\/span>into<\/span>\u00a0<\/span>formal<\/span>\u00a0<\/span>complaints<\/span>\u00a0or customer\u00a0<\/span>abandonment<\/span>\u00a0<\/span>enables<\/span>\u00a0<\/span>timely<\/span>\u00a0<\/span>interventions<\/span>\u00a0and\u00a0<\/span>improvement<\/span>\u00a0of the customer experience.<\/span><\/span>\u00a0<\/span><\/li>\n<\/ul>\n\n

    Achieving<\/span>\u00a0<\/span>Regulatory<\/span>\u00a0Compliance<\/span><\/span>\u00a0<\/span><\/h3><\/h3>\n\n

    One of the\u00a0<\/span>areas<\/span>\u00a0where 100% monitoring\u00a0<\/span>generates<\/span>\u00a0the\u00a0<\/span>greatest<\/span>\u00a0<\/span>return<\/span>\u00a0on investment\u00a0<\/span>is<\/span>\u00a0<\/span>regulatory<\/span>\u00a0compliance. In\u00a0<\/span>regulated<\/span>\u00a0<\/span>sectors<\/span>,\u00a0<\/span>every<\/span>\u00a0<\/span>conversation<\/span>\u00a0must\u00a0<\/span>comply<\/span>\u00a0with\u00a0<\/span>specific<\/span>\u00a0<\/span>obligations<\/span>\u00a0<\/span>regarding<\/span>\u00a0disclosure,\u00a0<\/span>consent<\/span>\u00a0recording, risk profiling, and product disclosure. AI makes\u00a0<\/span>it<\/span>\u00a0<\/span>possible<\/span>\u00a0to\u00a0<\/span>systematically<\/span>\u00a0<\/span>verify<\/span>\u00a0<\/span>that<\/span>\u00a0<\/span>these<\/span>\u00a0<\/span>requirements<\/span>\u00a0are\u00a0<\/span>met<\/span>\u00a0in\u00a0<\/span>every<\/span>\u00a0single interaction, building a complete audit\u00a0<\/span>trail<\/span>\u00a0<\/span>that<\/span>\u00a0can be\u00a0<\/span>consulted<\/span>\u00a0<\/span>immediately<\/span>\u00a0in the event of an\u00a0<\/span>inspection<\/span>.<\/span><\/span>\u00a0<\/span><\/p>\n\n

    This does not mean replacing human oversight, but enhancing it: the Compliance Officer receives a real-time dashboard with all adherence metrics, can set automatic alerts for specific types of violations, and has access to granular reports for each agent, team, and channel. <\/p>\n\n

    Implementation<\/span>: Where to Start<\/span><\/span>\u00a0<\/span><\/h3><\/h3>\n\n

    Many\u00a0<\/span>organizations<\/span>\u00a0<\/span>perceive<\/span>\u00a0the\u00a0<\/span>transition<\/span>\u00a0to 100% monitoring\u00a0<\/span>as<\/span>\u00a0a\u00a0<\/span>highly<\/span>\u00a0<\/span>complex<\/span>\u00a0project. In reality, a\u00a0<\/span>phased<\/span>\u00a0<\/span>approach<\/span>\u00a0makes\u00a0<\/span>it<\/span>\u00a0<\/span>possible<\/span>\u00a0to generate\u00a0<\/span>value<\/span>\u00a0from the\u00a0<\/span>very<\/span>\u00a0first weeks.<\/span><\/span>\u00a0<\/span><\/p>\n\n

      \n
    1. Assessment<\/span>\u00a0and\u00a0<\/span>objective<\/span>\u00a0<\/span>definition<\/span>:<\/span><\/span>\u00a0<\/span>identify<\/span>\u00a0<\/span>priority<\/span>\u00a0<\/span>KPIs<\/span>,\u00a0<\/span>regulatory<\/span>\u00a0<\/span>requirements<\/span>\u00a0to be\u00a0<\/span>met<\/span>, and\u00a0<\/span>existing<\/span>\u00a0scorecards to be\u00a0<\/span>translated<\/span>\u00a0<\/span>into<\/span>\u00a0<\/span>automated<\/span>\u00a0models.<\/span><\/span>\u00a0<\/span><\/li>\n\n\n\n
    2. Platform\u00a0<\/span>integration<\/span>:<\/span><\/span>\u00a0<\/span>connect<\/span>\u00a0<\/span>existing<\/span>\u00a0recording systems \u2014\u00a0<\/span>such<\/span>\u00a0<\/span>as<\/span>\u00a0omnichannel\u00a0<\/span>platforms<\/span>\u00a0\u2014 with the AI\u00a0<\/span>analytics<\/span>\u00a0<\/span>engine<\/span>,\u00a0<\/span>typically<\/span>\u00a0via\u00a0<\/span>APIs<\/span>\u00a0or native\u00a0<\/span>connectors<\/span>.<\/span><\/span>\u00a0<\/span><\/li>\n\n\n\n
    3. Calibration<\/span>\u00a0and training:<\/span><\/span>\u00a0fine-<\/span>tune<\/span>\u00a0NLP models on the\u00a0<\/span>specific<\/span>\u00a0<\/span>terminology<\/span>\u00a0of the\u00a0<\/span>sector<\/span>\u00a0and brand,\u00a0<\/span>validating<\/span>\u00a0<\/span>results<\/span>\u00a0in\u00a0<\/span>parallel<\/span>\u00a0with the QA team.<\/span><\/span>\u00a0<\/span><\/li>\n\n\n\n
    4. Progressive go-live and adoption:<\/span><\/span>\u00a0roll out full coverage,\u00a0<\/span>train<\/span>\u00a0team leaders on dashboard\u00a0<\/span>usage<\/span>, and\u00a0<\/span>redefine<\/span>\u00a0the\u00a0<\/span>role<\/span>\u00a0of QA\u00a0<\/span>evaluators<\/span>\u00a0<\/span>toward<\/span>\u00a0coaching and\u00a0<\/span>strategic<\/span>\u00a0<\/span>analysis<\/span>\u00a0activities.<\/span><\/span>\u00a0<\/span><\/li>\n<\/ol>\n\n

      Quality Automation in the Contact Center:\u00a0<\/span>Toward<\/span>\u00a0<\/span>Predictive<\/span>\u00a0Quality<\/span><\/span>\u00a0<\/span><\/h3><\/h3>\n\n

      100% monitoring\u00a0<\/span>represents<\/span>\u00a0an\u00a0<\/span>important<\/span>\u00a0milestone,\u00a0<\/span>but<\/span>\u00a0<\/span>not<\/span>\u00a0the\u00a0<\/span>final<\/span>\u00a0<\/span>destination<\/span>. Next-generation AI\u00a0<\/span>platforms<\/span>\u00a0are\u00a0<\/span>introducing<\/span>\u00a0<\/span>predictive<\/span>\u00a0capabilities\u00a0<\/span>that<\/span>\u00a0go\u00a0<\/span>beyond<\/span>\u00a0<\/span>analyzing<\/span>\u00a0the\u00a0<\/span>past<\/span>:\u00a0<\/span>i<\/span>\u00a0identifying in advance which interactions have a high probability of a negative outcome,<\/span>\u00a0<\/span>suggesting<\/span>\u00a0the best actions in\u00a0<\/span>real<\/span>\u00a0time\u00a0<\/span>during<\/span>\u00a0a\u00a0<\/span>conversation<\/span>, and\u00a0<\/span>modeling<\/span>\u00a0the impact of\u00a0<\/span>process<\/span>\u00a0<\/span>changes<\/span>\u00a0on the overall Customer Experience.<\/span><\/span>\u00a0<\/span><\/p>\n\n

      Quality Management\u00a0<\/span>is<\/span>\u00a0<\/span>evolving<\/span>\u00a0from a control\u00a0<\/span>function<\/span>\u00a0<\/span>into<\/span>\u00a0a\u00a0<\/span>strategic<\/span>\u00a0<\/span>lever<\/span>\u00a0for\u00a0<\/span>continuous<\/span>\u00a0<\/span>optimization<\/span>. Companies\u00a0<\/span>that<\/span>\u00a0<\/span>invest<\/span>\u00a0in\u00a0<\/span>this<\/span>\u00a0transformation\u00a0<\/span>today<\/span>\u00a0are\u00a0<\/span>not<\/span>\u00a0<\/span>simply<\/span>\u00a0solving an\u00a0<\/span>operational<\/span>\u00a0problem \u2014\u00a0<\/span>they<\/span>\u00a0are building a competitive\u00a0<\/span>advantage<\/span>\u00a0<\/span>capable<\/span>\u00a0of\u00a0<\/span>delivering<\/span>\u00a0concrete,\u00a0<\/span>measurable<\/span>\u00a0<\/span>results<\/span>.<\/span><\/span>\u00a0<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

      From Sampling to 100% AI Monitoring: How Artificial Intelligence Is Transforming Quality Management. Is\u00a0quality\u00a0automation\u00a0in contact centers\u00a0possible? For\u00a0decades, Quality Management in contact centers\u00a0has\u00a0operated\u00a0according\u00a0to a\u00a0well-established\u00a0logic:\u00a0listening\u00a0to a small\u00a0percentage\u00a0of calls \u2014\u00a0typically\u00a0between\u00a02% and 5% of the\u00a0total\u00a0\u2014 and\u00a0drawing\u00a0conclusions\u00a0about\u00a0overall performance.\u00a0This\u00a0approach\u00a0was\u00a0driven\u00a0by\u00a0objective\u00a0constraints\u00a0in time, human\u00a0resources, and\u00a0available\u00a0tools. Today, thanks to\u00a0artificial\u00a0intelligence and speech\u00a0analytics\u00a0and text\u00a0analytics\u00a0technologies,\u00a0this\u00a0paradigm\u00a0has\u00a0become\u00a0obsolete.\u00a0We\u00a0have\u00a0entered\u00a0the era of 100% Quality Monitoring:\u00a0every\u00a0voice, chat,\u00a0email, and social\u00a0media\u00a0interaction\u00a0is\u00a0automatically\u00a0analyzed,\u00a0evaluated, and\u00a0tracked.\u00a0 The Sampling Problem:\u00a0Why\u00a05%\u00a0Is\u00a0No\u00a0Longer\u00a0Enough\u00a0 The […]<\/p>\n","protected":false},"author":4,"featured_media":4604,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[3],"tags":[],"class_list":["post-4609","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news"],"yoast_head":"\nQuality Automation in Contact Centers<\/title>\n<meta name=\"description\" content=\"Quality Automation in the Contact Center: How 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