Alcuni prerequisiti per adottare l’AI e migliorare la Customer Experience.

AICEX: Negli anni ’90 era la Qualità, poi l’Ambiente, poi la Responsabilità Sociale, poi il Risk Management, poi il Digitale, adesso l’AI. Ma i fondamentali per avere successo sono sempre i soliti. Esattamente quelli dei quali spesso ci dimentichiamo.

AI-driven applications are hot and getting hotter. Forrester’s 2018 survey respondents who said they are investing in AI increased from 40% in 2016 to 51% in 2017.  The McKinsey Global Institute estimates that in comparison with the Industrial Revolution, AI’s disruption of society and business is happening at 300 times the scale and ten times fasterResearch done by the Boston Consulting Group and MIT Sloan reveals large gaps between leaders and laggards in every industry regarding AI usage, and predict that the gaps will magnify over the next five years.

The possibilities and potential for AI-driven applications to enhance Customer Experience (CX) seem endless, but if you’re thinking of jumping on board as soon as possible, think again.

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Livework: Come misurare la Customer Experience con l’NPS

AICEX: Ci vengono in mente almeno 6 Framework per misurare la Customer Experience e sono tutti “proprietari”, con il limite di avere una diffusione limitata. Anche l’NPS è una metodologia “proprietaria” ma ha ampia diffusione e molte aziende lo utilizzano già. Ecco perché è importante capire come possiamo utilizzarlo al meglio conoscendone limiti e vantaggi.

  • NPS does not capture the overall customer experience.
  • Businesses must decide the objectives and application of NPS alongside other metrics.
  • When NPS is used alongside other metrics, quick fixes in customer experience are revealed.

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Big data e Voice of Customer

NOTA AICEX: il forte legame tra Big data e Voice of Customer e la visione top-down versus bottom-up

Talk of Big Data is everywhere, but it is increasingly moving beyond the hype cycle to deliver real results to businesses. To start with, let’s define what Big Data actually is, given there are multiple descriptions in the market. According to Gartner, Big Data is “high volume, high velocity, and/or high variety information assets that require new forms of processing to enable enhanced decision making, insight discovery and process optimisation”.

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