Case Study: Esselunga

Individuazione automatica dei post critici su canali Social

Industry: retail

Case Study: Esselunga

Automatic identification of critical posts on Social Media channels

Industry: retail

The challenge

For Esselunga, we set ourselves the challenge of implementing an automated system to detect critical posts on Social Media channels.

The challenge was to achieve the following KPI:

  • identification of at least 90% of critical posts
  • Saving time on average operator time: -50%.

How we faced the challenge for Esselunga

Solution: Machine Learning and AI

To reach the goal of this challenge, we introduced an advanced system that, thanks to AI and Machine Learning, is able to analyse all public and private posts on Social Media channels.

Once identified, the process automatically queues up critical posts to operators, for rapid management on a multichannel front-end.

Solutions adopted

Centriko, la piattaforma per la Digital Transformation

Tools used

Artificial Intelligence

Machine Learning

Achievements

Automated Social Media coverage and cost reduction

Critical posts identified
0 %
Saving time on average operator time
0 %

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Make your company a successful case study in the customer experience journey.

Fill in the form and get in touch with us, you will be contacted by one of our sales staff.

Together we will create a path to redesign, improve and add value to your customer's experience.

Call2Net is the consulting firm specialising in innovative customer interaction solutions. Since 2007, Call2Net has revolutionized the traditional contact centre model by adopting phygital processes to always guarantee its customers an excellent customer experience.

Contacts

Call2Net S.P.A.
Legal and operative headquarters:
Viale Edoardo Jenner, 55
20159 Milano
P.IVA e C.F. 03751840277
Cap. Soc. 354.100€ i.v.

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