United KingdomRetail and e-commerce2018 – ongoingMarks & Spencer
Voice recognition for incoming store calls
Marks & Spencer cut store call volume by 50% after a voice assistant began routing incoming calls
Problem
Marks & Spencer had switchboards in 13 stores in the UK and Ireland, handling up to nine million calls a year. Store staff could not take online orders, and each type of request needed a different routing. The company expected call handling costs to rise as volumes grew.
Approach
In 2018 M&S asked the Google Cloud partner Sabio Group to build a natural language voice channel with Dialogflow and Twilio. Callers state what they need in their own words and the system maps it to an action. Contact center staff can add seasonal vocabulary themselves. After a few months the platform was rolled out to all stores in the UK and Ireland and to the customer service contact centers.
Results
Takeaway
Letting callers say what they want, instead of choosing from a menu, moved a large share of store calls away from store staff. Letting contact center staff edit the vocabulary meant promotions did not need engineers.
Categories
- Size
- Large enterprise
- Industry
- Retail and e-commerce
- Business function
- Customer service
- Innovation type
- Process innovation
- AI technology
- Conversational and voice AI
- Adoption
- Off-the-shelf tool or platform
- Evidence
- Vendor case study
Sources
Source summaries
Google Cloud's customer story describes how Marks & Spencer used Dialogflow, set up by the partner Sabio Group, to automate calls into its stores in the UK and Ireland. It reports a 50% drop in store call volume and a 92% intent match rate in under four months. The page carries no date; the Internet Archive first saved it on December 29, 2019.
Full details are in the original sources.
