Sentence examples for customer recommendation from inspiring English sources

A Barratt spokesman said: "We make the best use of space and our customer recommendation score is over 90%, the only major national housebuilder to achieve this.'' In London, where minimum space standards have been in force since 2011, new homes are significantly bigger.

Nosto, a customer recommendation marketing engine designed to help the smaller fish in the ecommerce pool make a bigger splash by improving their online stores with more tailored product recommendations and customer outreach, has closed a $5.5 million Series A funding round, led by European VC firm Wellington Partners.

Others may challenge that assertion and not all the reviews of its foods are flattering, but the idea of the privately owned German business as a British consumer champion has sufficiently taken hold to enable Lidl to launch an inventive marketing campaign, using customer recommendations picked from Twitter.

A subcommittee of that group is working on customer service recommendations that the T.S.A. "won't love," said its chairman, Geoff Freeman, chief operating officer of the U.S. Travel Association.

This knowledge could be exploited for different scopes: set temporal discounts for making the purchases of customers more regular with respect the time, set personalized discounts in the day and time window preferred by the customer, provide recommendations for shopping time schedule, etc.

One $16.80 purchase later Mr. Flanagan explained his managerial policy, that he is happy to offer customers his recommendations but not to impose them.

Mobile Action then uses this score to offer customers "actionable" recommendations that help them improve their ranking.

Oh My Green's tech-enabled service, which relies on machine learning to give its customers personalized recommendations for meals and snacks, has 200 customers today, including Lyft, Apple and Y Combinator.

Based on the prioritizations of customer orders, a recommendation was made to the case company.

Prediction's cloud-based ML tools analyze data in several domains such as customer sentiment analysis, recommendation systems and spam detection.

In an interview with Dr. Jeff Shuford where he discusses about customer service, his recommendation for new startups in technology is to "learn as much as coding as you can and always put your customer needs over financial gains".