Lenovo uses machine learning to analyse customer feedback

Lenovo, the world's biggest PC maker, has been analysing unstructured data from social channels such as YouTube and Instagram to gain a better understanding of how consumers feel about its products and what features it should include in future products.

Four years ago, the firm's focus was on engineering and its products. Lenovo based its strategies and product line on feedback from its engineers, test teams and lab teams. The firm's CEO Yuan Yuanqing realised that being more customer-centric could help bolster growth and innovation.

Lenovo wanted to combine traditional customer feedback such as online forums or surveys with social media.

The director of the Customer Insight Centre of Excellence, Strategy & Analytics at Lenovo, Mohammed Charra, took it upon himself to spearhead this new strategy by developing an app which enabled the firm to “capture the variety of feedback that is expressed by the customer, then structure it, mine it, get context out of it and provide that information back to the engineering team.”

Lenovo's app has been in production for the past two years and according to Chaara it has given the firm insight into its users.

When the firm decided to build the first device in its Yoga line it did so using unstructured data to have a better idea of what consumers were looking for in a device that was not merely a tablet nor just another laptop.

Using data collected from the app alongside data mined by Lenovo's staff, the firm is creating a training data set that will be used in conjunction with machine learning and deep learning to one day identify the data it collects from social media.

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