Since 2012, China has taken its place as the second-largest economy and third-largest IT market in the world.

However, IT spending per capita in China is still less than five per cent of that in the US. For technology retailers in China to succeed, they need to focus on retaining and winning customers.

Researcher Forrester has revealed its top five predictions technology retailers should take note of:

• Technology spending is slowing down in China and local vendors will gain share.
  Forrester estimates that China’s enterprise IT purchases will grow by six per cent in 2013 to 698 billion yuan, and a further eight per cent in 2014 to 752 billion yuan. Local vendors like Huawei, Inspur and Lenovo will likely benefit from the NSA/Snowden issue. These companies will gain share mostly in the hardware space, including server, storage and networking in 2014.
• China will become the world’s largest e-commerce market.
  The number of online buyers in China alone will reach 356 million in 2014 – surpassing the entire US population. The Chinese online retail market will continue to grow to $604 billion in 2017.
• Smartphones will become life hubs for most Chinese consumers.
  For many consumers in China, the smartphone will begin to resemble a “life hub” – a connected hub for people’s lives. Forrester estimates that 48 per cent of all Chinese mobile phone subscribers will own smartphones in 2014 and this number will grow to 64 per cent in 2017.
• Customer experience will surge as a priority.
  With technologies disrupting the way organisations serve and communicate with their customers, customer experience will become a hot topic for CIOs in the hypercompetitive Chinese market.
• Big data and analytics will gain popularity, but few IT organisations will meet business demands.
  Forrester believes that customer engagement will drive BI, big data, and analytics investments in China in 2014, especially at banking/finance and retail organisations. CIOs at many other Chinese organisations will face a broader big data agenda, including big data architecture, use case for predictive analytics, and big data-related skills and training issues.