Taking an AI approach in the transformation of the OEM market

The global smartphone market is in decline, with smartphone shipments slowing to just 2% growth in 2016, a dramatic decline from 2015.

Some may think this to be extremely surprising, in such a digitally-dependent generation where smartphones are overtaking PCs in fulfilling everyday activities.

However, when we consider that the average lifecycle of the handset was 31.2 months in 2016, compared to 24 months in 2011, the picture becomes much clearer.

Handsets are being kept for longer and hardware is not enticing users to change. So, it is now a case of survival of the fittest in the OEM industry; the mobile device manufacturer which responds quickest to rapidly evolving consumer usage habits and expectations, wins.

Why software first?

Put simply, the smartphone industry is completely saturated. Device life cycles in North America, Western Europe, Japan and Mature Asia/Pacific now exceed two and a half years.

Smartphone users are not replacing or upgrading their phones regularly enough to ensure profitability and this is not expected to change before 2021.

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Adding fuel to the fire is a lack of differentiation. All handsets follow a similar aesthetic. Hardware differentiation is no longer enough. Although, Android is set to retain an 81.1% worldwide market share of smartphone sales through to 2019, the wider OEM market needs to move to a software-first approach.

This will provide a more long-term solution to their current revenue shortfall. The industry as a whole needs to therefore think differently about their products and incentivise consumers to change their device.

The solution lies not only within software, but the integration of artificial intelligence (AI). Consumers crave technological innovation. Mobile browsing accounts for 51.3% of the world’s browsing activity, surpassing that of desktop at 48.7%.

Given this, it is unsurprising that consumer focus naturally gravitates towards what their device can actually do for them, quickly and intelligently.

Enhancing earning potential for the OEM

This increase in focus on mobile opens up an opportunity for OEMs, who can leverage the attention through mobile targeted advertising, a booming industry with huge revenue potential.

In the UK alone, mobile ad spend in the fourth quarter of 2016 increased 36% to £1.1 billion compared to the TV ad market, which grew by just 1% year-on-year to £1.3 billion.

Software advances incorporating AI have the potential to completely rejuvenate the market. Using software as a differentiator means OEMs can overcome competition and handset lifecycle challenges, reduce customer churn, and ultimately lead to increased profit margins.

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AI and machine- learning can also be used as an extension of data analytics – an area that mobile operators have already been exploiting for a number of years for churn reduction, marketing ROI and improved customer experience.

AI can not only help operators and OEMs to analyse data, but also predict, recommend and make automated decisions.

Increase revenue without hindering user experience

Achieving this device differentiation and healthier profit margins, without hindering user experience is a dilemma many OEMs are currently facing. The choice between developing in-house software at a huge overhead cost or sacrificing product differentiation and additional revenue are undesirable options.

Many OEMs choose to pre-install various apps, however this over deployment can only be seen as a short term revenue fix that ultimately clutters devices and more often than not has a negative effect on the user experience. This is ultimately counterproductive to the credibility of the brand.

An achievable way for OEMs to cost effectively adapt their approach, is by working with partners to pre-install unique software on their devices that will protect and enhance the user experience through customisation and personalisation.

Incorporating AI within this process changes the look and experience of the brand from other Android devices. As part of this, AI and recommendation technology can highlight apps and content based on the user’s preferences, through machine- learning, neural networks and artificial intelligence with a vast global web index.

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It is this experience of relevant content, personalised to individual interests, which is key to the user’s perception of the software and hardware. The more relevant the content, the more chance of customer satisfaction with the brand.

Embracing AI

Users are only just starting to see the true benefits of AI’s application to everyday devices. The way humans interact with technology has completely changed; AI and machine-learning can provide users with the content and information they like and want on their device without having to ask for it.

The technology also works to present the most relevant and targeted ads personalised to the user, meaning higher engagement will be achieved. And with profitability crucial, taking a share of this revenue will help to transform a competitive OEM market.


Sourced by Artem Fokin, VP international business, Yandex

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Nick Ismail

Nick Ismail is a former editor for Information Age (from 2018 to 2022) before moving on to become Global Head of Brand Journalism at HCLTech. He has a particular interest in smart technologies, AI and...