Businesses in the technology sector are driven by continual product development innovation. Constantly advancing, industry developments (such as the speculated release of the Apple iWatch) stimulate consumer purchasing behaviour rather than being driven by consumer need. But while this business model leads to rapid change and a consumer culture of ‘on-going upgrade’, for technology businesses it is very high risk/reward.
To be successful, tech companies must learn which products at what price and quality consumers are likely to purchase, and how frequently they’ll want to upgrade and expect new innovations. And in such a fast moving industry, perfect timing – to reach the right consumers with the right products at the right time – is crucial to minimise tech’s high-risk nature.
As a result, many of the companies at the forefront of the tech sector are increasingly looking to minimise risk and increase reward through adopting big data strategies.
Using big data to reduce industry risk
Technology and big data run hand-in-hand more than in any other sector. Without technology, big data wouldn’t exist or be manageable in the way it is today, and without big data, technology’s fast-paced (yet high risk) development simply wouldn’t be possible.
If used strategically, big data insights, gathered as a result of technology’s take-off (think email, social media and the like), allow marketers to gain enhanced awareness about their consumers and prospects, so can seamlessly target them via the optimum channel(s). This reduces risk levels, increases response and success rates, and forms an absolute goldmine of multichannel sales opportunity along with the satisfying proof of a well-invested budget.
For example in campaigns building excitement and pushing product pre-registration, the data generated from targeted sign-ups (across Facebook, email and the web) can be used to form a personalised focus at each campaign stage, from sign-up to conversion. Allowing marketers to learn exactly how each demographic is likely to act, marketing collateral can then target the most appropriate consumers via the most appropriate channels, with the most appropriate messages. A streamlined campaign will not bombard across all channels with the same message.
Explicitly, through using big data, tech companies may learn that younger households (in their early 30’s) with annual incomes above £54,000 are likely to purchase the latest type of technology (usually games consoles, tablets, smartphones), that they will regularly download music and other content to make full use of their tech (so cloud based storage offers would be relevant for these consumers), will purchase online, and have a high desire to keep up with the latest tech trends.
On the other hand, same-age households with children and lower incomes (c. £27,000 per year); though they’d like to spend more on technology and have similar interest levels to the former group, do not have the same indulgent spend opportunities, so are in the bottom percentile for technology spend. To target this group successfully, products must be price sensitive. Collateral promoting the latest upgrades for example would not be as successful and could even be repellent.
Knowing such data ensures the most responsive markets receive the most appealing offers to suit them uniquely; increasing industry success and minimising risk for new technology sales while streamlining marketing campaigns, making the best use of budget, increasing advertising ROI and reducing wastage all round.
Acxiom, The original Big Data Company, has over four decades of experience in answering Big Data challenges for some of the world’s largest companies in the technology sector. To find out how we can help you to utilise big data and technology together to simultaneously benefit your business and your customers, download our free 5 step roadmap to dealing with big data whitepaper.
Matt Hollingsworth is a Managing Account Director at Acxiom.
