Today’s digital world is rapidly changing as the boundaries between physical and digital disappear. This has created many opportunities for marketers. But there are hurdles to jump, from adopting new technology that combines online and offline data to acquiring a new skillset that makes sense of the rising tide of data.
Machine learning, data science and predictive analytics are the new and increasingly crucial components that can complement traditional marketing analysis and insight best practice to make brands stand out. Brands that are more technically-savvy and use these latest techniques are better placed to deliver more individually-personalised customer experiences in real time, which is what consumers crave.
Our recent research highlighted a data science skills shortage as the main barrier to adopting data-driven marketing techniques, with two in five marketers (40%) saying this holds them back from delivering effective customer relationship management strategies. As a result of this skills gap, two-thirds of marketers (65%) said they are implementing only basic or segment-based personalisation and only 18% are adopting advanced attribution techniques. Without data skills, brands are at risk of lagging behind in the delivery of enhanced customer experiences as well as gaining marketing efficiencies.
Competing with data science
Over the recent years, interest in data science has been on the rise. This is partly due to the vast quantities of data produced today. But also, it is because of reduced data storage costs, a rise in the prevalence of open source software that facilitates large scale data management, and very advanced analysis and modelling which have helped data science to become a specialist discipline. Regardless of these advances, many organisations are struggling to contend with what, in comparison, are relatively modest data and analytical challenges.
Brands have masses of data and need professionals who can gather and organise it in meaningful ways, as well as analyse it to enable them to make smarter business decisions. Marketers with data science and analytics support will see measurably better results, from improving individual customer relationships to understanding which macro-level marketing and media investments generate the biggest return. That’s why, in the last few years, employers from every sector have been increasing their efforts to plug the data science skills gap.
Yet, there is still a notable shortage in skilled data experts in the marketplace. And, while academic institutions race to prepare and adapt enough courses to include the right content, the potential of the data revolution is yet to be fully realised.
Filling the data skills gap
Many brands are aware of their data skills gap, but finding talented people with the right data management and analysis skills is a struggle. Despite their best efforts, many educational and professional training schemes struggle to catch up with the industry’s demands. As a result, organisations are left with no choice but to look for new ways to acquire talent with the necessary data skills.
Creating a holistic data infrastructure requires people with different skills, including technical, insight, analytics, predictive modelling, consulting, reporting and visualisation. It’s expensive and difficult to gain a fast start when building these resources. That’s where partnering with data experts and insourcing specialists can help.
Insourcing presents businesses with the opportunity to accelerate their data opportunities by bringing in the right mix of skills at the right time to drive programmes of change, whether that’s with a business starting their data journey or one looking to fast-track new initiatives. This means that businesses can acquire the exact type of data skills when they require them and pay only for the period they need them for.
These practitioners work on-site as part of the business, integrating with incumbent technologies and processes, supplementing existing resource to enable fast-tracking of data development opportunities. Introducing specialist external data science talent into a business often sees accelerated learning for existing staff, reduced operating costs and rapid assimilation of commercial goals and objectives.
As data continues to proliferate, the challenges of managing it and extracting value will, too. New technologies are helping us keep pace and artificial intelligence in particular offers some exciting opportunities to let machines, rather than people, do some of the clever thinking. However, even with these emerging technologies, marketers will still need to be able to plug them in to legacy systems and use analytically-derived insight to stay ahead. By insourcing specialist resource today, brands can effectively plug the data skills gap.