Since the turn of the millennium, there has been an explosion of world-altering tech, with brands such as Uber, Airbnb, and Netflix reshaping consumer behaviour. As the current global economic headwinds start to abate, businesses are looking for tech solutions to keep moving forward.
With 86% of organisations stating that increased adoption of new technologies would drive transformation in their companies, it is no surprise that CMOs ranked investment in marketing technology as a top strategic concern. With two-thirds of CMOs feeling overwhelmed by the amount of data on hand, this is undoubtedly an initial focus for digital investment.
Cloud computing is the solution that will truly revolutionise how CMOs and marketing teams handle their data. While cloud solutions have been around in advertising for many years, the worlds of marketing tech and cloud tech have traditionally remained separate. But with integration capabilities and computing power advancing, marketers can now more easily use the cloud to streamline their data and harmonise various silos within the business. Furthermore, these advances give marketers the ability to not only leverage existing generative AI capabilities to activate their data, but also to develop their own tailored solutions.
The power of combining marketing with the cloud
Using Google’s solutions as an example, many marketers have a good understanding of Google’s Marketing Platform (GMP). This suite of solutions — including Google Analytics 360, Search Ads 360, Campaign Manager 360, and more — is vital for the planning and execution of the modern digital ad campaign.
However, the power of Google Cloud Platform (GCP) is less well-known; it can simplify and streamline data ecosystems, and empower data for marketing solutions. By combining both Google solutions, marketers can produce actionable insights from comprehensive data analysis to predict consumer behaviour and deliver personalised experiences for impressive results.
Bringing together ad tech and the cloud will radically alter how marketers harness data. With cloud-based access, marketers can view and activate insights in real time. Cloud-based solutions also reduce operational friction and increase data security, providing simultaneous access for teams.
Once data marketing solutions are integrated onto the cloud, AI and machine learning tools are then able to assist with marketing optimisation. Tools like BigQuery and Vertex AI, for example, can automate repetitive tasks and extract data insights faster, allowing marketers to optimise their spend quickly. The data analysing power of BigQuery allows marketers to uncover additional insights to deliver campaigns with a stronger impact.
Learning to run before walking
So, what is holding businesses back? Perhaps it is the misconception that this increasingly consolidated and automated technology could lead to businesses overlooking the importance of their teams. However, far too often, brands integrate a wealth of solutions into their tech stack with little strategy or education on how teams can truly optimise these to deliver the marketing results and return expected from investment. Marketers are therefore left overwhelmed, with few valuable insights to optimise their campaigns.
Tech solutions are useless without the right human touch to guide them, which is why it’s vital for advertisers to gain specialist support. Without this comprehension — on how to manage and understand the data, and technical capabilities — investment will be wasted.
As a result, there is one role in particular that is instrumental in implementing and optimising these technologies: the data engineer.
The human side of tech
The high adoption rate of GMP and GCP has led to Google’s tech stack becoming the industry standard, which is largely down to its tools being compatible and not as complex to integrate as other tech stacks. , Far too often, solutions are added to a tech stack with little thought to how they will be utilised effectively by the teams, causing confusion and the inability to gather valuable insights.
This is where a data engineer’s work can make a huge impact. On a day-to-day level, data engineers are tasked with designing, maintaining, and optimising data infrastructure, providing marketers with easy access to data insights for evaluation and action. They act as the bridge between marketers and evolving technology, understanding their company’s needs and then using their expertise to pull out relevant insights to deliver results.
While external partners can provide expertise and assistance, data engineers — embedded in the process — provide ongoing maintenance and tailored optimisation to ensure the flow of data between tools in the tech stack and identify the relevant insights for marketing teams to deliver the best ROI.
Having company-specific knowledge, overlayed with expert data skills, means internal data engineers can more rapidly identify and address evolving requirements and solve arising issues. In addition to enhancing cost efficiencies, this understanding can also raise the value of solutions within the business to deliver increased ROI.
It is one thing to recognise the need for a specialist of this kind, but it is another to recruit one. Attracting top talent for specialised roles such as a data engineer can be tough in today’s tight job market, making trusted external partners key to bridging the gap. Not only can they provide close support in the short to medium term, but they can also deliver effective training to upskill team members to a data engineer role. Their support means brands can not only hit the ground running from day one with their cloud-supported marketing solutions but also develop a framework for long-term success.
While the integration of marketing and cloud solutions is not a new concept, generative AI’s well-documented ability to enhance scale and performance is now shining a light on the promise of technology to help deliver results. However, while digital transformation is necessary for many businesses to make the most of evolving cloud and AI technologies, these tools will be useless without the right human expertise and support.
Data engineers hold the key to unlocking technology’s true potential, and businesses need to start integrating their expertise into a long-term strategy to get the most out of martech investment.