Marketing teams are under increasing pressure to deliver. Amid a digital marketing slowdown, rising media fragmentation and macroeconomic uncertainty, organizations are demanding winning campaigns. Data is the key to making this a reality. It helps marketers effectively segment audiences, identify new market trends and understand critical success factors. But data quality and speed of delivery are essential to effective marketing.
Given the complexity of enterprise data ecosystems, good, fast data is easier said than done. Resilient data pipelines must be built to connect marketing data from a variety of legacy and cloud-based sources to their destination. There’s also a disconnect between marketing teams that need seamless data flows and the IT experts building those pipelines.
Cracks in the Pipeline
Like many modern enterprise functions, marketing is data-driven. Our research reveals that 40% of global data professionals receive weekly data requests from marketing teams. They want to harvest data from diverse sources like CRM systems, web analytic tools, social media and e-commerce platforms and use it to drive new leads and conversions. Yet demand is at risk of outstripping supply as IT teams are deluged with requests from all over the business.
Moreover, the fact that data sits in discrete, siloed systems and multiple formats makes the job of the data engineer that much harder. Although many end-user marketing professionals may not appreciate it, the complexity means creating data pipelines to spec and at scale is a huge challenge. It’s a labor-intensive effort requiring bespoke, hand-coded solutions that can’t be re-used.
Pipeline breakages are not uncommon, often due to the sheer volume and velocity of marketing data that needs to be assimilated. Marketers work from a vast diversity of real-time data – from click-throughs to open rates and sales figures to conversions. Maintaining an accurate record of all data sources and the pipelines that deliver them can be challenging. Other factors include bugs and errors introduced during a change, pipeline owners moving on without making a pipeline available to the rest of the team, and infrastructure changes like moving to a new cloud.
The result? Some 60% of marketing data professionals admit their pipelines are too brittle and crack at the first sign of trouble – significantly higher than peers across the business (39%).
Data Chaos is a Roadblock to Success
The move to the cloud has brought many benefits but also challenges like data integration friction. Although seen as an enabling technology that can help to overcome integration challenges, cloud migration can worsen data silos and require extensive IT effort to orchestrate, rework, and connect cloud systems to data pipelines. Failure to do so creates a “data drift,” which may ultimately break processes, corrupt data and disrupt the flow of business-critical information to marketing teams.
We should also remember that the cloud is just one piece of the puzzle. In fact, a marketing function will require data from multiple legacy, on-premises and cloud-based sources. The friction created by this data heterogeneity can have unintended consequences. Almost three-quarters (73%) of data professionals in marketing say that data in legacy systems like mainframes and on-premises databases is hard for cloud analytics tools to access, so they often “don’t bother” including it. This could see them overlook a vital trove of customer insight.
Another result of this data chaos is that it creates security and governance challenges. This is particularly worrying amid an increasingly strict regulatory regime for data protection and customer privacy. Unfortunately, while 81% of marketing data professionals want consistent security measures to protect data as it flows between on-premises and cloud sources, 56% admit that they actually have a data “wild west.”
Time to Collaborate
Over half (52%) of data professionals in marketing say data integration friction is a “chronic problem” in their organization versus an average of 43% across their peers. This means many teams are working with outdated or incomplete information, resulting in worse campaign outcomes and customer experiences. So how can marketing data professionals tackle the friction and chaos which characterizes many day-to-day operations?
First, data leaders and practitioners across the enterprise must work together to build the right environment to optimize data use. That means consolidating on a single, centralized management console to act as a data “mission control.” This will help embed good governance and streamline data integration, so end users like those in marketing can extract maximum value from data. This management layer could also empower LoB marketing users to self-serve by collecting “last mile” data and analyzing it themselves. That, in turn, will reduce the workload on IT and free up technical experts to focus on higher-value tasks.
Successful marketing is critical to business success at a time when customer loyalty has never been so hard won and easily lost. Building a more robust and streamlined data ecosystem should be high on the enterprise priority list.