Big data drives modern marketing. Every purchase and online interaction plays into a complex and far-reaching system. This vast data landscape generates valuable consumer insights and can even predict how customers or clients will behave in the future. This has major implications for businesses, their marketing departments, and especially the digital marketing professionals responsible for data-driven campaigns.

While data-driven strategies can unlock a world of potential for modern marketing initiatives, there are still weaknesses to address. Some of these involve a simple desire to stick with the previous marketing status quo. Gartner's Senior Director Analyst Joseph Enever explains, "Better data won’t increase marketing analytics’ decision influence alone," adding that there's a need to "address the real challenges—cognitive biases and the need for a data-informed culture."

Comprehensive training can play a significant role in preparing the marketing leaders of tomorrow to leverage data-driven solutions. The Bachelor of Science in Marketing is a particularly appealing option, integrating technical know-how with still-important soft skills. To that end, we explain how far digital marketing analytics have come, what's next for predictive analytics in marketing, and how targeted degree programs can shape the data-dominant landscape of tomorrow.

The Emergence of Big Data in Marketing

Marketing has long been a data-driven field. As former Forbes council member Jon Simpson explains, this "process of analyzing data and using findings to influence decisions" has been present for centuries and has been especially prominent these past two decades. However, Savitha Namuduri tells Chief Data Officer Magazine that these "early days of digital marketing were marked by challenges in data capture and storage." Resolving these issues has been key to unlocking the power of big data.

The use of data in marketing first picked up speed during the 1980s, particularly with the early development of customer relationship management (CRM) systems. Soon after, the takeoff of the internet prompted immense increases in data collection and analysis, with even more opportunities arriving as social media entered the digital landscape. This evolved into a powerful blend of CRM and marketing automation, which streamline critical marketing and sales processes.

The wealth of data means little of it cannot be efficiently analyzed, but thankfully, robust tools, technologies, and methods have entered the picture. With cross-platform measurement opportunities and solutions such as media mix modeling (MMM) and multitouch attribution (MTA), big data is now a central component of digital marketing.

Personalization at Scale

Today's demanding consumers desire personalized messaging and services that reflect their unique needs and preferences. Data-driven solutions provide valuable opportunities to meet these lofty demands by revealing what users want, how they've behaved in the past, and what they are likely to respond to in the future.

Perhaps more importantly, big data makes it possible to bring this personalized approach to a broader population of consumers. Previously, personalized marketing strategies were notoriously time-consuming, to the point that their return on investment (ROI) was often limited. With improvements in AI-centric strategies, though, it is possible to efficiently collect and analyze data from a wider range of sources—and synthesize this data to produce actionable insights.

As the Adobe Communications Team explains, today's most successful marketing teams strive to use "the right data at the right time through an end-to-end personalization strategy at scale." This means avoiding data silos while promoting a company culture that embraces data and agile marketing.

Predictive Analytics in Decision-Making

Drawing on the power of past interactions or purchases to reveal how consumers might respond to future campaigns, predictive analytics plays an increasingly central role in today's digital marketing initiatives. These days, consumer behavior analysis largely revolves around two methods. We briefly mentioned these earlier and now describe them in greater detail:

  • Media mix modeling (MMM) – Built on a strong foundation of aggregated data, MMM solutions track a broad spectrum of marketing activities, revealing how these influence ROI. Multilinear regression is a key component of this approach, as this shows how the dependent variable (like sales) is linked to independent variables (ad spend, for example).
  • Multitouch attribution (MTA) – Encompassing a range of consumer touchpoints, MTA grants fractional credit to various aspects of the customer journey to demonstrate the level of influence these channels or interactions have on eventual sales. This strategy can leverage data from numerous sources, including not only social media analytics and content marketing analytics but also paid search and even direct mail.

The Impact of Data Privacy Regulations

If the 2010s saw the rise of big data in digital marketing, the latter half of the decade and the first few years of the 2020s have produced considerable pushback in the form of strict data privacy regulations. We outline two of the most impactful below:

  • General Data Protection Regulation (GDPR) – Implemented by the European Union but increasingly relevant in the United States, GDPR represents the world's toughest data protection rules, which, although vast in scope, center on one main goal: to give users more control over how their data is collected and used. Under GDPR, website visitors must explicitly consent to having their information gathered and must also be notified if sites are breached.
  • California Consumer Privacy Act (CCPA) – Similar to GDPR, CCPA grants consumers extensive rights to dictate how their personal data is gathered and disseminated. Under this law, users are allowed to have their information deleted on request and cannot be penalized by businesses if they exercise these rights.

While these and other emerging regulations will have a huge impact on which types of data can be gathered and in what circumstances, they are not expected to slow the progress of big data in marketing. These days, many consumers are receptive to sharing their information but often want the chance to opt in or opt out. Furthermore, consent management systems and other privacy technologies promise to expedite the process of gaining consent.

Integrating Offline and Online Data

Data-driven marketing faces many challenges, and one of the most significant involves the integration of offline and online data. There are substantial volumes of both, and while online data tends to attract the most attention, disconnected offline data is also abundant. This can take various forms, such as purchase information, loyalty card history, and survey results.

When online and offline data are properly integrated, omnichannel optimization is well within reach. In addition, this approach is more likely to produce accurate consumer insights and audience profiles. Integration can produce exciting new revenue opportunities as well. Many organizations work with onboarding partners to streamline this process.

The Future of Data-Driven Marketing

The age of data-driven marketing has arrived. Some marketing firms and professionals have yet to catch up, however; every day that they fail to implement data-driven strategies, they yield even more advantages to their competitors.

As a greater share of organizations utilize data-driven solutions, the new focus will shift from whether these are used to how they are incorporated into campaigns and which technologies provide the best ROI. Artificial intelligence has a growing role to play in this, offering powerful opportunities to boost content optimization while helping forecast demand.

Moving forward, digital marketing professionals will be expected to master and embrace data-driven strategies while also getting comfortable working alongside AI solutions. Meanwhile, as GDPR, CCPA, and emerging legislation exert their influence, marketing teams will be more inclined to embrace first-party data, rather than relying on the third-party solutions of yesteryear. Other digital marketing trends to anticipate include:

  • More touchpoints in the consumer journey — dozens or even hundreds for some consumers. This distribution of these touchpoints will change, too, moving away from linear sequences.
  • Agile marketing solutions will leverage data-driven insights to allow teams to respond to challenges (and embrace new opportunities) in real time.
  • Data science teams will be relied on to boost customer segmentation, predictive modeling, and channel optimization.

Learn More, Today

Are you ready to embrace new trends and technologies as they relate to digital marketing? First, you need to develop a robust skill set. The University of Minnesota’s Bachelor of Science in Marketing is an online marketing degree that provides a deep dive into a variety of fascinating topics, such as consumer behavior and international marketing. We also provide numerous hands-on learning opportunities to help you apply your newly developed skills. You can emerge feeling confident and excited about your prospects in the fast-paced field of digital marketing. Reach out today to get started.