In just under two decades, the big-data industry has grown to mammoth proportions, and is slated to pass $200 billion in 2017, according to research from the International Data Corporation. The rich array of insights provided by data analytics is having an impact on multiple industries, from restaurants to mining to media. It is also impacting corporate structure, from finance to tech. As Wordstream CEO Larry Kim says, “Big data is the new oil.”
It is thus no surprise that the market for information-based services is growing rapidly (11.7% compounded annually), and thousands of highly successful SaaS products have sprung up in the wake of the boom. This digital transformation of customer insights has significantly changed the role of a CMO. Now even brands like E-chat are doing well to raise millions of dollars during an ICO to make sure personal data and finance can be better protected and not controlled from authoritative parties.
Most executives in marketing can relate to this shift. Waves of disruption, such as the rise of social and the takeover of mobile, have constantly reshaped the terrain for marketers. For those in the field, a common aspiration is to fulfill to role of what many refer to as “the new CMO” or “the CMO of the future” — implementing digital insights to gain an edge over an ever-improving market toolbox.
Explica, a media company based in Austin, Texas, has grown dramatically since it was founded in 2016. The company’s news/media destination site covers sports and entertainment for an audience of over 7 million monthly active users (MAUs) as of November. Armed with $1.2 million in recent Series A funding, the data-driven company is on track to reach 10 million MAUs and launch a mobile app.
Below, the team at Explica outlines how CMOs can take advantage of big data to build a successful digital brand. The company’s principals, Vip Sitaraman and Nando Luna, highlight a core company value that sums up their approach: “automate insights.”
Here are their 3 pillars of data-driven marketing:
1. Synthesize Different Data Sources And Types
As with most industries built off technological disruption, any client of the big-data services industry requires a variety of data sources and multiple types of data. These are offered by an array of very different products. In short, big data services is an extremely fragmented market. Because of this, perhaps the most important first step as a data-driven marketer is to interpolate different data sources.
The challenge is then to compare data that have different parameters or use different units. Many affinity-related services will offer relative indexes that are based on global or market averages within the industry. However, comparing data across multiple platforms that use different units (e.g., industry percentile vs. percentage of audience) is a key step in cross-referencing and verifying data between multiple third-party data providers. To adopt Larry Kim’s analogy, if big data is the new oil, then it must be refined before being used as fuel.
2. Real-Time Insights
The digital revolution was quickly followed by the rapid evolution of programming technology. With real-time bidding came real-time analytics. In the last decade or so, the world of analytics has diversified to draw from the growing repositories of data on the digital lives of individuals.
Today’s technology makes it possible to acquire information on anything from household size to the favorite NBA team of an individual, based purely on their digital behavior. These algorithms, which are often driven by artificial intelligence, can examine the minutiae of an individual user’s life and habits, but can also depict trends across groups of millions of people. This type of analytics often reveals sub-cohorts within user groups, and allows for day-to-day business adjustments.
3. Predict Performance
Demographic data is also key to identifying growth opportunities and projecting probabilities. For instance, Explica started as a primarily male site covering mainly sports. However, it has since grown to a 50–50 male-female split after diversifying to 3 new verticals, including celebrities and TV.
The takeaway here is that focusing on edge-case users—for any product—often reveals unseen market opportunities.
In the digital era, big data is as much a staple as oil was in the industrial era. Properly refining that oil and efficiently burning it is the key to building an efficient data-driven marketing engine. Because of the growing importance of digital performance across industries, most CMOs could benefit from synthesizing big data to predict performance and adjust their business strategy in real time.