Marketing 0

Setting Up Data-Driven Marketing
Great marketing usually comes from great market insights. Over the
past few decades, marketers have perfected the way they conduct
market research to uncover information that their competitors do
not have. A combination of qualitative research and quantitative
survey becomes the norm for every marketer before beginning any
marketing planning cycle.
In the last decade, marketers have also become obsessed with
collecting a robust customer database to facilitate better customer
relationship management (CRM). The availability of big data has led
to the rise of data-driven marketing. Marketers believe that hidden
beneath the massive volume of data are real-time insights that can
empower them to boost marketing like never before. And they began
to wonder how to merge two siloed sets of information from market
research and analytics into a unified data management platform.
Despite the promise, not many companies have figured out the best
way to do data-driven marketing. Most of them end up with a huge
technology investment but have yet to realize the full benefits of the
data ecosystem. The failures of data-driven marketing practice are
down to three primary reasons:
1. Companies often treat data-driven marketing as an IT project.
When embarking on the journey, they focus too much on
selecting the software tools, making an infrastructure
investment, and hiring data scientists. Data-driven marketing
should be a marketing project. The IT infrastructure follows the
marketing strategy, not the other way around. It does not merely
mean making the marketing people sponsors of the project.
Marketers should be the ones defining and designing the entire
data-driven marketing process. As many market researchers
believe, a larger volume of data does not always mean better

---

insights. The key is to understand what to look for in the oceans
of information by having clear marketing objectives.
2. Big data analytics is often considered the silver bullet that
unravels every customer insight and solves every marketing
problem. Big data is not a substitute for traditional market
research methods, especially the high-touch ones, such as
ethnography, usability testing, or taste testing. In fact, big data
and market research should complement and augment each
other because data-driven marketing needs both. Market
research is carried out on a regular cycle for specific and narrow
objectives. On the other hand, big data is collected and analyzed
in real time to improve marketing on-the-go.
3. Big data analytics brings so much promise of automation that
companies think that once set up, it can be on autopilot. The
expectation is that marketers can pour large datasets into the
black box called algorithm and get instant answers to their
questions. In reality, marketers still need to be very hands-on in
data-driven marketing. And although a machine can spot data
patterns that no human can, it always takes a marketer with
experience and contextual knowledge to filter and interpret the
patterns. More importantly, actionable insights require
marketers who will design new offers or campaigns, albeit with
the help of computers.