As technology-savvy, data-driven marketers, our job is to get the right message in front of the right audience at the right time to drive the desired consumer behavior -- more efficiently and effectively than traditional approaches.
This isn't easy - and it's not for the faint of heart.
Data-driven marketing requires a new mindset, organizational commitment and new tools and techniques.
As the label says, it requires data. Big Data.
Big Data, the broad term for accumulating, storing, and manipulating data sets so large/complex that traditional methods are inadequate, accelerated its maturation through 2015.
As the amount of data has exploded, the most sophisticated companies have developed new ways to capture, synthesize and act on Big Data. In a few short years, Big Data has come to dominate the marketing - and broader business - lexicon. Along with the Cloud, the new tools and technologies that have been created to capitalize on Big Data, have forever changed digital marketing.
In order for this maturation to continue, we need to go beyond Big Data. Big Data, but more of it, aggregated and processed at a faster pace, and actioned in real-time across a broader set of touchpoints. In 2016, Fast will be the new Big.
This evolution is driven primarily by the pervasiveness of personal devices that generate so much data representing behaviors that, to date, have been invisible.
Imagine correlating heart rate data with TV watching data. Devices exist that capture those data sets over time. But what to do with them? The challenge, as always, is to figure out how to efficiently and effectively tap into this newfound richness; to harness the power in these new data sets; to action on it in a way that moves the sales needle.
Many prognosticators have peered into their crystal balls to divine where the market is headed. Most will be wrong.
Where do I see this going? Where is my company placing our bets?
While these may be off by degrees, directionally this is the evolution of Big Data in 2016 and beyond:
1. Converged platforms will disrupt current data architectures
When it comes to solving data related problems, the tech landscape is still separated into transactional and analytic roles. Technologies and techniques for converging (unifying) these types of environments are becoming much more commonplace. We are inching closer to the realization of the efficient, unified database where raw transactional data combined with predictive insights is readily available in a user-friendly manner. Companies such as MarkLogic and the Apache Spark project, we are in the process of moving past Hadoop as an early adopter of Spark, will continue to move us in this direction.
2. Stream (real-time) analytics will become a focus
Once we have the converged platform, data access is easier. But what about timeliness? A platform that unifies all available data but is not current (due to processing lag, etc) is necessary but not sufficient. This is where stream analytics come in. Stream analytics technology and techniques provide the building blocks for the ingestion and processing of data that streams from devices, applications, and systems in real-time. It represents a core upgrade in combining traditional analytic techniques with a high-performance technical architecture and will allow marketers to correlate behaviors across the broader ecosystem of devices.
3. User-friendly machine learning implementations will become readily available
Machine learning has been applied to marketing analytics problems with the goal of finding predictive patterns in data. The challenge with operationalizing machine learning isn't with the results, but with the process. The accessibility of both the algorithms and results remains out of reach for most marketing professionals. This year, we will see momentum building around user-friendly machine learning and data exploration platforms. From IBM Watson Analytics to Microsoft Azure's Machine Learning to Google's Tensorflow, the industry is heeding the call for exposing the power of machine learning to the marketing department. Zeta's own patent-pending ScaaS (Scoring as a Service) engine is an example of a solution that builds on these systems to create a stronger product for data-driven marketers. But the introduction of these products does not means Data Scientists become less important. No, the transition of the marketing world from Mad Men to Mad Scientists will only accelerate as these new tools allow them to focus on even more complex problems.
4. Metadata and Master Data Management processes will re-emerge
As 2016 is poised to pick up the data "pace," and provide access to broader user population, with that acceleration comes risk. The risk is inherent in the more personal information we will have access to. To mitigate risk requires process and structure. We don't see things getting overly burdened with process, so as to squelch progress, but a return to organizational aspects of data management, with the inclusion of metadata and master data (data about your data), will occur. Higher level organizational data oversight, at the CIO and Data Steward levels will ensure that as we accelerate the data-driven marketing train more quickly, we don't careen off the tracks.
5. The Internet of Things (IoT) will become more ubiquitous.
The most interesting item on the horizon that is poised to change marketing for the next decade is the emergence of the Internet of Things (IoT). The IoT is the network of real world objects or "things" embedded with technology, which enables these objects to collect, manage, process, and exchange data. Think about the marketing progression from direct marketing databases, to offline customer databases, to online customer databases, to online customer behavioral databases, to the layering of mobile, social, and display actions, etc. Each technological advancement (phone, web browser, smartphone, smarthome, smartwatch, etc) provides the potential for a new layering of data about customers and their behavior. The full realization of the IoT accelerates data value incredibly quickly. Marrying the better techniques for processing and utilizing data in real-time and we have an ecosystem that can help us grow and thrive for the foreseeable future.
We are on the cusp of something truly amazing. New devices, new interactions, and new data captured at record speed being processed in real-time by the next generation of unified architectures and tools.
2016 will build on the momentum of 2015 to create something bigger, faster and better. One step closer to realizing the full potential of data-driven marketing.