How to Make Your Marketing Big Data Payoff

With the growth of Big Data tools and technologies, the state-of-the-art in marketing is rapidly evolving. Business Intelligence (BI) solutions have become synonymous with online marketing thanks to new software applications used to analyze an organization's raw data. Instead of traditional campaign planning and KPI-based analysis, marketers now have the power to fully track individual customer journeys and understand the impact of each interaction on business outcomes. Unlocking access to such granular levels of data gives marketers the opportunity to do what they do best: Ask "How can I improve the experience of my customer and the outcome to my business?" BI that is purpose-built for Big Data is the best way to visualize large datasets over time and allows data-savvy marketing professionals improve customer interactions by learning from and iterating faster on their marketing initiatives.

An excellent opportunity to understand how BI on Big Data is changing marketing is through real-life examples gleaned from working with Neustar’s marketing analytics service, MarketShare DecisionCloud. Neustar serves Fortune 1000 marketers from companies like MasterCard, Hilton, and Home Depot, connecting their efforts to increase revenue by analyzing customer interactions and the resulting business outcomes. Since Neustar switched its marketing analytics program to a more integrated approach, they’ve been able to improve the visual analysis capabilities of the Marketshare DecisionCloud to give a granular understanding of customer behaviors and touch points, empowering marketers to act on that information more quickly.

So, what did we learn, in terms of best practices and effective use of Big Data tools, in our work with Neustar that’s relevant to every data-driven marketer out there?

There are three key observations:

 

1. Reexamine how you leverage your big data architecture

Thanks to IoT and the seemingly unlimited online touch points available across channels, we have more data sources to analyze than we did even just five years ago. To stay competitive, businesses need to munge together data from different sources such as SalesForce, Google Analytics, and social media, which often means having to reexamine outdated data storage and analytical systems to streamline them. More and more businesses are looking to open source Big Data platforms like Hadoop because it’s an efficient and economical way of storing data. However, there are missed opportunities if all we do with this granular data is store it without providing visual access.

Organizations see the biggest return on investment from their BI and Big Data initiatives when a broad spectrum of business users have access to data and analytical tools. What motivates business users and analysts (not just data scientists) to explore this data? The short answer is interactivity and user-friendly interfaces. If you have to request IT for data exports every time you ask a new question, or if you have to rely on programmers to write code before you can validate hypotheses, you are likely not going to have much to do with your Big Data system. On the other hand, running analytics and BI/visualizations natively on Hadoop enables business users to dip into the same data pools at the same time, streamlines security and access controls, and combines multiple data sources while providing familiar access methods. All of these benefits broaden the potential audience who can access analytics and insights, and put it into action.

2. Look for better insights using real-time data

Real-time analytics may be the biggest game-changer in modern marketing technology to date. With real-time analytics, marketing performance can be tracked during different times of the day. For example, in retail environments, real-time floor diagrams can show how customers move through the sales funnel; from being aware of a brand, to interacting with the brand, to converting. Heat maps can show how different time points in the day perform relative to others.

Legacy BI tools don’t have the capacity for such a heavy data traffic flow. When organizations try to incorporate real-time streaming in their legacy visualization stack they often encounter extremely slow load times and siloed analytics that don’t scale.

By running analytics off of one data source, you get a more holistic picture of your business. That’s where the real fun begins; imagine being able to compare marketing spends side-by-side in real-time, comparing the Los Angeles market vs. New York market. You’d be able to optimize and calibrate your spend mid-sales cycle.

3. Drive business user engagement with a visualization-first approach

Marketers like to iterate and research promotional options with data. We often seek exploratory data analysis tools with lots of charts and graphs to help us understand our marketing program’s impact at a quick glance. Being able to actually see and interact with data makes a huge difference in comprehension.

One of our client's architects has a nifty mantra for data visualization best practices called UPS: U standing for UX, P for performance, and S for scalability.

Since our client specializes in tracking customer conversion journeys, visualization plays a huge role in the marketing analytics application (DecisionCloud) that is built using Arcadia Data technology. The client needed to track customer journeys from raw data and then apply predictive models in order to understand what interactions were changing consumer behavior toward the brand to finally convert to a purchase.

These reports not only need to track the conversion journey, but also deliver rich insights on the customers themselves. Over time these visualization and reporting programs enabled the client's customers to get prescriptive recommendations every day on how to change their media buys, so they could course-correct and optimize their marketing programs in near real-time.

In summary, working closely with your BI technology to create a solution tailored to your specific daily needs will ensure successful use of analytical data within your organization; cutting down on time, cost and confusion. It’s time to demand payoff from the Big Data promises that we’ve all heard.

 

by Steve Wooledge

VP Marketing, Arcadia Data

Steve Wooledge is VP Marketing at Arcadia Data, provider of the industry's first real-time modern business intelligence (BI) platform for Big Data.

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