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BizReport : Advertising archives : November 09, 2015

Top 5 tips to improve Big Data use

With the wealth of data out there, it is surprising that more campaigns aren't raging successes. The problem, according to one expert, is in how brands use - or don't use - big data. Here's how you can better use big data.

by Kristina Knight

1. Know Your KPIs Before You Buy

"Big Data becomes a big problem when we become overwhelmed with the sheer quantity of data. However, we can make it work for us if we truly know our key performance indicators (KPIs) before going into the investment. First, you must define the mechanisms through which you can improve your KPI numbers," said Malcolm Stewart, CEO, YouEye. "For example, if customer acquisition is a KPI, do you want to concentrate on mobile, social, digital ads, desktop, radio, in-store and print to increase that measurement? Once you know the mechanisms through which you want to improve your KPIs, you can focus on the metrics you need to measure within that for campaign effectiveness. It's vital that you carefully determine what your true KPIs are. For example, don't rely on email open rates for your email marketing when what really moves the needle for your organization is click-through rate. Or, don't rely on cost per click in paid search when what really matters is cost per acquisition."

2. Understand the Difference Between New Data and Old Data Imagined Differently

"There is a real difference between capturing new data and just visualizing old data in a new way. Data visualization is a nice component of data analytics, but should never be seen as the complete picture. You'll end up spending all of your time analyzing charts and graphs, and not enough time making effective decisions," said Stewart.

3. Recognize What Data Analytics Are Fundamentally Reporting

"Data analytics tools have their limitations. While Google Analytics can tell you a lot about number of visitors, conversions and bounce rates, it can't give you insight into user intent and emotion. Some data points can even offer sentiment analysis, but those algorithms aren't generally up for grasping the user's frame of mind at the time, or taking into account details like the slang we use in language," said Stewart.

4. Remember, Correlation Does Not Equal Causation

"The problem with having a lot of data is assuming that more data means more accurate predictions," said Stewart. "Some believe that with big enough data sets and smart enough algorithms, you can mirror causation with inferential models."

5. Big Data Should Not Be As Complicated As it Feels

"A user-friendly analytics interface is crucial when investing; your CMO should not have to rely on the reports that an analytics administrator set up at the beginning of the engagement," said Stewart. "Also, don't be blinded by sales pitches that show you everything you can do with a program's reports. If the analytics aren't customized to your KPIs and goals, you're just going to end up wasting money."

Image via Shutterstock

Tags: advertising, advertising data, big data tips, big data trends, YouEye

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