Got big data? Big data can lead to big innovations or big disasters. What makes the difference? Here are a few mistakes that can snag you up when it comes to delivering powerful insight and meaningful marketing from big data. Avoid these common mistakes, and you'll be scoring high with big data marketing in no time!
With Big Data, Bad Data Gets Bigger
Bad data is always a problem. But when you assimilate a few small errors scattered across an enormous set of data, the problems compound exponentially. Not all marketers realize how badly a few bad apples can affect the overall analysis when it comes to big data marketing. It's essential to cleanse the data before running analytics so that your end results are as close to accurate as is possible.
Failing to Use Market Simulations to Advance Big Ideas With Big Data
Big ideas are bold and daring, and often marketers determine the most innovative ideas are too bold to actually pull off. What happens is that someone comes up with a huge idea. When collaborating with colleagues, the biggest, boldest parts of the idea get voted down, and the end result is another bland, unmotivated campaign that shows little or none of the boldness and innovation that the concept held. With big data, if you're brave enough, you can conduct market simulations to determine how those wild ideas will play out in the real marketplace. Surprisingly often, those most daring ideas end up being the best.
Neglecting to Acquire or Hire the Big Data Analytics Skills You Need
Big data analytics is a lot different from the marketing analytics of old, and the team absolutely must get additional training or hire someone else from the outside with data science skills and experience. However, these skills can be learned, and it's quite possible for your tech savvy folks to delve into analytics if they are motivated to do so. Data analytics requires a keen understanding of math, particularly statistics, as well as some programming knowledge and the artistic sense to coax the data into delivering insight.
If no one on your marketing team has the tech know-how, it will be necessary to hire from outside. Big data analysis leans heavily on tools like Hadoop, which is based on the Java programming language, and NoSQL, which is a lot different than traditional relationship databases like SQL. You can either choose a platform and hire based on that, or hire a data scientist and allow them to guide the organization towards the right tools. Alternately, you can contract with a vendor until your data analytics is delivering a ROI.
ReachForce helps marketers increase revenue contribution by solving some of their toughest data management problems. We understand the challenges of results-driven marketers and provide solutions to make initiatives like marketing automation, personalization and predictive marketing better. Whether you have an acute pain to solve today or prefer to grow your capabilities over time, ReachForce can unify, clean and enrich prospect and customer lifecycle data in your business, and do it at your own pace.
To learn more about how ReachForce can help you optimize demand generation and your impact on revenue, check out our real-time web form enrichment demo, or request a free marketing data diagnostic. Get the power to let data drive marketing and higher performance.