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Big Data Myths Debunked

For all the focus on Big Data and its opportunities, most marketers are far from realizing its potential.

Here’s a dirty little secret: Marketing professionals are still plagued by bad information and an inability to use data to its full advantage. They’re struggling to create an omni-channel, personalized strategy that improves sales and profitability.

In a recent study that ZoomInfo conducted with Ascend2, successful, data-driven marketers listed “personalizing the customer experience” as their top objective this year but said “improving data quality” is their No. 1 challenge.

From what I’ve seen, many organizations are merely scratching the surface with data-driven marketing. They retroactively analyze campaigns and channels but spend little or no time predicting what works best.

Marketers need to combine retroactive analysis with other data-driven tactics to cover the spectrum of digital marketing and forecasting. They should use multiple, integrated platforms, such as Google Analytics and CRM and marketing automation software, to evaluate the results of everything they do (from webinars to events to e-mail campaigns) and all interactions with prospects and customers.

For example, it’s now possible to follow the full cycle from a prospect’s first visit to your website to lead conversion and revenue generation. Robust statistical analysis can help you not only determine what target markets and buyer personas to pursue but also precisely how to reach individuals. The right business intelligence can automatically and continuously identify ideal buyers, helping you replicate success.

These kinds of Big Data use are essential to personalizing communications with prospects and customers in real time, as well as easily pinpointing new opportunities to improve ROI. Benefits of this approach include creating a consistent digital ecosystem with a streamlined customer experience, closer marketing and sales alignment and faster corporate growth.

So what is holding back the Big Data tide? Part of the problem is the reliance on myths. Here are four of the most common misconceptions and related real-life findings:

  1. The more data you analyze, the more value you will gain.

Actually, too much data can be harmful, and quality is equally important. If you track too many data points, you’ll detect patterns that have nothing to do with reality. For example, you may find that people with the first name Joe tend to buy your product on a frequent basis when that isn’t a valid predictor of sales success.

Here is a useful rule of thumb: The number of data points you evaluate should relate to the size of your company, your number of sales leads, the size of your prospect database and similar factors. If you have a few hundred leads in the pipeline, 10 data points may suffice. You need to select the highest-quality data to track. Add a human element by reality-checking your data points with sales and customer service colleagues.

Quality often trumps scale for B-to-B marketers. Using data to achieve more relevant targeting and messaging enables better campaign results and more qualified leads, in turn driving growth and profitability.

  1. Marketing technology can do all the work for you.   

Incorporating multiple marketing technologies in your marketing strategy and operations is vital, but it requires skilled human involvement. You need a proper perception of what all the numbers mean. To take full advantage of the different marketing technology software your team is using, you need a team member who has deep understanding and stays on top of changes. That includes keeping up with software releases and knowing how code is implemented on your website, so everything can be measured.

You also should integrate all your data to see the big picture. Using different types of data can help you understand what you’re doing well and where you need to invest more and expand. Otherwise, you’ll be navigating blindly.

It’s essential to set up your analytics properly. Enlist at least one marketing technologist with appropriate expertise to help with the setup and reality testing. You need people who can think strategically, are tech savvy, have analytical skills and a related passion. Marketing experience helps but may not be necessary.

  1. You can look at analytics just once and keep applying the same findings.  

One data snapshot won’t do. You need a robust, dynamic quality assurance process because everything from web pages to lead scoring changes constantly and your analytics have to be refined accordingly.

  1. Simply collecting data is all a marketer needs to do.

Extracting and assembling business intelligence are only the first steps. Making data actionable is critical to improve prospect and customer engagement, increase qualified leads and raise conversion rates. You need to assess all your information together to understand the performance of all channels – such as your website, e-mail communications, third-party advertising campaigns and social media. And you need to study the behavior of your prospects and customers. Then you can make incremental improvements and methodically measure the impact of those changes.

Big Data isn’t an elixir for all problems marketers encounter. However, if you fully understand its capabilities and leverage them wisely, it can be indispensable in helping you improve your company’s top and bottom lines.

Hila Nir is vice president of marketing and product of B-to-B business intelligence provider ZoomInfo.