Big Data Pitfalls That Undermine Marketing Automation Goals

August 16, 2017
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According to the Lenskold Group’s 2013 Lead Generation Marketing Effectiveness Study, 49% of businesses use marketing automation. Marketing automation allows businesses to cut costs and make better informed marketing decisions.

Successful marketing automation strategies are highly dependent on big data. Brands should understand the role big data plays and have a clear strategy to collect and use it effectively.

Why Marketing Automation Depends on Big Data

There are several reasons companies adopt marketing automation:

  • There are a variety of ways they can use marketing automation technology such as GetResponse to streamline their marketing processes, such as scheduling social media posts and procuring new content.
  • They can collect more data, which may be used to make better marketing decisions.

Big data plays a key role in marketing automation. Here are some reasons big data is so important:

  • You can monitor trends, which play an essential role in day-parting and timing of marketing strategies.
  • You develop a more granular understanding of your customers. Most data storage options have multi-dimensional arrays, which allow you to gather data on numerous demographic variables.
  • You can measure the cost-effectiveness and ROI of different marketing tactics in real-time.

If you collect high-quality data, you will have a highly effective marketing automation strategy. On the other hand, your marketing automation efforts will fail if you collect inaccurate data or fail to use it wisely.

Big Data Strategies to Improve Marketing Automation

Your marketing automation strategy depends on the quality of your data. Here are some strategies to collect the right data and use it effectively.

Only Collect Relevant Data

Cloud technology and other data storage options allow brands to store hundreds of gigabytes of data. Many companies get carried away and store a lot of data that they don’t actually need.

Having too much data can be a problem. Even the most sophisticated data-mining tools have difficulty aggregating terabytes of unnecessary data.

This is why you need a detailed marketing automation strategy before collecting data. You need to begin by developing a unique value proposition template. According to Michael Skok, serial entrepreneur and founder of Startup Secrets, a good value proposition should include:

  • The buyer
  • Their problem
  • The unique solution you provide

All data should be collected with these three factors in mind.

Have Quality Controls in Place

Ensuring the quality of your data should be your top priority. If you made marketing automation decisions off inaccurate data, you may be worse off than if you didn’t collect data at all.

Here is an excerpt from a recent paper by IBM on the important of ensuring the quality of your data.

“The outcome of any big data analytics project, however, is only as good as the quality of the data being used. As big data analytics solutions have matured — and as organizations have developed greater expertise with big data technologies — the quality and trustworthiness of the data sources themselves are emerging as key concerns.”

You need to carefully screen all inputs for false positives and false negatives. You also must cross-reference existing data fields against new inputs to identify human input errors. New AI tools make this job easier than ever, so use them to your advantage.

Use Big Data Consistently and Properly for Marketing Automation

Collecting big data is one of the most important steps of any marketing automation strategy. However, it won’t do you any good unless you actively use it.

Make sure everyone in your team understands the role data plays and how it must be used. Here are some tips to follow:

  • Understand the role all data plays in the brand’s marketing strategy.
  • Only make decisions after you have a statistically significant sample size.
  • Use the same process consistently to avoid discrepancies in branding messages and other problems.

Your team needs to understand that big data is important, but they need to use their own common sense to incorporate it into their marketing automation strategy.