Edd Dumbill recently wrote a column for Forbes, entitled “Big Data Variety Means That Metadata Matters.” In the column, Dumbill argues that of the “three V’s” associated with big data – volume, velocity, and variety…
…it’s the variety in data that holds the most potential for exploitation. While not everybody has the huge problems of volume and velocity that a Facebook or a high frequency trader has, even the smallest business has multiple data sources they can benefit from combining. Straightforward access to a broad variety of data is a key part of a platform for driving innovation and efficiency.
This is very true when it comes to marketing data, particularly in this day and age of digital marketing, when marketers use so many different services to reach their target audience. Here are just a handful of the common types of data used in marketing:
- Website traffic data
- Advertising data, which has a lot of different types of its own (display, search, social, mobile, etc.)
- Social media marketing data
- Email marketing data
- Search (SEO) data
- Customer data
- Sales transaction data
Because each of these data types has its own characteristics, combining them is not straightforward. In the past, we have written about the integration challenges associated with marketing data, and the commonly quoted estimate, that obtaining and cleansing data sets is 80% of the work required for analysis, reinforces our assessment.
Even so, organizations are starting to recognize that combining data sets to get valuable insights is no longer a luxury, it’s a requirement. For example, marketing campaigns typically involve a variety of activities – advertising, social media, web content, etc. – so in order to understand the performance of a campaign, it is important to measure the performance of the various activities and compare them to the results of an overall goal (e.g., sales).
But what are marketing teams to do. They understand the value in combining data, they show a willingness to make it happen, but they struggle with how to do it. Typically, they start with a “simple” use case that combines a few types of data. They soon learn, however, how much effort is required – even for only a few data types – and as a result they revert to their sub-optimal, non-combined approach.
At Origami Logic, we feel there needs to be an easier way. We are committed to providing a solution that gives marketers insights based on data from multiple sources, without the effort historically required to combine data. Stay tuned as we will provide more details later this year.
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