Datavores are good at creating an edge with data: creatively acquiring new data & using technology to understand context through data.
This is why the first step in the journey to become a Datavore starts with the data, creating a single view of your customers, maximizing your knowledge about them using your current & acquired data.
The framework for becoming Datvores is described in more detail here:https://customeriq.substack.com/p/who-are-datavores
Although the term ‘metadata‘ was coined in the ’60s, people became familiar with it after the Snowden leaks. In 2014 in his TED Talk Snowden explained that metadata could reveal ‘who you are talking to when you are talking to them, where you travel.’
An IDC study titled “Discover the Digital Universe of Opportunities” states that from 2013 to 2020, the digital universe will grow by a factor of 10x—from 4.4 trillion gigabytes to 44 trillion. However, the IDC study estimates that only 3% of the potentially useful data will be tagged. So this is a huge gap & companies need to be aware of how powerfully they can leverage metadata.
Here is an example from Collen Jones: “Amazon knows I look at and buy Star Wars costumes for dogs, so Amazon recommends more. (I’ll probably buy them. I know, it’s a problem.) Amazon brings together data about my behavior and metadata about its products to deliver highly relevant recommendations. You can do this with your content if you have the right metadata in place”.
She goes on to describe how Metadata can be powerful for Marketers with the following 4 D’s:
I feel that companies just don’t spend enough time or resources in building the metadata required. Imagine if Retailers could use the metadata from the product descriptors to improve their ability to personalize recommendations for customers. And imagine if banks could use the vast metadata available to them about the context of a life stage to improve their banking experience.
Personal metadata – digital contextual information about users’ location, phone call logs, or web-searches – is undoubtedly the heart of data-intensive algorithms in the modern world.
Here is an example from Data Science central: “Let’s look at an example of the metadata associated with a 140-character tweet. 140 characters wouldn’t seem to be much data, even with a voluminous number of tweets. However, data volumes explode when you start coupling the tweet with all the metadata necessary to understand the 140-characters in the context of the conversation”
This theme of how my data can be controlled & managed by me has been worked on extensively by MIT.
“Metadata has however yet to realize its full potential. This data is currently collected and stored by hundreds of different services and companies. Such fragmentation makes the metadata inaccessible to innovative services, researchers, and often even to the individual who generated it in the first place. On the one hand, the lack of access and control of individuals over their metadata is fueling growing concerns. This makes it very hard, if not impossible, for an individual to understand and manage the associated risks. On the other hand, privacy and legal concerns are preventing metadata from being reconciled and made broadly accessible, mainly because of concerns over the risk of re-identification”.
https://customeriq.substack.com/p/its-my-data