Here’s the catch on data driven storytelling examples

Here’s the catch on data driven storytelling examples
6 March 2017 Rutger Verhoeven

Here’s the catch on data driven storytelling examples

I’m always interested in great examples on data driven storytelling. What is happening on this engaging topic around the world and what can I learn from that. So I decided to try my luck. While surfing the net and letting Google lead me the way to interesting articles, opinions and great business examples on big data I stumbled on this article with an interesting quote

“Data decisioning is fundamentally about using analytics to dramatically improve the decision processes within an organization — to ensure that decisions taken are timely, relevant and complete”.

Giving the fact that we’re running a startup company that tries to improve content strategy based on big data delivered insights I was glued to the story.

What does it take for a story to be spot on, relevant and highly engaging

Nobody seems to be able to give real good examples to break through the ultimate puzzle of delivering the right content, to the right target group, in the right channel on the perfect moment with the best tone of voice. What does it take for a story to be spot on, relevant and highly engaging. If the answer is ‘big data’ and the promise is that it can help us unravel the puzzle let’s see what else is out there.

Since I’m fairly new on the concept of ‘data decisioning’ I decided to search further on the topic. It lead me to the next story with another interesting statement on picking the right metrics:

“There is a difference between numbers and numbers that matter,” according to Jeff Bladt and Bob Filbin. […] One of the most important steps in beginning to make decisions with data is to pick the right metrics. Good metrics “are consistent, cheap, and quick to collect.” But most importantly, they must capture something your business cares about.

Good metrics are consistent, cheap, and quick to collect

A little further the article speaks of Analytics 3.0. I found out that this is a Harvard Business Research survey where it states that Analytics 1.0 is about the era of business intelligence, Analytics 2.0 is the era of big data and the Analytics 3.0 the era of data-enriched offerings.

At the end of the article the author (Thomas Davenport) points out 10 requirements to capitalize on Analytics 3.0. For the purpose of this blog I’ll just pick out one.

Prescriptive analytics.

“There have always been three types of analytics: descriptive, which reports on the past; predictive, which uses models based on past data to predict the future; and prescriptive, which uses models to specify optimal behaviors and actions. Although Analytics 3.0 includes all three types, it emphasizes the last. Prescriptive models involve large-scale testing and optimization and are a means of embedding analytics into key processes and employee behaviors. They provide a high level of operational benefits but require high-quality planning and execution in return.”

This is of course very interesting but also very theoretical. I just want some smashing examples — how does this work in real life ?

I’m still not satisfied left out with 2 burning questions.

why aren’t there any good examples of companies, brands or specific cases having benefits from the use of big data
why aren’t there any examples on optimization of online storytelling and content strategy with the use of big data
When I give keynotes I always use this one sheet that says: There are 3 types of content strategists:

– the ones that don’t know anything about it
– the ones that say they know all about it, but in fact they don’t have a clue
– the ones that try

Of course you need people from the third group. I believe you can only come closer to the truth by trial and error. And of course the truth has many faces. Hence, every brand wants to accomplish something else within the digital domain.

Maybe it is so hard that everyone keeps the results to themselves

The fact is that the net is not crowded with great examples of cases from the third group. I believe this can only mean 2 things:

A great data driven storytelling strategy is really hard and therefor there aren’t many examples or
It is so hard that everyone keeps the results to themselves.
So if you read this and have good examples on how content strategies have improved impressively with the use and insights of big data please let me know. We’ll start a discussion or even a platform!