In recent years there's been a quiet shift within journalism. Amidst a widespread tightening of the belts within editorial teams there is one corner which is still growing: data journalism. It's just as well because this year more than any before has highlighted the need - and appetite - for data-driven stories. The requirement for part data scientist, part newshound to decipher the numbers behind the biggest story in a generation is a completely unique set of skills - but skills that are highly sought after.
It's created an opportunity in public relations too. For the first time a data scientist like myself can have one to one conversations with data journalists. We can work in partnership with them to tell stories from our clients. But how does it work? What do we need in order to create a story that resonates with journalists?
Where should you get your data?
The basics of data story-telling: headline first, data second
You've got to capture a journalist's attention within a sentence or two - they don't have time to read every pitch they're sent. Successful data storytelling still needs the fundamental tenants of public relations - present your best stat up front and structure your press release in layers, each building on the previous.
A great example is our work on prescription data with Exasol. We had so many possible storylines, we had to focus on the best.
Don't mould the data to fit your narrative, find the story within
It's a common mistake to shoehorn your message into data- you see it most often with survey results. Journalists smell it a mile away. Don't despair if the data doesn't fit your carefully crafted plan, take a step back and think about the results and how they impact your client. The most unexpected results sometimes lead to the best press releases because you'll tell the journalist something they don't know. And that is gold dust.
Visualise your story
The easier the data is to digest, the better. Consumers don’t want to root around an article for their key take-aways, so heatmaps, infographics, and visual statistics are a great accompaniment to a story.
Journalists, too, like to understand the gist of the information as quickly as possible, so you’ll also increase the chance that your story and visual will be included in a target publication.
Bigger is better, and combining datasets creates something magical
The holy grail of data storytelling is a huge – national, if possible – dataset. The beauty of analysing such a large source of information is that your results tell the true story, not a small representation.
Our analysis, for example, of England’s latest census data accurately revealed localities that the highest ratio of over 80s – giving us a story and heatmap with unquestionable findings.
While big datasets such as these can be hard to obtain and difficult to analyse, PRs and organisations should always strive for this. Small data sets have value too – for example consumer surveys – but try to find additional information to corroborate what you’re saying. The sum of two independent sources of data is bigger than its parts.
If you'd like to discuss the best data storytelling approach for your organisations, get in touch: Hello@resonancecrowd.com