Data analytics for storytelling, PRmoment-Weber Shandwick's Chai Talk breaks down the tools to use

What kind of data tools and skills do storytellers and marketeers. Speakers at Chai Talk Online stated that it was more important to understand what you need the data for, then worry about individual tools.

Jonny Bentwood, global head of Data & Analytics, Golin Global explains, "A lot of people think all we must buy this because everyone's got it. That's the wrong way of working. You need to think what are the scenarios I'm trying to fix.

Bentwood lists some of these scenarios, "Now, typically, within communication, there's about 10 main scenarios, it could be listening to understand what's happening. Audience intelligence to understand your, your clients brand and who's speaking, you're in the audience what they like and dislike, what are called clickstream. After they see content, what do people do? How do they search? What do they click on? What websites do they go back to? And repeat visit? What apps to the download?"

Bentwood further clarifies, "But the important thing is, I don't just start to say, Okay, let's go for this piece of tech, I think, well, the majority of my job is spent doing x. And therefore, these are the different tools that enable me to fit that scenario, I'll never be able to find one tech that does everything. But if I can find something that does 80% of what I'm looking for, I'm delighted with that. And the whole point of technology is to be smarter. So if I can find a job that will allow my team of analysts to be smarter and get on with their job as opposed to spending their time searching, that's great."

On the question of whether human insights can be accurate at scale, Joel Bacall, Cultural Researcher at Quilt.AI  said, "When we started out, we saw a need in the market to go beyond the likes of prescriptive surveys and focus groups.

So the really important thing to get to deep human insight is to be as resourceful as possible for us, because people will show different sides of themselves on Instagram. And then on Twitter, they'll show their troll side. On Reddit, they'll probably be a lot more honest. So the real trick is being as as resourceful as you can, in how you model and kind of analyse data, and in the sources you're choosing from. Otherwise, what you're going to get is somebody's kind of single faceted face on one platform, and then you're kind of left just piecing things together. 

Bacall added, "When you look at some of the more conventional research methods out there, I do believe you can get pretty close, especially when you use some of the more intimate platforms, people are very honest online. And in fact, online, you can be a lot more honest. So, in a short answer. I think it's quite effective, depending on what you need to understand."

to watch the entire podcast drop in here:

The episode also covered:

1) As a communicator client, what skills do you need in a data analyst for communication.

2) What tools to use for data storytelling.

3) The communication scenarios you need to identify for data analysts.

4) Confirmation bias in storytelling planning, how data can help you avoid it.