Join Doug Rose for an in-depth discussion in this video Weave a story together, part of Learning Data Science: Tell Stories With Data.
- So, now you've seen that you can use five different threads to spin the yarn of your story. Let's take a step back and see the different types of ways you can use it to rope in your audience. A story is not anything you might say. A television commercial isn't usually a story. Saying that I waited in a long line to get movie tickets isn't a story. That doesn't mean that these can't become stories. Remember that stories help an audience connect to some larger meaning.
There's no larger meaning in the fact that I waited in a long line to get tickets. I wasn't struggling to find meaning, I was simply trying to see the new Star Wars movie. There are different story helpers you can use to weave together your larger story. These five helpers are particularly useful when you're trying to explain data science concepts. These are anecdotes, case studies, examples, scenarios, and vignettes. Let's start with anecdotes.
Anecdotes are usually the most useful at the start of your story. They're a short, personal account of something that's relevant to your larger topic. The key here is short and relevant. You want your anecdote to be long enough to be interesting, but short enough to not distract from your story. Let's say that you're telling a story about why so many of your customers are abandoning their purchase just before they checkout. You might start out by telling a small anecdote about the times that you left the store without purchasing anything.
You might say that it was caused by the stress of making the decision. Then you could connect that to the story of why so many customers might be abandoning their purchase. Another great helper is a case study. A case study is when you relay a small problem and how it led to a solution. A case study is really helpful when you're trying to present a story with a possible solution. It's generally tied to a similar problem you've solved in the past. It's really easy to invoke reactions from people with a case study, especially if they have experience with similar situations.
You could talk about a past data science challenge and the solution that solved the problem. Let's say that you want to use a case study to figure out why customers are abandoning their purchase. You could start off by telling that when the team helped redesign the website, there was a small drop in purchases. So, the team went back and simplified the website and the purchases went back up. Then you could relay the case study to a larger story where you suggest that the checkout process is too complex.
The third story helper is examples. Examples are similar to case studies, except they don't necessarily lay out the challenge and the solution. You want to use examples when you're trying to justify some part of your larger story. Maybe you'll point out that several other companies are trying to simplify online purchases, so the story you're about to hear is not necessarily unusual, or isolated to your own organization. The fourth type of story helper is scenarios. A scenario is when you lay out a series of events and ask your audience to consider or predict each outcome.
Scenarios are effective because they're hypothetical. They get ideas out in the open. Unfortunately, this technique is not very widely used. That's too bad, because it's often a great way to get your audience thinking about the future. A lot of storytellers think scenarios sound like children's stories. That's why it's important to make sure that your scenario is not too simple. A scenario usually works best at the start of your story. It should also be told in the third person. You don't want the scenario to sound like a personal anecdote.
You could start out your story by saying imagine that our customer has five minutes to find their product. After three minutes, they've found their product, and they put it in their shopping cart. Just as they're about to check out, they see four other products they also want to buy. They don't have the money for all five, so what are they going to do? This scenario should help your audience think about the key questions. The final story helper is a vignette. A vignette is like a little scene. It's almost like a tiny little movie. They're usually told in the third person.
A good vignette will capture the audience's attention. You might want to open up your story with a small vignette of your frustrated customer. Something like a customer saying "why do they always redesign the website? "I just figured out where everything was "from the last redesign." These five story helpers will help you engage your audience. Remember that these are not stories in themselves. They can help you, but they don't replace your larger story and its meaning.
- Structuring a data science story
- Defining plot, conflict, and details
- Going beyond reporting
- Knowing your audience
- Working with data
- Introducing visuals
- Eliminating distractions
- Incorporating metaphors
- Motivating the audience
- Avoiding pitfalls