Inside most organisations you’ll likely see a marketing team distill their customer base into a cluster of persona(s), which in their view is a core representative of a segment of their audience in a meaningful & believable form. These persona(s) are likely to be accurate or moreover a confirmation on a series of instincts that may or may not have supportive data to underpin their factoids. The issue with these personas is that they are likely to be a representative of the past, that is to say using them isn’t really about transplanting their behaviors into the future, instead its a snapshot in time of what happened at the time they were documented.
The definition of Ethnography basically distills to what i’d class is happening in the persona research space, especially when you commission design agencies to do the research. They are usually quite thorough in their research and often don’t miss a step in cataloging the series of data points needed in order to build a picture as to whom they are looking at and what the behavioral traits the persona(s) in question are likely to have in a range or clustered form.
Downside for UX people like myself is there’s no real jump off point for this type of data, as for me, it’s not really about whether or not “Max” is prone to water-sports or is in the age bracket of 25-35, i have really no need for excessive metadata. The challenge for me is to map these series of personas back into a timeline of graduation both in simplicity vs complexity but also around how their confidence levels are organised in a way that outlines the cold/hot spots within a feature(s) experience needs.
If you were to take a feature, break it down into its intended audience, complexity required to use it and lastly its overall metrics that help define its success/fail – well you’d likely end up with a lot of moving parts that don’t offer up any tangible qualitative value that helps you at the very least sniff out “what just happened”. What if you instead take the marketing personas, take a guesstimate around who you’re targeting, the features likely markers that trigger the metric and infer based on this data, the outcome – this would in turn be called confirmation bias.
There’s the uppercut with Persona(s) as you can easily set out to build on a solid foundation of healthy data but it’s only when you transfer or map these series of data points to the actual set of features & content within an experience that it starts to unravel and threads of its truisms get caught up in a lot of inferred guesstimates.
The root cause for this failure in qualitative data is simply due to the past being used to dictate the future, again remembering that at the time you interviewed and inspected your persona(s) it was based on either “what if” or questions that point to competitors or existing experiences that are already set in stone. Today and tomorrow you’re not keeping those experiences locked like that, in fact you’re probably looking to move the needle or innovate in a different direction which means you have small to large impact on their behavior, so thus the experiences can often involve dramatic or not so dramatic change(s). The only way to test or baseline the change is to have this continuous sampling that keeps checking & rechecking the data points in the hope of change makes itself prominent.
Problem – change isn’t always obvious, it can be subtle, the slightest introduction of a new variable or experience can often lead to adjustments that go unnoticed. I’ll cite an example in abstract form.
A respondent is asked to walk on a path through a forest from A to B. The respondent is asked to count how many “blue” objects are lined along the path, and the said respondent’s heart rate will be also monitored (also base-lined / zeroed out). Before the respondent takes off the testers place a stick that has similar shape to a coiled snake midway on the path.
The respondent is then asked to proceed on the journey, and they begin to count the blue objects and at the end of the path when they arrive, they give an accounting of their blue object findings. Their heart rate was normal in line with normal physical activity.
Respondents were less likely to notice the stick.
Next round of respondents are asked to the same, only this time the seed of fear is planted in their subconscious with “oh others noticed a snake a few hours ago along the path, be careful and if you see it sing out, it should be gone by now and we couldn’t find it earlier so just take note”.
Respondents begin the journey on the path, they notice the stick initially and a lot of messaging between the optics and brain are moving at lightning speed trying to decipher the pattern(s) needed to place a confirmation on “threat or non-threat” levels. Heart rate is spiking and eventually they realize its a stick and proceed, as they walk past the stick still keeping a very close eye and proximity buffer between the stick and them.
The point of that story is this, that with an introduction to the standard test of a new variable (fear) you’re able to affect the experience dramatically to the point where you’ve also touched on a primal instinct. In software that “stick” moment can be anything from moving the “start button” on a menu through to moving the way a tabular amount of data has been traditionally been displayed.
As a User Experience creator, we typically move the cheese a lot and it’s more to do with controlling change in our user(s) behavior (for the greater good). Persona(s) don’t measure that change, all they measure is what happened before you made the change. All you can do is create markers in the experience that help you map your initial persona baseline back to the new in the hopes it provides a bounty of data in which “change” is made obvious.
It doesn’t… sadly… it just doesn’t and so all we can do is keep focusing on the past behavioral patterns in the hope that new patterns emerge.
Persona(s) aren’t bad, they aren’t good, they are just a representative sample of something we knew yesterday that maybe still relevant today. The thing i do like about personas from marketing folks is this, it keeps everyone focused on behaviors they’d like to see tomorrow re-appear and that in the end is all i ever really needed.
Where do you want to head tomorrow?
Last example – NBC Olympics were streamed in 2009 to the entire US with every sport captured and made available. At the time everyone inferred that an average viewer would likely spend 2mins viewing time. In actuality they spent 20mins average viewing time and sent massive ripples in the TV/Movie industry in terms of the value of “online viewing”. If we had of asked candidates back then both as content publishers and consumers, they’d probably have told us data that they asserted to be relevant at the time. In this instance the Silverlight team were able to serve up HD video for the first time too many people online, and that’s what changed peoples experience. Today, its abnormal to even contemplate HD video streaming online as anything but an expected experience for “video” … 5 years ago, it didn’t exist. Personas compared to then and now are all dramatically different now, so while change can in some parts be slow… they can easily expedite to days, months as well as years.
I don’t dislike Persona’s, i just remain skeptical always of the data that fuels them – but thats my job.