If there is one thing the universe agrees on, it is that you should just provide data… You should provide INSIGHTS!!!
In the 807,150 (!) words I’ve written on this blog thus far, at least 400,000 have been dedicated to helping you find insights.
In posts about advanced segmentation, in posts about how to build strategic dashboards that don’t suck, in encouraging you to reimagine how you pick metrics to obsess about using the magnificent Impact Matrix, and on and on and on.
Go for insights!
In time, I've come to hate the word insights.
In our world – marketing research and analytics – that word has come to represent data puking.
It has come to represent telling people, with dozens of reports or eighty slides, that water is wet.
I've observed, during my work across the world, when we deliver insights, we mostly deliver to our audiences things in-sight – things they can already see!
As in, the blue line is 20% above the red line. I CAN SEE THAT! Or, life-time value of California purchasers is 3x when compared to those who reside in Georgia. Oh, please, I can also see that on the table with my eyes.
This, unsurprisingly, ends up being a massive waste of your incredible talent, and an insult to the intelligence of our audience (the people who pay your salary).
The last time I changed jobs, I wanted to change the aspiration of what our talented team and I should shoot for.
Instead of insights, I coined a new phrase for a new start: Out Of Sights!
Our aim would be to provide out-of-sights – things people can't see.
As in, the blue line is 20% above the red line because our biggest competitor launched a new product and priced it 10% below our best product. You are explaining the performance. BOOM!
It is such a small play on words. But, my goal was to provide each peer this pause-worthy moment when they bring the results of their work: OMG, is this really an out-of-sight?
The influence on our culture, on our actions, on our audacity was profoundly dramatic. Turns out, cultural transformations can start with a word. :)
Every time we were done with our analysis, we now had a higher standard to shoot for. We challenged each other by saying, are you sure that is an out-of-sight?
Four Attributes of Out-of-Sights.
While we got the spirit right away, scaling understanding requires a common language we could share.
Our team was up to the challenge, and off to the whiteboard we went to systematically approach the problem of creating a simple framework to identify what’s an out-of-site.
This is when I feel super blessed to work with such smart people. At the end of a couple of whiteboard sessions, we came up with our criterion that every out-of-sight had to meet…
1. Novel: New and surprising.
Is this truly new (data, source, research type)? If it has been provided before, what was the impact? Why do we need to provide it again?
What do we have here that we, or the audience, never knew before? Is this just the result of a fishing expedition?
Could the audience – your peers, boss, public – get this data from anyone else? What makes you so special if you provide it?
Novel is a tough, high, standard. It eliminated 90% of the data puking and made work so much fun for the Analyst.
2. Actionable: Expressed with a clear implication for the audience.
What could the audience do as a result of your findings?
What specific current or future campaigns, activities, internal or external business strategies are being influenced by the out-of-sight?
If you don't have an identified what to do, whose job is it? Does that person know it is their job to figure out what to do based on the data?
Would it be wiser to work with your peers who make decisions, who understand strategy, to come up with actions to take based on data before you call your data actionable?
Actionable is the single most crucial element if you deal with data. It requires knowledge well beyond the data – requiring an understanding of the business, a robust set of cross-functional relationships, and an ability to persuasively influence.
3. Credible: Data source – tool, people, entity – is respected by the audience.
What steps have you taken to identify the soundness of the source?
Do you understand the limitations of how the data is collected? Have you noted the assumptions for sharing with the audience?
Does it pass the foundational 24 filters of skepticism? For example, is it simply a correlation or have you teased out causality? [Premium subscribers see: TMAI #298: Smart Statistical Significance Reporting.]
Is there room for an alternative explanation? If so, find it.
I have the following ask of the analytics team:
We have to be the biggest enemy of our work. We have to ask hard questions. We have to poke at every corner. We have to seek alternative explanations. It seems harsh, but we are probably the most analytically savvy individuals who will look at this data. After that, it is our business peers who will typically have less analytical knowledge than us. So. Be our work’s best enemy. It builds credibility.
Credibility is very helpful. Be the biggest enemy of your analytical work.
4. Relative: Expressed in context.
Is the out-of-sight expressed so that there's no doubt as magnitude or urgency?
Context derived from:
and so much more, including benchmarks
[Premium members also see TMAI #263.]
The relative attribute helps speed up understanding. It ensures your out of sights really sink in.
Every finding from your rigorous data analysis has to meet the above-mentioned four attributes – N-A-C-R –, before it can be called an out-of-sight.
When you set yourself on the quest for out-of-sights, you set a standard for yourself, for your team, for your data, that will result in everything you discover being meaningful and material.
Your Out-of-Sights Jumpstart Guide.
You will find your own way to discovering out-of-sights for your company. Still, I want to help a little bit. I would like to give you a list of questions that will increase chances that you will bump into more out-of-sights.
Questions provide context, questions lead to relationships, questions expand your horizon, questions enhance your business savvy, and in doing all that, and more, questions provide that magical missing ingredient: Purpose.
And, knowing purpose increases the chances you’ll discover out-of-sights that qualify as such with all four attributes: Novel, Actionable, Credible, and Relative.
Here’s a helpful list:
1. How can I improve revenue by 15 percent in the next three months from our website?
2. What are the most productive inbound traffic streams, and which sources are we missing?
3. Have we become better at allowing our customers to solve their problems via self-help on the website, rather than our customers feeling like they have to call us?
4. What is the impact of our website on our phone channel?
5. How can I increase the number of customer evangelists by leveraging our website?
6. What are the most influential buckets of content on our website?
7. If we could only do one thing to increase revenue on our website, what would it be?
8. What is the incremental impact of our display ad campaigns?
9. Are we building brand value via activity on our website?
10. Do fully featured trials or interactive demos work better on the website?
11. What are the top five problems our customers face across our digital channels?
12. What is the cost for us to earn $1.00 on our website?
13. What is the effect of our mobile paid search strategy on our offline sales?
14. How much does the lifetime value of a customer increase if we can convert them into a 7-day active user of our mobile app?
15. What would the impact on unaided recall of our brand if we shut down all our Facebook efforts?
Not an exhaustive list by any means, just a representation of the kinds of questions I strongly believe your talent and emphatically answer.
You answer these questions not with insights (things people can already see), but with out-of-sights (things people can’t see).
When you check if the results of your analysis pass against all four N-A-C-R attributes, chances are 90% of what you do today needs to die. Because telling people water is wet, week after week, results in only sadness.
Don't deliver sadness, deliver meaning and impact. Make your job fun!
What percentage of your team's insights this week met all four of the out-of-sights criterion?
The post Winning With Data: Say No To Insights, Yes To Out-of-sights! appeared first on Occam's Razor by Avinash Kaushik.