Product Management: 5 Ways statistics can help product managers

Statistics was never one my favorite topics but I was reintroduced to it when I went back to school  and now I cannot stop talking about. It also helps that BigData is now affordable to a lot people, cheaply I might add and the fact the predictive analytics is “in” thing right now.
                          I usually get a chance to talk to few new product managers and I am always surprised how little value they give to statistics in general. Yes doing regression analysis on variables may not sound cool but if you master a few techniques you can actually go far. In this blog I document 5 areas where a little bit of statistics can help

Segmentation

If you are product marketer or product manager this is one activity you have to do. Segmentation is critical activity even in the context of a startup.  If you need to create a new niche in the marketplace or focus on a particular type of client archetype or experience this is key. One statistical technique you can use effectively is regression analysis to see which independent variables influence the dependent variable. If you don’t know what I am talking about I would recommend the following books as a great primer on statistics
Heads first Statistics or Statistics in a nutshell  both book happen to be from O’Reilly media because they are actually useful books

Value Analysis  

Every once in a while you are asked what is value or how do you know what is valuable to your client base. In statistics there is a tool you can use called Conjoint Analysis.  Conjoint analysis let you look at different aspects or features and figure out how to maximize and identify the right features and function to deliver by looking at the data (which you should have after meeting your clients). One of the best explanations of Conjoint Analysis is given in the book Marketing Metrics. Conjoint Analysis is very powerful tool and can also give you broad insight into managing your requirements better for the various products you bring to market

 

Analyzing trends 

Trends are the anathema of product managers especially if  the trend has already taken a foothold in the marketplace.  Obviously the most simple way to spot a trend is a to plot on a graph and see the trend (if you are doing that, it means the trend has already taken hold and you are late in the game). In order to stay ahead of trend and if you are constantly engaging with your clients, you should be able to see what variables are important to them. There are some tools like binomial distribution that can help in identify a trend manifesting in a sample survey you with your client base. Binomial distribution can always provide a good proxy for a full blown research effort but they can offer a quick an dirty way to get an idea of what is going on.

Client Satisfaction analysis 

I am big fan of Pareto Charts or most commonly known at the 80/20 rule. You can  identify the top issues that matter to clients and focus your efforts in remediating those top concerns in your overall user experience. There are plenty of credible examples of how to develop a pareto chart but the simplest explanation that I have read is on a blog written by blogger Duncan Haughey. Please check out his blog at the following URL:  http://goo.gl/4E2VV

Quality

The definitive book in this context is Katrina Maxwell’s book called Applied Statistics for Software Managers 
There simple regression analysis techniques that Katrina highlights that can be used not only by software managers but these techniques are applicable to anyone launching a new product whether it be software or hardware manufacturing
As you can statistics can be applied very effectively in product management activities and just like everything you can provide context. I do want to emphasize just looking at raw data would not do, you actually need to get out of the office and talk to clients and get the data.  You can use other 3rd party research to do the same.  The emphasis on using statistics will start to happen more and more in every one’s jobs as Big Data infrastructure continues to be accessible to people.

You can contact me @ kkanakas on twitter with your comments

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