How big is your toolbox? More analytics methods to try
Given the interim results of our recent survey, I thought it might be helpful to share some content; on less common analytics methods & applications.
It was striking, when looking at those early results, that certain uses of analytics methods were rarer than expected. So, using that as my initial challenge, I’ve been trawling the wealth of analytics blogs (to see who is sharing relevant content that might help).
Here are some of the under utilised methods & applications of analytics, that appear to deserve more of a hearing.
Tool 1: Customer Segmentation
In the same order as our survey, the first topic is consumer segmentation. Interim results showed less use of attitudinal & geo-demographic segmentations. This short post by Uzra Edery on Merkle’s blog reminds us of the benefits these can offer instead.
It’s become popular, in recent years, to consider that traditional approaches to segmentation should be replaced by a focus on ‘jobs the consumer needs to get done‘. This idea does have some merit and was popularised by articles published in Harvard Business Review. If you too have started down that route, of focussing on the job to be done not any concept of a stable customer segment, here is a great critique as to the pitfalls of such an approach; from leading researcher Kevin Clancy:
Useful cautions, I’m sure you’ll agree.
Tool 2: Descriptive Analytics
So, our next question (and results) related to descriptive analytics. Here, the under-utilized methods included univariate analysis, which was a surprise.
Here is a useful refresher, on outlier detection, using two different techniques. Handling outliers effectively can add real value to both data quality & your analysis hypothesis:
Hopefully, that was helpfully specific & something you or your team can action right now.
Tool 3: Behavioural Analytics
The next scores, from your interim results, covered behavioural analytics. Focussing more on the application of analytics, it was surprising to see no votes for applying behavioural analysis to product purchase order, channel switching or relationship networks. To help you make sense of the latter, here is a fascinating article from Peter Perera on the benefit of a Master Graph or ‘connectome‘ to explore your customer networks:
That was well worth a read & inspires me to try new approaches with clients in future.
Tool 4: Predictive Analytics
Last, in my search of relevant blog content, is that related to our last survey question. That was on predictive analytics. The surprise, in votes for this question (so far), is the lack of using machine learning & other forecasting techniques. Not as surprising, but still a missed opportunity, is no usage of survival analysis. In case you’ve not come across this econometric method previously, here is an introductory video from Venko Rao explaining the basics:
Which other Analytics Methods will you try
I hope those resources are helpful. Perhaps they will encourage you to expand your toolbox & try new analytics methods. What could you or your team do differently this week? Which of the above articles resonates with a business challenge you are facing right now?
Best wishes for an analytically productive week.