On 2009-02-26 08:16:00, Allan Engelhardt wrote in CYBAEA Journal:
Over the last years we have been doing a tremendous amount of customer segmentation work with the marketing departments in companies across a number of industries. We have experienced that there are many misconceptions about what “segmentation” really is, why we do it, and what we can expect to achieve from it.
Why are we doing customer segmentation? When we come in there is obviously a desire to “make more money”, and that is not a bad top-level ambition. But to translate that into specific set of activities you need take your thinking to the next level of understanding. And this is something we find that most organizations have failed to do.
Here is a list that we have found useful as a starter and which you can use as a base for your own work:
The important point about these is that they are all measurable. If we can measure it then we can build something that delivers it. Let’s look at each briefly in turn.
We want to use the segments in the business, so knowing that the segment is the fifth to eighth decile of the third principal component or some such is really not helpful. Knowing that it consists of plumbers and the like who work for themselves or in small teams and use their mobile telephones primarily on the job to keep in touch with their customers may be useful.
We will know that it is useful if it helps us develop new products, offers, or services (propositions) and if these are profitable and advance our business goals (increased market penetration, margin contribution, or whatever they may be).
The segmentation should help us to communicate more effectively with our customers. That usually means talking to them about the things we offer that may genuinely be interesting to them, and only about those things. Communication and dialog instead of spamming. We need more marketing campaigns and therefore campaign ideas, but these campaigns are smaller, better targeted, and deliver much higher returns.
We have introduced our Insights Driven Campaign Creation process to our clients with tremendous success. Insights Driven Campaign Creation is a process for systematically turning your data into insights and turning those insights into campaign ideas that generate real money. It takes the information from standard reports on customer Inflow, Base, Retention, and Outflow (IBRO), turns that into insights about the behavior of the customer base, and actions those insights through the whole marketing campaign process from concept to cash.
This should be a rather trivial point but in our experience it is not. Your segmentation should tell you something about your customers, and not just externalities.
We looked at a segmentation done by a very famous data analysis company. We were concerned about the methods and variables they used to determine the segments so we investigated their stability. We ran the segmentation for three consecutive 3-month periods and we looked to see how many were in the same segment from one period to the next. We knew that at least our high-value customers had been with us for long periods of time (more than 36 months) and so we expected that most users (say, much more than 50%) would be in the same segment from one quarter to the next.
What we found was that typically ⅓ of the customers in a segment fell into the same segment the next quarter. That is a truly awful segmentation for this client with a large, stable, long tenured customer base! Looking at the detailed technical definition of the segments it was not hard to see why it was so bad: it was extremely sensitive to a few variable with a very irregular usage and a usage that was heavily influenced by our marketing campaigns. So the segmentation primarily told us if our customers had been the target of our own marketing!
Another point that should be trivial but most emphatically is not in many of the organizations we encounter. We find these pre-existing segmentations with fancy titles and superficially engaging descriptions, but when we look at the things that actually matter to the business we find no significant differences between the segments!
Remember that you actually want to do something with your segments. If your company offers subscription based services and all segments have the same churn profile then the segmentation is not really going to help you manage your churn problem. If all segments have the same usage profile, how are you going to use the segmentation to stimulate usage and increase revenues? If all segments have the same distribution of preferences for receiving communications by post, telephone, and email, how will the segmentation help you manage your marketing communications better?
This is probably the subject of another detailed post to consider when you should use what kind of segmentation approach, but for now at least consider the things that are important to the operations of your business in the next 6-12 months and see if your segments actually have very significantly different distributions on these attributes.
If churn is important to you, then you want loyal and opportunistic customers in different segments. You want to be able to look at what customers are valuing so you can offer them the best incentive to stay (and develop a compelling proposition for them if you do not already have one). So you probably should have people who value price more than service in a different segment from those whose prioritize convenience over costs. You undoubtedly want different profitability in different segments so you can manage then differently (e.g. move low-margin customers to self-service channels). And so forth: the details will vary a little with your industry but you get the idea. Do not assume that your segments have different distributions of the things you care about: measure it.
On 2010-03-08 14:46:00, Allan Engelhardt wrote in CYBAEA Data and Analysis:
I needed a fast way of eliminating observed values with zero variance from large data sets using the R statistical computing and analysis platform. In other words, I want to find the columns in a data frame that has zero variance. And as fast as possible, because my data sets are large, many, and changing fast. The final result surprised me a little.
Read more (~501 words).
On 2009-08-17 09:18:00, Allan Engelhardt wrote in CYBAEA Journal:
We knew the potential existed already, of course. Mobile devices in the USA generates some 600 billion transactions per day, each tagged with the location and time. Jeff Jonas: Every call, text message, email and data transfer handled by your mobile device creates a transaction with your space-time coordinate[...].
The mobile operators have this data, of course. We all know this (especially here where we have been using some of it for social network analysis). No real surprises here, except perhaps in the volumes.
But did you know that the operators are sharing your data? What is new, at least to me, is that this data is being provided to third parties that are leveraging specially designed analytics to make sense of our space-time-travel data.
Read more (~449 words, 1 comments).
On 2009-07-27 19:38:00, Allan Engelhardt wrote in CYBAEA Data and Analysis:
O'Reilly's recent publication Beautiful Data has a chapter by Jeff Jonas which is enough reason in itself for me to recommend it. The chapter, Data Finds Data, is also available as a PDF download.
Read more (~66 words).
On 2009-07-22 13:37:00, Allan Engelhardt wrote in CYBAEA Data and Analysis:
This is by far the best description of why traditional parallel databases (like Teradata, Greenplum et al.) is a evolutionary dead end. But much more than a theoretical discussion, they have built a solution which they call HadoopDB. It is based on Hadoop, PostgreSQL, and Hive and is completely Open Source. Alternative, column-based, backends to PostgreSQL are being implemented now. Read: Announcing release of HadoopDB.
Read more (~83 words).
On 2009-07-22 06:59:00, Allan Engelhardt wrote in CYBAEA Journal:
The nice people at Velocity has released The B2B Content Marketing Workbook. It is behind a registration wall which means we wouldn’t normally recommend it but you can just type junk in the fields if you are not comfortable with giving your personal details to a marketing agency. (Think about it....) If you are relatively new in the B2B world, say having joined a professional services or consulting organization, you may find this one useful.
Read more (~263 words).
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