On 2009-02-26 11:15:00, 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.
All too often marketing departments thinks that database analysis is the first, last, and only step in segmenting the base of existing customers. In fact, identifying clusters of common behaviors is only the first activity you should undertake in creating a customer base segmentation.
Customer segmentation is not a piece of database work. It is a strategic or tactical business activity with with hard monetary benefits. Yes, you do need to do some data mining, and how clever you are in doing that is important, but that is not (or should not be) the primary activity.
Assuming that you are doing segmentation for the right reasons and you therefore know how to measure if you are successful, then what are the steps you need to make it happen?
We have found the following list useful:
This is not intended to suggest that you must always perform all the activities on the list. Sometimes you may only need some of them to achieve your objectives. But it is an ordered list so start at the top and work your way through until you have achieved (and measured!) your goals.
Let’s look at the steps in turn.
The first step is to take your customer data and analyze it to determine clusters of similar behavior. Much has been written on the subject elsewhere so I will not go into technical details here.
But from a business perspective it is essential that you know why you are segmenting so you know which variables you want the clusters to split. We discussed this in some detail in our previous article about the 3 things we want from customer segmentation.
You want the segments to be different on the variables that are important for your business. Otherwise the segments are not useful. All too often we see marketing departments commissioning data mining without specifying clearly how they want to use the resulting segments. “Find us some clusters” is not a project brief. The analysts will find you clusters without any problems, but they will not be commercially significant or deliver the bottom-line benefits that you need.
Sometimes the database clusters may be sufficient. Maybe you only want to improve the targeting of some existing campaigns. But if you want to consider developing new campaigns or new propositions then you need at least some business understanding of these customers. Not just what they do (step 1) but also who they are (step 2).
Usually you will to this by asking them. You take a small random sample and interview them about who they are. This is classic market research and there is plenty of available literature on the subject. You know what you need to do, just realize that your organization is probably not very good at it unless it is a specialized agency and it has a large budget (which is rarely cost-justified). But it doesn’t have to be perfect, it has to be useful. You can (and should!) almost always trial your campaigns first to see if they really deliver what you expect.
You’ll want to understand your organization’s desired position in the market so you can develop the right segments witht he right propositions. It is that vision thing again.
You need to have a vision for your company and where it is going. As a marketing manager, it is your responsibility to translate this into customer segments. Who are our customers. Who are our non-customers? Who are our customers that are not using all of our services or products? How do we target them better and how do we articulate the value that we as a company can add to their lives.
You need this when you want to develop new campaigns, new marketing messages, and new propositions.
This is segmentation as a strategic business tool. You’ll want to understand your organization’s desired position in the market so you can determine which segments to develop. Depending on how strategic the marketing department is considered with the company, and depending on the status and ambition of the marketing manager, this may be a step too far. But if you want to play at the top table this is what you do.
One company we worked with commissioned additional market research on their segments to measure them on two dimensions: lifetime value (x-axis) and how well the segment was aligned with the organization’s strategic direction as expressed in its vision (y-axis).
They then focused their attention on the segments to the right of the dotted line. That does not mean giving up on the others, but most of new campaigns and propositions target the strategic focus segments.
This picture proved to be an important tool in communicating at the CXO level what the company was about, where it was headed, what the challenges were, and where the opportunity lay. This is an extremely powerful tool.
There may not be enough growth opportunity in your strategic segments from the previous analysis. Or maybe you are responsible for developing new propositions. In that case you want to develop an needs-based segmentation not just of your customers but of the whole market.
You can start with your customers and understand their needs, especially the needs your company is not currently fulfilling. In fact, you should start by analyzing and questioning your customers since (a) it is much easier to sell to an existing customer and (2) you (probably) know who they are so they are easy to contact.
Eventually you will probably want to commission market research to identify unmet needs in the general population of potential customers. But this is expensive research and it is hard to make sure you develop the right offers and very expensive to bring them to market. So make sure you get the most of your existing customers.
We will talk more about this some other time. But as the marketing manager it is your responsibility to clearly demonstrate the business value of the segmentation that you are developing at each step in the process and to ensure organizational buy-in to use them as the reference for communication and activities. Segments are not just for marketing.
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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