CRM & Marketing Top Fields for Data Miners


Customer relationship management and marketing remain the top fields for data miners, according to a recent survey conducted by Rexer Analytics, a Boston analytics and CRM consulting firm.

Forty-one percent of data mining professionals polled for Rexer's 4th Annual Data Miner Survey reported working in the CRM/marketing field. Rexer said 735 data miners from 60 countries participated in its 50-question survey, conducted in early 2010.

CRM/marketing has remained the top field of respondents since the polling began four years ago. Other sectors employing large numbers of data miners include financial, academic, insurance, and telecommunications.

Source: 2011 Data Miner Survey, Rexer Analytics
Source: 2011 Data Miner Survey, Rexer Analytics

Other conclusions from the survey:

  • Most data miners use decision trees, regression, and cluster analysis, though in the latest survey, 22 percent of respondents reported using ensemble models, which made their first appearance in the Rexer survey.
  • Data miners tend to prefer models with fewer variables. A third of the respondents reported building final models with 10 or fewer variables, while only 28 percent built models with more than 45 variables.
  • The majority of data miners reported using open-source tools and working on laptops or desktops with data stored locally.
  • The biggest challenges for data miners remain dirty and difficult-to-access data, as well as the ability to explain their work to others effectively.
  • Data quality and analytics capabilities continue to prove problematic. Only 13 percent of data miners rated their company’s analytical capabilities as excellent, and only 8 percent had confidence in the strength of company data.

Despite the challenges, the survey clearly shows an increase in the demand for data mining, a cause for general optimism in the field. More than 75 percent of data miners anticipate more projects at their companies in the near future. These are over and above increases reported in the previous survey.

In addition, Rexer said it has measured the use of the term “data mining” in a variety of online job ads and found strong requirements.

Have you seen an increase in the number of data mining projects and a rise in skill requirements in your company or organization? What fields do you believe make the greatest use of data mining today?

Shawn Hessinger, Community Editor

Shawn Hessinger is a community manager, blogger, social media and tech enthusiast, journalist, and entrepreneur based in Northeastern Pennsylvania. He serves as community manager and blogger for BizSugar.com, a business news and information Website, and contributes regularly to the online business news source, Small Business Trends. He is the founder of PostRanger.com, an online content and media community, and has provided blogging and social media services and consulting for companies all over the world. He researches and writes on a variety of business, Internet-related, and other tech topics including business intelligence and analytics. He is also keenly interested in computer-aided data management as it relates to his various online ventures. A newspaper journalist with more than 11 years experience as a reporter and then managing editor, Shawn began blogging in 2006 and now provides a variety of consulting and outsourcing services in Search Engine Optimization, Web development, and online marketing to companies large and small. He is a strong advocate for the use of BI and related computer data management in business decision making, whether using software as a service (SaaS), cloud, or other applications, and in the opportunity these technologies provide to transform small startups and larger established businesses alike.

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Re: Top Fields for Data Miners
  • 11/22/2011 3:48:28 PM
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@ Dataguy - Thanks, you make some really great points.  There really is a great divide in the work force. 

Re: Top Fields for Data Miners
  • 11/22/2011 3:35:33 PM

@Seth: from my experience, dirty and difficult data is a problem because it is difficult to convince stakeholders of the importance of cleaning it up. So we either publish untrustworthy results quickly, or we anger those who pay our salaries by taking too long. Tools are good, but this is time consuming and expensive and not always seen as valuable.

On the other hand, explaining the work effectively includes the above conundrum but goes far beyond it. There is a tremendously deep and wide set of significantly complex science involved in data analytics, but explaining this to anyone at all is challenging.  It is hard enough to find qualified people to do the work competently. If you want them to communicate effectively also, you're reducing your talent pool even further.

Re: Top Fields for Data Miners
  • 11/22/2011 3:07:50 PM
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I have definitely seen an increase in the requirments for analytics in many job postings and like the chart says, in marketing. Like others, I am surprised that CRM/marketing is number one, but I guess that makes sense as it's more profitible to retain and market to a current customer. 

I would like to know more about the reasons behind "The biggest challenges for data miners remain dirty and difficult-to-access data, as well as the ability to explain their work to others effectively."   Is it the lack of tools or the lack of understanding? 

Top Field for Data Miners - the CRM/Marketing set
  • 11/13/2011 7:00:09 AM
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One thought about this - I can see how data miners would be mostly into the CRM/Marketing segment. It's easily identifiable by a manager to budget with so much interest in targeting customers better.  

Also there are more CRMs incorporating social media, so certainly there is a need to manage highly continuous information.

 

 

Re: Top Fields for Data Miners
  • 11/13/2011 6:55:40 AM
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Shawn,

What does internet-based mean in the survey? Are they cloud services which are non marketing related? I was just surprised by the CRM/Marketing distiction from internet-based.

 

Thanks for any insight. 

Re: Academics is #3?
  • 11/10/2011 11:41:40 PM
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Hi Cordell,

Yes, especially insurance given the potential importance of data mining in risk assessment. But I have to honestly say that I was also surprised by the distance that medical and Internet are behind, two fields where it is obvious to see the benefits of data mining.

Re: Data Mining: Real Challenges Ahead
  • 11/10/2011 11:38:27 PM
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Cordell, Thanks for the clarification of standard practice on credit scores. I see your point that it is not the variable in itself that is the issue, it whether is has any significant meaning to the question(s) at hand.

Interesting insight.

Academics is #3?
  • 11/10/2011 10:33:31 PM
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Surprised to see academics ahead of insurance and telecom.

Re: Top Fields for Data Miners
  • 11/10/2011 10:30:38 PM
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@dataguy.   Certainly terms get jumbled a lot.  I recall talking to a lot of people about "analytics" which took to mean predictive analytics and they were typically talking about reporting or BI.  Some really confusing conversations!  Nevermind people passing off analytics that aren't.  See our discussion on sentiment analysis that's just keyword search.

Re: Data Mining: Real Challenges Ahead
  • 11/10/2011 10:21:46 PM
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@louis.  I can confirm that most credit scoring models don't have more than about 15 characteristics though they may start with hundreds.  It's not the management of variables that's the problem it's that after about 15, new variables add little to the model.  Of course credit scores have been around for a long time and over the years the strongest variables are fairly well known so there's a good starting point already.

I totally agree about communication.  If findings can't be communicated accurately then what's the point!  This is an ongoing skill set deficit.  Tough to find analysts that are good communicators.  It's a stereotype I know but it seem to be directionally correct at least.

 

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