By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData Collective
  • Analytics
    AnalyticsShow More
    data science anayst
    Growing Demand for Data Science & Data Analyst Roles
    6 Min Read
    predictive analytics in dropshipping
    Predictive Analytics Helps New Dropshipping Businesses Thrive
    12 Min Read
    data-driven approach in healthcare
    The Importance of Data-Driven Approaches to Improving Healthcare in Rural Areas
    6 Min Read
    analytics for tax compliance
    Analytics Changes the Calculus of Business Tax Compliance
    8 Min Read
    big data analytics in gaming
    The Role of Big Data Analytics in Gaming
    10 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-23 SmartData Collective. All Rights Reserved.
Reading: The opportunity for opportunity analytics
Share
Notification Show More
Latest News
ai in automotive industry
AI Is Changing the Automotive Industry Forever
Artificial Intelligence
SMEs Use AI-Driven Financial Software for Greater Efficiency
Artificial Intelligence
data security in big data age
6 Reasons to Boost Data Security Plan in the Age of Big Data
Big Data
data science anayst
Growing Demand for Data Science & Data Analyst Roles
Data Science
ai software development
Key Strategies to Develop AI Software Cost-Effectively
Artificial Intelligence
Aa
SmartData Collective
Aa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Business Intelligence > CRM > The opportunity for opportunity analytics
CRMData MiningExclusivePredictive Analytics

The opportunity for opportunity analytics

JamesTaylor
Last updated: 2010/06/16 at 1:04 PM
JamesTaylor
6 Min Read
SHARE

Some time ago Neil Raden and I did some research on analytics. It was clear as we did this that there were two main threads of analytic use in companies – risk analytics and opportunity analytics. I blogged before on the use of analytics to manage risk one risk at a time so I thought I would write about opportunity analytics.

Risk analytics are about using historical data to make a prediction about the risk of a particular customer, a particular transaction going or being bad in some way. Risk analytics help you estimate and account for the downside risk of a decision – if I get this wrong, what’s the worst that could happen? Opportunity analytics, in contrast, are focused on estimating the upside – the opportunity.

I regularly write about the importance of focusing analytics on operational decisions and their role as a corporate asset. If we think about these kinds of operational decisions then opportunity analytics come to bear on customer-centric decisions like cross-sell and up-sell decisions, or decisions to retain a customer who has called to cancel. Opportunity analytics are used to answer questions like how profitable might this customer be in the …

More Read

data-driven approach in healthcare

The Importance of Data-Driven Approaches to Improving Healthcare in Rural Areas

Data Mining Technology Helps Online Brands Optimize Their Branding
What Role Does Big Data Have on the Deep Web?
How Data Cleansing Can Make or Break Your Business Analytics
Accessible Business Analytics Set to Be a Boon for Small Businesses

Some time ago Neil Raden and I did some research on analytics. It was clear
as we did this that there were two main threads of analytic use in companies –
risk analytics and opportunity analytics. I blogged before on the use of analytics to manage risk one
risk at a time
so I thought I would write about opportunity analytics.

Risk analytics are about using historical data to make a prediction about the
risk of a particular customer, a particular transaction going or being bad in
some way. Risk analytics help you estimate and account for the downside risk of
a decision – if I get this wrong, what’s the worst that could happen?
Opportunity analytics, in contrast, are focused on estimating the upside – the
opportunity.

I regularly write about the importance of focusing analytics on operational decisions and their
role as a corporate asset
. If we think about these kinds of operational
decisions then opportunity analytics come to bear on customer-centric decisions
like cross-sell and up-sell decisions, or decisions to retain a customer who has
called to cancel. Opportunity analytics are used to answer questions like how
profitable might this customer be in the future, how profitable might they be if
they accept this offer, which offer is most likely to attract them? Opportunity
analytics predict response, opportunity, potential. They predict the propensity
of customers to buy products, the likely profitability of a customer if they buy
a particular product, which offer is likely to be most appealing to a prospect.

Unlike risk decisions, there is often little difference between good and bad
opportunity-centric decisions. If a company gets such a decision right, they
might increase the profitability of a customer, or retain a customer into the
future. They have little exposure if they make a bad decision. While, in theory,
a bad cross-sell offer might so annoy a customer that they abandon their primary
purchase, this kind of negative impact is highly unlikely. With opportunity
analytics, companies are trying to maximize their upside not manage their
downside. A poorly made risk-centric decision can result in fraud, bad debts,
theft. A poorly made opportunity-centric decision simply wastes an opportunity
to increase profitability.

This difference changes the cost justification of analytics. Risk decisions
have been the more common use of data mining and predictive analytics
historically because the time, hardware and skills involved could be easily
justified by avoiding the potentially huge downside. Opportunity analytics are
growing fast, however, as the tools get easier to use and the cost of hardware
and data management continue to drop precipitously. With new tools, and more
readily available experience, squeezing extra profit out of these decisions with
analytics is becoming more and more worthwhile. The embedding of analytics into
decision-making systems for marketing and CRM is increasingly common. Because
opportunity analytics are targeting small improvements, they must change rapidly
to take advantage of competitive and market circumstances. This drives an
ever-increasing use of adaptive analytic models, those that use automated
experimentation to constantly adapt and refine an analytic model.

Opportunity analytics may not have the pay off that risk analytics do but
companies should still be thinking about using their customer data to maximize
the value of every opportunity.

TAGGED: analytics, business analytics, crm, data mining, operational decisions, propensity models
JamesTaylor June 16, 2010
Share this Article
Facebook Twitter Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

ai in automotive industry
AI Is Changing the Automotive Industry Forever
Artificial Intelligence
SMEs Use AI-Driven Financial Software for Greater Efficiency
Artificial Intelligence
data security in big data age
6 Reasons to Boost Data Security Plan in the Age of Big Data
Big Data
data science anayst
Growing Demand for Data Science & Data Analyst Roles
Data Science

Stay Connected

1.2k Followers Like
33.7k Followers Follow
222 Followers Pin

You Might also Like

data-driven approach in healthcare
Analytics

The Importance of Data-Driven Approaches to Improving Healthcare in Rural Areas

6 Min Read
data mining
Data Mining

Data Mining Technology Helps Online Brands Optimize Their Branding

7 Min Read
big data technology has helped improve the state of both the deep web and dark web
Big Data

What Role Does Big Data Have on the Deep Web?

8 Min Read
data cleansing tips for business analytics
Big Data

How Data Cleansing Can Make or Break Your Business Analytics

9 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

ai in ecommerce
Artificial Intelligence for eCommerce: A Closer Look
Artificial Intelligence
ai is improving the safety of cars
From Bolts to Bots: How AI Is Fortifying the Automotive Industry
Artificial Intelligence

Quick Link

  • About
  • Contact
  • Privacy
Follow US

© 2008-23 SmartData Collective. All Rights Reserved.

Removed from reading list

Undo
Go to mobile version
Welcome Back!

Sign in to your account

Lost your password?