Predictive Analytics On Demand for B2B Marketers: The Benefits, Challenges and Pitfalls

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Predictive Analytics On Demand for B2B Marketers
The Benefits, Challenges and Pitfalls
Feb 2008 Dr. Ian J. Scott, VP-Consulting
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On-Demand Predictive Analytics for B2B Marketing

• What is it?
• Why is it Happening?
• What is the USP/Value Prop?
• Examples
• What are the Benefits?
• What are the Risks?
• What To Look For ltFeaturesgt?

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What is it

• Predictive Analytics
• Not old school reporting predictions about
  future outcomes and customer behaviors
• On-Demand
• Been going on for a long time but more than
  traditional outsourcing, list management etc.
• Confluence of technology and people capabilities
• Pressure to expand access across all types of
  users, technical and business
• More sophisticated from capabilities and
  deployment POV closer to real time
• For B2B Marketing
• Over stretched consumers and consolidation at
  top of enterprise market make this the market
  everyone wants to be in everyone wants a piece

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Why is it Happening

• Industry Trends
• Buyer Marketplace
• Looking to leverage data more internal resource
  constraints and challenges (pilots problem)
  looking for partners to add value etc
• Enterprise Paradigm (Pilots) vs SME Buyer Market
• Vendor Marketplace
• Consolidation Commoditization Differentiation
• Same paradigm huge providers (eg Acxiom) etc
  versus SME Vendor market

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USP / Value Prop

• Usability
• Capabilities, services and people Designed for
  and delivering to the needs of the segment (SME)
  not gear head stuff
• Affordability
• TCO way lower even looking at sw only leaving
  aside the hardware and people savings
• Scalability
• Using Internet platforms and technologies
• Flexibility
• Platform for delivering a variety of analytics
  capabilities segmentation, profiling, response
  models, cross-sell, up-sell, sales targeting
  lists, customer value analytics etc.

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Case Studies

• KnowledgeSEEKER for Salesforce.com
• Enhancing the original on-demand solution with
  advanced analytics
• FundGUARD for Mutual Funds Wealth Management
• B2B Market Sizing

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Case Study 1Angoss KnowledgeSEEKER for
Salesforce.com
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Angoss KnowledgeSEEKER for Salesforce.com
Questions Angoss Answers with Confidence

• Which Leads will close, and why
• Which Opportunities will close, when and for how
  much
• Which Accounts have untapped spend potential, and
  when
• What are the predictive drivers of Wins and
  Losses that drive these outcomes
• Which Tasks and Activities have most impact on
  positive sales outcomes, and when should we use
  them

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Angoss KnowledgeSEEKER for Salesforce.com
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Business Value Benefits for Users
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Case Study 2FundGUARD

• FundGUARD is a predictive, intelligent call
  rotation system created for the resource
  constrained mutual fund distribution industry.
• Used by both inside and outside wholesalers,
  FundGUARD delivers monthly lists of highly
  targeted "predictive tickets" that require
  immediate sales coverage.
• Immediate sales coverage is important since each
  advisor on the rotation schedule is most likely
  to be buying (or redeeming) more than a set
  minimum amount of product within 30 days.
• The key to increasing the size of, or retaining a
  predictive ticket, depends on the rep's ability
  to cover the advisor prior to the transaction
  date. It is 'just-in-time selling"

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How FundGUARD Works

• Client provides Angoss with monthly transactional
  data (non personally identifiable information).
  Segmentation and Predictive models are built
  together with the clients input using Angoss
  data mining capabilities end of job typically
  within 30 days.
• Clients advisors are scored (monthly) with the
  models resulting in a list of highly targeted
  "predictive tickets" delivered to inside and
  outside wholesalers for immediate sales coverage.
  These tickets predict significant advisor
  events 30-60 days in advance.
• Once coverage is complete (by phone or visit) and
  sales results are logged, incremental net sales
  results are delivered.
• Sales performance, advisor segment tracking
  territory management reports are made available
  for management use.

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FundGUARD - Customer Quotes
President FundGUARD is one of the key reasons
for the turn around in our sales
performance. Head of Sales After having
initiated our coverage of clients using
FundGUARD Leads, one of my reps came into my
office saying...'This is eerie, these leads are
great. I've been trying to reach 3 of these
names for a year and after calling them today,
each of them mentioned that they were thinking of
us." Wholesaler As an experienced wholesaler,
I was skeptical about FundGUARD at first. But
when Angoss presented my territory results at the
end of our 3-month trial, I completely bought
into the process. Not only did they prove how
much more incremental revenue I had made by
covering theirs vs. my leads but also how much
money I could have made had I covered all of
their leads
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FundGUARD - Segmentation
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FundGUARD - Predictive ModelsOne month ahead
purchase/redemption
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FundGUARD - ROI Case Study

• FundGUARD delivers substantial incremental
  revenue per lead provided
• Company provided with over 2000 predictive leads
  per month
• Sales staff executed monthly sales calls
  according to leads provided as well as calling on
  those that were not predictive of buying behavior
  (control group)
• Incremental value of each predictive lead
• Increase in net sales per lead 100K
• RESULT Over 300M increase in net sales
  generated in during FundGUARDtrial

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FundGUARD - ROI
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FundGUARD - ROI Coverage Lift
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FundGUARD - ROI
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Case Study 3B2B Market Sizing

• Large Canadian Telco wanted to know where the
  revenue opportunities were
• Potential revenue for Current Clients Prospects
  
• Approach
• Build Segments on current customer data
• Current customer should have decent examples of
  all possible customer types
• You must have a couple of good customers in
  there somewhere
• Filter out the desired market
• Mid market (gt100 employees) in this case
• Find potential customers in DB that look most
  like best current customers

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B2B Market Sizing
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B2B Market Sizing - Prospects
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B2B Market Sizing Sample Segment Profile
Extremely High Value Give Me, Help Me
Connectivity Extremely High Revenue Average
Penetration   Fully saturated with Data Private
Line Services. Small opportunity to increase
Internet Dedicated penetration.   Voice revenue
driven by Outbound LD and Local, yet below
average penetration levels. High penetration of
Toll Free, yet extreme low revenue generation.
  Infrastructure Management Extremely High
Revenue Extremely High Penetration High
penetration across all IM products. Revenue
primarily driven by MNS, Equipment and Hosting.
Low revenue generation from Security services,
yet penetration levels are high.   
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B2B Market Sizing Predictive Modeling

• Large Canadian Telco wanted to know where the
  revenue opportunities were
• Potential revenue for Current Clients Prospects
  
• Approach
• Build Predictive Model to estimate potential
  revenue
• Estimates at the account level (as opposed to the
  segment)
• For current customers we can use all available
  information
• For prospects we have more limited information
  but the model accuracy is known
• Filter out the desired market
• Mid market (gt100 employees) in this case

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Case Studies
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Demo
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On Demand Analytics Pros/Benefits

• Cost
• Security
• Time to Solution etc
• Leverage your relationships add value

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On Demand Analytics - Challenges

• Security
• Privacy
• Loss of control
• Challenge of closing the loop
• Risk to revenue of showing how analytics can
  reduce traditional costs