Allison MacLeod, Sr. Director of Demand Gen at Rapid7 presented "Making Predictive Analytics Work" at the MassTLC sales and marketing conference, March 2016

1. MAGIC EIGHT-BALL: MAKING PREDICTIVE
ANALYTICS WORK FOR YOUR ORGANIZATION
Allison MacLeod
Sr. Director, Demand Generation & Marketing Operations,
Rapid7

2. About me
2
Allison MacLeod
Sr. Director of Demand, Customer & Marketing Ops
@ Rapid7
www.rapid7.com
Allison_macleod@rapid7.com
@allib1121
https://www.linkedin.com/in/allisonbmacleod

3. Agenda
3
•Rapid7’s story with (marketing) predictive analytics & scoring
•A framework/checklist to put into practice
•Q&A

4. Confidential and Proprietary 4
Rapid7’s Story | The Challenge
 Traditional lead & behavioral scoring became
inaccurate
 Too many ‘junk’ leads passed through= too much noise!
 High lead volume model = not able to automatically
scale qualification process on scoring and scrubbing
data alone

5. So Many Options!
5

6. Solution & Technology Chosen
INFER
PREDICTIVE LEAD SCORING & ANALYTICS
WWW.INFER.COM

7. Why Infer?
7
• Great POC and free trial(45 days) process – able to see it in action before
purchase
• Fast implementation time – 2 weeks
• Dedicated CSM – model updates every 90-120 days
• Accuracy and better quality= scale!
• Solution direction
• Cost
• Integration

8. Uses
8
Contact
Scoring
• Inbound
• Threshold for becoming
Marketing Qualified Lead
(MQL)
• Prioritization
• Focus on programs
• Other uses – high
volume
programs/events, lists,
etc.
Account
Scoring
• Prioritization of accounts
for sales – especially
useful with territory
models
• Focus for Marketing
team on ABM programs
– Enterprise/Named
accounts
*Intent-
driven
• Beta stage
• Greenfield accounts
delivered
• Intent- based (by key
terms)

9. Results
9
Decrease (20%) in quantity
of leads passed = higher
quality
5% MQLs dispositioned as
Junk
10-20 20-30 30-40 40-50 50-60 60-70 70-80
20-30 30-40 40-50 50-60 60-70 70-80 80-90 90-100
20-30 30-40 40-50 50-60 60-70 70-80 80-90 90-100
Conversion to
opportunity
Conversion to
SQO
Higher opp &
deal size
The higher the score….

10. Next Steps
10
•Leverage intent driven data – nurture, sales alignment
•Model revisions (geo, industry)
•Embed in ABM efforts

11. A FRAMEWORK FOR
GETTING STARTED

12. A Framework/Checklist
12
GETTING STARTED
Ask yourself…
 What is the challenge I’m trying to
solve?
 How will I use/implement the data?
 Is sales aligned?
 For scoring – do I have a high
volume model?*
CHOOSING A VENDOR
Consider…
 Do they offer a POC or trial?
 Upfront cost? Ongoing?
 Will they commit dedicated resources?
 Customizable?
 Integration?
 Competition?
 Roadmap?
IMPLEMENTATION
Take the following steps…
 Test/pilot with small team
 Gather feedback
 Refine model
 Test again
 Launch!
ALIGNMENT & ONGOING USE
Make sure you…
 Create a champion in sales
 Prove efficacy and value – quickly!
 Gather feedback frequently
 Update your models (quarterly)
 Expand!

13. THANK YOU!
ALLISON_MACLEOD@RAPID7.COM