Hear how real customers are infusing predictive analytics into their go-to-market machines.
In this Presentation you'll learn:
• Differences in approaches to launching a predictive solution
• Top use cases for getting started
• How to measure success
11. Sales Prioritization
Cost of Sales Team
$1.2M 30% $360,000
Bad Leads $$$$
Number of Sales
Reps
20 Sales Reps $60,000 $1.2M
Average Monthly Cost
per Rep
$$$$
12. Sales Prioritization in Action
Kevin Gaither
Focused sales on highest
value lead targets
Decreased time spent on bad leads
by almost 20%
Established data-driven workflows
with aggressive follow-up
Drove top-line results through effort
reallocation
SVP of Sales
Fully Loaded Cost of
the Inside Sales
Team
Headcount 19% $$$
Sales Effort Saved by
Not Working Bad Leads
Monthly Cost Savings from
Reduced Effort on Bad
Leads
Cost Savings
4x Conversion Rate
By prioritizing leads based on data and
following up more aggressively
3x Average Deal Size
By spending more time on the right
customers
13. Sales Prioritization in Action
Kevin Gaither
Focused sales on highest
value lead targets
Decreased time spent on bad leads
by almost 20%
Established data-driven workflows
with aggressive follow-up
Drove top-line results through effort
reallocation
SVP of Sales
Total Revenue by
Lead Score
Before Infer (Day
Zero)
After Infer (Day 60)
Infer A-Leads
Infer B-Leads
Infer C-Leads
Infer D-Leads
+53%
+154%
+180%
+690%
15. Aligning Lead Effort with Impact
Lauren Licata
Reps call Infer A and B-Leads First
Email A Leads within 5 min and call
within 1 hour vs. 8 hours it takes
Increased effort spent on A-Leads
by 3x & decreased effort spent on
D-Leads by 1.5x
Result: Increased sales by 30%
VP of Marketing
16. +30%
increase in sales-
qualified leads
+30%
lift in sales
~3x
increase in the effort
spent on A-Leads
1.5x
decrease in the
effort spent on D-
Leads
2x
lead to demo
conversion
17. Using Fit & Behavior Buying Signals Together
Isaac Wyatt
Route best fit & engaged free-trials
directly to sales
Find hidden segments of leads
Prioritize daily sales outreach
Interpate buying behavior
Director of Marketing
Strategy & Operations
18.
19. ALEXANDRE PAPILLAUD
DIRECTOR, GLOBAL DEMAND
CENTER, INTEL SECURITY
Lattice helps us filter out low probability leads
before they reach sales. I love the ability to
dive deep into the predictors of what makes
a good lead…and our sales team loves
Lattice because they know they are focused
on the best opportunities.
Proprietary & Confidential
“20%Lower cost per
opportunity
21. Data-driven Insights for Prioritizing Leads
Share of Servers Virtualized
at Company
Public vs. Private Cloud
at Company
Network-Based Storage
at Company
Company is Undergoing
Rapid Growth
Company is Using
Amazon Web Services
10,000+ Business and Tech Attributes
on 100M+ Entities
22. 30%Greater velocity
We wanted sales to work the most
enterprise-ready accounts. Lattice was
able to surface accounts with high
likelihood of conversion and accelerating
them in the pipeline.”
“
Shantel Shave
Director, Demand Gen
Accelerating the Enterprise Business
25. 20%Higher call to win rates
on list-based outbound
efforts
VP/GM of Distribution
We understand a good customer when
it sees one, but with a small sales team,
it would be impossible to visit millions of
websites to find the ideal prospects.
With Lattice, we can identify the right
revenue opportunities.”
“
Increasing Penetration into SMB
$1B+ Financial Payments
Processor: Optimize list buys
30%Lower acquisition costs
27. Top LinkedIn Post on Tuesday, 10/27/15
50%
Lower cost per
opportunity
Direct Mail for High-Value, High Intent Targets
28. Direct Mail for High-Value, High Intent Targets
Identified high value
targets
Determined buyer
stage
Created custom data
visualization
Added to direct mail
campaign
Offer to meet and
explain
Tangible package Automated follow-up Email & Phone call
from rep
• How we created this?
• Insights gained about
your network
29. Improving Marketing Efficiency
Kevin Bobowski
Route highest best leads to sales for
immediate follow-up
Develop regular full-funnel pipeline
forecasts
Continuously score marketing
channels to test & invest
Optimized content syndication and
list-buy programs
CMO
33. A
B
C
Leads Opportunities Lead to Opp
3,000
5,000
7,000
500
325
125
16.7%
6.5%
1.8%
Type of Lead
A-Leads
worth
almost 3x
B-Leads
34. A
B
C
10
30
100
140 $5,000
Type of Lead
Campaign 1
Leads Cost $ / Lead Fcast Opps Forecast & / Opps
1.7
2.0
1.8
5.4$35.71 $926
A
B
C
35
30
45
110 $5,000
Type of Lead
Campaign 2
Leads Cost $ / Lead Fcast Opps Forecast & / Opps
5.8
2.0
0.8
8.6$45.45 $582
Campaign 2
wins on
quality
weighted cost
35. Adam von Reyn
Instant campaign feedback
Reduced cost-per-lead
Tests new marketing copy against
D-Leads
Developed MQA for ABM strategy
Decreased 40% of total
lead flow
VP of Growth Marketing
37. Real Results
5000
Marketing-qualified
leads were
unconverted in its
database, leading to
a dramatic run-rate
increase
3x
The number of leads
converted to closed
deals tripled
+150%
Conversion rates
increased by 150%,
from 0.8% to 2%
+76%
Closed deals for new
solutions were
boosted by 76%
39. • Ran a series of roadshows to drive pipeline for their
Enterprise business
• Scored their database to identify high fit accounts who
would receive targeted ads promoting the roadshows
• Identified high fit late stage buyers who would be invited
directly by sales (in addition to receiving an ad)
• Enriched Marketo with account data so they could deliver
hyper-personalized messages
Hyper-segmentation for ABM
at Scale
40%
70%Greater ROI on ad spend
Increase in pipeline
35%
Higher engagement within
target accounts
Ads Email SDR Calls
40. Every account gets scored and the next steps for
engagement are initiated.
Lift curve changed to protect customer confidentiality
Score and Prioritize Targets
42. Orchestrate Multi-channel Outreach to Maximize Conversion
“A” Targets
Targeted Ads Personalized
Email Invites
SDR Calls
only for those in
market
“B” and ”C” Targets
Generic Email
Invites
43. Orchestrate Multi-channel Outreach to Maximize Conversion
“A” Targets
Targeted Ads Personalized
Email Invites
SDR Calls
only for those in
market
“B” and ”C” Targets
Generic Email
Invites
Personalize based on key
attributes:
• Complementary tech
• Amazon AWS
• Google Cloud
• Microsoft Azure
• Industry
• Financial Services
• High Tech
• Telecom
44. Standard Ad
Ad for companies
using Amazon AWS
Ad for companies
using Google Cloud
Example: Customer personalized their ads based on developer
platforms they were using (e.g. Amazon AWS, Google Cloud,
etc).
Hyper-personalize Content and Messaging
45. Standard Ad Ad for companies
using Amazon AWS
Ad for companies
using Google Cloud
Example: Customer personalized their ads based on developer
platforms they were using (e.g. Amazon AWS, Google Cloud,
etc).
Hyper-personalize Content and Messaging
46. Social Tables Challenge
Steady flow of 1,400 trial
leads every month like
clockwork
Took on a paid content
marketing strategy
Leads skyrocketed to 6,000
total Net New Leads per
month
#humblebrag
50. Hyper-Segmentation with Profiling
Ray Miller
Launched high-value outreach with
personalized nurture
Identified 900+ high-potential
prospects for sales
Hyper-segmented current and past
trialers into ICPs
Prioritized A & B-Leads for
accelerated sales follow-up
Senior Marketing
Operations Manager
51. AT A GLANCE
+7%
boosted overall
revenue
+10%
increased average
deal size
+$500k/mo
grew opportunity
pipeline
+35%
increased trial
signups
+25%
Expanded MQL
volume
53. Sales & Marketing Alignment
Demand Gen compensation plan
built on Infer
Uses Infer to negotiate w/
partners and Lead providers
Leverages Infer to overcome the
Sales and Marketing divide to
define MQL
Nick Ezzo
VP Demand Gen
54. Sales & Marketing Alignment
Demand Gen compensation plan
built on Infer
Uses Infer to negotiate w/
partners and Lead providers
Leverages Infer to overcome the
Sales and Marketing divide to
define MQL
Nick Ezzo
VP Demand Gen
55. +23%
Increase in Average Deal
Size
-53%
Decline in poor quality
leads
Sales & Marketing Alignment
+200%
Increase in incremental
revenue
+31%
Lead to MQL improvement
Every company should use predictive analytics to gain clear customer
parameters that the whole organization can agree on – now that we
have predictive scores, I’ll never go back.
Our Infer model makes all the difference when it comes to sales and
marketing alignment.
Nick Ezzo, VP Demand Gen
56. DATA QUALITY
MATTERS
A Predictive Model is
only as the good as the
data that goes into it.
YOUR BUSINESS IS NOT
ONE-SIZE-FITS-ALL
And a One-Size-Fits-All modeling
approach leads to bad results
across your business.
OPERATIONALIZATION
IS CRITICAL
Marketing and Sales cannot
execute without Full
Transparency and Actionable
Insights.
LACK OF ENTERPRISE
SECURITY IS A NON-STARTER
You are giving the vendor
access to your CRM and MAP
and your data needs to be
protected.
Key Operational Considerations
57. THANK YOU!
Q&A
• Write your questions in the tab above
• Check out the attachments tab
• Please leave feedback
Kerry Cunningham
Sr. Research Director
SiriusDecisions
@KerrySirius
Sean Zinsmeister
Sr. Director, Product Marketing
Infer, Inc.
@szinsmeister
Nipul Chokshi
VP Marketing, Lattice Engines
@nipulc
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