We now have enough data to move beyond linear lead scoring and account targeting based on tribal knowledge. In this deck, I share some of what we have found on the journey to data driven B2B marketing using Eloqua, LatticeEngines Salesprism, and Salesforce.com
Data Driven Marketing: Can We Clone George Clooney in Oceans 11?
1. CAN WE USE BIG DATA TO
CLONE GEORGE CLOONEY
IN OCEANS 11?
Abner Germanow
@AbnerG
Wrongless.tumblr.com
Director, WW Marketing
Juniper Networks
2. JUNIPER AT A GLANCE
2012 Revenue: $4.5 Billion
124 Offices In 45 Countries: 16 24x7 Support Centers: 5 R&D Centers
9000 Employees
1997: Service Provider
Core
#2 In Core
Routing, SP Routing,
Network Security
2004: Secure
Enterprise Edge
#1 In High-end
Firewall & Mobile VPN
2008-13:
Switch, WLAN, Mobile
Security
#3 In Edge Routing,
Ethernet Switching
20,000+ Customers, Including 96 Of Fortune 100
Powering 6 Of The World’s 7 Largest Stock Exchanges
Juniper Is Deployed In More Than 380 Federal Government Agencies
6. A TALE OF TWO REPS
1 Account
1,200 Accounts
Knows all the key people
Knows some people
Knows the organization
Knows some organizations
7. GEORGE KNOWS:
HUMAN BEHAVIORS
Product or training certifications
Social media activity & engagement
Competitor product or training certifications
Work history
Event attendance and interaction
Role and responsibilities
Browsing history
Content consumption / engagement
Title / job responsibility
Incentives / bonus structure
8. GEORGE KNOWS:
ORGANIZATIONAL BEHAVIORS & ATTRIBUTES
Prior purchase history
Deployed technologies
Industry
Financial health
Employee population changes
Real estate moves, adds, and changes
Social media buzz
Credit scores
Technical support events
Geographic footprint
Executive changes
Merger & Acquisition activity
Private equity investment
Information intensity of business
Technology investment persona
Customer segmentation attributes
Competitor Investments
9. A TALE OF TWO LEADS
Lead 1
Lead 2
Attended a Data Center Webinar
Attended a Data Center Webinar
Clicked through to white paper
Clicked through to white paper
Financial Services
$200k security installed base
Real Estate Move
10. ANALYTICS BY ENGAGEMENT STAGE
Data Source: SFDC Deal Flow
Current Data Visibility: XXXXX
Current Data Quality: XXXXX
Analytics Needed: XXXXX
Predictive Opportunity: Optimize current Q close
Build one of these for
each stage
MQL
SAL
SQO
Install
Base
CrossUpsell
WON
Are these the
right attributes to
assess?
Sales
Data Source: salesPrism
Current Data Visibility: XXXX
Current Data Quality: XXXXX
Analytics Needed: XXXXX
Predictive Opportunity: Optimize sales sourced opps
Responder
Inquiries
Marketing
Data Source: Eloqua Activity
Current Data Visibility: XXXX
Current Data Quality: XXXXX
Analytics Needed: XXXXX
Predictive Opportunity: Optimize lead scoring
11. HOW I SPEND MY TIME
Navigating Legacy
Data, Systems, and
People
Training / Culture
Play Design
Customers
17. It gives us the
information we need so
we don’t look dumb.
- Inside rep
18. RESEARCH IN SALESPRISM IS CORRELATED TO
LARGER OPPORTUNITIES
Research use case
Targeting use case
All accounts
Pipeline, $ Thousands
Accounts with plays
Pipeline, $ Thousands
+34%
+82%
When reps
researched an
account in
salesPrism, they
created larger
opportunities.
$152
When reps engaged
accounts with
recommendations, t
hey created larger
opportunities.
$172
$129
$83
Not engaged
Engaged
Not engaged
Engaged: rep views account details page and/or logs activity against the account in PRISM.
Engaged
Tribal Knowledge is valuable. To what extent can you rely on it?
How do you augment or challenge tribal knowledge with data?
We also have or can buy much of this data.
Again, we have or can buy much of this data. No one buys a network because they want to, they buy because of a forcing or group of trigger functions.
If you don’t look at the problem holistically, you risk “random acts of analytics” – point your money at the biggest problems, not just the sexy stuff.
I spend time with the data, but also with customers. Why? Because data doesn’t tell the whole story.
The spectrum is broad. Calling down a list isn’t productive, but it’s what some people do. Ocean’s 11 style selling can win big, but takes a large investment in time and money.
There is value to the Highest Paid Person’s Opinion, but (most of the time) not at the expense of observed behavior.
Don’t spend time on “this model is slightly better than your model” If you have made it to the point where that conversation actually matters, you are already winning. Otherwise focus on culture and adoption.