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Today’s Presenters
SEAN ZINSMEISTER Senior Director of Product Marketing,
Infer
SARAH NELSON Director of Demand Generation,
Yesware
What We’ll Cover
The Challenges: what’s the current marketing/sales challenge
Find White Space: understand what’s likely to close in your funnel
Redefine SQL: leverage predictive data and key buying signals
Align with Marketing: ensure MQL maps to SQL definition
Measure Success: measure and incentivize revenue-generating activity
What is Predictive Analytics?
Actionable Intelligence for Sales & Marketing
Machine Learning Thousands of external data points
Keywords: ● Machine Learning ● Data Science ● Predictive Analytics● AI
Existing Customer DataWith Pre-Build Connectors
Add Infer’s External SignalsThousands of Data Points
Build Personalized ModelsUsing Machine Learning
CRMSales Automation
Marketing Automation
Fit ModelsBehavioral Models
Usage Models
Public FilingsData Partnerships
Proprietary Web Crawlers
Prospect ID
Prospect ID
Prospect ID
Prospect ID
Prospect ID
Prospect ID
Prospect ID
Prospect ID
Prospect ID
Won
Won
Lost
Lost
Lost
Won
Won
Won
Lost
Step 1: Start with your existing data
Step 2: Add thousands of signals mined from the web
Prospect ID +
Prospect ID +
Prospect ID +Prospect ID +Prospect ID +
Prospect ID +Prospect ID +
Prospect ID +
Prospect ID +
Won
Won
Lost
Lost
Lost
Won
Won
Won
Lost
• Employee Count• Company Revenue• Sells Globally• First Trademark < 7 Years Ago• Featured in Top Industry Websites• Is Hiring Support Agents• eCommerce Technology • Actively Advertising • Recently Expanded to New Office• Raised Funding of $20-$100M• Featured in Inc. 5000• Not Spammy
Add thousands of signals
Prospect ID +
Prospect ID +
Prospect ID +Prospect ID +Prospect ID +
Prospect ID +Prospect ID +
Prospect ID +
Prospect ID +
Won
Won
Lost
Lost
Lost
Won
Won
Won
Lost
Step 3: Determine what signals are predictive
Prospect ID +
Prospect ID +
Prospect ID +Prospect ID +Prospect ID +
Prospect ID +Prospect ID +
Prospect ID +
Prospect ID +
Won
Won
Lost
Lost
Lost
Won
Won
Won
Lost
Step 4: Determine what signals are predictive
Sales & Marketing Challenges
Too FewProspects
Too Many Prospects
Missing Opportunities Unclear Segmentation
Which are the best fit to buy?
Are there more lookalikes? Which prospects are most engaged?
Who is my ideal customer profile?
Finding the White Space in your Pipeline
● Marketing ● Sales Development● Account Executive Opportunities
Pioneering Predictive for Sales & MarketingTying it All Together...
● Forecast revenue growth● Find gaps in GTM process● Pipeline acceleration
AT A GLANCE
+7%boosted overall revenue
+10%increased average deal size
+$500k/mogrew opportunity pipeline
+35%increased trial signups
+25%Expanded MQL volume
Sales Prioritization
Cost of Sales Team
$1.2M 30% $360,000
Bad Leads $$$$
Number of Sales Reps
20 Sales Reps $60,000 $1.2M
Average Monthly Cost per Rep $$$$
Aligning Lead Effort with Impact - Belly
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
Sales & Marketing Alignment
Demand Gen compensation plan built on InferUses Infer to negotiate w/ partners and Lead providersLeverages Infer to overcome the Sales and Marketing divide to define MQL
Nick EzzoVP Demand Gen
Sales & Marketing Alignment
Demand Gen compensation plan built on InferUses Infer to negotiate w/ partners and Lead providersLeverages Infer to overcome the Sales and Marketing divide to define MQL
Nick EzzoVP Demand Gen
+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
Redefining our MQL
1. Paid Users: win rate increases with between 1-5 paid users for SMB, Mid Market, and Enterprise leads
35
2. Infer Rating: 90% revenue on closed won deals had Infer Rating A or B (this score is based on external factors vs internal)
3. Behavioral: 28% revenue came from accounts with 0 paid users
Standing Out is ImportantPeople receive 116 business emails every day, so you need to
pick your words wisely to get their attention
Measuring what’s working
•What do you need operationally to measure what’s working?
–Lead stages and clear sales process on what to use,when
–Sales outreach needs to be logged (image of salesforce sidebar)
Measuring Results
•It’s all about closed-won revenue and ROI from marketing programs not just volume of leads into top of funnel or volume converting to SQL…
•Diff ways to measure ROI... Best way to identify actual return
Maybe an image showing dollar signs coming out of bottom of a funnel? Or something that correlates with money in general?