© 2015 Mintigo. All Rights Reserved. www.mintigo.com
How To Be A Data-Driven Marketing Powerhouse With Predictive Analytics & Big Data
Tony Yang Webinar Host
Russell Glass Head of Products
Megan Heuer VP & Group Director,
Data-Driven Marketing
John Bara President & CMO
© 2015 Mintigo. All Rights Reserved. www.mintigo.com
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© 2015 Mintigo. All Rights Reserved. www.mintigo.com
Mintigo Enterprise Predictive Marketing Platform
Our mission is to master data science to revolutionize the way
people market and sell.
© 2015 Mintigo. All Rights Reserved. www.mintigo.com
Russ Glass!Head of Products!
@glassruss!
@LinkedIn!
“The number of transistors on a computer chip will double approximately every two years.” Gordon Moore, founder of Intel
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“Big data is the most disruptive business force there is. Big data is the stuff that is really moving economic power from one group to another.” Geoffrey Moore, Crossing the Chasm and Inside the Tornado
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“Half the money I spend on advertising is wasted; the trouble is I don't know which half.” John Wanamaker, Pioneering 19th Century Retailer
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THE BIG QUESTION ABOUT BIG DATA: How do I implement big data principles in my own business?
PRINCIPLE NO. 1
Determine what you know (and want to know) about your customer.
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THE BIG QUESTION ABOUT BIG DATA: How do I implement big data principles in my own business?
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PRINCIPLE NO. 2
Start small by thinking, ‘Big data, little triggers.’
THE BIG QUESTION ABOUT BIG DATA: How do I implement big data principles in my own business?
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PRINCIPLE NO. 3
Be prudent but not shy about investing in technology: CRM systems are a must, marketing automation is becoming so, and analytics tools are a no-brainer.
THE BIG QUESTION ABOUT BIG DATA: How do I implement big data principles in my own business?
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PRINCIPLE NO. 4
Hire the right people. Marketers must hire data-oriented people, math majors, and left-brained thinkers.
THE BIG QUESTION ABOUT BIG DATA: How do I implement big data principles in my own business?
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PRINCIPLE NO. 5
Test, test, test, measure, measure, measure. Ideally, measure your contribution to revenue: It is the way to prove marketing’s value.
© 2015 Mintigo. All Rights Reserved. www.mintigo.com
John Bara!President & CMO!
@John_Bara!
@Mintigo!
© 2015 Mintigo. All Rights Reserved. www.mintigo.com
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~80% of marketing budget is wasted…
This is a scientific fact!
THE MARKETING BLACK HOLE
MQL
SAL 66%
SQO 32%
Won 7%
“ T h e C l i f f “ There is no leverage in today’s demand gen process
2.89 wins per 1,000 inquiries*
93% Loss Rate
AN INEFFICIENT PROCESS
60% to 80% Data is bad or has no chance of closing
40% to 50% Wrong nurture track / inability to see stage
4x to 10x Top line growth leU on
the table
Process relies on data shared by the customer with liWle augmentaXon
MARKETING AUTOMATION
Campaigns List buys
Whitepapers Webinars Tradeshows
DEMAND ACTIVITY MARKETING FUNNEL
Nurture Score Analyze
MQL SAL SQL
DEMAND GEN PROCESS
Cost per Win Outstrips ROI in Most Cases
AN EXPENSIVE PROCESS
2.89 wins per 1,000 inquiries @ average $43 per inquiry
Leverage vast amounts of data and science to predict which markeXng acXons have a high probability to succeed and which ones will probably fail.
DEFINITION: PREDICTIVE MARKETING
© 2015 Mintigo. All Rights Reserved. www.mintigo.com
• Leverage Data Science in every step of your workflow
• Put Data Science in your hands
FIRMOGRAPHIC DATA: Company name Domain Industry Revenue CONTACT INFORMATION: Name Title Email BEHAVIORAL DATA: Downloaded whitepaper
Data Is The Key – Current Data Points
Technologies • API Provider • Saas product • Databases:
MySQL User, MS SQL Server, Oracle DB • Mobile Developers: iOS Developers • VMWare User & VirtualizaXon Experts • Oracle User • Cloud Compu6ng Tech: AWS • Cloud Compu6ng Tech: Azure • Data Center User
Apps & Tools • Email Service: MS Exchange Online • MS Office 365 User • MS SharePoint User • CollaboraXon Tools User: Jive, Yammer, ChaWer • Atlassian & Jira Users • Hiring Enterprise Content Mgmt Expert
Web Technologies • DNS: Neustar, GoDaddy, Dyn, MadeEasy, Amazon • CDN Technology: Akamai, Amazon • CMS Technologies:
SiteCore, Joomla, WordPress, Drupal • Web Analy6cs Technologies:
WebTrends, OpXmizely, CoreMetrics, Adobe Omniture, Website Technology: Ad Services, Live Chat
Company • Growing Company: Hiring >250 Employees • Has MulXple LocaXons • Company Employs Field WorkForce • Mobile: BYOD IniXaXve • Mobile: MDM/MAM Technology • Alexa Ranking • PPC Budget Spend • Company has Call Center • Compliance: SOX, HIPAA, FINRA/FISMA • AdverXsing Technologies: Atlas, Google Adroll,
Google Adwords, DoubleClick for AdverXsers
DATA: Mintigo’s Marketing Indicators
IDENTIFY THE CUSTOMERDNA™
Ideal Prospect 150-‐250 MIs
Customers
Prospects
Fit score & appended Leads
2,500+ MI’s 10 MM Companies 150 MM Contacts
Data as is . . . Enriched Validated Appended
• Who are my ideal prospects ? Discover your CustomerDNATM
• How should I communicate to them ? Use Marketing Indicators to create micro-segmentations
• What should I say to them ? Predict best content to segment fit
• Where do I put my resources & focus ? Create scoring models
Decisions: Making the Right Marketing Decision
LEAD PRIORITIZATION
• IdenXfy leads most like to convert • Pass high scores directly to sales • Nurture B leads • Scale for capacity • Leverage MI’s to assign nurture
Lead Enrichment & PrioriXzaXon Telesales ProducXon
Loosen Status Quo
Commit to Change
Exploring SoluXons
Commit to SoluXon
JusXfy Decision
Make Decision
COVERING THE BUYER’S JOURNEY
Discovery Consideration Decision
Fit Analysis -‐ Journey Relevance
Inside the Funnel Outside the Funnel
Mintigo Data Customer Data SiriusDecisions, Buyers Journey Model
Intent Analysis -‐ Journey Relevance
Behavior Analysis -‐ Journey Relevance
PREDICTIVE IS MORE THAN A SCORE
Target Accounts
Air Traffic Control
Customer Lifetime Value
Campaign Design
Segmentation
Cross Sell
Lead Enrichment & Prioritization Telesales production
Nurture Design
Customer focused
Content focused
Valu
e Fo
cuse
d
Higher ASP
Data Validation & Enrichment
Insights Up Sell
Customer Retention
Partner cDNA
Net New Focused
List Buys
Incentivized Content
Syndication
A B C
Real-Time Optimization
New Accounts
© 2015 Mintigo. All Rights Reserved. www.mintigo.com
Megan Heuer!VP & Group Director!Data-Driven Marketing!
@megheuer!
@SiriusDecisions!
© 2015 SiriusDecisions. All Rights Reserved
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Getting Started With Predictive Analytics & Big Data
• How can you tell it's time to bring in analytics to improve performance?
• Where are the most valuable places to apply data-driven approaches right now?
• What are the biggest pitfalls to avoid with introducing data-driven approaches?
• What is important to consider when choosing an outside partner?
© 2015 SiriusDecisions. All Rights Reserved
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Big Data’s Value Comes Down To Doing The Basics Better
Data-driven marketing is analyzing and applying what we know to the choices we make about who and how to engage and to measuring how much those actions contribute to growth.
© 2015 SiriusDecisions. All Rights Reserved
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Data-Driven Marketing Delivers On The Ideal Combination of Math Problem and Personality Test
Marketing must align its efforts to the accounts and actions most likely to deliver growth. Marketing must execute in a way that respects and engages individual customers based on their needs, preferences and timing.
© 2015 SiriusDecisions. All Rights Reserved
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“Data-Driven” Really Means “Customer Driven” at Scale
Our organization and products
The tactics marketing loves to use
The accounts and buying centers sales wants to target
The tactics that should be used
The target audience within accounts our business needs to
address
Who or what is most influential on its decisions
FROM:
TO:
© 2015 SiriusDecisions. All Rights Reserved
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How To Tell When You Can No Longer Live Without Data-Driven Demand Creation
Inquiry Outbound Inbound
Marketing Qualification
Teleprospecting Qualified Leads (TQLs)
Teleprospecting Accepted Leads (TALs)
Automation Qualified Leads (AQLs)
Teleprospecting Generated Leads (TGLs)
Sales Qualification Sales Accepted Leads (SALs)
Sales Generated Leads (SGLs)
Sales Qualified Leads (SQLs)
Close Won Business
Response Rate Low(er)?
Harder to Get Right Contacts on the Phone?
Sales Acceptance Lower Than It Used to Be?
Too Much In “Dreaded Stage 0?”
Takes Longer to Close Deals?
Marketing Not Sourcing As Much Pipeline?
© 2015 SiriusDecisions. All Rights Reserved
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Identify Areas That Require Insights Then Prioritize Efforts Based on Impact, Data Access and Skills
2. Personalization 5. Outbound Outreach
1. Market Intelligence
Who do I want to engage, where do they want to engage and what will they care about?
How do I maximize conversion to revenue by only spending time on leads we can close?
How do I make sure leads get to the right person fast?
How can I segment customers and prospects using meaningful insights and behavior triggers?
How do I maximize engagement at all stages of buying and post-sale?
What and who do I need to know in my target market(s) and accounts and what do I have already?
6. Reporting
7. Analytics
How do I prove the value of marketing?
How do I use past performance to improve future results?
How do I make smarter predictions?
Seven Data-Intensive Marketing Focus Areas
3. Lead Scoring
4. Lead Routing
© 2015 SiriusDecisions. All Rights Reserved
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Don’t Try This At Home: Pitfalls on The Road To Becoming a Data-Driven Marketing Powerhouse
Pitfall Group One: Things We Don’t Have or Don’t Do
Lack of communication Lack of training/skill development Lack of outside tools or services Not tracking results or impact
© 2015 SiriusDecisions. All Rights Reserved
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Don’t Try This At Home: Pitfalls on The Road To Becoming a Data-Driven Marketing Powerhouse
Pitfall Group Two: Marketers Who Do Too Much
Taking on too many projects Making projects too complicated Attempting full roll-out too soon Covering up data issues
© 2015 SiriusDecisions. All Rights Reserved
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The Scariest Pitfall Of All Is The Monster We Create Ourselves
Internal politics and culture
© 2015 SiriusDecisions. All Rights Reserved
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Choosing the Right Partner: Experience Is The Key Driver of B-to-B Decisions
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B-to-B Buying Decision Drivers From 2015 SiriusDecisions Study Question: What was most significant driver of decision to select vendor of choice?
Dire
ct 34% Previous experience with the company
8% Implementation of customer support services were the best 7% Relationship with salesperson
10% Influence of references sourced independently 8% Influence of references provided by vendor 4% Perception of brand with no previous experience In
dire
ct
71% of b-to-b decision drivers are based on direct or indirect customer experience
vs. 18% of decision based on promise of offering to meet needs vs. 9% of decision based on the price was the best
=
© 2015 SiriusDecisions. All Rights Reserved
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Choose Partners Wisely: Three-Part Checklist
2. Technology Fit 3. Experience Fit 1. Solution Fit
• Do we have goals for what we want the solution to deliver?
• Do we know how we’ll measure whether we achieved those goals?
• Do we have resources on our team prepared to make the solution work (i.e., skills, bandwidth, project management)?
• Will this tool work within existing infrastructure?
• Will the tool/service address most of what we need?
• Is it redundant with anything we already have?
• What integrations are required for it to be valuable?
• How much of the solution will we be able to use right away based on our current state of data and skills?
• What do customers with similar goals say about their experience?
• Will we get help we need to deploy?
• Will post-sale support and account management be high quality?
• Can we learn from this vendor?
• Are we comfortable with them in meetings with our team?
• Would we be comfortable if they had to present to our boss?
• Would we feel comfortable if one of their executives met our CEO?
© 2015 Mintigo. All Rights Reserved. www.mintigo.com
Q&A
Tony Yang Webinar Host
Russell Glass Head of Products
Megan Heuer VP & Group Director,
Data-Driven Marketing
John Bara President & CMO