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Big Data, Big Revenue: How Big
Data Means Millions for Marketing
Jon Miller
Rosanne Saccone
Pentaho Corp
Enabling the modern big data driven business
Business Analytics for all Data
Any
Data
Any
Analytics
We all know the amount of data in the
world is growing exponentially
Big Data Opportunity for Marketers
Seamlessly connecting to relevant customer activity
Powerful Insights from Combined Data
The Value of Big Data
Marketing related use cases
Drive incremental revenue
• Understand and monetize customer behavior
• Personalize customer experience
• Predict customer behavior across all channels
Big Data Driven Marketing Use Cases
ONLINE RETAILER
Understand buying
patterns of five million
users via click stream data
GAMING
Better monetization of
premium game features via
player data analysis
SOCIAL COMMERCE
Better campaign performance
via analysis of social media,
page clicks and email data
TRAVEL/ENTERTAINMENT
Enable thousands of travel
partners to improve
promotional targeting
ON-LINE ADVERTISING
Real-time analysis of customer
data for personalized offers &
targeted advertising
CUSTOMER LOYALTY
Enable customer behavior and
social media driven marketing
& rewards programs
Big data combined with operational data
IT IS HARD
• Big data technology is immature
• Few big data coding experts
• Use case must be clear
So why doesn’t everyone take
advantage of big and diverse data?
Find Optimal
Campaign and
Promotion Mix
Understand Best
Marketing
Activities and
Interactions
Analytics
BLEND
Relevant
Data On-
Demand
Leverage Your Company’s
Big Data Projects
DECIDE & ACT!
Big Data
Store
Social
Website
Operational
Data
Store/Analyt
ics
Marketing
Sales
Customer
Find where the data lives and get the right tools
Metrics that Matter
Get a seat at the table: Know impact to business goals
Drive Net New Business
1. Marketing Qualified Leads (MQLs)
2. Sales Accepted Opportunities (SAOs)
3. MQL to SAO Conversion Percentage
Drive Thought Leadership
4. Share of Voice
5. Press and Analyst Influence
BUT, Metrics Data Lives in
Various Sources
Each data set is an important part of the total picture
SOCIAL & WEBSITE
Marketing Forecast Model
WW Net New Amount
Non Core Net New
Amount
Target Net New
Historical Average
Deal Size
Historical Close
Rate %
Historical
CarryOver %
Lost %
$1,750,000 $0 $1,750,000 $28,000 0% 15% 85%
Plan Date
SAO 5%
Goal
Distribution
%
CarryOver
Units
Open Units
Forecast
Units
Accumulated
Units
Close Rate
%
Forecast
Win Units
Average
Deal Size
Forecast Net
New Amount
Dec-01-2012 200 14.4% 38 306 29 373 15% 56 50,000 $2,796,273
Jan-01-2013 200 16.3% 56 48 61 165 15% 25 50,000 $1,239,812
Feb-01-2013 200 20.3% 25 50 102 177 15% 27 50,000 $1,326,149
Mar-01-2013 260 15.9% 27 53 142 222 15% 33 50,000 $1,664,255
Apr-01-2013 260 10.1% 33 2 172 208 15% 31 50,000 $1,557,471
May-01-2013 260 7.1% 31 3 199 233 15% 35 50,000 $1,746,635
Jun-01-2013 310 5.4% 35 8 226 269 15% 40 50,000 $2,018,854
Jul-01-2013 310 2.6% 40 3 246 289 15% 43 50,000 $2,167,950
Aug-01-2013 310 3.1% 43 1 266 311 15% 47 50,000 $2,330,184
Sep-01-2013 400 2.7% 47 296 342 15% 51 50,000 $2,568,541
Oct-01-2013 400 1% 51 1 319 372 15% 56 50,000 $2,786,521
Nov-01-2013 400 0.8% 56 344 400 15% 60 50,000 $3,000,862
Dec-01-2013 120 0.3% 60 323 383 0% 0 28,000 $0
Tue Dec 11 02:48:22 EST 2012
Forecast Snapshot Date : 12/01/2012
Sales Country Type : 'Core' Sales Region : '*ALL*'
Rate Period : 10/01/2012
PIPELINE & BOOKINGS
FORECAST
LEADS &
OPPORTUNITIES
Multiple reports hard to manage
Manage Optimal
Campaign & Content
Mix by Target Audience
Understand Marketing
Campaigns that Drive
Closed Won Deals
Analytics
Our Approach – Blend and Analyze
Assess Impact of Campaigns from Various Data Sources
Focus on Highest ROI: Optimize Limited Marketing Resources
BLEND
Relevant
Data On-
Demand
Operational
Data
Store/Analyt
ics
Big Data
Store
Monitoring Trends to Make an Impact
Big data, small data blended for full picture
We Start with Booking Goals
• Leads by Campaign Types
• 20 Major Nurturing Tracks: 6 – 10 Touches
• Lead Conversion to Sales Opportunity
• Nurturing Effectiveness
• Opportunities across Sales Stages to Closed
• Effectively Forecast Sales Results
Revenue Foundation:
Must be Timely, Accurate
and Actionable
Expect to manage the entire marketing/sales flow
Blend Key Sources that Matter
A single view into the health of Pentaho
How do I target and
influence my most
ready-to-buy
prospects?
• Ads
• Events
• Software Trials
• Social
• Forums
• Email
• Website
• Search
• Webinars
• …
Gain Insight into the Funnel
2. How do created SAOs
impact pipeline?
3. How much pipeline is
closed won?
4. What’s average deal
size?
1. How do MQLs move
thru the lead funnel?
Four fundamental metrics to understand deeply
MQLs to SAOs
• 20% - Current Month
• 30% - Next Month
• 50% - Next 3 Months
Expected close date
• 32% - Current Qtr
• 27% - Previous Qtr
• 41% - Prior to that
Deal Size
• $200k - Current Qtr
• $250k - Previous Qtr
• $375k – Prior to that
Close won %
• 15% - Current Qtr
• 26% - Previous Qtr
• 10% - Prior to that
The Rest is Math
Qtr Pipeline
Needed
SAOs
Created to
Date
Gap MQL
Created
Current Qtr
MQL
Created
Qtr +1
MQL
Created
Qtr +2
Current
Qtr
1,250 1,000 250 250
Qtr +1 1,500 1,000 500 350
Qtr +2 2,000 500 1,500 800
Need to create 250 + 350 + 800 = 1,400 MQLs
in the current quarter
Waterfall effect of how leads created drive future pipeline
Final Step: Once Know Goals…
Market Creatively and Aggressively
How Big Data Analytics Can Drive Millions in Marketing Revenue
How Big Data Analytics Can Drive Millions in Marketing Revenue
How Big Data Analytics Can Drive Millions in Marketing Revenue
How Big Data Analytics Can Drive Millions in Marketing Revenue
How Big Data Analytics Can Drive Millions in Marketing Revenue
How Big Data Analytics Can Drive Millions in Marketing Revenue
How Big Data Analytics Can Drive Millions in Marketing Revenue
How Big Data Analytics Can Drive Millions in Marketing Revenue
How Big Data Analytics Can Drive Millions in Marketing Revenue

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How Big Data Analytics Can Drive Millions in Marketing Revenue

  • 1. Big Data, Big Revenue: How Big Data Means Millions for Marketing Jon Miller Rosanne Saccone
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  • 15. Pentaho Corp Enabling the modern big data driven business Business Analytics for all Data Any Data Any Analytics
  • 16. We all know the amount of data in the world is growing exponentially
  • 17. Big Data Opportunity for Marketers Seamlessly connecting to relevant customer activity Powerful Insights from Combined Data
  • 18. The Value of Big Data Marketing related use cases Drive incremental revenue • Understand and monetize customer behavior • Personalize customer experience • Predict customer behavior across all channels
  • 19. Big Data Driven Marketing Use Cases ONLINE RETAILER Understand buying patterns of five million users via click stream data GAMING Better monetization of premium game features via player data analysis SOCIAL COMMERCE Better campaign performance via analysis of social media, page clicks and email data TRAVEL/ENTERTAINMENT Enable thousands of travel partners to improve promotional targeting ON-LINE ADVERTISING Real-time analysis of customer data for personalized offers & targeted advertising CUSTOMER LOYALTY Enable customer behavior and social media driven marketing & rewards programs Big data combined with operational data
  • 20. IT IS HARD • Big data technology is immature • Few big data coding experts • Use case must be clear So why doesn’t everyone take advantage of big and diverse data?
  • 21. Find Optimal Campaign and Promotion Mix Understand Best Marketing Activities and Interactions Analytics BLEND Relevant Data On- Demand Leverage Your Company’s Big Data Projects DECIDE & ACT! Big Data Store Social Website Operational Data Store/Analyt ics Marketing Sales Customer Find where the data lives and get the right tools
  • 22.
  • 23. Metrics that Matter Get a seat at the table: Know impact to business goals Drive Net New Business 1. Marketing Qualified Leads (MQLs) 2. Sales Accepted Opportunities (SAOs) 3. MQL to SAO Conversion Percentage Drive Thought Leadership 4. Share of Voice 5. Press and Analyst Influence
  • 24. BUT, Metrics Data Lives in Various Sources Each data set is an important part of the total picture SOCIAL & WEBSITE Marketing Forecast Model WW Net New Amount Non Core Net New Amount Target Net New Historical Average Deal Size Historical Close Rate % Historical CarryOver % Lost % $1,750,000 $0 $1,750,000 $28,000 0% 15% 85% Plan Date SAO 5% Goal Distribution % CarryOver Units Open Units Forecast Units Accumulated Units Close Rate % Forecast Win Units Average Deal Size Forecast Net New Amount Dec-01-2012 200 14.4% 38 306 29 373 15% 56 50,000 $2,796,273 Jan-01-2013 200 16.3% 56 48 61 165 15% 25 50,000 $1,239,812 Feb-01-2013 200 20.3% 25 50 102 177 15% 27 50,000 $1,326,149 Mar-01-2013 260 15.9% 27 53 142 222 15% 33 50,000 $1,664,255 Apr-01-2013 260 10.1% 33 2 172 208 15% 31 50,000 $1,557,471 May-01-2013 260 7.1% 31 3 199 233 15% 35 50,000 $1,746,635 Jun-01-2013 310 5.4% 35 8 226 269 15% 40 50,000 $2,018,854 Jul-01-2013 310 2.6% 40 3 246 289 15% 43 50,000 $2,167,950 Aug-01-2013 310 3.1% 43 1 266 311 15% 47 50,000 $2,330,184 Sep-01-2013 400 2.7% 47 296 342 15% 51 50,000 $2,568,541 Oct-01-2013 400 1% 51 1 319 372 15% 56 50,000 $2,786,521 Nov-01-2013 400 0.8% 56 344 400 15% 60 50,000 $3,000,862 Dec-01-2013 120 0.3% 60 323 383 0% 0 28,000 $0 Tue Dec 11 02:48:22 EST 2012 Forecast Snapshot Date : 12/01/2012 Sales Country Type : 'Core' Sales Region : '*ALL*' Rate Period : 10/01/2012 PIPELINE & BOOKINGS FORECAST LEADS & OPPORTUNITIES Multiple reports hard to manage
  • 25. Manage Optimal Campaign & Content Mix by Target Audience Understand Marketing Campaigns that Drive Closed Won Deals Analytics Our Approach – Blend and Analyze Assess Impact of Campaigns from Various Data Sources Focus on Highest ROI: Optimize Limited Marketing Resources BLEND Relevant Data On- Demand Operational Data Store/Analyt ics Big Data Store
  • 26. Monitoring Trends to Make an Impact Big data, small data blended for full picture
  • 27. We Start with Booking Goals • Leads by Campaign Types • 20 Major Nurturing Tracks: 6 – 10 Touches • Lead Conversion to Sales Opportunity • Nurturing Effectiveness • Opportunities across Sales Stages to Closed • Effectively Forecast Sales Results Revenue Foundation: Must be Timely, Accurate and Actionable Expect to manage the entire marketing/sales flow
  • 28. Blend Key Sources that Matter A single view into the health of Pentaho How do I target and influence my most ready-to-buy prospects? • Ads • Events • Software Trials • Social • Forums • Email • Website • Search • Webinars • …
  • 29. Gain Insight into the Funnel 2. How do created SAOs impact pipeline? 3. How much pipeline is closed won? 4. What’s average deal size? 1. How do MQLs move thru the lead funnel? Four fundamental metrics to understand deeply MQLs to SAOs • 20% - Current Month • 30% - Next Month • 50% - Next 3 Months Expected close date • 32% - Current Qtr • 27% - Previous Qtr • 41% - Prior to that Deal Size • $200k - Current Qtr • $250k - Previous Qtr • $375k – Prior to that Close won % • 15% - Current Qtr • 26% - Previous Qtr • 10% - Prior to that
  • 30. The Rest is Math Qtr Pipeline Needed SAOs Created to Date Gap MQL Created Current Qtr MQL Created Qtr +1 MQL Created Qtr +2 Current Qtr 1,250 1,000 250 250 Qtr +1 1,500 1,000 500 350 Qtr +2 2,000 500 1,500 800 Need to create 250 + 350 + 800 = 1,400 MQLs in the current quarter Waterfall effect of how leads created drive future pipeline
  • 31. Final Step: Once Know Goals… Market Creatively and Aggressively

Editor's Notes

  1. Our #1 secret is that we believe that buying has changed forever, and that marketing and sales need to change as well.Not that long ago, there were few 3rd party sources of information – information scarcity – which meant that a buyer had to get most of their information from sales. In this world, it made perfect sense for marketing to pass all leads over to sales. It also meant we lived in a world of attention abundance, with fewer channels competing for a buyer’s attention. Traditional marketing, characterized by Mad Men-style marketing, grew up in this era.
  2. But now, there is an explosion of readily available information… According to IBM, we create 2.5 quintillion bytes of data — so much that 90% of the data in the world today has been created in the last two years alone.This is a recent phenomenon…When Marketo was founded in 2006, the iPhone didn’t exist, Twitter had not launched, and Facebook was only for college students. All this data = buyers today are more empowered. The Web provides them with instant information gratification. They can access detailed specs, pricing, and reviews about goods and services 24/7 with a few flicks of their thumbs. Meanwhile, social media encourages them to share and compare, while mobile devices add a wherever/whenever dimension to every aspect of the experience. Result: Forrester Reports that 65-90% of buying process is complete when consumer is walks into store/branch/dealer, or contacts salesRequires deep changes in how we market to consumers. That’s how we approached our marketing process at Marketo.
  3. Your consumer is like a sponge, and all those marketing messages are like the water.How do you ensure that your message is the one of the 4 that get absorbed into the sponge? After all, a potential buyer can only absorb so much, and your competitors are vying for their attention too.
  4. We’ve moved from a manufacturing economy to an experience economy. Today, businesses have to create amazing, memorable experiences, rather than simply delivering reliable products at the right price. But this is more critical than ever in a world awash in instantaneous, high-volume information delivered through every conceivable channel.While oil fueled the manufacturing economy, data is the fuel that drives the experience economy. But unlike oil, data is increasingly abundant. In some cases, it’s overwhelmingly abundant–leading to the phrase “Big Data”.
  5. Icons are nice and the build-order is great!My suggestion the top 3 icons on the left-hand side:CustomerProvisioningBillingSuggestion for the bottom 3 icons:WebNetworkSocial Media(note: Location seems to be important to AT&T but we can just mention this)I need to come up with an explanation for why the arrow below “Just in Time Integration” is bi-directional instead of just flowing to Analytics
  6. Many marketers are perceived as a cost center. You can’t expect your organization to place value on something you’re unable to quantify. But when you do use the right metrics and processes, there is nothing more powerful to help marketing earn it’s rightful seat at the revenue table.Here I show you how Marketo does it.
  7. Here we see what works for Marketo over the last 12 months to generate prospects. Explain columns…Website+Blog = 38% of all oppsBut I’d be a bad stock picker if I put all my money in one stock, and I’d be a bad marketer if I bet all my prospect generation on one source. The reality is you need a portfolio of prospects and channels to achieve the best results. In fact, Marketo runs an average of 40 different Prospect generating programs each and every month across all these sources.
  8. ModelNote Success Path and Detours; Inventory and SLAs
  9. Google Analytics for Revenue