Big Data, Big Revenue: How Big Data Means Millions for Marketing


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  • 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.
  • 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.
  • 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.
  • 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”.
  • 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
  • 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.
  • 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.
  • ModelNote Success Path and Detours; Inventory and SLAs
  • Google Analytics for Revenue
  • Big Data, Big Revenue: How Big Data Means Millions for Marketing

    1. 1. Big Data, Big Revenue: How Big Data Means Millions for Marketing Jon Miller Rosanne Saccone
    2. 2. Pentaho Corp Enabling the modern big data driven business Business Analytics for all Data Any Analytics Any Data
    3. 3. We all know the amount of data in the world is growing exponentially
    4. 4. Big Data Opportunity for Marketers Seamlessly connecting to relevant customer activity Powerful Insights from Combined Data
    5. 5. 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
    6. 6. Big Data Driven Marketing Use Cases Big data combined with operational data ONLINE RETAILER ON-LINE ADVERTISING Understand buying patterns of five million users via click stream data Real-time analysis of customer data for personalized offers & targeted advertising GAMING TRAVEL/ENTERTAINMENT Better monetization of premium game features via player data analysis Enable thousands of travel partners to improve promotional targeting SOCIAL COMMERCE Better campaign performance via analysis of social media, page clicks and email data CUSTOMER LOYALTY Enable customer behavior and social media driven marketing & rewards programs
    7. 7. So why doesn’t everyone take advantage of big and diverse data? IT IS HARD • Big data technology is immature • Few big data coding experts • Use case must be clear
    8. 8. Leverage Your Company’s Big Data Projects Find where the data lives and get the right tools DECIDE & ACT! Analytics Customer Sales Operational Data Store/Analyt ics BLEND Relevant Data OnDemand Marketing Social Website Find Optimal Campaign and Promotion Mix Big Data Store Understand Best Marketing Activities and Interactions
    9. 9. 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
    10. 10. BUT, Metrics Data Lives in Various Sources Each data set is an important part of the total picture SOCIAL & WEBSITE LEADS & OPPORTUNITIES PIPELINE & BOOKINGS FORECAST Marketing Forecast Model WW Net New Amount Non Core Net New Amount Target Net New $1,750,000 $0 $1,750,000 Plan Date SAO 5% Distribution Goal % CarryOver Open Units Units Historical Average Historical Close Deal Size Rate % $28,000 Historical CarryOver % 0% Forecast Accumulated Close Rate Units Units % 15% Lost % 85% 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% 51 319 372 15% 56 50,000 $2,786,521 Nov-01-2013 400 0.8% 56 344 400 15% 60 50,000 $3,000,862 60 323 383 0% 0 28,000 $0 Multiple reports hard to manage Dec-01-2013 120 0.3% Forecast Snapshot Date : 12/01/2012 Sales Country Type : 'Core' 1 Rate Period : 10/01/2012 Sales Region : '*ALL*' Tue Dec 11 02:48:22 EST 2012
    11. 11. Our Approach – Blend and Analyze Assess Impact of Campaigns from Various Data Sources Focus on Highest ROI: Optimize Limited Marketing Resources Analytics Operational Data Store/Analyt ics BLEND Relevant Data OnDemand Big Data Store Manage Optimal Campaign & Content Mix by Target Audience Understand Marketing Campaigns that Drive Closed Won Deals
    12. 12. Monitoring Trends to Make an Impact Big data, small data blended for full picture
    13. 13. We Start with Booking Goals Expect to manage the entire marketing/sales flow • 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
    14. 14. Blend Key Sources that Matter A single view into the health of Pentaho • • • • • Ads Events Software Trials Social Forums How do I target and influence my most ready-to-buy prospects? • • • • • Email Website Search Webinars …
    15. 15. Gain Insight into the Funnel Four fundamental metrics to understand deeply MQLs to SAOs 1. How do MQLs move thru the lead funnel? • 20% - Current Month • 30% - Next Month • 50% - Next 3 Months Expected close date 2. How do created SAOs impact pipeline? • 32% - Current Qtr • 27% - Previous Qtr • 41% - Prior to that Close won % 3. How much pipeline is closed won? • 15% - Current Qtr • 26% - Previous Qtr • 10% - Prior to that Deal Size 4. What’s average deal size? • $200k - Current Qtr • $250k - Previous Qtr • $375k – Prior to that
    16. 16. The Rest is Math Waterfall effect of how leads created drive future pipeline Qtr Pipeline Needed SAOs Created to Date Gap MQL Created Current Qtr Current Qtr 1,250 1,000 250 250 Qtr +1 1,500 1,000 500 Qtr +2 2,000 500 MQL Created Qtr +1 1,500 MQL Created Qtr +2 350 Need to create 250 + 350 + 800 = 1,400 MQLs in the current quarter 800
    17. 17. Final Step: Once Know Goals… Market Creatively and Aggressively