The path to marketing accountability and business impact is lined with data

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1 AND ITSMA Online Survey Abbreviated Summary April 2011 Julie Schwartz ITSMA Susan McKittrick Susan Aldrich Patricia Seybold Group Final Report March 2011 SV4581 The path to marketing accountability and business impact is lined with data If you have a data-driven marketing organization, you will see business benefits that fall directly to the bottom line. But becoming data driven isn t easy and takes time ITSMA and Patricia Seybold Group. All Rights Reserved. 2 Page 1

2 B2B services marketers recognize that data driven marketing is important How important is data driven marketing (making decisions based on data and analysis) to your marketing organization? % of Respondents(N=107) Mean Rating= =Not at All Important =Very Important Note: Mean rating based on a 5-point scale where 1=not at all important and 5=very important. Source: ITSMA and Patricia Seybold Group Survey:, March ITSMA and Patricia Seybold Group. All Rights Reserved. 3 Most embrace the test and learn approach so critical in today s marketing How strongly do you agree or disagree with the following statement? Our executive leadership embraces a test and learn approach to marketing, enabling us to conduct controlled experiments or limited pilots to determine the effectiveness of marketing programs and campaigns before rolling them out fully. 13 Strongly Agree Mean Rating= Agree Neither Agree nor Disagree Disagree Strongly Disagree Note: Mean rating based on a 5-point scale where 1=strongly disagree and 5=strongly agree. Source: ITSMA and Patricia Seybold Group Survey:, March ITSMA and Patricia Seybold Group. All Rights Reserved. 4 Page 2

3 Yet, very few considers themselves as leading edge users of marketing data How would you characterize your overall level of data usage to support marketing activities? Leading edge. We use data analysis to make both tactical and strategic decisions, such as estimating the impact of marketing investments on revenue (in addition to what is described below) 11 Above average. We use data analysis to make tactical decisions that improve the impact of marketing such as optimizing the landing pages (in addition to what is described below) 28 Average. We regularly collect and report data, providing organized information in reports or dashboards to show the impact of marketing 48 Back of the pack. We rely primarily on anecdotal information to show the impact of marketing 13 Source: ITSMA and Patricia Seybold Group Survey:, March ITSMA and Patricia Seybold Group. All Rights Reserved. 5 And only a handful of senior executives are relying on marketing data to make decisions To what extent are other functions or organizations using the data and metrics developed by marketing? BU or Division leaders Sales CEO Service delivery/ operations COO CTO CFO/ Finance Don't Know Does Not Use Marketing Data At All Receives Marketing's Reports Reviews Marketing's Reports, Asks Questions, Provides Feedback Holds Marketing Accountable for Performance Relies on Marketing Data to Make Decisions Source: ITSMA and Patricia Seybold Group Survey:, March ITSMA and Patricia Seybold Group. All Rights Reserved. 6 Page 3

4 We identified 23 data savvy organizations in our study sample: data savvy organizations have three important characteristics that help drive business benefits A Culture that Places Importance on Making Decisions Based on Data and Analysis Formalized Data Collection Processes and Clear Expectations Leading Edge or Above Average Data Usage to Support Marketing Activities 2011 ITSMA and Patricia Seybold Group. All Rights Reserved. 7 The data savvy report shorter sales cycles and lower sales costs In your last fiscal year, how did your sales organization perform in the following areas: % of Respondents Compared with two years ago our average Time to Revenue (Pipeline velocity: time from sales-accepted lead to deal closure) was:* Compared with two years ago our Sales Cost per Order Dollar (cost of sales divided by revenue) was:* Data Savvy (N~21) Data Savvy (N~21) All Other (N~62) All Other (N~62) Significantly or somewhat longer About the same Significantly or somehwat shorter Significantly or somewhat higher About the same Significantly or somehwat lower *Indicates a statistically significant difference. Source: ITSMA and Patricia Seybold Group Survey:, March ITSMA and Patricia Seybold Group. All Rights Reserved. 8 Page 4

5 They also report greater improvement in market share in the last two years In your last fiscal year, how did your marketing organization perform in the following area: % of Respondents Compared with two years ago our Market Share was:* Data Savvy (N=22) All Other (N=77) Significantly or somewhat worse About the same Significantly or somehwat better *Indicates a statistically significant difference. Source: ITSMA and Patricia Seybold Group Survey:, March ITSMA and Patricia Seybold Group. All Rights Reserved. 9 What characterizes this better performing data savvy group? 2011 ITSMA and Patricia Seybold Group. All Rights Reserved. 10 Page 5

6 The Data Savvy: Rely more on data and analysis when making marketing decisions Use marketing data much more extensively Are also technology savvy Use more technologies and methodologies and for a significantly longer period of time Have worked to address data governance challenges Have dedicated analytics groups 2011 ITSMA and Patricia Seybold Group. All Rights Reserved. 11 Nevertheless, even the data savvy are not quite there yet 2011 ITSMA and Patricia Seybold Group. All Rights Reserved. 12 Page 6

7 Even in data savvy organizations Marketing data is not widely used to make decisions that impact the business Marketing faces familiar challenges: Lack of budget/resources/time Lack of integrated data/centralized database (data resides on multiple systems) Poor data quality Lack of IT systems and tools for data collection and analysis requiring time consuming manual processes Lack of analytical and/or data management skills in the marketing department Difficulty linking marketing performance metrics to business metrics Source: ITSMA and Patricia Seybold Group Survey:, March ITSMA and Patricia Seybold Group. All Rights Reserved. 13 Data driven marketing is an iterative learning process Experience counts. Perseverance will pay off! 2011 ITSMA and Patricia Seybold Group. All Rights Reserved. 14 Page 7

8 What does it take to become data savvy? Get started as soon as possible Start small, demonstrate value, build the business case, expand incrementally Set objectives and develop an executive champion. Consult with the CFO and major users of marketing data (sales, business units). Designate/hire leader for analytics group Develop plan and identify measures to track progress toward goals Develop a three-year rolling marketing technology strategy and roadmap Hire a chief marketing technologist to liaise with IT Work towards a centralized customer database Invest in the technology, training, and systems administrator Undertake change management initiatives to establish skills, processes and organizational practices needed to leverage the new capabilities (start before purchase) (Continued) (Continued) 2011 ITSMA and Patricia Seybold Group. All Rights Reserved. 15 What does it take to become data savvy? (Continued) Identify sources for all marketing-related data and gain cooperation of functions/geographies that oversee it Establish processes for collecting, sharing, updating, and using marketing-related data Document data governance policies and procedures, implement appropriate actions Move towards managing marketing data at an enterprise level (i.e., across functions, geographies, etc.) Build a dedicated analytics group Develop formalized written processes Provide training on analytics to all marketing staff Establish a reporting routine, creating reports tailored to the needs of each major user of marketing data Hold weekly or monthly meetings with each non-marketing department head to review reports and modify plans or actions as needed Collect and publish success stories Continue to discover organizational uses of marketing data 2011 ITSMA and Patricia Seybold Group. All Rights Reserved. 16 Page 8

9 Methodology and Respondent Demographics 2011 ITSMA and Patricia Seybold Group. All Rights Reserved. 17 Methodology Online Web-based survey and 17 follow-up 30-minute qualitative phone interviews Survey invitations were ed during March 2011 to ITSMA member and nonmember companies 107 representatives from 71 companies responded to the Web survey ITSMA analyzed the data by: Company type (Sells products and services or Primarily services) Annual revenue (Less than $250M, $250M $5B, More than or equal to $5B) Degree of data usage and maturity (Data savvy and All others) Source: ITSMA and Patricia Seybold Group Survey:, March ITSMA and Patricia Seybold Group. All Rights Reserved. 18 Page 9

10 Participating Companies Aditya Birla Minacs Alcatel Lucent Amdocs Aon Hewitt Aprimo ArcSight, an HP Company AT&T Avanade Avaya Aviat Networks Basware Black & Veatch BT GS C&N Capgemini CA Technologies CGI Cisco Systems Cognizant Colt CompuCom Systems, Inc. Convergys Crimson Consulting CRU Solutions CSC CSS Corp Deloitte Dimension Data Eloqua Emerson Network Power Avocent Ericsson AB Event 360 Firstsource Fujitsu HCL Technologies HP I-Lek Technology Inc. IAG Consulting IBM Global Business Services Infosys Infotech Enterprises ISBEL Istituto Internazionale di Ricerca ITC Infotech Juniper Networks KPIT Cummins Infosystems Ltd. Microsoft Motorola Solutions NAUMEN NHANZ NSN OBS Global Orange Business Services Patni Americas Planwork Ltd. PointBridge SAP Siemens Enterprise Communications Siemens Medical Solutions SunGard Syclo Tata Consultancy Services Limited Thirdware Unisys Williams Lea Wipro Technologies Wood Mackenzie Source: ITSMA and Patricia Seybold Group Survey:, March ITSMA and Patricia Seybold Group. All Rights Reserved. 19 Industry Sector Which of these categories best describes your industry subsector? 5 Other Telecommunications Services Provider Network Systems and Solution Provider Computer Systems and Solutions Provider Software Solutions Provider 45 Professional Services Firm (Consulting, outsourcing, and systems integration) Source: ITSMA and Patricia Seybold Group Survey:, March ITSMA and Patricia Seybold Group. All Rights Reserved. 20 Page 10

11 Role, Type of Business, and Services Offerings Which of the following best describes your role at your company? Marketing senior executive (CMO, SVP, VP, AVP) 22% 78% Marketing director/ manager How would you describe your company s business? Do you sell: Primarily services (10% or less revenue from products) 50% 50% Both products and services How would you describe your company s services offerings? Both B2B and B2C 13% 87% 100% B2B Source: ITSMA and Patricia Seybold Group Survey:, March ITSMA and Patricia Seybold Group. All Rights Reserved. 21 Size of the Services or Solutions Business How large is your services or solutions business? Greater than $5B in services revenue 34 $1 5B in services revenue $ M in services revenue $ M in services revenue $ M in services revenue $50 99M in services revenue Less than $50M in services revenue Source: ITSMA and Patricia Seybold Group Survey:, March ITSMA and Patricia Seybold Group. All Rights Reserved. 22 Page 11

12 Region In which geography are you based? Australia (2%) South or Central America (2%) Asia (14%) North America (57%) Europe (25%) Source: ITSMA and Patricia Seybold Group Survey:, March ITSMA and Patricia Seybold Group. All Rights Reserved. 23 Definitions: Types of Marketing Data Marketing programs (e.g., how much they cost, new contacts identified, existing prospects touched, likely revenue impact from program) Customers (e.g., who they are, what they bought, what they are likely to buy in the future, how satisfied/loyal they are, how profitable they are) Sales-accepted leads (e.g., who they are, how they found the company, what they are likely to buy and when) The competition (e.g., perceptions of competitors, market share, pricing, offerings) Markets (e.g., how much market segments are spending and with whom, what issues affect future spending, perceptions of company brand, awareness measures) Contacts whom marketing is nurturing (e.g., who they are, how they found the company, what interests them, how likely they are to buy) Source: ITSMA and Patricia Seybold Group Survey:, March ITSMA and Patricia Seybold Group. All Rights Reserved. 24 Page 12

13 Definitions: Data Gathering Analysis Technologies and Methodologies marketing metrics: measures used to track, s delivery and actions taken by the recipient (open, click through, forward, etc.) Lead management reporting: tracking lead progress through the phases of a lead management process. Website analytics: structuring analysis, measuring and reporting on web visitor traffic and behavior tied to specific conversion events. Campaign management metrics: campaign attributes and activity and performance measures. Web visitor behavior tracking: reporting individual web visitor behavior, often in realtime. Customer analytics: analyzing data about behavior of customer segments. Lead scoring and routing: assigning scores to characteristics and behaviors of leads to indicate readiness to buy and then applying rules to route leads for appropriate action based on cumulative score during a time period. Marketing asset management: tools to streamline the collection, access, production, distribution, and archiving of marketing content. Revenue attribution/management: techniques for assigning marketing influence over touchpoints that preceded generation of revenue. Marketing resource management: tools for planning, budgeting, scheduling, expense control, workflow management, and performance tracking. Dynamic list segmentation: automated segmentation of list based on responses to a campaign or updated/new attributes in the list. Predictive analytics: analyzing data to develop models for predicting future actions. Social media monitoring: tracking and reporting of social media content to determine activity and sentiment around a brand or topic. A/B testing: comparison of performance of a control sample to a variety of samples that have a single variable changed. Progressive profiling: gradual gathering of web visitor information by asking one or two additional questions each time a visitor registers to complete an action such as a download. Social media sentiment analysis: analyzing social media content to determine the tone (e.g., positive, negative, neutral) of content around a brand or a topic. Multivariate testing: a technique for testing hypotheses on complex multi-variable systems, especially used in testing market perceptions ITSMA and Patricia Seybold Group. All Rights Reserved. 25 Appendix: Table of Contents for ITSMA Online Survey Slide Executive Summary 3 Methodology and Respondent Demographics 27 Detailed Results 36 Business, Marketing, and Sales Performance 37 Using Marketing Data 42 Types of Marketing Data 52 Data Gathering Analysis Technologies and Methodologies 58 Analysis by Marketing Data Usage and Maturity 63 Analysis by Type of Company 103 Analysis by Company Size 145 Appendix: Definitions Used in this Study 187 Full report available at ITSMA and Patricia Seybold Group. All Rights Reserved. 26 Page 13

14 AND For More Information Julie Schwartz Senior Vice President Research and Thought Leadership ITSMA Phone: ITSMA and Patricia Seybold Group. All Rights Reserved. 27 Page 14