Use Data Strategy and Customer Analytics to Drive Business Decisions. Alison Shaffer August 26, 2010

Transcription

1 Use Data Strategy and Customer Analytics to Drive Business Decisions Alison Shaffer August 26, 2010

2 Agenda Intro to WebEx Importance of data strategy and framework Increasing data usability Applying the framework to multiple types of analysis: customer analysis free trial conversion adoption measurement P2B model usage Lessons learned/best practices 2

3 Joined Cisco family in May 2007 Headquartered in Santa Clara, CA Leader in Software-as-a-Service (SaaS) industry Provides on-demand web collaboration applications delivered via the Cisco WebEx Collaboration Cloud Online meetings Web conferencing Video conferencing applications 3

4 More Facts We re global: WebEx has customers in 150 countries We service SMB through Enterprise size companies 90% of Fortune 500 companies are WebEx customers We have 10+ million registered hosts worldwide We re busy each month! On average we host: 4.6 million meetings per month, with over 16 million meeting attendees Our newest accomplishment: WebEx reached 1 billion meeting minutes in May

5 You can have data without information, but you cannot have information without data. Daniel Keys Moran - writer

6 Data is the Key All successful marketing strategies are based on a foundation of actionable and usable data Data is the key driver for making business decisions Drives business objectives Used to evaluate progress and success Data is dynamic Data quality changes over time depending on interactions, transactions 6

7 The Foundation: a Data Strategy Determine business areas where insight/knowledge is needed Identify opportunities to apply analytics and statistical methodology Develop a data framework to optimize processes involving collection, usage and delivery of data 7

8 Build a Scalable Framework A dynamic and efficient process to Collect, Access, and Deliver data Collect Deliver Access 8

9 Collect Collect Examples: Data Point Metric/Measurement Transactional Made X purchases/spent X dollars Product Usage Had 5 meetings last month Website Spends 10 minutes on website/day Campaign Response Responded to X campaigns in FY06 Contact History Received 3 s in March Firmagraphic SIC Code 8741 Market Research Gartner Tier 1 Collect from multiple sources and load into system Challenges: Standardization, global, compliance Cross Company Social Media Contact Preferences Owns Cisco IP Phone WebEx Facebook fan -Yes Mail-No Phone-No 9

10 Access Access Retrieve data from multiple systems Data is queried to run reports, output lists for targeted marketing, conduct customer analysis Challenges: Ability to access in correct format, locate all sources 10

11 Deliver Deliver Data, reporting and analysis is distributed to stakeholders Challenges: frequency, tools to use, stakeholder criteria, scalability, ability to automate, consistency 11

12 Increase Data Usability Deliver Collect Access The level of actionability from your data Integrity, accuracy, hygiene How effectively you re able to leverage information to make decisions Quality vs. quantity Companies with highly usable data are able to: Drive initiatives that leverage, data driven decisions Transform raw data into useful information Increase the quality of insights Measure results and create benchmarks 12

13 Two Effective Methods for Increasing Data Usability 1. Continuous Investigation Audit, monitor data Run reports, play with data, look for anomalies Data Governance, DMM Methodology 2. Append Supplement current data with new data Use multiple sources Load into CRM system or data mart 13

14 Append: Using Multiple Data Sources Original Record Entered into SFDC by rep: Company Name: Consulting & Chad Hoovers ZoomInfo D&B Factiva D&B D&B Jigsaw Cisco Contacts DB Company Name: IT Consulting By Chad Decision Maker and Title: Chad Nicholas, CEO SIC Code: 8741 Industry Category: Business Services/Consulting Years in Business: 12 Number of Employees: 17 Additional Contacts: Liza Nicholas, IT Buyer; Polly Shaffer, CIO Cisco Customer? Yes Cisco Product? IP Phone 8900 series 14

15 Many choices 15

16 How does the data framework impact WebEx Analytics? Collect Deliver Access Customer Analysis Free Trial Conversion Adoption Measurements P2B Model Usage 16

17 Customer Analysis Most common type of analysis request; educate on basic customer profile or dig deeper into firmagraphic and behavior correlations Important: Align customer definition across the company organizations Using Framework Collect: Identify data elements needed Access: Can we retrieve most recent customer activities? 17

18 Customer Breakdown by Vertical 57% of WebEx customers are part of the Services industry SIC/ Vertical Groups % Cust Services 57% Manufacturing 11% Finance 11% Wholesale 5% Communications 3% Insurance 3% Government 3% Retail 1.5% Transportation 1% Mining 0.5% Construction 0.5% Real Estate 0.5% Agriculture, 0.5% Energy,Utilities 0.5% Using Framework: What kinds of businesses make up Services? Services % Cust High Tech 59% Consulting 11% Travel & Tourism 5% Education 4% Engineering/Biotech 3% Health Care 3% Media/Advertising/PR 3% Accounting 2% Legal 2% Access: data from multiple sources; SFDC, customer database Deliver: format and frequency Insight for Marketing: How to target Examine segment for more similarities 18

19 SMB Conversion Rate From Different Verticals Lead Conversion by SIC/Vertical SIC/Vertical % All Leads Accepted % Upgraded to Opps % All Deals High Tech - Software 28.7% 14.0% 29.0% Services- Consulting 14.0% 11.3% 13.2% Health Care 9.2% 7.6% 4.2% Wholesale 6.6% 9.1% 7.0% Manufacturing 5.3% 9.2% 10.0% Education 5.3% 6.0% 3.1% Financial Services 4.5% 7.3% 7.2% Telecommunications 3.4% 8.0% 2.9% High Tech - Hardware 2.6% 8.0% 12.9% Retail 2.3% 3.2% 1.9% All Other 18.2% 16.4% 8.6% Using Framework: Access: multiple sources; SFDC, D&B Deliver: appropriate stakeholders, frequency Insight for Marketing: High or low contribution to leads does not always equal high or low conversion; needs deeper analysis 19

20 Buyer Conversion From Free Trial 3 Easy Steps 1 2 Sign Up Use Buy 3 Conversion rate: sign up to user: 71% Conversion rate: user to buyer: 20% 20

21 Which Sources Contribute the Most to Free Trial Buyers? Top 10 Sources of Free Trial Leads Track ID Lead Source Name % all leads Contact us link -WebEx.com 51.5% Quick Tour Link Free Trial 11.0% Free Trial link 7.0% Buy page CTA 5.0% SEM 4.7% SEM 4.1% CTA 3.5% Post Meeting Attendee Page 2.7% Ft link on /login page 2.5% SEM 2.2% Using Framework: Collect: How much data can be collected during sign up Conversion rate: user to buyer: 20% More analysis needed on 80% who did not convert 21

22 Adoption: Enterprise Customer Segment Objective: Develop methodology for identifying adoption levels in Enterprise segment First step: define adoption/usage/utilization Using Framework: Collect: ideal project to add qualitative data, identify relevant metrics needed to measure behavior Access: from multiple sources; including product 22

23 Multiple ways to measure adoption Measurement #1: Which measurement meets objective and is actionable? Total number active hosts vs. total number host licenses purchased Measurement #2: Total number of meetings in specific time period vs. Total number of attendees during time period Measurement #3: Total number of knowledge workers in company vs. total number of WebEx registered hosts in company Available Metrics: Total host licenses purchased Total registered hosts Total active hosts Total Meetings Average meetings per week/month Total Attendees Average attendees per meeting Total Employees Total PC s Total Knowledge Workers 23

24 Develop Adoption Metric Comparison of Adoption Rates in Enterprise Customer Segments Segment Adoption Rate % total Franchise 81% or more 22% Footprint 80% - 21% 20% Greenfield 20% or less 58% Compares current number of active hosts vs. number of host licenses the company purchased Run cluster analysis to find best groupings Identify segments of customers with high adoption opportunities Using Framework: Collect: Identify data sources for future analysis 24

25 Use Cohort Analysis to Determine Churn Rate Program To Date Overall Churn Rate 8-Aug 8-Sep 8-Oct 8-Nov 8-Dec 9-Jan 9-Feb 9-Mar 9-Apr 9-May Total Total Orders 463 1,016 1, ,146 1,121 1,263 1, ,535 Users as of 5/ Churn Rate 31% 31% 27% 25% 20% 17% 12% 11% 4% 1% 16% Retention Rate 69% 69% 73% 75% 80% 83% 88% 89% 96% 99% 84% Develop a simplified churn rate for high level trending and to identify areas needing additional analysis Use total orders each week, and apply co-hort methodology to identify remaining active users and calculate churn and retention rates Using Framework: Access: Sometimes unable to retrieve ideal data needed Deliver: Additional insight needed, as churn rate by itself not always actionable 25

26 Leverage P2B Model from Cisco Business Intelligence Group Cisco uses P2B models to identify likelihood of purchase from multiple technology groups; including: Switching, Routing, Wireless, UC, Security; added WebEx as new group Model results give us ability to: Build high value prospect universe by identifying Cisco customers who have high likelihood to purchase WebEx products Using Framework: Collect: Qualitative information from internal group so you have full understanding of all data being used Access: Collaborate with other internal groups to retrieve data 26

27 Learnings/Best Practices A solid data framework guides multiple types of data efforts Collect Deliver Access 27

28 Learnings/Best Practices Agree on data definitions before starting project, Data Governance, DMO Set up new data sources for future use Consistently seek feedback from stakeholders Set expectations Be creative when exploring possible data sources Good behavorial data is not always obvious or yet identified need to dig Develop consistent measurements and formats when delivering reports and analysis Always deliver actionable data with insight Document-Document-Document Promote the work-be visible Increase Data Usability! 28

29 Questions? Thank You 29