Leveraging the Microsoft BI Stack to provide a Digital Marketing Dashboard Chris Kuelbs, Lead Project Manager Polaris Industries 1
About Polaris Annual 2009 sales of $1.6 billion Polaris designs, engineers, manufactures and markets all terrain vehicles (ATVs), including the Polaris RANGER, snowmobiles and Victory motorcycles for recreational and utility use. Victory motorcycles, established in 1998, represents the first allnew American made motorcycle from a major company in nearly 60 years. Polaris also enhances the riding experience with a complete line of Pure Polaris apparel, accessories and parts, available at www.purepolaris.com. Information about the complete line of Polaris products is available anytime from the Polaris homepage at www.polarisindustries.com. 2
Our Current Reality Product groups are truly different business units and as a result are very much siloed. There is not one true source of truth- different areas report the same information from different sources. Lack of data standards- the same term can be defined differently by different people. Technology varies- multiple reporting tools that do not lend themselves to allowing the user to be self-sufficient. 3
4 Where is Polaris?
5 The Genesis of BI at Polaris
Our Daunting Task Shift our thinking from 1.0 to 2.0 Use relevant content and one-to-one marketing to capture leads, pull them down the purchase funnel and deliver to our dealers on the 1 yard line BUILD THE BEST WEBSITE IN THE POWERSPORTS INDUSTRY 6
Our Solution Analytics Reporting KPI s Scoring 1) Life time value 2) Propensity to buy Marketing Online/Offline Advertising & Promotions Leads Capturing names Building profiles CRM Dynamic Content Pull consumers Relevancy Website/Email/Direct Mail Promotions Offers Targeted Marketing Dealer Tools Backward/forward CRM integration Higher quality information Improved prospect ranking system Robust reporting 7
Cool stuff but.. MS CRM Webtrends MS SQL Server ALL Web KPI Dashboard KPI JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC Leads Engagement Total Visits 2008 871,746 919,325 944,554 767,696 865,941 738,179 981,738 1,062,249 912,007 919,688 787,779 751,481 2009 1,106,578 843,892 991,911 Total Visitors 2008 638,306 690,694 553,048 573,267 673,820 574,794 752,956 811,235 692,931 698,295 603,432 575,380 2009 773,761 635,544 741,869 Total Registered Visitors 2008 N/A N/A 65,415 71,293 68,739 66,071 63,941 65,798 55,584 61,087 61,524 56,008 2009 84,540 64,535 61,202 % of reg. Visitors/Leads 2008 N/A N/A 44% 38% 35% 38% 42% 48% 39% 49% 53% 36% 2009 61% 54% 68% # Of Unique Leads 2008 N/A 13,588 29,014 26,934 24,301 24,782 26,567 31,335 21,719 29,700 32,304 19,894 2009 51,792 34,567 41,668 # Of New Unique Leads 2008 N/A 13,588 28,029 24,101 20,186 19,158 20,685 16,879 13,272 19,140 23,929 17,086 2009 37,800 24,690 21,245 Web Influence Web Units Influenced 2008 N/A 90 1,041 1,111 1,403 746 871 951 1,074 1,099 720 1,116 2009 622 1,006 1,223 % of Reg. Visitors Influenced % of Total Units Sold Total Units Sold Total Hot Prospects % Hot Prospect Units Influenced Hot Prospect Units Influenced % Of Total Units Sold Online Engagement Total Visitors % Of Campaign Acquisition Awareness Wishing Consideration Average Reg. Visitor Score 2008 N/A N/A 1.6% 1.6% 2.0% 1.1% 1.4% 1.4% 1.9% 1.8% 1.2% 2.0% 2009 0.7% 1.6% 2.0% 2008 N/A 0.6% 5.4% 5.8% 6.3% 5.4% 6.3% 5.4% 5.5% 6.0% 5.7% 5.8% 2009 6.5% 9.4% 10.0% 2008 12,051 13,923 19,433 19,135 22,130 13,830 13,724 17,690 19,635 18,433 12,537 19,342 2009 9,523 10,662 12,230 2008 14,277 8,612 15,424 13,516 13,555 12,415 11,956 10,198 10,127 10,043 11,144 10,003 2009 12,909 11,096 8,073 2008 1.1% 2.4% 2.5% 2.8% 3.8% 2.3% 2.6% 3.0% 2.8% 2.4% 2.0% 3.6% 2009 1.7% 4.5% 7.5% 2008 154 209 386 381 513 286 306 304 285 239 228 360 2009 214 502 605 2008 1.1% 2.4% 2.5% 2.8% 3.8% 2.3% 2.6% 3.0% 2.8% 2.4% 2.0% 3.6% 2009 2.2% 4.7% 4.9% 2008 638,306 690,694 553,048 573,267 673,820 574,794 752,956 811,235 692,931 698,295 603,432 575,380 2009 773,761 635,544 741,869 2008 N/A N/A 5% 5% 4% 4% 4% 4% 3% 4% 5% 3% 2009 7% 5% 6% 2008 N/A N/A N/A N/A N/A 446,134 472,183 511,517 480,048 501,428 417,125 400,465 2009 580,651 468,315 563,654 2008 N/A N/A N/A N/A N/A 174,287 191,816 371,410 328,973 366,270 296,771 258,055 2009 377,821 301,592 377,703 2008 N/A N/A N/A N/A N/A 103,948 100,400 102,950 102,867 101,615 78,601 72,296 2009 147,682 109,088 99,311 2008 N/A N/A N/A N/A N/A 26.35 23.59 26.96 30.02 30.47 28.63 27.64 2009 35.10 31.85 30.25 ExactTarget MS Access 8 Very manual, very clunky
Polaris BI Objectives Governance: Adherence to and delivery of a common corporate strategy for business data storage and presentation Agility: we need to become more agile with our ability to deliver BI to our constituents. Process: Delivering information in a consistent manor using a consistent set of tools. Standards: Development of and adherence to standards around data definitions, architecture and processes. Self Sufficient: we want to establish the use of a platform that allows us to become self-sufficient for all facets of delivery of BI. Self Service: Putting the power in the users. Provide communications and training around new capabilities and tools to ensure adoption. 9
Polaris Commitments for BI 1. Steering Team The steering team will help guide and direct the BI initiatives that are currently proposed and any future ones that may arise. The steering team is designed to help in the following ways: Develop Road Map and Governance for Polaris BI Identify and prioritize ongoing BI projects Determine ongoing investments in BI platform Ensure that all BI projects adhere to the guiding principles presented in the Roadmap document Team made of key IS managers, key business users and strategic partners 10
2. Technical BI Team BI Sub-Committees The Technical BI team will ensure that all BI initiatives adhere to the technical standards laid out in the strategic planning phase. The technical team is designed to contribute in the following ways: Take part in design sessions for all BI-related projects Enforcement of governance and standardization of data definitions Data architecture and enterprise data mart/warehouse Ensure proper use of BI technologies are being employed Dedicated BI Team reporting to Infrastructure Manager Project Manager/analysis Data Architect Data warehouse 11
Web KPI Solution Architecture Source Systems Stage Database Data Warehouse SQL OLAP Presentation MSFT CRM WebTrends ExactTarget Stage Marketing Data Mart Marketing Dashboard MAPICS Data staging and mapping tables Star Schema Analysis Services: Cubes Perspectives Reports Excel Zip code DB & categorization files 12
Digital Marketing Data Mart Staging Data Model Stage 13
Digital Marketing Data Mart - Data Model Marketing Data Mart 14
Results Standard data definitions and measurements Get everyone playing on the same field Full complement of Web Dashboards Marry-up Webtrends Analytics, ExactTarget Email and Microsoft CRM data Direct insight into Campaign Performance (including search terms)- our ROI On-demand access with daily updates Provide ad-hoc insights via simple reporting interfaces Ability to segment data in-house and model Frees up key resources to work on other critical initiatives 15 Putting their annual Marketing dollars to better use
16 Web Engagement Screen Shot
17 Sales Funnel Screen Shot
Our Solution- Complete! Marketing Effectiveness Dashboard - ROMI Ad / Search Performance Email Performance WebSite Performance Campaign Performance Targeted Marketing Customer Behavior Marketing Funnel Financials Act vsbud Analytics Reporting KPI s Scoring 1) Life time value 2) Propensity to buy Marketing Online/Offline Advertising & Promotions Leads Capturing names Building profiles CRM Dynamic Content Pull consumers Relevancy Website/Email/Direct Mail Promotions Offers Dealer Tools Backward/forward CRM integration Higher quality information Improved prospect ranking system Robust reporting 18
Moving Forward Web KPI with the Digital Dashboard Framework is the base The learning taking place on this project will start a best practices approach for future BI projects and is led by some of the best BI resources in the US today. Foundational information pillars are being developed that will be used on additional projects, reducing the development costs of those projects from the start. The datamart is built and can expand to an Enterprise Data Warehouse Develop and prioritize the queue of next BI projects Sales and Marketing Base will be set with CRM data and Purchase History More reliable platform and ability to deliver sales reporting via mobile devices Deeper data insights to support critical initiatives Overlay of sales data/web traffic Warranty and Service Manufacturing and Supply Chain 19
20 Questions??