Get the audience up to speed on some of the ideas behind marketing software on the internet. Be sure to mention that people can download the program and then later pay for it to get the full edition. The try-before-you-buy model for marketing is very common. Even big name companies such as Microsoft do it.
The Business Intelligence Process is no more and no less than: Identifying information needed to make informed decisions Identifying sources of data Systematically convert that data into actionable information Repeat. It ’ s a continual iterative process!
Everyone has a website. Your website has less than 30 seconds to communicate it ’ s point. So, are you effectively marketing your product or are you driving away your prospective customers? Web analytics can tell you page views and bounce rates, but what about the money? The Business Intelligence Process integrates data from multiple sources to answer these more complicated (and important) questions.
The pattern of software downloads observed in the web site logs during the period. The huge jump at quarter 4 is not expected given the normal product life-cycle. The leap is directly related to a crack patch being released for the main product. The spike in downloads was from people who came from the crack site without any intention to purchase.
The sales trend for this product shows the product life-cycle for a program which was release, promoted, and then left alone over time. The sales for quarter 4 were unaffected by the download spike shown on the previous slide.
These are some of the references used in the paper entitled “ Business Intelligence for the Micro-ISV. ”
Moss and Atre ’ s “ Business Intelligence Roadmap ” is a great place to learn about the how a Business Intelligence Process can be implemented. Winston ’ s “ Data Analysis and Business Modeling with Microsoft Excel ” is a very valuable reference for doing analysis and modeling with spreadsheets
Witten and Frank ’ s “ Data Mining ” is a wonderful technical treatment of the topic. You can get some insight into some methods for cleansing and working with data.
Rietta Business Intelligence for the MicroISV
Business Intelligence for the Micro-ISVAre You Effectively Marketing Your Product? Do you Know How to Tell? Frank S. Rietta
Programmer or Marketer? • Try-before-you-buy software online • Identify your target • Consumer or Business? • Technical or Beginner? • On Google’s first page • Press coverage • Download sites Are You Effectively Marketing Your Product? What Questions Would You Ask?Bus. Intelligence:
Agenda: The BI Process 1. Why Business Intelligence? 2. Patterns in Data 3. Mind Your Ratios 4. Discovery Process 5. SpreadsheetBus. Intelligence:
Why Business Intelligence? • Highly competitive and connected markets • Drowning in data • Turn that data into actionable information It’s a competitive advantage It’s the difference between survival and failureBus. Intelligence: 1
Patterns in Data: Download Volume Total Downloads Data from the website logs for rietta.com Quarters 1 Jun 2003 – 31 Dec 2005Bus. Intelligence: 2
Patterns in Data: Sales Total Revenue by Quarter $ 1,400.00 Revenue from Software $ 1,200.00 $ 1,000.00 Sales $ 800.00 $ 600.00 $ 400.00 $ 200.00 $ 0.00 Q 1 2 3 4 5 6 7 8 9 10 11 12 13 Quarter Data from the payment processor logs for rietta.comBus. Intelligence: 2
Sources of Data • Raw web site logs • Analyzed web site logs • Payment processor logs • DatabasesBus. Intelligence: 2
Mind Your Ratios ConversionsBus. Intelligence: 3
Trial Conversion Ratio Purchases Total Downloads • The Program Has a Broken installer • It Crashes • It is Cracked • It is Falsely Identified as MalwareBus. Intelligence: 3
The Discovery Process 1. Identify Information that is needed 2. Find Sources of Data to be converted into that info 3. Perform Data Analysis to understand the raw data 4. Build an ETL process to gather & cleanse raw data 5. Build a Decision Support System, which can be a spreadsheetBus. Intelligence: 4
Have You Ever Used This Menu?Bus. Intelligence: 5
Collecting Data into a Spreadsheet • Make a worksheet for each data source • Add a Quarter column to serve as the correlation/pivot point for the data • =I N T ( (M O N T H (B2) + 2) / 3 ) + ( (Y E A R (B2) - 2003) * 4 ) • Repeat for other data sources • Create a Pivot Table from the data sourcesBus. Intelligence: 5
One Worksheet Per Data Source Aggregate Data from Text File Import Quarter Batch Date Hits Traffic Last Download Date File Program Type 1 20-Jan-03 303 0.31% 30-Jan-03 /menusnap/mnusnp15.zip MenuSnap FW 1 20-Jan-03 169 5.30% 30-Jan-03 /downloads/robogen/robogen152.zip RoboGen SW 1 20-Jan-03 20 0.01% 30-Jan-03 /downloads/robogen/RoboTag.zip RoboGen SW 2 20-Apr-03 251 0.19% 29-Apr-03 /menusnap/mnusnp15.zip MenuSnap FW 2 20-Apr-03 143 4.12% 29-Apr-03 /downloads/robogen/robogen152.zip RoboGen SW 2 20-Apr-03 1610 62.77% 30-Apr-03 /downloads/whoisweb_setup.exe WhoisWeb SW 5 20-Feb-04 30 0.01% 28-Feb-04 /downloads/robogen/RoboTag.zip RoboGen SW 5 20-Feb-04 3228 66.56% 29-Feb-04 /downloads/whoisweb_setup.exe WhoisWeb SW 5 20-Feb-04 69 0.63% 26-Feb-04 /downloads/whoisweb_setup.exe WhoisWeb SW Derived field on which to pivotBus. Intelligence: 5
Pivot Graph Drop Page Fields Here Sum of Hits 90000 80000 70000 60000 Program 50000 MenuSnap PDM 40000 RoboGen Speedar 30000 SQLConverter 20000 WhoisWeb 10000 SQLConverter 0 1 2 RoboGen 3 4 5 6 7 8 MenuSnap 9 10 11 12 QuarterBus. Intelligence: 5
Questions? More details in the paper, also called “Business Intelligence for the Micro-ISV”Bus. Intelligence:
Leadership is W.A.R. • Working on the right problem. • Asking the right questions. • Removing barriers that impede progress toward the ultimate goal. - Herman Cain on his Radio Show (circa March 2006)Bus. Intelligence:
Further Reading 1. B. Drolias. Shareware marketing e-metrics. http://www.shareware-marketing.net/shareware_marketing_e- metrics.html, 2003. 2. E. F. Ian H. Witten. Data Mining: Practical Machine Learning Tools and Techniques, Second Edition. Morgan Kaufmann, San Francisco, CA, 2005. 3. L. T. Moss and S. Atre. Business Intelligence Roadmap: The Complete Project Lifecycle for Decision-Support Applications. 4. F. S. Rietta. Business analysis of web application information. http://www.rietta.com/whitepapers/mysql_webapps_excel.html, 2005. 5. C. Z. S. Christian Albright, Wayne L. Winston. Data Analysis and Decision Making: With Microsoft Excel. Thomas South-Western, Mason, OH, 2006.Bus. Intelligence: