1. Presented by Ian McNamara Matthew Tamea Building an Effective Supporter Selection Strategy 15 th October 2008

2. Sector challenges 1. Data strategy 2. Software in Action 3. What are the benefits? 4.

3. 1. Charity Sector Challenges A clearer view on relationships is required  Other relationships are becoming more important  Recruitment through events, activism, legacy pledging, catalogues, hand raising on the increase More sophisticated approaches to segmentation needed to drive further income  RFV is fine but does not work for all engagement  We need to find ways of approaching all supporters who have the potential to give More innovation in recruitment is needed  Acquisition needs to be an organisation wide discipline  Co-ordination of contact is very important

4. 2. Data Strategy Basic objectives:  Increase the size of the supporter base  Increase the income from each supporter  Cut costs – primarily through management of communications Basic questions  What is the size of the supporter base?  How much income is received from each supporter?  How do I tailor my communications?  What are the costs and how are they assigned?

5. Most organisations find it hard to answer to these questions, regardless of the sector Data Strategy – Why?  The data to answer them is usually not in one place:  Fundraising system  Legacy database  Financial systems  On-line database  MS Excel on various computers  Data  Information  Knowledge  Decisions  Profit Effective data management leads to informed decisions which in turn leads to improved resource allocation

6. Data Strategy: Key Components  Data and technical infrastructure  Reporting and management information  Supporter understanding, analysis and segmentation  Communication management

7. Reporting/Management Information:  Tells you what has happened, in the time and frequency you require Key Performance Indicators:  How much; When; Which channel; How often Supporter Change:  Segment movements; attrition rates; acquisition rates Campaign Analysis:  Individual campaign level; programme level; year to date  Income measurement Reporting and management information OUTPUT – a regular ‘fact base’ of information to provide a view of the change in the supporter base

8. Segmentation  Many types for different purposes  Data driven, RFV, motivational, research based Data Analysis  Tells you what and why things happened  Structured vs. un-structured  Enhance with market research Data Modelling  Predicts what is likely to happen in the future  Value analysis – current, NPV, LTV, potential Supporter understanding, analysis & segmentation OUTPUT – a much deeper understanding of the supporter base that will inform decisions

9. Communication Management How do we apply all of what we have learned into our campaigns?  Inclusions  Exclusions What additional sophistication can be put into campaigns?  Contact and response history  Optimisation  Event/Triggers OUTPUT – a structure to look at the selection for any campaign How do we balance our cost to generate maximum income across:  Channels  Supporter types  Acquisition and Retention

10. Campaign Management/Selection How sophisticated are the users? Who needs access to the information? What can be distributed/ out-sourced? What should this cost?

11. Low end  Blue Tahiti (demo) Middle ground  FastStats (demo); Business Objects; Higher end  Alterian (demo); Smartfocus, SAS, Chordiant Top-end  Affinium Self-serve tools  Zebra, Fusion, Vision Campaign Management/Selection Tools Huge choice of tools available:

12. Live Demonstrations

13. Benefits Ongoing Measurement of Success Generate campaigns faster through re-use of functionality Reduce wastage in communications by cutting out non- responding segments SAVE MONEY.MAKE MONEY.DRIVE EFFICIENCY. Increase Income through better targeted communications

14. Thank you. Further questions?