Presented by

Ian McNamaraMatthew Tamea

Building an Effective Supporter Selection Strategy

15th October 2008

Sector challenges

1.

Data strategy

2.

Software in Action

3.

What are the benefits?

4.

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

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?

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

Data Strategy: Key Components

Data and technical infrastructure

Reporting and management information

Supporter understanding, analysis and segmentation

Communication management

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

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

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

Campaign Management/Selection

How sophisticated are the users?

Who needs access to the information?

What can be distributed/ out-sourced?

What should this cost?

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:

Live Demonstrations

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

Thank you.Further questions?