1 / 21

How simple analysis opened up a new source of income Lee Gisbourne – Database Marketing Manager

How simple analysis opened up a new source of income Lee Gisbourne – Database Marketing Manager. Agenda. Background Database Marketing The Challenge The Analysis The Campaign Results Questions. 1 Background (a). Key dates. Charity founded in 1824

leiko
Download Presentation

How simple analysis opened up a new source of income Lee Gisbourne – Database Marketing Manager

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. How simple analysis opened up a new source of income Lee Gisbourne – Database Marketing Manager

  2. Agenda • Background • Database Marketing • The Challenge • The Analysis • The Campaign • Results • Questions

  3. 1 Background (a) Key dates • Charity founded in 1824 • (National Institution for the Preservation of Life from Shipwreck …) • Royal National Lifeboat Institution 1854 • First co-ordinated rescues with helicopters 1957 • Inland waters and beach lifeguards 2001 • Hovercraft and lifeboats on the Thames 2002 • Training college & survival centre 2004

  4. 1 Background (b) Key facts • Saving lives at sea • 235 stations • 330 lifeboats • 4,600 crew 3,000 shoreline helpers • 163 beaches • 20 boats, 11 RWC • 900 lifeguards / 120 volunteers • 1,000+ fundraising branches and guilds • 35,000 volunteer fundraisers • 97% volunteers

  5. 1 Background (c) The cost … • £64.2M rescue • £49.6M operational service • £4M prevention • £23M fundraising • No UK Government funding

  6. 1 Background (d) … and the benefit • 8,713 launches in 2010 • 309 lives saved • 8,313 rescues (23 a day) • Beach Lifeguards called to 16,664 incidents in 2010 • Assisted 18,779 people • 107 lives saved • Since 1824 more than 139,000 lives saved

  7. 2 Database marketing Key responsibilities • Mailing selection & extraction – 100+ campaigns • Data management - 2M supporter records • Campaign results analysis • Ad-hoc reporting • KPI reporting • Insight delivery • …delivery of data driven marketing

  8. 3 The challenge (a) RNLI challenge • Find a ‘significant’ new income stream • …from existing supporters • Believed we have an affluent supporter base • £25 average gift • Full calendar of appeals and asks • Within the constraints of current internal systems

  9. 3 The challenge (b) Marketing challenge and aims • Recognise ‘higher value’ supporters • Provide a personalised supporter experience • Introduce a tangible ask - £1214 to train a crew member • Short term - 1 year commitment to training • Allow the supporter to donate in the way that suited them • Bridge the gap between ‘high level donors’ and ‘higher value’ supporters

  10. 4 Analysis (a) Understanding the supporter base • Past behaviour • Transaction history • Personal data • Purchased demographics • Acorn classifications • Wealth intelligence • Acxiom variables

  11. 4 Analysis (b) Acorn classifications - wealthy achievers • Do the RNLI have an affluent base? • Is this just the charity supporting population?

  12. 4 Analysis (c) Household affluence • Acxiom waited attribute including; ~ Household Income ~ Type of Property ~ Council Tax Banding of property ~ Home ownership Status ~ Number of earners in household ~ Dependent children in household ~ Investment Activity ~ Credit Cards in household ~ Technology in household

  13. 4 Analysis (d) Wealth intelligence • Data audit • Wealth bands • Geographic region • Age bands • Social and corporate attitudes • Charity segments

  14. 4 Analysis (e) Year of last donation • 1/3 this year - active • 1/3 1 to 4 years • 1/3 5 years and over

  15. 4 Analysis (f) Total value of gifts over the last 12 months • 30% - under £25 • 60% - £25 - £100 • 3% - £200 - £5000

  16. 5 The Campaign (a) The target market • Analysis showed an affluent supporter base • Decided to adapt a classic RFV • Had given between £200 & £5,000 per year • Had to have given it for the last 2 consecutive years • Been supporting for over 5 years

  17. Personalised letter – giving history and years supporting A case for support document – highlighting what training crew go through Donation form and reply envelope Personal welcome call Several update mailings themed around training 5 The Campaign (b) The ‘pack’

  18. 5 The Campaign (c) 3 Test segments • High value committed givers - 370 • High value cash supporters - 410 • High value supporters choosing multiple payment methods - 370 Targets • Learn • 1% response rate

  19. 6 Results (a) Campaign results • Committed – 4% RR • Cash – 11% RR • Multi – 12% RR • 87 gave the full amount • Pack cost £5.16 • Extra costs to manage elements externally • Gift Aid Income £23K • 12 months before £44,000 • 12 months following £117,000 • 166% increase in income

  20. 6 Results (b) Next Steps • Monitor the responders for the next 12 months - what do they do when they aren’t asked? • 23 supporters have decide to continue • Roll out to a large audience in 2012 • Tackle internal processing issues

  21. 6 Results (c) Key Learning's and Advice • People will analyse your date for free … let them • You have a database full of data … you know your data better than anyone • Recency, Frequency, Value is always a good place to start • Supporters will give high value gifts … but you do have to ask • Do not let internal systems stop you testing something new … if you wait for systems to be perfect it will never happen

More Related