How to avoid some of the pitfalls when deploying legacy targeting models david dipple - adroit data and insight
Fellow of Royal Statistical Society Worked with Not For Profit and Charity Clients for over 25 years Recognised as an expert data modeller Trained numerous analysts and fundraisers in the use of analysis in fundraising Worked with charities in UK and mainland Europe
An approximate answer to the right question is worth a great deal more than the precise answer to the wrong question. -The first golden rule to applied mathematicsThe formulation of a problem is often more essential than its solution which may be merely a matter of mathematical or mental skill. •A. Einstein
Traditionally many legacy campaign have been designed and devised around a message they are not shaped around supporters needs and requirements To fully tap the legacy potential of the base a more supporter lead strategy would match supporter interests and propensity to legacy message
Method ◦ Mail ◦ Phone ◦ Event ◦ Online The halo effect
Behavioural Recency, Frequency, Value, Forms of help. Segmentation Demographic AttitudinalLifestage, Age, Gender Questionnaires, Geodems Interests & Beliefs
Payment Type InterestsAmount LifestyleDate Cause Name Address Gender LTVs Donor & Age RFVs Demographic Income Scores Details Media codes Responses Method
Geo-Dems are great for cold and certain aspects of warm targeting For small population analysis they tend to be less useful ◦ For one model that I created by using a geo-dem it added 0.5% to the power of the model Take care with including or excluding people based on their geo-dem coding
Academic Centres, Students and Young Acorn Description ProfessionalsPersonicx Retired - Low income - Aged in the CityDescription Suburbs
People tend to be interested in people ◦ But why are they interested? ◦ What aspects of your cause excites them? ◦ What motivates them to give you money?
What data do we currently have? ◦ What is its quality What data would we like to have? ◦ What barriers are there to getting it?
But what type of model? ◦ Legacy ◦ Pledger ◦ Legacy & Pledger ◦ Residuary/Pecuniary The past determines the future ◦ Lifetime Model ◦ Time Limited Model ◦ Something Else
SPSS Excel FastStats MapInfo & MapPoint My own software
Type of Data ◦ Number of Relationships ◦ Supporter Lifetime ◦ Number of Gifts ◦ Age of Supporter ◦ Gift Aider Time is not our friend!
Beware of False Relationships Gender Response Age Response Male 8% Young 12% Female 10% Old 12% Population Response: 10% Gender: Male Gender: Female Response: 8% Response: 12% Age: Young Age: Old Age: Young Age: Old Response: 15% Response: 5% Response: 10% Response: 16%
c Clas sification Table Predicted a b Selected Cas es Unselected Cas es Legator Percentage Legator Percentage Obs erved 0 1 Correc t 0 1 Correc t Step 1 Legator 0 776 134 85.3 908940 153597 85.5 1 173 725 80.7 83 272 76.6 Overall Perc entage 83.0 85.5 a. Selected c as es sel_var EQ 1 b. Unselected c ases sel_v ar NE 1 c. The cut value is .500Multiple ways of understanding if amodel has worked. Most of the outputcan be ignored by non statisticiansand the key – The key is finding whatneeds to be communicated tomarketers and in what form. used todetermine power.
Selected High Score SupportersEven with a smallpopulation outcomemodels – test downthe model to reducethe Tom Smith effect. Model Score
Building legacy models has so far been carried out by building statistical propensity models. These need previous results to determine what will happen. But if there are no previous results you can’t build a model or can you?
The factors that increase propensity to make a pledge or leave a legacy are fairly well know – as we saw earlier Create binary flags for each of the data items given earlier and then add them all up. The higher the result, the more likely to make a pledge (and it works).
Analysis of a legacy campaign tends to be point based, That is how many responded to being contacted To truly understand the effect of legacy campaigning the relationship over time needs to be examined, including the effect on non legacy messages – that is the full supporter journey
Message 1 Message 2 Message 3 Message 4Single model thatdetermines bothwho should be No Contact Modelcontacted and with (at this point…)what message. Warehouse
The biggest barrier to producing efficient models is lack of data – especially demographic and attitudinal data Understand what the data is saying and then use an appropriate model - There is no one perfect solution There is no certainty in modelling – models are built from past behaviour and if you change what you are doing it can take a while for the data to catch up Examine the whole supporter journey to understand the full relationship Define the question and the answer will be much easier – remember a model is not a panacea