Exploring Segmentation

Transcription

1 Practical ways to use your data to drive up results Exploring Segmentation Fiona McPhee Pareto Fundraising Proudly Sponsored by

2 Segmentation as your starting point Targeting, testing & analysis as the goal

3 Assumptions I ve had to make a few about what you already know and do so we have time for the good bits

4 We agree that: Communicating with everyone, every time is not effective fundraising Not everyone is the same Not everyone wants the same thing

5 We agree that implementing some form of segmentation will benefit your fundraising program by primarily helping you to: Understand how your supporters behave Make informed decisions

6 We acknowledge segments of One is the goal? Tailored to the individual Right ask, right time, right channel Best ROI possible (short-term / longterm)

7 Acknowledge segments of One groups is the reality?

8 My starting point for segmentation Use it to create fairly homogenous groups which are likely to respond in similar ways to our strategies Use it to prioritise these groups in order to target and understand their behaviour

9 Key: we need to use segmentation consistently to Target & Measure Who What When Outcome Inform next move

10 My starting point for segmentation Use it to create fairly homogenous groups which are likely to respond in similar ways to our strategies Use it to prioritise these groups in order to target and understand their behaviour Options?

11 Psychographic Segmentation Powerful potential the goal of many Marketing & Fundraising teams Often revealed by qualitative research e.g. personal experience of services offered by charity Data very hard (expensive) to capture and maintain at an individual donor level (and nearly always an additional cost to standard database stored information such as transactions) Psychology is more complex than a data point or two (e.g. people change their minds) and so even psychologists find it hard to determine practical marketing psychographic segments that can be effectively used for targeting. May be easier to use psychographic segments to inform creative treatment only

12 Demographic Segmentation Social and economic information is fairly commonly available data (internally or externally) and therefore somewhat practical Age can be a useful additional overlay Widowers with absence of grandchildren correlates strongly with bequest realisation Not a reliable predictor of behaviour - no obvious practical value for a targeted communications programme Helps us to know who is in our segments

13 Geographic Segmentation Basic and obvious insights Affluent areas/ higher donor penetration areas Proximity to Charity service areas if relevant (e.g. a Hospital) No obvious practical value for a targeted warm communications programme Can be helpful for acquisition targeting Profiling (geodemographics + some behavioural) even better

14 Behavioural Segmentation The product of psychographics and geodemographics A charity s (your) supporters are already a highly niche, homogenous market segment (why swaps work) RFV / RFM is the most common behavioural segmentation Adapting for fundraising & your program / donors and your activity is key

15 My starting point for segmentation Use to create fairly homogenous groups which are likely to respond in similar ways to our strategies Use to prioritise these groups in order to target and understand their behaviour I use segmentation primarily by Recency, Frequency, Value (RFV)

16 Tailoring RFV Donor Type

17 Response Rate 16% Response Rate by Donor Type 14% 12% 10% 8% Group lower volume for ease 6% 4% 2% 0% Cash Donor Lottery In Memoriam Other Event

18 Regular Givers Cash Donors Campaigners Lottery Players Event Attendees In Memoriam In Celebration Peer-to-Peer Fundraisers Peer-to-Peer Sponsors Members Virtual Gift Purchasers

19 Regular Givers Member & Cash Donor Cash Donors Members Only Virtual Gift Purchaser Other Regular Givers Only Lottery Players Regular Givers & Cash Donors Event Attendees Regular Givers & Members Cash Appeal In Memoriam In Celebration

20 Cash Donors Members Only Member & Cash Donor Virtual Gift Purchaser Other Regular Giving Conversion Lottery Players

21 Tailoring Donor Type RFV

22 Likelihood of transacting again Common Fundraising RFV Potential value of the transaction Recency Frequency Value 0-12 months >1 a$ b$500-$ c$250-$ d$100-$ e$50-$ f$25-$ g$10-$ h$0.01-$9.99

23 The following question is often asked of a data set How much of our warm donor base is optimum to mail (or phone, offer lottery)? The best way to answer this is via a segmentation model which will help identify not only those donors that will respond, but the value of the responses.

24 Response Recency 20% 18% Typical effect of Recency on Response 16% 14% 12% 10% 8% 6% 4% The most important variable for likelihood of response 2% 0% Recency (months since last gift)

25 Response More recent supporters respond better than those donors who haven t transacted for some time. 30% Typical effect of Recency on Response 25% 20% 15% 10% Those who did it recently are the most likely to do it again 5% 0% Recency (months since last gift)

26 Response Rate Frequency 35% 30% 25% 20% 15% 10% 5% 0% Typical effect of giving interval on response - Multi Donors < >36 Cash giving interval The purest way of considering frequency in a RFV model is to look at the interval between gifts

27 Response Rate Split by 12 month intervals highly predictive, but more so for 0-12 donors than the 13+ that may be unprofitable 20% 18% 16% Typical effect of giving interval on response - Multi Donors 14% 12% 10% 8% 6% 4% 2% Resting (not giving a chance to do it again) will affect response in short-term 0% < >36 Cash giving interval

28 Response Rate An alternative, and simpler to implement, way of looking at frequency is simply to look at the number of gifts a donor has made. 25% 20% Typical Effect of frequency on response 0-12 recency 15% 10% 5% Jump in response once a donor has made 3 or more gifts 0% Cash Gifts

29 Response Rate When we look at the 13+ recency donors, the jump in responsiveness comes at the 2 nd gift 7% 6% Typical effect of frequency on response 13+ Recency 5% 4% 3% 2% 1% The more gifts given in the past the more likely they are to give, useful for reactivation 0% Cash Gifts

30 Response Rate For practical reasons, splitting by single and multi donors provides good distinction in for these lapsed donors as well as your new donors. Who is profitable to mail? 16% 14% 12% Typical Effect of frequency on Response for lapsed donors 10% Active 8% 6% 4% Refining who of the Lapsed? 2% 0% 1 >1 Cash Gifts

31 Summary How much of our warm donor base is optimum to mail? Those who gave more recently Those who give more often Recency & Frequency are our predictors of response

32 Income per donor mailed Income per donor mailed Income per donor mailed Value options: Total giving, Value of last gift, Average gift or Highest Gift. The total giving is usually excluded because it effectively combines the frequency and value. $70 $60 $50 $40 $30 $20 $10 $0 Typical effect of Value on Income Highest Gift $80 $70 $60 $50 $40 $30 $20 $10 $0 Typical effect of Value on Income Last Gift Potential Value (Highest Gift) $80 $70 $60 $50 $40 $30 $20 $10 $0 Typical effect of Value on Income Average Gift Value (Last Gift) Actual Value (Average Gift)

33 Segment Donor Type Recency (months) Frequency Value (highest gift) Last Year ROI Include this year (Y/N) 011 Cash 0-12 (active) Multi (>1) $25 - $ Y 012 Cash 0-12 (Active) Single (1) $25 - $ Y 027 Cash (Lapsing) 028 Cash (Lapsing) 043 Cash (Lapsed) 044 Cash (Lapsed) Multi (>1) $25 - $ Y Single (1) $25 - $ N Multi (>1) $25 - $ N Single (1) $25 - $ N

34 Segments Targeted Last year pygmy possum appeal responder 2013 pygmy possum appeal responder Active Multi donors Active single Donors Lapsed multi donors, $50+

35 Segments Targeted Last year pygmy possum appeal responder 2013 pygmy possum appeal responder Active Multi donors Active single Donors Lapsed multi donors, $50+ Segments Targeted Active Multi donors Active Single Donors Lapsed multi donors, $50+ Last year pygmy possum appeal responder 2013 pygmy possum appeal responder

36 Regular Giving Factors Recruitment channel Recency of recruitment Value Additional transactional behaviour Active Regular Giver F2F Recency of recruitment Cash (Y/N) Upgrader (Y/N) Monthly value band Recency of recruitment Cash (Y/N) Phone Upgrader (Y/N) Monthly value band

37 Behavioural / RFV Challenges System (Database) Internal Expertise Internal Capacity (staff resource) Size of program (what level of granularity is worth it)

38 Another application of segmentation analysis is to take the significant variables, and create a scoring model that combines response and value predictors. SCORING

39 Good for phone activity Requires initial analysis of potential variables impacting response to be: Identified Validated Refined over time Refreshed and assessed for accuracy/changes over time Fixed costs are limited Marginal costs / cost per contact are high Need a more precise view of the return per donor Example of use: higher scored donors would be called more frequently for rolling cash phone program

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41 Bequest Scoring RFV Bequest Prospect Demographic indicators Bequest Prospect

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45 Donor Attribute Score Loyal Donor (RFV driven) Number of gifts (e.g. 10+, 5+) Length of giving (e.g. 10+ years) Donor Type (e.g. RG & Cash, Cash Only) Gift value band (RFV driven) Payment type(s) Age (</>) Has children / grandchildren Proximity to cause Responded to survey Changed details

46 Bequest Scoring RFV Other Overalys Bequest Score

47 OVERLAYS

48 Mailing F2F Recruits What overlays may indicate potential? Some form of direct response Age Longevity Upgrade Other channel usage e.g. Phone Response to a declined payment communication

49 New Donor overlays: what impacts Topic of Acquisition value and second gift Premium Type / Value Premium vs. non-premium recruits Recruited via a swap Have been swapped Subjective list then analyse

50 Extending your segmentation OTHER IDEAS

51 Number of comms touch points Address Landline Mobile address

52 Addr1 Addr1 Addr1 Landline Addr1 Landline Mobile Addr1 Mobile Addr1 Landline Addr1 Addr1 Addr1 Landline Addr1 Mobile Addr1 Landline Addr1 Addr1 Addr1 Landline Addr1 Landline Mobile Addr1 Mobile Addr1 Landline Addr1 Mobile Mobile Addr1 Addr1 Addr1 Landline Addr1 Landline Mobile Addr1 Mobile Addr1 Landline Addr1 Mobile 2 nd Gift rate by contact type segments & recruitment type 80% 70% 60% 50% 40% 30% 20% 10% The more info provided = better second gift rate 1,400 1,200 1, % 0 Cash Recruit Virtual Gift Recruit Emergency Recruit Disaster Recruit 2nd Gift Rate (Year 1) Recruits Base: Recruits

53 Addr1 Addr1+ Landline Mobile Landline Mobile Addr1 Addr1+ Landline Landline Mobile Mobile Landline Mobile Addr1 Addr1+ Landline Mobile Landline Landline Mobile Mobile 2 nd Gift rate by simplified contact type 50% 45% 40% 35% 30% 25% 20% 15% 10% 5% 0% Simplified view of the contact segments shows us that Address plus something else or just address are best 2 nd gift opportunity. 4,000 3,500 3,000 2,500 2,000 1,500 1, Cash Recruit Emergency Recruit Disaster Recruit 2nd Gift Rate (Year 1) Recruits Base: Recruits

54 Satisfaction Levels Donor satisfaction with the quality of service provided by the fundraising team is the single biggest driver of loyalty towards the organisation

55 Satisfaction

56 Motivational Segmentation Right thing to do Environmental issue Advocacy Education Rights issue Its all three Basic Needs

57 Quick Summary Tailored RFV models are highly predictive Your donor types Recency (months) Frequency (number of gifts) Value (highest, last, average) Hierarchy of donor types Apply consistently Scoring models good for high marginal cost activities Overlays on RFV to test responsiveness Comms touch points Tracking satisfaction levels Motivational segmentation

58 Thank You Fiona McPhee Linkedin: nz.linkedin.com/in/fmcphee/en Twitter: fimcphee