A thought-provoking webinar where we looked at:
- How bad data traps us into putting out data fires reactively
- Why every organization needs a proactive data management plan
- The difference between a data map and a data plan, and why you need both
- What are the characteristics of a good data management plan
Speakers included:
Debbie Snyder - Adcieo, Vice President, Sales and Marketing
Debbie is responsible for leading sales and marketing for Adcieo and ensuring that Adcieo’s expertise, strategies and tools are positioned to create solutions for our nonprofit clients. Debbie is responsible for leading sales and marketing for Adcieo and ensuring that Adcieo’s digital expertise, strategies and tools are positioned to create solutions for our nonprofit clients. Debbie is focused on improving financial performance for Adcieo clients by driving faster and stronger constituent engagement, across all channels, thus increasing the overall value of constituent relationships.
Gary Carr is the President and CEO of Third Sector Labs, a company challenging nonprofit organizations to re-think their data practices. Believing that today's brand relationships begin and end with data, Gary's goal is to help nonprofits succeed through data best practices. Understanding the challenges of good data management becomes the key to realizing opportunities to succeed through data.
2. 2
Welcome and Agenda
Please participate in our online poll
while we get organized
Today’s agenda
1. Why we don’t have data management plans
2. Why we need them
3. How to create one
4. What to do with it
3. 3
Our Experts
Gary Carr
President & CEO
Third Sector Labs is a data services
company helping nonprofits to re-think
their data management practices and
solve data problems.
ThirdSectorLabs.com
gcarr@thirdsectorlabs.com
www.linkedin.com/in/gpfcarr
Leading digital marketing firm serving the
nonprofit community through strategic
planning, implementation and support for
multi-channel fundraising solutions.
adcieo.com
debbie.snyder@adcieo.com
linkedin.com/pub/debbie-
snyder/0/448/89b
Debbie Snyder
VP, Sales & Marketing
4. 4
LEVEL 1:
ASSESSMENTS AND
CLEANING
LEVEL 2:
DATA
MANAGEMENT, ENRICHMENT, MI
GRATION
LEVEL 3:
WAREHOUSING, MINING, V
ISUALIZATION
Also Exclusively Serving Nonprofits
---- Data Services ----
Founded in 2013 by professionals with 20+ years of technology and data experience with
Fortune 500 companies, the federal government, and nonprofits
Offices in Washington, DC and Seattle, WA metro areas
www.thirdsectorlabs.com
5. 5
FUNDRAISING STRATEGIES
• Strategy consulting
• Multi-channel campaign
development
• Change management
• End user support
DIGITAL MARKETING
• Website design
• Custom development
• Implementation
• Mobile apps
DATA MANAGEMENT
• Database migration
• Data integration
• Data hygiene
Exclusively Serving Nonprofits
Digital marketing consultants helping nonprofits create, launch and manage multi-channel
fundraising strategies.
www.adcieo.com
6. 6
Let’s get started
If you are a typical nonprofit …
• You have a strategic plan
• You have a fundraising plan
• You do NOT have a data management plan
• But your fundraising success depends on data
Hmmmm ….
8. 8
Why don’t we have data management plans?
1. We have lots of other plans!
2. Data is intimidating
3. We have a dba, what else do we need?
4. We cleaned our data last year – is that what you
are talking about?
5. Plans are time consuming to create
6. We plan events … we react to data
9. 9
When we think of data management plans …
Examples of data
management plans
12. 12
6 reasons why we need them
1. Data degrades
2. More data than ever to deal with
3. More (newer) technology
4. Fundraising plans change
5. Competition for donors‟ attention
6. Not having a plan is wasting time and money
Let’s talk about these a bit more …
13. 13
1. Data degrades
“If your data isn‟t getting better, it‟s getting worse.”
-- TSL data scientist
“Why?”
-- audience
14. 14
Data degradation
What does that mean?
Data degradation – [DAY-tuh deg-ruh-DAY-shun], noun
Refers to the worsening of data quality over time. With assets like a donor database, degradation is inevitable. Why? Because
of the many, sometimes unavoidable, negative influences acting on your data quality. These include: consumer data naturally
changes as people change jobs, relocate, have families, and go through the normal cycles of life; data inputs are often flawed
and/or manual, and the manual labor can be poorly trained; related data is changed, purged or updated; data migration to new
systems such as CRM software.
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Data degrades
Cause #1: your organization
– Lack of data entry standards
– Unskilled data entry workers
– Common mistakes
– Record fragmentation
Cause #2: the technology
– Multiple, disparate systems
– System upgrades
– Integration, processing errors
– Sheer volume of data
Cause #3: those darned donors … life!
– Change in address … every 5 to 7 years
– Change in jobs … 9 to 11 jobs in a lifetime
– Family / life event … divorce rate, birth of children, death … what else?
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Your CRM view of your data
Manage those
contact data
changes.
17. 17
Our view of your data (once we export and analyze)
Sal
utat
ion
Last
Name
First
Name
M.
I.
Address 1 City State Zip Phone Email DOB Gender
MR Setters m
MS SIMMS Laurie 1313 Danger Ln Appleton CA 73111 310.555.5555 Laurie@mail 04/29/81 F
Mr. singletary Mike T 310.555.1234 mts@mail.com
Singletary Michael 310.555.1234 mike@mail.com M
Solvington Allen 5201 Marshall
Lane
Cupertino CA 91001 323.555.5990 also@mail.com 05/30/75
Mr. soprano Cindy P. 222 Main St. Cupertino CA 91002 cindy@mail.com f
Dr. Standish Bradford 1141 Duke Ave Los
Angeles
CA 91010
Stevens Allison 8726 Elm Ave Appleton CA 90009 310.555.5551 01/01/01 f
STEVENS ROBERT 2 2101 Data Ave Los
Angeles
CA 91010 rs2@mail.com 12/14/60 m
Sr Tahoma Juan 20B Eldora Mexico
City
+52-55-5222-
2222
jtahoma@mail.com 01/14/59 M
Incomplete
record
Salut./gender
mismatch
Incomplete email
CA ≠ 73111
Multiple
normalization
issues
M.I. = 2 ?
Moved last year
(NCOA)
Foreign address ?
DOB is bad
Potential dupe (ph #)
18. 18
2. More data than ever
Donation$
Special events
volunteering
Emails
and
emails
Broker lists
Socialmedia
Job change
Address change
Financial transactions
newsletters
Directmail
Alma mater
Family updates
polls
Robo calling
spreadsheets
Donations to
other charities
Onlinesurveys
We leave
footprints
everywhere
21. 21
Recent TSL webinar poll question
How many different technologies doe you
depend upon to manage a fundraising
appeal/campaign?
• 53% of attendees used 3 – 5 technologies
• 47% used 6 or more
• 0% used 1 - 2
But …
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4. Fundraising plans change
Raise
more
money
1. From
new / more
donors
2. Who we
reach over
more
mediums
3. With
specific
messaging
4. Relying
on outcome
reporting
5.
Targeting
donor
segments
6.
Identified
by data
analysis
23. 23
5. Competition
1. Nonprofits encounter donors / prospects /
volunteers / advocates in more „places‟
2. There is more “noise”
3. Data cuts through the noise to
– Anchor outcomes
– Communicate results
– Establish and maintain relationships
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6. Wasting time and money
Some examples are very visible
• Direct mail production and delivery costs
• Spam, ISP blocking
• Staff time
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Wasting time and money
Some are hidden
• Mail to a deceased donor
• Make a large ask to a donor with small giving potential
• Make a small ask to a donor with a large giving potential
• Hospital references wrong healthcare issue when trying to
build up a new relationship
• University sends rejection letter to a student and donation
request to his parent … on the same day!
Lost donors = ??
26. 26
Remember
Data is your organization’s knowledge
and memory
What you know
What your organization
knows
Vs.
28. 28
How to create a data management plan
• Multiple types of data
– Donor
– Event
– Newsletter
– Social
– Service outcomes
– Financial
• Plan for each
• We will focus on constituent / donor data for the
rest of this presentation
Constituents
29. 29
How to create a data management plan
Remember …
• We aren‟t trying to get to the moon
• Start simple and …
• Be practical.
• Think of a data management plan as a
commitment to proactively manage
your data!
30. 30
Data management plan: 3 questions
1. Where do you want to
go?
2. Where are you now?
3. How will you get from
here to there?
You need a map … and a
plan
Map first!!
Assess problems
Revise db
Web capture
THERE
HER
E
Assess
problems
Clean
data
31. 31
The map
1. Determine the data you
need to support your
fundraising strategy
– Markets, segments, messaging
2. Get a data quality
assessment
3. Determine your data gaps
– What do you need but are not
collecting?
Assess
problems
Clean
data
Web
capture
THERE
HERE
32. 32
The plan – phase 1
1. Document your
fundraising/events/communications schedule
2. Set that aside!!!
We are going to separate data management from
events management Fundraising / events
schedule
Data management
schedule
33. 33
The plan – phase 2
1. Prioritize the data quality
problems from the data
assessment / gap analysis
that you intend to address
2. Create one or more tasks
to close each gap
Assess
problems
Revise db
Web
capture
THERE
HERE
Assess
problems
Clean
data
34. 34
The plan – phase 2
3. Create a new schedule for data
management … monthly,
quarterly, per data type needed
4. Establish data quality standards
for data governance
36. 36
Remember: start simple
The map
1. What data do you
need
2. Data assessment
3. Gaps
The plan
4. Prioritize gaps
5. Action item for each
6. Schedule
7. Governance
37. 37
Step 1: (The map) What data do you need?
Start with your fundraising plan
Fundraising strategies Tasks
1 Target lapsed donors 2 communications
2 Increase prospects 10% Outreach thru web, events
3 Convert 20% of Target conversion plan for
constituents to donors newsletter subscribers, event
attendees, volunteers
4 Develop donor Data analysis to produce
segmentations 3 – 4 segments for future
communications
… helps #3
38. 38
Step 1 (cont.)
Continue to the data requirements
Fundraising strategies Tasks Data requirements
1 Target lapsed donors 2 communications Lapsed report, contact info
2 Increase prospects
10%
Web, event outreach Upgrades to website features,
Event forms for data capture
3 Convert 20% of
constituents to donors
Target conversion plan
for newsletter
subscribers, event
attendees, volunteers
Run a constituent report,
identify donor data fields
needed, can you create
donor profiles?
4 Develop donor
segmentations
Data analysis to produce
3 – 4 segments for
future communications
Same as #3
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Step 2: (Map) Data assessment says
1. 20% of records are duplicates
2. 30% lapsed donors
3. 15% incomplete addresses
4. Not tracking gender, DOB,
alma mater, family status and
other data needed to segment
messaging
5. 35% of all constituents are
also donors
40. 40
Step 3: (Map) Gaps to close
1. Bad data to be cleaned
2. Duplicate records to be removed
3. Address fields to be completed
4. 10 new data fields to be captured
– DOB, gender, alma mater, family, employer, other
charitable interests, contacting preference, social media
usage, etc.
5. Donor profiles to be completed (from #3 and #4)
41. 41
Step 4: (The plan) Priorities
1. Clean bad data and remove duplicate records
2. Enable capture of more data – easy tasks
– ID needed fields
– Add fields to db
– Add website registration option for Facebook login
– Create Facebook page
3. Address clean up
– NCOA check
4. Enable capture of more data – harder tasks
– Marketing service to capture website visitors
– Add survey and poll questions to website, newsletter
– Develop communications piece to invite more constituent
“conversations” and sharing of data
5. Determine new data segmentations to support fundraising
in the future
42. 42
Step 5: (Plan) Actions
Fundraising
strategies
Tasks to support Data requirements Actions to improve
data quality
1 Target lapsed
donors
2
communications
Lapsed report,
contact info
A – clean data
B – update addresses
2 Increase
prospects 10%
Web, event
outreach
Upgrades to website,
other forms of data
capture
A – marketing service
to capture web
visitors
B – event capture tool
C – social media / Fb
3 Convert 20% of
constituents to
donors
Target conversion
plan for
newsletter
subscribers,
event attendees,
volunteers
Constituent report,
expanded donor data,
donor profiles
A – add new db fields
B – add website data
capture features
C – data broker
D – test donor profile
capacity and analysis
4 Develop donor
segmentations
Data analysis to
produce 3 – 4
segments for
future
communications
Same as #3 Similar to #3 … but
focus on segments
you want to market to
for future fundraising
43. 43
Step 6: (Plan) Schedule
First 3 months
Clean bad data
Modify dstabase(s)
Improve website registration
Create Facebook page
NCOA clean up
Second 3 months
Data broker service for one-time
augmentation
Implement website survey, polls
Lapsed donor data cleanup (after
lapsed donor campaign has
completed)
Third 3 months
Create new donor segmentations
Test against target message
marketing program
Fourth 3 months
Measure results of segmentation
Revise data management plan
Every quarter
Data cleaning
Re-run assessment
Measure new data
collection methods
44. 44
Step 7: Data governance
What is that?
Data governance– [DAY-tuh GUHV-er-nuhns], noun
A set of rules or policies that encompass the people, processes and technologies required to create and maintain higher quality
data assets for an organization. Data governance goals resulting from higher data quality include: better compliance with third
party standards, decreased risk of regulatory violations, improved decision making, improved data and organizational security,
and greater profitability.
45. 45
In other words, standards
1. Schedule for monthly or quarterly data
management … cleaning, enrichment, etc.
– Be proactive, not reactive
2. What defines a “complete” record?
– Focus on better data, not more
3. How old is too old?
– Depends on the type of record?
4. How many versions do you retain?
– How many old addresses?
– Event attendance records?
46. 46
Also …
1. Control data inputs
– Via people, systems, imports
2. Review data capture tools against strategic data
needs for fundraising regularly
3. Do you enable donors/consumers (or a subset) to
manage their own information via online
accounts?
4. Do you have self-select removal processes from
(e)mailing lists?
49. 49
Do this!
1. Assign responsibilities
2. Budget
3. Work it for 6 months
4. Measure results
– Quality of data up?
– Event or appeal results?
– Data governance standards being followed?
– No more delays for communications due to reactive data
cleaning?
– Cost savings
5. Review with leadership
6. Revise and continue
50. 50
Let’s wrap it up
Takeaway
Old thinking: we plan our events, we react to data
New thinking: we plan our events AND we plan our
data management
51. 51
We’d like to hear from you!
Please submit your questions…
Q & A
52. 52
Thank You!
Gary Carr
President & CEO
ThirdSectorLabs.com
gcarr@thirdsectorlabs.com
linkedin.com/in/gpfcarr
adcieo.com
debbie.snyder@adcieo.com
linkedin.com/pub/debbie-snyder/0/448/89b
Debbie Snyder
VP, Sales & Marketing
Editor's Notes
Moderator: Welcome everyone … and thank you for attending.
Presenter: GaryIntroduce TSL’s areas of expertise:
Presenter: DebbieIntroduce Adcieo’s areas of expertise
Debbie starts here …
Debbie’s section
These diagrams represent samples of data management plans you can find on the Internet … they are complex and confusing to many people.
We are NOT trying to put a man on the moon.
Transition to Gary …
Gary’s section … quickly click through the animation for this slide.
The problem is NOT some gremlin in your database …The problems are normal, predictable and SOLVABLE.
Summary details rolled up and transaction summary data view. Address information changes at 14% per year. Emails and phone numbers change even more frequently.
We export into a flatten database and analyze. This slide has many examples of the problems we find. These are all examples of data degradation.
We – consumers – are leaving data footprints everywhere …
With so much data available, our records … OUR DONORS and constituents … become fragmented.
Gary: The important point here is that we can de-fragment our donors without having to replace all of our existing databases. The reality is that no software will ever be “one size fits all”. Relationships, communications … life! … are too complicated. In the data science world, the goal is to build databases and create data architectures that make it easier to both store and share data.
Gary: How did I copy and save in this tool vs that tool? How many tasks are repeated between systems?Multiple systems … each has its own interface … each is used differently … collectively, they are wasting your time
Ask Debbie to comment here …
This point is really important … many organizations don’t like hearing it, because it sounds almost like we are de-humanizing the donor … we are not.Organization knowledge REQUIRES … CRM … database store … actual data
Gary’s sectionSo, we can all agree that we need a data plan to help us manage data / information / knowledge proactively, then how to we get one?
What does a map DO for us?It defines the journey … we need to get from here to there. Since we “aren’t there yet”, we have gaps to fill in.
Transition to Debbie …
Debbie’s section …This slide is a quick review of Gary’s points about … what goes into the map, what goes into the plan. Let’s review each one …
It is critically important to start with your Fundraising Strategy … you can’t have a reliable data management strategy without knowing what your fundraising strategy requires of the data.In the example, we have 4 strategies to this basic fundraising plan. Each strategy has one or more tasks associated with it.
In this slide, we now identify the data requirements associated with each task that we need to complete in order to support the fundraising plan.In the case of the data requirements column, YOUR plan will have more details around each point. For example, here we see the need to identify additional data fields that we need to capture … those will vary nonprofit to nonprofit.
Getting a data assessment is very important. What do you have now? What is the quality of your data? Here we show a sample Data Quality Assessment from Third Sector Labs – they run these for FREE if you provide them the data.
Now we identify the gaps between where we are now (from the Data Quality Assessment) and where we need to be (from our Fundraising Strategy needs).Great … we have our map … now, on to the plan!
Prioritization is always a challenge. Here we’ve broken down priorities from the gap analysis, and we’ve focused on what is easier to accomplish vs what is more difficult / time consuming to accomplish.
Debbie – you can ask Gary to comment on the Action steps in the far right column. Basically, the point is to assign one or more actions to fulfill the data requirements.
Debbie … do you want to throw this over to Gary?
Back to Debbie
Debbie’s section
Debbie takes this …If no one is responsible, it does not get done. No budget? See previous point.Measuring results can take many forms.
We PLAN our events … now let’s PLAN our data managementIf your data isn’t getting better, it’s getting worse …