10 Decisions You Will Face With Any Donor Data Migration ProjectBloomerang
Donor data migration to a new CRM can be downright frustrating for some nonprofits. Planning is critical. More importantly, however, you need to prepare for the inevitable decisions you will have to make during the process.
In this webinar, we will examine 10 decisions for which every nonprofit needs to be prepared in order to experience a successful transition to a new CRM.
Learning Objectives:
Understand the CRM data migration process.
Identify the key decisions that will be made along the way.
Discuss pros and cons of decision options.
Take away from the event a sense of preparedness and control over your next data migration project.
Be able to apply what you’ve learned to other data migration projects at your organization.
10 tough decisions donor data migration decisions (Webinar hosted by Bloomera...Brandon Fix
If you’ve migrated donor data from one CRM to another, no doubt you have dealt with a lot of difficult decisions. In fact, our donor data migration clients often express surprise at the number of decisions they have to make. In this post, we discuss our list of Top 10 Tough Donor Data Migration Decisions. From our webinar hosted by Bloomerang on August 20, 2014. Presented by Gary Carr, CEO Third Sector Labs.
10 Decisions You Will Face With Any Donor Data Migration ProjectBloomerang
Donor data migration to a new CRM can be downright frustrating for some nonprofits. Planning is critical. More importantly, however, you need to prepare for the inevitable decisions you will have to make during the process.
In this webinar, we will examine 10 decisions for which every nonprofit needs to be prepared in order to experience a successful transition to a new CRM.
Learning Objectives:
Understand the CRM data migration process.
Identify the key decisions that will be made along the way.
Discuss pros and cons of decision options.
Take away from the event a sense of preparedness and control over your next data migration project.
Be able to apply what you’ve learned to other data migration projects at your organization.
10 tough decisions donor data migration decisions (Webinar hosted by Bloomera...Brandon Fix
If you’ve migrated donor data from one CRM to another, no doubt you have dealt with a lot of difficult decisions. In fact, our donor data migration clients often express surprise at the number of decisions they have to make. In this post, we discuss our list of Top 10 Tough Donor Data Migration Decisions. From our webinar hosted by Bloomerang on August 20, 2014. Presented by Gary Carr, CEO Third Sector Labs.
Adcieo recently co-hosted a data management webinar with Third Sector Labs. The topic - "Why don't you have a data management plan?" - focusing on why you need, and how to create, a nonprofit data management plan.
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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.
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This session explored the ideas beneath the Open Leader Method(TM), a unique leadership programme for leaders in IT.
Don't let bad data be the grinch to your holiday appeal (dec 10 2013)Third Sector Labs
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Your year-end holiday appeal is about to launch. Most of the work has been done. What next?
If you are like most organizations, you can't wait for the responses to start coming in. The impact of your holiday appeal reaches throughout your organization. But are you ready to manage the response? Did your plan include a 'before' and 'after'? Are you managing your donor data, or is it managing you?
-The most common advice consultants are sharing with their clients about fundraising mistakes - and why they are wrong.
-How bad data trumps the best of content.
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Data Management: Case Study Presented @ Enterprise Data World 2010Jaime Fitzgerald
A Fitzgerald Analytics client case study about the practical, high-value first steps taken by the head of technology at Bridgestone Firestone's consumer credit company, which provides private label credit cards used by millions of customers in 5,000 retail stores selling tires and automobile repair services. The presentation describes a technology and data management gap that existed, successful steps taken to fix the gap, and the benefits achieve in quality, efficiency, and ROI on data analytics from a major data warehousing and data integration effort.
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As the Comptroller's Handbook states, "a bank’s first defense against excessive credit risk is the initial credit-granting process, sound underwriting standards, an efficient, balanced approval process, and a competent lending staff." The start of a new year is the perfect time to review and improve your credit risk culture.
Garrett Morris, director of consulting at Sageworks, discussed the key elements of a strong credit risk culture, including:
-Three Ps of credit analysis
-Five Cs of credit
-Five Cs of data collection
-12 questions to ask at your institution
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In this presentation Daragh O Brien looks at the history of information management, the challenges of data quality and governance, and the implications for big data...
Do you spend hours struggling to manually produce the reports management demands? Are you working with disparate islands of outdated data? And, after all that hard work, are the reports produced inaccurate and untrustworthy?
One of the easiest ways to improve the quality of information that you are able to provide is by simply sourcing good data. This presentation will show you the best practices for sourcing data to ensure that it is trusted, credible and reliable.
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2. Welcome
o Your year-end appeals are done
o Spring activities will soon be upon us
o So that means it is … (finally) … time to
tackle that data migration to your new CRM
Today, we are going to talk about a very
common problem with data migrations
3. Agenda
1. Introductions
2. Decision to move to a new CRM
3. Challenges of data migration
4. Problem of data degradation
5. Solution: data governance
6. Measure of data migration success
7. Conclusions
4. Introductions: Bloomerang
Bloomerang offers a cloud-based CRM solution
incorporating best practices in fundraising, loyalty
engagement, and donor retention.
o Jay Love is the co-founder and CEO of
Bloomerang
o Jay’s experience with nonprofit software
includes co-founding eTapestry, and leadership
positions with Avectra, Blackbaud and Master
Software Corporation.
Website:
www.Bloomerang.co
Email:
jay.love@bloomerang.co
LinkedIn:
www.linkedin.com/in/jaybarclaylove
5. Who is Third Sector Labs?
Third Sector Labs is a data services company
challenging nonprofits to re-think their data practices
o Gary Carr is co-founder and CEO of TSL
o Gary’s leadership experience includes Carr
Systems, Kintera, KindMark and United Way
Website:
www.ThirdSectorLabs.com
Email:
gcarr@thirdsectorlabs.com
LinkedIn:
www.linkedin.com/in/gpfcarr
Our data tip of the week:
Facebook & Twitter
7. Setting aside the lexicon debate
Systems for managing an organization’s interactions with current
and future consumers
o CRM
o Customer relationship management
o Constituent relationship management
o Customer-centric relationship management
o Donor management
o Membership management
o Social CRM
o There are other terms
8. Which CRM?
o You’ve made a very difficult decision …
o You selected new CRM software
( Whew! )
o The hard part’s over, right?
o Well … no.
Keep
old
system
Pick new
“just
right”
system
Pick
new
super
fancy
system
9. Why aren’t we done?
o We will get to that …
o But first, let’s look at the decision you’ve just
made
10. 10 Reasons to Change CRMs
1.
It’s just old
2.
Inflexible database – can’t customize
3.
Not enough supporting modules – like events, email, social
4.
Poor reporting
5.
Limited accessibility / no mobility
6.
Too hard to get the data out
7.
Too expensive
8.
Client server hosted / no cloud version
9.
Incapable of supporting new fundraising initiatives
10. The data is a mess ... and that must be the CRM’s fault
11. How did you make the decision?
1. Hire a consultant
2. Involve internal stakeholders
3. Establish criteria for the new CRM
o Must haves
o Nice to haves
4. Test drive multiple solutions
o … because we LOVE talking to salespeople
5. Narrow the contenders, final reviews, confirm
the budget, and CHOOSE!
12. Most importantly …
o You’ve made a forward-looking decision.
o You’ve bought one of these.
o And now you are getting ready for the new
racing season.
13. What about the data?
o “That’s easy … move it all!”
o This is the most common expectation we
encounter
o And so we enter the dark, cavernous world
of …
15. Don’t be scared by data
o Data is fueling the growth of the Internet,
technology and business.
o Especially personal data.
o And it’s the ultimate renewable energy …
everyone produces it, every day.
17. How do we get the right fuel
into your new CRM?
The challenges of data migration
18. In other words …
o You can’t take all that old data with you
to your new CRM
o It will …
o Slow your system down
o Hold you to old business practices
o Cost you money
19. Recognize the change of direction
o Old system reflects your old way of doing business
o New system reflects new way of doing business
o For example …
o Fields, field definitions have to be re-mapped
o Those notorious “miscellaneous text fields” need to be
interpreted and parsed …or just ignored
21. Data degrades – why?
Cause #1: your organization
o
o
o
o
Lack of data entry standards
Unskilled data entry workers
Common mistakes
Record fragmentation
22. Data degrades – why?
Cause #2: the technology
o
o
o
o
o
Record fragmentation
Multiple, disparate systems
System upgrades
Integration, processing errors
Sheer volume of data
23. Data degrades – why?
Cause #3: the donor … life!
o Change in address … every 5 to 7 (?) years
o Change in jobs … 9 to 11 jobs in a lifetime (?)
o Family / life event … divorce rate, birth of
children, death … what else?
26. Our view (once we export and analyze)
Salut
ation
Last Name
First
Name
MR
Setters
MS
SIMMS
Laurie
Mr.
singletary
Mike
Singletary
Michael
Solvington
Allen
Mr.
soprano
Cindy
Dr.
Standish
M.I.
Address 1
City
State
Zip
Email
DOB
Gender
m
1313 Danger
Ln
Appleton
CA
73111
Cupertino
CA
91001
222 Main St.
Cupertino
CA
1141 Duke
Ave
Los
Angeles
CA
8726 Elm Ave
Appleton
CA
90009
STEVENS
ROBERT
2101 Data Ave
Los
Angeles
CA
Juan
20B Eldora
Mexico
City
also@mail.com
91010
Tahoma
mike@mail.com
323.555.5990
04/29/81
F
M
91010
Allison
mts@mail.com
91002
Bradford
Laurie@mail
310.555.1234
5201 Marshall
Lane
310.555.5555
310.555.1234
T
Stevens
Sr
Phone
P.
2
05/30/75
cindy@mail.com
310.555.5551
f
f
rs2@mail.com
+52-55-5222-2
222
01/01/01
12/14/60
m
jtahoma@mail.c
om
01/14/59
M
29. And let’s not forget
o Bad data costs your
organization money … every
time you try to use the data!
Bad data
Incomplete data
Corrupt data
Too much data … big data …
really BIG data
o Fragmented data
o
o
o
o
Can you
afford to flush
money
away??
30. Let’s look at some
customers
The data migration lineup
32. The Purger
o Knows they have data problems
o Doesn’t trust own data
o Has 15 appeal codes, uses 3
o Hasn’t deleted a record in 6 years
o Wants to start all over
o The more we say “this can’t be migrated”, the happier they
are
o Migration = freedom
33. The Hoarder
o Also hasn’t deleted a record in 6 years … or 10 years
o Wants to keep everything … “just in case”
o Doesn’t understand the cost of so much bad data
o Will put “DECEASED” into Notes field, “BAD ADDRESS” into
address field
o Has 3 versions of the same field code
o (event, annual event, special event … used interchangeably)
o Needs training / time to understand why they have too much
data, in too many fields, with too many codes
34. The Merger
o Comes to the migration “ready to deal”
o Knows they need help
o Understands CRM can be a tool to help them
“control” their data
o Focuses on the future, and is willing to let go of bad
data
o Able to provide constructive feedback on data
mapping
35. “You decide”
o May or may not understand the extent of the data problems
o Doesn’t know the org history of how the data has been
managed
o Understaffed and doesn’t want to invest time in data migration
decisions
o Willing to let the consultant “do what needs to be done”
36. “OKAY … WE GET IT!
What do we do?”
That’s where we come in
37. Step one: admit the problem
In other words …
o Recognize that all of your legacy data isn’t
coming over to your new CRM
38. Step two: apply data governance
Data governance
o What’s that?
39. So, let’s standardize …
1. How old is too old?
o Depends on the type of record?
2. How many versions do you retain?
o How many old addresses?
o Event attendance records?
3. What defines an incomplete record?
o Do you have a process to enrich / complete those incomplete
records?
4. Also …
o Do you enable donors/consumers (or a subset) to manage their
own information via online accounts?
o Do you have self-select removal processes from (e)mailing lists?
40. And prioritize
1. Which standards are most important?
2. Which are least?
Give your data migration engineers the guidance
they need to do the job you need done
41. Step three: Target outliers
o What are the exceptions?
o What about those miscellaneous text fields – how will
they be interpreted, parsed and migrated?
Last Name
First Name
M.I.
Address 1
Soprano
Cindy
P.
222 Main St.
Standish
Bradford
1141 Duke Ave
Stevens
Allison
8726 Elm Ave
Address 2
…
Notes
Graduated U of Michigan in
1988 … on Board of United
Way of SE Michigan … 3
children
Apt B
Naval Academy … loves
outdoors, biking, hiking …
married with 1 child
42. Step four: Review and go
o Once the new CRM database is created and the
data fields are mapped between legacy and new,
make sure you understand what is being migrated
and what is being left behind.
o Is this acceptable?
o Be flexible.
o Then stick by your decisions and go.
44. Measure of success
NOT THIS!
Setting a % target …
“We loaded 85% of the old
data into the new system.”
Old
Data
45. Measure of success
THIS!
You have the donor data that you need in order
to conduct the fundraising and communication
activities that you have planned.
Good data!!!
46. But before you finish that migration
o Run reports
o Test exports
o Test the new CRM and its data against an upcoming activity
Working?
Good.
You are done.
Almost.
47. Don’t forget step five: archive
o Archive a copy of the legacy database in an
accessible format
o This is your piece of mind!
48. Final thoughts
1. Data cleaning
o Do you need it?
o Before or after migration?
2. Data enrichment
o What is the best approach to improve the amount and
quality of data associated with each record?
3. Data management plan
o Have you considered a quarterly data review to keep your
data as clean and current as possible, and to expose
emerging problems?
49. How we can help
... Start with a data assessment,
schedule data hygiene or develop a data quality
plan
… CRM platform built to deliver higher
donor retention and better fundraising results
50. Thank you !!!
Questions ???
You can read more about this topic on our blog at:
Thirdsectorlabs.com
Please stay tuned for our upcoming webinar in March:
“If your data isn’t getting better, it’s getting worse: why?”