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Present

&

Why Don’t You Have a Data Management Plan?

(it’s not that hard)

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Welcome and Agenda

Please participate in our online poll while we get organized

Today’s agenda1. Why we don’t have data management

plans2. Why we need them3. How to create one4. What to do with it

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Our Experts

Gary CarrPresident & 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.comwww.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 SnyderVP, Sales & Marketing

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LEVEL 1:ASSESSMENTS AND

CLEANING

LEVEL 2:DATA MANAGEMENT,

ENRICHMENT, MIGRATION

LEVEL 3:WAREHOUSING,

MINING, VISUALIZATION

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

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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

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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 ….

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Why don’t we have data management plans?

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Why don’t we have data management plans?

1. We have lots of other plans!2. Data is intimidating3. 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 create6. We plan events … we react to data

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When we think of data management plans …

Examples of data management plans

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It may feel like this …

But it’s not

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Why do we need data management plans?

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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 …

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1. Data degrades

“If your data isn’t getting better, it’s getting worse.”

-- TSL data scientist

“Why?”

-- audience

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Data degradation

What does that mean?

Data degradation – [DAY-tuh deg-ruh-DAY-shun], nounRefers 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 degradesCause #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.

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Our view of your data (once we export and analyze)

Salutation

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 #)

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2. More data than ever

Donation$

Special events

volunteering

Emails and emails

Broker lists

Social m

edia

Job change

Address change

Financial transactions

newsletters

Dir

ect

mail

Alma mater

Family updatespolls

Robo calling

spreadsheets

Donations to other charities

Onl

ine

surv

eys

We leave footprints

everywhere

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3. More technology Takes us from this …

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More technology

Aha!Here she

is!

To this …

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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

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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 = ??

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Remember

Data is your organization’s knowledge and memory

What you knowWhat your organization knows

Vs.

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How do we create a data management plan?

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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

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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!

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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

HERE

Assess problems

Clean data

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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

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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

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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

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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

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Sounds harder than it looks … an example

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Remember: start simple

The map1. What data do you

need2. Data assessment 3. Gaps

The plan4. Prioritize gaps5. Action item for each6. Schedule7. Governance

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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

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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 duplicates2. 30% lapsed donors3. 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

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Step 3: (Map) Gaps to close

1. Bad data to be cleaned2. Duplicate records to be removed3. 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)

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Step 4: (The plan) Priorities

1. Clean bad data and remove duplicate records2. 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

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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 dataB – update addresses

2 Increase prospects 10%

Web, event outreach

Upgrades to website, other forms of data capture

A – marketing service to capture web visitorsB – event capture toolC – 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 fieldsB – add website data capture featuresC – data brokerD – 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

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Step 6: (Plan) Schedule

First 3 monthsClean bad data

Modify dstabase(s)Improve website registration

Create Facebook pageNCOA clean up

Second 3 monthsData broker service for one-time

augmentationImplement website survey, pollsLapsed donor data cleanup (after

lapsed donor campaign has completed)

Third 3 monthsCreate new donor segmentations

Test against target message marketing program

Fourth 3 monthsMeasure results of segmentationRevise data management plan

Every quarter Data cleaning

Re-run assessmentMeasure new data collection methods

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Step 7: Data governance

What is that?

Data governance– [DAY-tuh GUHV-er-nuhns], nounA 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.

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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?

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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?

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When it comes to data …

garbage in, garbage out

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What do we do with our data management plan?

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Do this!

1. Assign responsibilities2. Budget3. Work it for 6 months4. 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 leadership6. Revise and continue

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Let’s wrap it up

TakeawayOld thinking: we plan our events, we react to

data

New thinking: we plan our events AND we plan our data management

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We’d like to hear from you!

Please submit your questions…

Q & A

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Thank You!

Gary CarrPresident & 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 SnyderVP, Sales & Marketing