simplified data mining for direct mail

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Sponsored by: Simplified Data Mining for Direct Mail Sue and Ron Rescigno May 28, 2013 Use Twitter Hashtag #npweb Part Of:

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Don’t waste time and money by trying to communicate to those who have shown little or no affinity to your cause. Our webinar will examine how to look at your constituents through the filter of your database, thus providing a better understanding of who they are and what they are interested in. Know your audience…manage your data. Successful fundraising strategies depend upon it!

TRANSCRIPT

Page 1: Simplified Data Mining for Direct Mail

Sponsored by:

Simplified Data Mining for Direct Mail

Sue and Ron Rescigno

May 28, 2013

Use Twitter Hashtag #npweb

Part

Of:

Page 2: Simplified Data Mining for Direct Mail

Sponsored by:

Protecting and Preserving the

Institutional Memories of

Nonprofits Since 1993

www.cjwconsulting.com

(866) 598-0430

[email protected]

Part

Of:

Page 3: Simplified Data Mining for Direct Mail

Sponsored by: Part

Of:

Coming this June

Page 4: Simplified Data Mining for Direct Mail

Sponsored by:

Today’s Speaker

Ron and Sue Rescigno President & Vice President

Rescigno's Marketing Connections

Hosting:

Cheri J Weissman, CJW Consulting & Services, Inc. Assisting with chat questions: Jamie Maloney, 4Good

Part

Of:

Page 5: Simplified Data Mining for Direct Mail

Simplified Data Mining for Direct Mail

Ron and Susan Rescigno

708.974.2600

Page 6: Simplified Data Mining for Direct Mail

In this presentation we will answer…

What is data mining?

What data should I be gathering?

How can I use data for my fundraising campaigns?

How can looking at data save me money and

reduce my costs?

How can I maximize my fundraising budget by

making more money with less of a budget?

How can I give this data to a mail house that

understands what I mean?

Page 7: Simplified Data Mining for Direct Mail

Data Mining is the search for hidden information:

The locating of previously unknown

patterns and relationships within data

using a database application.

Page 8: Simplified Data Mining for Direct Mail

The real answer to that depends on how you want to target your message to your audience. But

here are a few that you absolutely should collect:

Name (first and last in separate fields)

Salutation (My name is Susan but most people call me Sue)

Age

Year of Graduation

Affiliation with your organization

Gift Amount

Date of last gift

Response code (what solicitation they responded to)

Programs or Services that they are interested in supporting

Birthday

ETC…

What information should you be gathering to improve

your fundraising campaigns?

Page 9: Simplified Data Mining for Direct Mail

Once you have collected the

information and put it into the system,

it can be used by segmenting your

data into groups and writing

specifically to each group member.

Here are some ideas of different

segments…

Page 10: Simplified Data Mining for Direct Mail

Ideas for Segmenting

Donor/Non Donor

Age

Gender

Friends

Current Parents/Parents of Alums

Lybunts/Sybunts/Event Attendees/New Members

Past Patients Community Members

Page 11: Simplified Data Mining for Direct Mail

Segment Options

•Major donor – this referenced their largest gift

from the past 5 years

“John, the Brothers always appreciate your

support. Among your gifts over the years was an

especially generous $1,500. Please know that

we are grateful for your support at whatever

level is comfortable for you. We would like to

ask, however, if you could consider renewing

your support at that significant level.”

Page 12: Simplified Data Mining for Direct Mail

Segment Options

LYBUNT – last year donor

“John, the Brother’s always

appreciate your support and thank you

for keeping up with us, most recently

with your contribution on March 5,

2011 of $100. We hope we can rely on

your continued support at this level.”

Page 13: Simplified Data Mining for Direct Mail

Segment Options

Event Attendee

“John, the Brothers always appreciate your

support and thank you for keeping up with us

through your attendance at alumni events over

the years. If now would be a good time for you to

invest $50 or $100 or more, you would be helping

us significantly as we strengthen our efforts to

invite young men to join us.”

Page 14: Simplified Data Mining for Direct Mail

Personalized Mail

Campaigns offer:

– Increase Response Rates

– Increased Average Gift

Rates

– Improves Campaign ROI

The average response rate

for a static direct mail piece

today is .5%, but when we

personalize that piece, the

response increases to 3% -

4%.

Why should you worry about collecting data and using it in

your direct mail campaigns?

Example:

2,500 x .5% = 2.5 responses

2,500 x 3% = 75 responses

5,000 x .5% = 25 responses

5,000 x 3% = 150 responses

10,000 x .5% = 50 responses

10,000 x 3% = 300 responses

Page 15: Simplified Data Mining for Direct Mail

“The Question should not be how many can

we mail within our budget. The question

should be how many do we have to mail in

order to achieve the desired results.

Personalizing your piece will get you higher

response rates. The desired result is always

a better response!”

- HP 2010

Page 16: Simplified Data Mining for Direct Mail

So how can we save money by looking at our data?

First look at how many you are mailing to and what your

response rate is

Should you be mailing to all of these people on your list?

When is the last time you heard from these people?

Are you writing to them about something they are interested in?

Are you writing to them just because this is the list you inherited and you

never really looked at it?

Page 17: Simplified Data Mining for Direct Mail

Data mining is the most cost

effective way to increase your

ROI for direct mail

$ $ $

$

Page 18: Simplified Data Mining for Direct Mail

Staying Cost Effective

If you are mailing to 12,000 people and getting basically

the same 1,300 donors to renew their gift every year,

then you have to ask yourself if that is cost-effective.

By taking a look at your donors, you can find the patterns

or similarities in them and find out what your average

donor looks like. For example:

Gender

Age

Income range

Geographic location

Page 19: Simplified Data Mining for Direct Mail

What’s NEXT?

You can then take that information and find those

that match that group in your non-donors. You could

cut your list in half or even more.

I am not saying don’t communicate with those other

but in a time when you have to watch your budget so

closely, maybe you shouldn’t be mailing to them as

much as the donors.

Keep them on newsletter lost and email list.

Page 20: Simplified Data Mining for Direct Mail

This is an example of a small non-profit, only

8 years old, that wanted to start a direct mail

program. Instead of mailing to everyone on

their list, they narrowed their list of 10,000

people to 1,202

Community College Foundation – Current Client

Description Quantity Mailed

Responses Average Gift

Total Dollars Raised

Response Rate

ROI

Holiday Appeal

1202 81 $135.21 $10,707 6.7% 331%

Page 21: Simplified Data Mining for Direct Mail

Description Quantity

Mailed Responses Average Gift Total Dollars

Raised Response Rate

ROI

Holiday Appeal 1202 81 $135.21 $10,707 6.7% 331%

So, let’s look at this and use these numbers to get a good picture of this

organization. This is the first time they have mailed a solicitation letter to

their constituents.

-They started with a small number of 1,202 prospects

-Their response rate was 6.7%, so they targeted the right list

-They raised $10,707 dollars

-They received a 331% return on their investment

(They invested about $3,000 into this project and raised over $10,000.)

-They also have 81 people who have given them a gift with the

majority being first time donors

Page 22: Simplified Data Mining for Direct Mail

Now what..?

Now that we’ve discussed what data mining

is, what kinds of information should be

gathered, how are other organizations using

their personalized data and how you can use

it to save money on your direct mail, we need

to talk about how you can collect the data

and present it to the mail house so mistakes

are not made.

Page 23: Simplified Data Mining for Direct Mail

Data – what to include

•Minimum fields:

•Name (full name or prefix first middle last suffix fields)

•Address

•City, State Zip

•Additionally:

•Company

•Title

•This is your ADDRESS BLOCK

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Data – what to include

•Include additional fields used in the mailing

•ID

•Ask Amounts

•Last Gift

•Salutation

•Segment Version

•Include fields not needed in the mailing for internal use,

such as ID numbers or dates or last gift

Page 25: Simplified Data Mining for Direct Mail

Sample Data with Extra Fields

This is a sample of data with the mailing info, but

also fields needed to segment on our end and data

used by the client to pull their data.

Page 26: Simplified Data Mining for Direct Mail

How to add information to your existing data

•Put reply codes on reply devices to track campaigns

•Personalize your reply cards and ask for updates (incl. ID

#’s to make data entry easier)

•Leave room for Cell #’s, Email, etc.

•Utilize data append services – can add age info, income,

ownership, etc.

Page 27: Simplified Data Mining for Direct Mail

Data – formats

•Best – Excel or Access table

•Also accepted – comma or tab separated

•Each field should be in its own column

Page 28: Simplified Data Mining for Direct Mail

Data – what NOT to do

•Do not include line breaks in data – example:

•7501 W 85th St

•Suite 110

•It should instead read: 7501 W 85th St Suite 110

•Do not include notes in the address fields

•Do not setup the list as “address labels” in word or excel

Page 29: Simplified Data Mining for Direct Mail

Data – what NOT to do

•Do not include multiple mailing addresses (like home and

work) in the same record. You should have TWO records

for this person

•We CAN fix data that is not in the right format, please

contact us BEFORE the job comes in.

Page 30: Simplified Data Mining for Direct Mail

Your data and you…

•Your donor database should be your institutional memory.

•it should make it easy for you to look up donors, view

giving histories, understand relationships and analyze

trends.

•It should help your fundraisers work more effectively.

•It should be an aid, NOT a chore!

Page 31: Simplified Data Mining for Direct Mail

Rescigno’s Data Consulting

•Rescigno’s Marketing Connections can help you with your

data.

•Available for consultation, database creation and

updates/pulling queries

•We can host your database and give you remote access to

it.

•We can append your data with more information.

Page 32: Simplified Data Mining for Direct Mail

Thank You!

Any Questions??

708.974.2600

Page 33: Simplified Data Mining for Direct Mail

Sponsored by:

Find listings for our current season

of webinars and register at:

NonprofitWebinars.com

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