In a perfect world, a fundraising database would be, well, perfect.  Imagine for a moment your CRM system with every name spelled correctly, all addresses and emails updated, every gift entered accurately – it’s a beautiful thought, isn’t it?

It is, however, extremely rare to find a “perfect” database.  There are always issues, anomalies and mistakes.  And, of course, donors and prospects don’t always give us their full information or don’t alert the organizations they support when they move or change information.  Indeed, we can always expect some level of data degradation year after year.

The challenge, though, is that loss of data quality over time tends to compound in the absence of any attempts to correct or update records.

For example, imagine a database of 10,000 records that stays relatively constant from year-to-year.  It’s made up of donors and prospects and the Average Constituent Value of each individual is calculated each year.

A quick sidenote – Average Constituent Value of a prospect is a measurement of what each record in a database is worth to the organization.  The formula is basically this: Total Dollars Donated (Paid) divided by Total # Records.  For the purposes of our example, we’re saying $78,000 divided by 10,000 individuals equals Total Value of $78.  In other words, every record in the database is worth $78.  (This metric is, of course, different than Average Gift which is total dollars divided by number of donors.)

Our hypothetical database has a 2% rate of data hygiene issues.  That is, 200 records have some data quality issue that means the prospect cannot be reached (this is, of course, separate from Do Not Mail, Do Not Solicit, Do Not Call, etc.).  In Year 1, that accounts for $15,600 in potential dollars lost.

If nothing is done to correct the data hygiene, that loss compounds year after year.  Over five years, those same 200 individuals represent a total potential loss of $81,800.

What also happens, though, is that additional records start to degrade in quality so the pool of “lost” donors grows.  As does the compounding dollars lost.

  Year 1 Year 2 Year 3 Year 4 Year 5
Total # Records 10,000 10,000 10,000 10,000 10,000
Total $ Donated (Paid)  $780,000  $840,000  $860,000  $820,000  $790,000
Average Prospect Value $78 $84 $86 $82 $79
Un-solicitable Records 200 200 200 200 200
(Hygiene)   50 50 50 50
      50 50 50
        50 50
          50
Dollars Lost $15,600 $21,000 $25,800 $28,700 $31,600
Dollars Lost Year 1 Prospects $15,600 $16,800 $17,200 $16,400 $15,800

Over time, the dollars lost relative due to poor data hygiene starts to translate to real dollars and significant lost opportunity in money raised and ongoing relationships with donors.

The Solution

First and foremost, maintaining data quality becomes a key priority for everyone who has access to the database.  Creating – and following – a data style manual helps to ensure both accuracy and consistency in data records.  WealthEngine’s Annual Fund Workbook and Growing Individual Gifts Workbook both detail auditing procedures and recommendations for creating a data style manual.

Regular data cleansing and appends become of critical importance as well.  Conducting regular NCOA updates, phone and email appends and deceased overlays also help to ensure that data quality remains consistent.

Some records just cannot be fixed – people have moved or there is no way to find what the correct data is.  “Coding these out” as unsolicitable becomes critical and any evaluation of prospect value should not include these unsolicitable records.

The above example assumes a static database; there are always new prospects and donors coming into a dataset so ensuring that the quality of new data is high helps to offset loss in quality of existing records.  When new lists are acquired, ensure that all records have valid, solicitable addresses before importing into the database.

Data quality is everyone’s job.  No area has more impact on potential dollars raised at every level than how good – or bad – the data is.  Plus, it’s good stewardship to ensure we’re able to stay in touch with the individuals who support our mission.

Check out more information on WealthEngine’s data cleansing process, WE Clean, or list acquisition, WE Prospect.

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