Easily Offending Most of the World - Data Validation Errors

I'm a huge fan of clean data, anyone who has read this blog for long knows that. However, clean data can never trump customer experience. Many times, simple tactics that you use to manage your incoming data can have large and unintended consequences.

The example that prompted this post was a Zip Code validator on a web form. The form did not specify country, and it was for the download of a whitepaper, so it was not something that seemed likely to be restricted to only viewers from the United States. However, the Zip Code field had a validation javascript on it, and required a Zip Code that was correct according to US standards.

I'm from Canada, and we have Postal Codes that use numbers and letters in a A9A 9A9 format, so clearly this did not pass the test, and I received an error alert. I dashed off a quick note to the site owner, and then filled in the only Zip Code I have top of mind - 90210.

This is an interesting example, as it highlights a mis-match between the user experience on that web form, and the quality of the data. Bringing the data management in house into an inline data management process like a contact washing machine is usually the best bet, while minimizing the burden placed on web form visitors. For address information, using address validation to balance the user experience can often be better than restrictive forms.

In thinking about the experience of your landing page visitors, be sure to balance the need for quality data with the need to deliver a great experience to your visitors.

Address Validation and the User Experience

It’s challenging to optimize the forms on your landing pages to make sure that you maximize both your conversion rate and the quality of the data flowing into your marketing database. The more fields we require, the worse our conversion rates are.

Similarly, performing inline validation on form data that prevents a submit can be very dangerous if done incorrectly as it will prevent submissions or frustrate visitors. One area that offers great promise to optimize is in the realm of address correction. If you are collecting physical addresses, either to use for direct mail marketing or for management of sales territories, you want the addresses to be correct.

However, we have all had experiences with websites that attempt to force an inline correction of our address and end up frustrating us as visitors.

Luckily, there is an approach that balances data quality with customer experience. Using a built-in function within your marketing automation programs, you can leverage Pitney Bowes global address standards database to automatically correct your addresses. This allows you to let visitors to your website experience a very flexible free-form approach to entering their addresses, but allows you to quickly correct those addresses to ensure that your data is very accurate.

To do this, from your marketing automation program, create a step that is an "Address Correction" step, into which your contacts, prospects, or companies will flow. The action, available under the "Data Tools" set, is "Run Address Validation". Note that this is a paid service, but the per-hit fee is very reasonable.

Within the program builder step, that is all you need to configure. However, if you want to configure the fields that are sent/returned for correction, you can configure them in the Setup area.

Go to Setup->Management->System Management->Add-on Manager to manage the address validation add-on.

Select the Address Validation add-on.

Within the setup interface for the Address Validation add-on, you will see a Task menu in the upper right corner, under Tasks, select Set Field Mappings.



This then gives you the mapping interface for the set of fields that are sent out to the address validation service and returned in a corrected manner. Select the fields from your own marketing database that you would like to use, or use the defaults that are already set.



If you use an address validation service, rather than forcing the user to wrestle with an inline validation, you allow the 5% of new or unknown addresses to pass through without causing user frustration.