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In 2017, Whip Your Data into Shape

  • Tamara Berry

    Tamara Berry

Created at January 5th, 2017

In 2017, Whip Your Data into Shape

It’s that time of year when everyone is talking New Year, New You. New beginnings, changes in fortune, and for marketers another chance to achieve our “omnichannel” dreams.

Our inboxes will soon be flooded with Key Marketing Trends for 2017, State of the Industry Reports, Statistical Fact Books, 2017 Industry Previews and the like. We will feel the stress of looking back at our past campaigns and determining our success rates. What went right? What went wrong? Was our creative on point? Did we generate revenue? And we will begin asking ourselves what to do to bring marketing to the next level – reaching for the holy grail of “omnichannel.” How does one engage with customers and prospects across channels with consistent messaging without being annoying?

Start with the basics: current, correct and clean data

Before you can reach anyone on any channel you need to know that the customer and prospect data you have is current, correct and clean.

In a survey of more than 1,200 organizations, 42 percent of respondents cited inaccurate contact data as the biggest barrier to multichannel marketing. 83 percent of marketers say they’re struggling to create a single customer view due, in large part, to the poor quality of their data. (Econsultancy 2014)

Data quality is the foundation of a successful marketing program and a successful business. It’s simple; if your customer database isn’t clean, correct and up-to-date, your perfectly tuned messages won’t reach the targeted recipients. You’ll spend more money for a lower response rate, reducing your return on investment.

So ask yourself: Is your customer data giving you the right foundation, or are you building marketing campaigns in the sand?

If you or your company are not performing regular maintenance to ensure the quality and accuracy of your customer data, the answer may be yes. But it’s never too late to start. Simply understanding how data hygiene works is the first step to having cleaner, better data on which to build your marketing campaigns.

Quality data regularly goes through data hygiene. It is “clean data.” It has been standardized, updated and void of redundant information (no duplicates). It is correct, complete and current.   And it’s never a one-time thing. Going through a quarterly data hygiene review is key to maintain accurate contact records because dirty data can sneak into your marketing process in a variety of ways.

Some include:

  • Missing data: Form fields left empty, either intentionally or unintentionally, that should contain customer information.
  • Outdated data: Customer information that was correct when input but has since changed.
  • Mislabeled data: Data that has been entered into the wrong field and is assigned to an improper element.
  • Non-conforming data: Data that hasn’t been normalized.
  • Duplicate data: A single account, contact, lead, etc. that occupies more than one record.
  • Customer error: Misspellings, typos and variations in spelling, naming or formatting.
  • Intentionally incorrect data: Data that contains false information. This can range from a fake name to nonsense and profanity purely intended to fill a required field.

To help you fight the good fight, here are three tips for improving data quality. The more proactive you are about data quality and the more you plan for it, the greater the ROI you’ll achieve!

Clean Once

You have tons of customer data collecting dust in your marketing database. Don’t wait to start cleaning existing data – act today to start benefiting from the results! It is likely you have lots of outdated information. Thankfully, there are many solutions to clean your data. Many companies offer a service that allows data to be sent, processed and returned quickly. Even if rules and regulations prevent the updated data from being used directly, at least there is information about the state of the data and what effect the quality of data has on existing operations.

Clean Early

Correcting a record before it gets in your customer database is in your best fiscal interest. Once the data becomes “official,” it becomes exponentially more expensive to get rid of.

Therefore, businesses should implement a process for cleaning data as it comes in. This includes defining the standards for what complete and normalized records look like so the database grows in a healthy way. The best ways to do that are through a real-time process and preventive measures. Creating form requirements that mandate an @ symbol in an email address field can help minimize mistakes and false data. Using the right tools and processes will limit the amount of bad data.

Clean Often

Because data quality decays so quickly, data must be processed regularly to minimize data quality issues. As with the initial cleaning, data can be sent to a third party for processing, but you may also want to consider using a quality data solution in-house. There are many solutions that allow in-house, on-premises data quality processing.

The future of marketing is here, and it’s rooted in data quality. New Year, New You; Better Data, Better Marketing Campaigns.

If you want to learn more about better data hygiene, download Acxiom’s eBook “Big Data’s Dirty Problem.”