Customer Data & Analytics Blog

Data Quality Can Make or Break Your Campaign

Josh Fayer | 1 minute read

data_qualityIn the business of data-driven marketing insights, quality matters. There are a lot of ways data can go awry and lead campaigns in the wrong direction. The logic is pretty straightforward: marketers use data to better understand and manage their relationship with their consumers. If this data misrepresents the population, so will the campaign. But how can data be faulty? What does it mean to have “bad” data, and what can marketers and data scientists do to set their campaigns on the right track? There are a lot of potential answers to this question.


Data accuracy is one of the most important qualities of data; essentially, it is a metric of whether or not the data is correct in what it portrays. Outdated or factually incorrect information can lead to targeting clients who don’t exist, or clients who moved or changed phone numbers, for example. Sending promotions to clients under incorrect information is wasted effort, and can create problems when analyzing the effect of a particular campaign. Data must be validated to make we’re doing our job.


Having an email address attached to a consumer’s name is all well and good, but in order to truly target an individual in a personalized campaign, marketers need to gather data from external sources to build a profile on each client. Pairing demographic, geographic, lifestyle, and social data to a consumer is the best way to paint a detailed picture of clients.


Duplicate, outdated, and otherwise poor-quality records that are lurking in your data serve to reduce the overall quality of a given data set. Cleansing is the process of sifting these out of an otherwise higher quality data set.


Great data only works to guide a campaign if marketers know how to use it properly. Applying the right analytic strategies to a large enough sample of data is the best way to support a campaign with data.


In summary

Using data to guide marketing efforts validates outreach, and drives a personalized message to individual customers in ways marketers never could before. But throwing data at a problem isn’t necessarily a standalone solution. High-quality data used intelligently across a campaign helps marketers understand the who, what, where, when, and how of running their campaigns.

 Josh Fayer manages Marketing Communications at Zylotech, where he brings an extensive background in public relations and computer science. Josh Loves music! He sings with an a cappella group, Orange Appeal, (whose recent album Unpeeled he shamelessly plugs at work), and at home he loves to mess around with a variety of instruments. Josh enjoys spending quality time with his adorable dog, and exploring around his new home near the South Shore of Boston.

If you liked this post, check out our other blog post on how to compete with companies like Amazon.

Topics: Customer Intelligence