When it comes to contact data, many marketers want to collect as many contacts as they can. There are so many pieces of content to be shared that sometimes all we care about is getting as many people in our audience as possible. Quantity becomes more of a priority than quality. However, it’s times like this when we have to take a step back and remember that the quality of our data is actually the most important thing to remember.
Why Is Data Quality So Important?
As mentioned in our 2017 Budgeting whitepaper, data-driven marketing is becoming more and more imperative with all of the data analytics tools coming into the market. That means data-driven marketing campaigns are expected to improve your conversion rates and bring back significant ROI. However, if the data quality isn’t up to standards (consistent, relevant, and accurate), your insights from the marketing campaign could be misleading! If you’re bringing back insights from dirty data, you may end up creating a strategy that hurts your conversions and ROI rather than helps it. No one wants to end up in that situation and that is why it is so important to maintain high quality data. Focus on who the ideal audience is for your content and then find data that matches that criteria. Even if the quantity is low, it’s more important to set yourself up for success with quality data rather than dealing with large quantities of misleading, risky data.
How Do You Know It’s Quality Data?
There are a few elements that go into answering this question. First, you need to know your own goals for a campaign. Who are you trying to target? Once you know that, you can identify the similar characteristics of your audience and pull from that information. Generally, these characteristics or traits are found within a customer’s contact record. So if the contact data you collect meets your campaign goals of finding people similar to your target audience, then the data is high quality.
Second, the data must be clean and up-to-date. Quality and cleanliness go hand-in-hand. Unfortunately, it’s impossible for a marketer’s database to be 100% clean, but marketers can get pretty close with data cleansing. In our blog about the current state of data quality in B2B marketing, we mention that marketers aren’t traditionally skilled at collecting and analyzing data, let alone cleaning it, so it’s important to team up with a data partner, whether in-house or outsourced, to keep your data clean and in its highest quality on an ongoing basis.
Third, the data is normalized and standardized. This means that of all the different ways the data is input, once it’s put into your database, it keeps a consistent pattern so that you don’t find duplicates later on. For instance, phone numbers are all listed in the same format (i.e. (123) 456-7890 or 123.456.7890) or titles are all standardized (i.e. VP, V.P., and Vice President are all listed as Vice President).
Lastly, the data is enriched. The standard fields collected are first name, last name, company, and email, but quality data will go beyond just those fields. If a contact record is enriched with multiple fields of extra data like expertise, address or title, then you know it’s quality data. A validated email address is also a good sign of quality data.
How Do I Maintain This Level of Data Quality?
As previously mentioned, marketers aren’t exactly skilled at keeping up with all this data, but teaming up with a data partner can solve that issue. While it may sound simple to maintain a clean and up-to-date database, you’ll be surprised to know that dirty data can slip through the cracks. With a data partner to help you manage your data, you can rest easy knowing quality data is attainable. If you can’t afford a data partner, then make sure you’re constantly cleaning your database manually.
In conclusion, while quantity can be appealing when it comes to data, it’s important to remember that quality data will always take precedence. After all, according to an Ascend2 benchmark report on Marketing Data Quality Trends, a clear majority of marketing influencers (62%) point to improving the quality of marketing data as the most important objective of a successful marketing data strategy.
What are your thoughts on quality over quantity? Do you agree or do you have an argument for why quantity is better? Leave your thoughts in the comments below!