By now, even the most entry-level marketers understand the concept of “garbage in, garbage out.” Even so, data quality remains a problem for the average organization. In fact, according to Harvard Business Review, bad data costs the U.S. $3 Trillion per year. Just when marketing operations professionals got a handle on properly obtaining and standardizing data, new technology and compliance regulations presented new challenges.
With an expanded technology stack comes many silos of data. Now, beyond just keeping data clean, we have to worry about applying data governance to break down silos. Data orchestration is a big part of modern data hygiene—the practice of taking separate data sets from multiple storage locations, combining and organizing them, and formatting them so that it’s available for data analysis tools. It’s one of the most important processes that businesses can undertake in order to automate and streamline data-driven decision-making.
Even if you’re not at the advanced stage of real data orchestration, you need to do your best to keep data clean and reliable. The things you do every day are what make a difference in your overall data hygiene. Here are 10 straightforward tactics that you should make a habit of if you want to make an impact on data quality.
10 Habits for the Highest Data Quality
1. Audit Your Data Sources
First, you need to get a complete view of your systems and any problems. Look at all data across platforms and understand what is useful and where there are gaps. What data points are needed? Which areas need the most help? Make sure you understand what information is more harmful than helpful.
2. Create a Data Quality Plan with KPIs
What expectations do you have for your data? Create KPIs that will measure the health of your data. How will you track them? You want to develop a plan for maintaining data quality moving forward, as well as understand where most errors occur and how to address them.
3. Standardize Your Data at the Point of Entry
It’s simple: your data will never be healthy if you let unhealthy data into your system. Check all important data at the point of entry—Marketo Engage forms, list imports, API integrations, etc. Make sure all information is standardized at entry, which will make it easier to catch duplicates. Work with your team to develop a Standard Operating Procedure (SOP) for data entry for long-term success.
4. Validate Data Accuracy
In order to standardize your data at the point of entry, you need to have a way to understand the accuracy of your data in real-time. There are a lot of tools out there that can help you to clean data, such as list imports. Look for tools that also offer email verification. If you’re not ready to invest in a third-party tool, you’ll need to do this manually (which is possible, but a significant undertaking that is likely to be skipped often).
5. Identify Duplicates
These records waste space in your CRM system. They also increase your campaign costs and present a host of other problems. Get rid of them as fast as you can. Make the time to go through your data periodically and scrub your contacts for dupes. This is easier if you’ve followed steps 3 and 4!
6. Erase Irrelevant Data—Prompty
Companies have a tendency to collect data they don’t need. The more information you collect, the harder it is to properly analyze and apply. Focus on collecting data that is relevant to your business and customer efforts. Try asking fewer questions of your customers. Review all of your forms and data entry points and streamline the fields to essential information.
7. Identify Gaps in Your Data
Even as companies overestimate the data they need and hang on to extra data, they might be missing fields that actually matter. As part of the data audit mentioned earlier, have a list of fields that are essential to your efforts. Think about the types of campaigns you use. For example, if direct mail is frequently leveraged, a full address including zip code will be important. Determine which contacts do not have this data, and where you will get it.
8. Append Missing Data
Having more complete and accurate data allows for better marketing as well as better decisions. However, it’s unlikely that you have the same data points for every single contact. There are platforms out there that capture information directly from first-party sites, and some software solutions can clean and compile that data for you. As regulations continue to evolve, companies will need to be more careful about how they accomplish this process. First-party data that you’ve captured yourself on each contact is ideal.
9. Keep Updating Data
Data quality is an ongoing issue. You can do one mass cleanse to start with, but you need to continue to update data as you enter it. After all, people change roles, they move, their status in your sales funnel changes. Data changes and you need to keep up with it. Document a process for ongoing maintenance and uniformity.
10. Leverage Data Cleansing Tools
A professional data cleansing tool will help you to accomplish the ongoing upkeep that is required. Otherwise, you’ll have to rely on strenuous manual research and data entry. Regularly using a professional data cleansing tool will help you to analyze problem areas and ensure your data is relevant, up to date, and easily accessible.
MarTech is a Bad Investment Without Good Data Hygiene
The fact is that even the most sophisticated marketing technology platforms are dependent on high-quality data to be effective. Your data will only be high-quality if you implement habits across all marketing operations.
Not sure where you start? Learn more about optimizing all facets of your data orchestration efforts at the upcoming Marketo Top Tips Event. Our experts will expand on data orchestration and answer tough questions on how to keep data clean in today’s complex landscape.