Marketing Data Management: Challenges and Best Practices
Having a good understanding of data is key for many areas of business. It’s necessary in order to understand the general dynamics of your business, improve the sales process, and tailor marketing to the specific needs of each type of customer.
When dealing with marketing data, you’re likely to work with multiple data sources, multiple campaigns, and multiple metrics. Setting up a system that can handle that perfectly can be quite a challenge at the start. If you’re having trouble figuring out marketing data management, use this guide as a resource. You’ll learn how marketing data management can positively impact your business and how a data management system can be built.
What is the role of data management in marketing
Data management deals with organizing data in a uniform, easily accessible form. It encompasses gathering data from multiple sources to a single depository, transforming data to fit a single format, and preventing data errors. This allows marketers to understand their efforts more cohesively and personalize marketing offers based on user data.
Take a look at the following example of a data management solution expressed in a dashboard. It helps you analyze the performance of paid ad campaigns from Google Ads, LinkedIn Ads, and Facebook Ads in one place.
Normally, to build a dashboard like this, you’d first need to import data and then transform it, which includes cleaning, matching, and stitching data. Clearly, data management is not an easy thing to do. However, investments in it are worth the cost since you get a powerful and reliable tool for data-driven decision-making.
Marketing, and especially digital marketing, is now heavily reliant on personalization and data analysis. Personalization has become the norm in digital marketing. It is now so common that 66% of users expect companies to understand their needs and may be displeased if they don’t.
Data analysis is rendered completely ineffective without proper data management. You can’t make the right decisions based on corrupted data, stored in multiple disorganized formats, or otherwise hard to analyze.
This makes marketing data management an important first step in the marketing process that makes precise analysis and personalization possible.
Types of marketing data management
There are multiple operations happening in an average digital marketing data management system. Here are the most common ones.
Data integration
As marketing typically involves dozens of data sources, from marketing channels to CRMs, data integration is a key process in the data management cycle. It involves taking data from multiple sources that may have different data types and formats and bringing it together in the data storage facility.
Executing it correctly takes a deep understanding of the data systems of each of the sources used and transforms the data to conform to a uniform standard.
Data refining
Refining data is a process that searches for and eliminates data that is incorrect or corrupted. During data refining, your analytics tools should check for data entry mistakes and other inconsistencies, and catch wrong formatting like mixed-up date formats, duplicate or confusing column names, etc.
This turns raw data into a format that is easy to parse and analyze.
Data enrichment
Datasets are rarely complete, but thanks to having access to multiple sources, there’s a chance there is plenty of duplicate data. While the bulk of it should be cleansed during the refinement process, you can use some duplicate data to enrich your dataset. This means fixing missing data.
This also means adding more columns of data to a dataset, for instance adding sales data to the Facebook ads dataset. The result is a dataset that may provide much more insight into the effectiveness of your marketing campaigns.
Data stitching
Data stitching operates on a similar idea. It’s the process of taking customer data that is present across different datasets and integrating it into a single one. This allows for a deeper understanding of how customers interact with different departments like marketing and sales.
Data mining
Data mining helps businesses make more sense of large volumes of data. This process involves analyzing datasets to find trends and correlations. These are used for further business analysis and can help you arrive at conclusions about your marketing performance that may not be achievable with a simple marketing dashboard.
Benefits of digital marketing data management
Creating a digital marketing data management system is an arduous but important step in the overall marketing process. Here’s what it can do for your business.
Understanding the customer
The most important task that data management pursues in marketing is understanding the customer better. Having the correct data gathered from multiple sources of interaction with the customer like Facebook ads and Mailchimp email campaigns and stored in a uniform format is key to understanding your customers.
It allows your organization to have a single source of truth when it comes to data analysis that serves as a solid foundation for all further data operations.
Personalizing marketing
Personalization is the basis of high-performing marketing. It allows you to create tailored experiences, whether it’s suggesting curated content in the email newsletter or reaching customers with targeted social media ads, which leads to much better engagement rates and conversions.
All of this is impossible without having a stable frame of reference that marketing data management can provide. Inconsistencies in data on customer behavior can lead you to false trends and make marketing personalization ineffective.
Understanding your marketing campaigns
To truly understand how effective your marketing campaigns are and what factors may influence their outcome, you need more than ROI and sales volume. Organizing performance data of your campaigns across multiple channels lets you understand trends and correlations in data that may have eluded you otherwise.
This can lead to a deeper understanding of how campaigns perform and how they differ in terms of results.
Another thing you can expect from marketing data management is a more accurate ROI attribution. Marketing campaigns are often led through multiple channels and it’s not always easy to see which channels contributed to the final conversion. With a data management system combining all sources, you can track touchpoints and understand the customer journey across channels.
Analyzing data for insights
Learning from your marketing campaigns isn’t always intuitive. Sometimes, it’s not clear what exactly made a campaign perform under or overperform. Bringing the data gathered during the campaign into one place, organizing, and analyzing it lets you understand your marketing campaigns better and implement the findings in future ones.
Data security
Data management for effective digital marketing isn’t just about data integration and analysis. It also involves building a secure data storage solution that protects user data. Experiencing a data leak can severely harm business reputation, especially if you store sensitive data like banking information and addresses.
Creating a data management solution that can store all that data in a secure and anonymous way is key to making your customers and your brand safer.
Challenges of data management in marketing
With several marketing channels, dozens of campaigns, and thousands upon thousands of data points in each, making sense of it all can be quite challenging. There are many complications in marketing data management, but most business owners will come across the following three.
Arriving at insights
The biggest challenge in data management in marketing is transforming a huge amount of data into actionable insights that can move the business needles. When you’re just starting to figure out data-based marketing, it can be hard to find the right framework for analysis.
Without knowing what metrics to take a closer look at and where to search for correlations, your data is just a pool of numbers that can’t do anything productive for the business. That’s why your first step after perfecting data management should be experimenting with different approaches to data to form a framework for analysis.
Poor data quality
All data experts have to deal with data quality issues. Since marketing in most companies often produces a lot of data, some of it is bound to be corrupted or incomplete. Values may be stored in different formats across channels which leads to confusion. Names of data ranges may have different names and not synchronize as a result. Other values can be simply missing.
When data quality is lacking, making sense of data becomes progressively harder, and can lead to misinformed decisions.
Proper data integration
Marketing departments in large SaaS companies may have dozens of apps in active use, and 60% of companies use more than four marketing channels. This creates dozens of sources of data that all have to be brought together to form a cohesive opinion about your marketing operations.
Integrating all that data from multiple sources and unifying the formats is a major challenge.
How to efficiently cope with marketing data management challenges
Creating a solution for data management in digital marketing from scratch is pretty hard. If your organization has only been storing data and running a very basic set of reports on it, you’re going to have to learn quite a lot. This can take your team’s time away from business operations.
Coupler.io offers a data automation and analytics platform that you can integrate into your marketing data management activities. In terms of data automation or integration, e.g., for reporting, you can use the Coupler.io ETL tool. It allows you to gather and combine data from different sources used by marketers, such as Google Analytics, Facebook Ads, Mailchimp, etc.
In terms of data management in marketing, you can opt for the marketing data management consulting service. Our expert team can help you with finding the right approach to your marketing data management, analytics, and visualization. This allows you to stay focused on making decisions based on correct data and executing them. Here is an example of a Performance Ads dashboard made by Coupler.io.
Coupler.io data team has the knowledge and tools necessary to understand your business needs and build a data management solution that can be scaled easily. This includes integrating all your data sources into a single storage solution and creating custom dashboards to track the effectiveness of your campaigns.
5 marketing data management tips
Whether you’re doing marketing data management yourself or hiring an agency, it’s important to know the best practices. Here are five tips that will create a solid basis for your data management system.
Create a data architecture first
Before you can accurately analyze data and turn it into insightful information, you need to set up the data architecture. Doing this first gives you a solid frame of reference when it comes to further analysis and ensures data is correct. You can do this in six steps:
- Define data sources
- Check how compatible data is between them
- Define a single format for data that may come in a multitude of formats
- Find a reliable marketing data warehouse
- Find an integration solution of data sources in the warehouse
- Test for inconsistencies and errors
Unify the data
One of the most important steps in data preparation is putting it in a single format. For instance, the customer age group can be presented as 25-35 in one tool and “middle-aged” in the other. This creates an inconsistency in your database and prevents accurate analysis.
Find inconsistencies like these, settle on a single format, and transform the data into that format when importing it into your database.
Maintain data quality
Incorrect data leads to incorrect decisions. Ensuring the quality of your data is paramount to the accuracy of the analysis. The first thing you have to implement is to set a high standard for the quality of data entry.
If your marketing department works with manually entered data, you need to create a data quality checklist to ensure there are little to no human errors. Other common problems with data can be eliminated by searching for duplicates and removing them, updating data, and cleansing data from errors such as typos or wrongly placed decimal points.
Ongoing analysis
The most important thing in data management is not treating it as a one-off thing. If you want to significantly increase key business metrics, it’s enough to run a couple of reports on your data. This would let you find something to improve your business, but you can’t call it a day.
Data analysis needs to constantly be a part of your schedule to make a long-term difference. The problem is, not all organizations have the resources to do all data-related tasks on top of the regular business operations.
Even the most experienced data scientists and advanced analytics staff spend the majority of their time prepping data, rather than conducting analysis. Outsourcing tedious tasks like data quality assurance and building the necessary architecture frees up your teams’ time to analyze data in more detail.
Data regulation compliance
Marketing data has plenty of sensitive elements, and many countries are now protecting web users legally. Check out the GDPR compliance checklist to bring your data management system up to the EU standards if you want to work in an EU country.
Only three states in the US currently have comprehensive data privacy legislation, California, Virginia, and Colorado. If you’re operating in those states, check the relevant legislation to see how you have to comply.
Most likely, you will have to implement the following steps:
- Create a data safety infrastructure within the company
- Anonymize user data
- Create company-wide data safety policy and train employees
- Let users access the information you have on them
- Delete that information upon request.
Marketing data management solutions
A data management system is comprised of multiple components. Here are some of the tools you’re going to be bringing together.
CRMs
Customer relationship management systems like HubSpot hold a wealth of data that facilitates marketing personalization. Sales data can say a lot about customer preferences. This can be used to craft more compelling email marketing campaigns targeted at warm leads as well as be used in other forms of marketing.
Most businesses would use a single CRM, so there’s no need to integrate data from multiple CRMs. The main challenge here is to use CRM data together with other data sources to understand your clients better.
Marketing automation systems
Marketing teams use marketing management and automation systems to control marketing channels easily. These tools let you schedule marketing activities like creating social media posts or automate tasks like sending email sequences. They also record data on all marketing activities.
An average company may be using MailChimp for email marketing, Buffer for social media marketing, Google Ads for PPC advertising, and a unified communication solution for SMS marketing or calling. The more channels you’re working with, the more tools you have in your arsenal.
Each one is a source of data that needs to be integrated with the others in one place for further analysis.
Data storage facilities
In terms of data management in digital marketing, a data warehouse is one of the most important elements. It allows for storing huge amounts of data in a format that’s easily accessible by business analytics tools.
Finding a reliable architecture for the data warehouse ensures all your analytical activities run smoothly. A straightforward choice of an easily scalable data warehouse that won’t take too many resources from the start is either MS Azure or BigQuery.
Analytics tools
Apart from data sources and a data storage facility, a data management system needs an analytics solution. The easiest way to analyze and visualize data is to opt for MS Excel or Google Sheets. These tools are great for working with imported data, however, can’t be effectively used to run marketing data analytics in real time.
There are plenty of specialized marketing analytics tools that are capable of doing that. Most specialize in one of five areas of marketing: website visitor actions, SEO, email marketing, social media, and lead attribution.
Marketing analytics tools track important user events like open rates in email marketing campaigns or purchase data. Hundreds of these events are later transformed into meaningful business statistics like cost per lead or return on investment.
Why you should invest in data management in digital marketing
Data management in digital marketing is not as straightforward as A/B testing Facebook ads or doing a content audit on the website blog. It involves a substantial upfront investment and can take away from your team’s resources, potentially requiring new hires.
The results of implementing data management in your company pay for themselves — it allows you to understand marketing much better, create more involved campaigns, personalize your offerings, and more.
If you don’t want to spend time figuring out the details yourself, schedule an exploratory call with Coupler.io’s data management team. We can take on all the hard work, freeing your time to do the only thing that truly matters — making business decisions based on correct information.
