Marketing functions can experience a variety of pain points in their management of data. Understanding these challenges and arriving at effective solutions can offer many benefits.
Big data is constantly growing, and for marketers, problems are only increasing. New leads enter the marketplace every single day. Data management for marketing can be a complex endeavor. Data siloing in the modern age results in efficiency challenges and can be costly to an organization.
Marketers seem to have many issues with data management. High-quality data is crucial – but are marketers throwing money at a problem without analysis? Statistics show that at least 63% of marketers in 2020 have put more money into being data-driven.
That is good – but unless that money is spent actively targeting pain points, it travels nowhere. Consider some of the more prominent data management challenges marketers face and where solutions may lie.
Resources are Running Dry
A critical problem, according to Gartner, is that many marketing firms aren’t able to pull data into a reasonable shape. Gartner’s analysis shows that data scientists in marketing firms may work to build leads instead of arranging data for effective decisions.
Data preparation is vital for all lead building. However, unless that data is effectively organized, it will continue to cause strain for years to come. Quality data capture is crucial. However, if that data is left to rot, lead generation will have been pointless.
For example, marketers may find that they are unable to connect effectively with leads long-term. The sheer power of personalization in modern marketing is still growing.
Therefore, marketers may benefit from a single point of contact for all data. A platform, for example, that may offer real-time statistics and insights midway through the sales funnel could help data scientists spread their focus a little wider and have a larger effect on the organization’s capabilities.
Marketing Teams May Not Know How to ‘Use’ Big Data
Ensuring that lead data is even usable in the first place is likely to be challenging. Marketing staff with a rudimentary knowledge of data organization may struggle to analyze complex numbers. This isn’t a condescending statement – it is crucial for marketers to partner with IT specialists who understand data and data management and who can help marketers to expand their knowledge and skills.
However, that may not be the only potential solution. Building relationships among marketers, data scientists, and IT specialists are crucial long-term efforts. However, a more efficient way to make the most of data long-term is to use appropriate systems.
If data is dirty or inaccurate in the first place, it is still going to pose a significant challenge for IT experts. That’s why ensuring accurate data capture from the beginning is so beneficial long term. A streamlined, singular platform for data cleaning and collation can only help marketing experts.
Growing Too Much
It is easy to assume that becoming data-driven revolves around taking on more data. Naturally, if this additional data goes straight into lakes and silos, such moves will be pointless.
More data does not always denote greater insight. Many marketing firms are happy to cast money on data issues without understanding the challenges to using data effectively. However, the solutions to data pain points rely on smarter use of funds, not necessarily bigger investments.
Data precision is more important than sheer volume. Various analyses show that accruing or piling up data isn’t healthy. Yes – big data will never stop growing. However, unless data is managed efficiently, it always runs the risk of becoming irrelevant.
Marketing firms, by their very nature, will consume incredible amounts of data per year. Lead generation is data consumption by design. However, marketing experts may be chasing the wrong solution by increasing their data purely to improve data analytics.
The answer lies in rethinking data that you already have available. A more effective way to deploy data scientists within marketing may be to break down existing silos.
Failure to Understand Data Management for Marketing
As discussed, marketers may not necessarily know how to handle data at the outset. Understanding how to manage data correctly often comes with practice. For example, moving to a unified platform or engine could help data consumers to see the bigger picture.
Therefore, a big problem for marketing experts is that they may not know what clean data looks like. Dirty data has issues such as duplication, outdated records, and generally inaccurate information – result of the lack of attention to characteristics of data quality. Unless marketers dive into data lakes to analyze this content, they may not realize there is a problem. They may decide it is simpler to handle the data at face value.
Bad or dirty data costs the US $3 trillion per year. This is money that is easy to find once again through clearer, smarter data management. Dirty marketing data leads to missed connections, inappropriate advertising, and sheer wasted opportunities.
It is all the more reason why marketers need access to data unification platforms that teach and collate. A user-friendly data cleaning system can help marketers understand the critical drivers for dirty data. Otherwise, understanding marketing data quality will only become more of a challenge.
Ultimately, while the best tools can help clean and reorganize data, data management education is just as important.
What can be done?
Marketing data is some of the most complex on the planet. Moreover, it is constantly growing. Leads will never stop generating for as long as the population expands. There will always be new people and new companies who can receive advertisements and connections.
Mastering data management can help a marketing firm get a tighter grip on its data silos. By working to pull and collate data from disparate lakes and sources, effective data management will help break down piles of dirty data and give users access to transparent, manageable data strategies that can simplify processing and decisions.
Conclusion
Data management for marketing will continue to become more complex each year and each business cycle. Marketing functions that are swimming in impenetrable information should look for help, and act on good advice on how to improve the current state.
