3 Common Data Management Challenges Facing DTC Brands (and how to solve them)
We love data. Armed with the right set of CRM data, DTC (direct-to-consumer) brands can enhance their marketing output and create customer engagement. Putting your customers front and centre is the key to any sort of success, and having that data is so important. However, collecting, managing and analysing this data can often be a challenge.
Let’s look at some common data challenges facing DTC brands and how to solve them.
1) Problem: Data Quality is hard to maintain
Current estimates suggest that collectively, businesses juggle 328.77 million terabytes every day. That’s a huge amount of data, and as internet usage grows, this data set will only get bigger. While this might seem like a great opportunity for DTC brands, it is a double-edged sword. Collecting more and more data, and not having the right systems in place to manage it all, can lead to a degradation of your customer data. This is especially true if you use multiple programs to collect and store your customer data.
Solution: Centralise your CRM software.
Choosing a software package that allows you to store all your data in one place is an easy solution to this problem, meaning you can easily manage it yourself, or automate the process.
2) Problem: A lack of training
One of the biggest challenges facing DTC brands when it comes to data management is the lack of training with new software packages. After all, there is no point in using the latest, most powerful software if your team can’t actually engage with it!
Solution: Choose a CRM system that comes with a training module.
Certain CRM platforms have extremely robust training packages, offering your team the chance to take part in virtual training sessions, and even earn official certificates. This will provide them with the right sort of knowledge base to effectively utilise your customer data. Another option is to get in contact with the experts and seek their advice.
3) Problem: Data Migrations are risky and error-prone
As any CRM manager will tell you, data migrations are notoriously prone to error. In fact, it is estimated that 83% of data migration projects either completely fail, or massively exceed both budget and schedule. One of the biggest reasons they fail is that poor data quality slows down the entire migration process, as records are often incompatible with new systems and technologies that have stricter standards for data inputs. Considering that migrations can sometimes involve hundreds of thousands (if not millions) of records, the amount of time and effort required to identify and correct erroneous and unstandardized records is astounding.
Solution: Standardise your data
Keeping a clean, easy-to-navigate database is key when it comes to data migration. By standardising your data, you are making sure that no matter what system you use, it can understand your data set allowing you to focus on your customers. This is also just good practice, ensuring your team can understand and effectively use the data available to them.
