We all know how important it is to get customers to the “Aha moment” quickly and onboarding customers successfully plays a huge role.
But many companies are still glossing over a really important part of onboarding: data.
Product teams are saddled with building out complex CSV importers, while Customer Success teams have to fix customer data in order to make it work within the product.
Flatfile's Data Hooks® are a useful data healing element to re-format, validate and/or correct data automatically during the import process. Translation: a user won't need to manually go in and correct data.
In this article, we describe Data Hooks and the problems this feature addresses.
Depending on your product and your customers, importing data might be a nuisance or even a nightmare. Most software products are completely unusable without customer data.
But importing this data in a timely manner can be a struggle for both the customer and the company.
If you don’t think data onboarding is a problem, think again. Importing CSV or Excel files is no one’s idea of a good time.
In our State of Data Onboarding survey, we discovered that 23 percent of companies reported that it takes weeks or months to import their data and that 96 percent have run into problems when importing data.
For customers, data importing can be time consuming, unintuitive, and confusing. Customers often need to put serious effort into prepping their data before it’s ready to upload. And data importers don’t usually give useful troubleshooting tips when something goes wrong.
Worse still, fixing the data requires a user to leave the application, hunt for the issue in their file, and then return to the platform to re-upload it which is a less than ideal experience.
The majority of companies importing data today are using either an internally-built tool, manual data import processes or a combination of both.
That means that the responsibility of data importing falls on the in-house team. They must build a quality data importer that offers a great experience for users, and they also have to step in with manual assistance when that data importer inevitably fails, or when an individual customer struggles to make good use of it.
Some companies even have full time employees devoted entirely to preparing and onboarding customer data. This manual work isn’t a necessity. It represents a lack of efficient, scalable data onboarding systems.
Data Hooks is a specific feature within Flatfile's data onboarding solution that allows your team to address the data import problems that slow everyone down.
Data Hooks allow for more fringe use cases of data healing and validation using Flatfile Portal. When used properly, they can be used for things like automatically reformatting area codes or country codes, removing special characters, validating emails against external data, and really anything else a user can code up.
At Flatfile, we're continually building more data healing and validation functionality, but Data Hooks cover anything that’s not yet included in our core product.
There are two types of Data Hooks:
Field hooks are for columns - Field hooks run validation on a particular column of data during the matching and importing process.
Record hooks are for rows - Record hooks run validation on each row of data, and can be used for single-field, multi-field, or cross-field validation.
In our Data Hooks documentation, you’ll find a growing library of code snippets you can use to handle a variety of data validation or transformation needs, including:
Reformatting specific value formats - As an example of single-field validation, a CSV file might state “zip” whereas your data schema calls this the “zip code.” The simple Data Hook snippet would allow this to be automatically mapped, and the customer could review and accept the mapping.
Splitting specific value formats - Let’s say a customer has a source file with many full names on it, but your data schema only allows the first name and last name fields. A Data Hook for field splitting ensures that data imported with Flatfile Portal is input not only correctly, but with the minimal amount of involvement from your customer as possible.
Validating data with your server - You wouldn’t want customers uploading duplicate contact records to your CRM for example. You can use a Data Hook to validate data with your server, so that during the import process a callback function denotes which email addresses or phone numbers already exist in the database.
Cross-field validation - Maybe you want to require a column of data only if other data isn’t included. For example, if phone number and mailing address aren’t present, then an email address is required for that row of data to be uploaded.
At Flatfile, we’re building out all of the data validation and healing that we can, as quickly as we can. Data Hooks ensure that you can use Flatfile Portal for rarer use cases that we haven’t fully built out yet, and that it will be easy to do so.
The other good news is that we can see which Data Hooks are being used most frequently so we know what to add to Flatfile Portal next.
But it’s not about us is it? It’s about your customers and your team.
Customers using Flatfile Portal and the Data Hooks snippets you’ve implemented from our library will enjoy a much easier importing flow. Customers won't have to leave your application in order to make the necessary changes to their files that might be required during troubleshooting. That means no context switching. The entire data import process becomes smoother and faster.
Companies using Data Hooks to solve common data importing problems not only save time for their customers, but themselves as well.
Customer success teams can focus less on helping customers import data and more on building relationships to drive real value. Similarly, software engineers won’t get roped into cleaning up a customer’s data file and can instead focus on their current sprint and building out their core product.
Data Hooks allows your team to scalably address data import challenges - instantly increasing efficiency!