If your company has made upgrades to your marketing process, but the number of leads is lower than ever and sales is complaining about the quality, don’t panic. There is a simple yet often overlooked explanation: data migration. However, if done poorly, orchestrated data migration can have a detrimental impact on your business. Consider using an app like Tableau ServiceNow for easy data export.
According to the 2019 State of the Cloud Report from Flexera, companies plan to spend 24 percent more on public cloud in 2019 in comparison to last year. The extra spend results in 24 percent more data migration because data has to get to the cloud somehow. Additionally, enterprises spend even higher, with 38 percent exceeding $2.4 million per year and half (50 percent) above $1.2 million per year. When data migration is executed poorly or fails completely, the money spent on migration is lost. And that’s not the only fiscal impact of a data migration gone wrong.
Simple missteps when moving data from one system to another can have a negative ripple effect throughout your marketing process and carry over into sales, potentially sinking your sales and marketing efforts for months depending on the severity of the failed data migration.
I’ve been involved in hundreds of data migrations, both for internal marketing data and overseeing MountainTop Data’s client data migrations. We’ve had to pick up the pieces of a client’s data after they went through a poorly conceived data migration and saw small oversights wreak havoc on our own marketing campaigns. Today, it is estimated that 87 percent of online marketers use email as it is still considered the number one source for online sales and is used more than any other form of lead generation. Hence why it is paramount that data migrations need to run smoothly and efficiently before it stalls marketing efforts.
Therefore, accurate company and contact data is critical, and a company’s internal information on clients and prospects are frequently overlooked when making hardware and software upgrades. Assuming new systems will properly identify, process, and accept your data is a big mistake. Every situation varies and close attention should be paid to all data fields.
Data migration typically includes three steps: extract, transform, and load. Before extracting from your current system, create a backup. Without a backup, all data could be lost if something does go wrong.
Extract
Some systems have integrations that allow you to define data paths and migrate directly from one database to another. A common step is to export your data from your current system into an excel spreadsheet or another common database file. The structure of related fields in your current database may require you export several data tables, so be sure to export all fields including unique identifier keys (contact ID, company ID, etc.), so records can be easily tracked.
Transform
This is the most important step in a data migration because you must look at each data column. Check that all data has exported properly and inspect the data formatting for each. Specifically, ensure that all records and fields from your original migration are included as file handling special characters are different from your initial database.
It would also be wise to proceed with caution as some file types will see a prompt to separate the data into multiple fields, causing a data offset issue. Thus, check each field to assure it’s not formatted in a way that has caused data loss. This can be as simple as losing the 0 from the front of zip codes to an error identifying the data causing a null value. Lastly, check that fields with a lot of text haven’t been truncated by a restriction on the number of characters allowed for that field in the formatting.
Load
Once your file is clean, you’re ready to import the data into your new system. Depending on the data structure in your new system you may need to separate your file into several imports. Before you import, reformat fields in your file to match specific format requirements for the new data location. You would have learned these on your test run.
In addition, you need to spot check your new data set to see if there were issues you missed and let anyone you will be working with to raise the alarm if any data abnormalities are noticed. Finally, keep a copy of the original data set for at least a couple months. This will allow you to revert to the original and redo the migration if necessary.
The key consideration of migrating data into the cloud is a simple one: data is only useful if it is accurate. Data improperly migrated into the cloud and into a new CRM could render your sales team’s accounts missing information — or missing altogether. The purpose is to oversee a smooth migration, encouraging account managers to incorporate a CRM and utilize the technology to achieve lofty sales goals.
