Data migration on a CRM Project is a much much bigger workstream than anyone thinks.
Corrupt, inaccurate, inconsistent, irrelevant or incomplete data renders your system useless, no matter how much you spend on adding bells and whistles.
You really don’t want to bring over poor quality data into your new CRM, so you’ll want to clean it up, de-dupe the data, and perhaps enrich it with more information.
This task can take a long time; much longer than you expect.
Plan, schedule, budget and resource this task.
There are a few ways to do it (not exhaustive):
1. Assemble a team and schedule some time weekly to clean your data at source, perhaps every Friday morning for 3 hours.
2. Hire some temps and blitz this task in a few months.
3. Outsource this to an external team to do it.
4. Outsource this to an external AI machine to clean/dedupe the data automatically
Best option is (1), because only your team can understand the context and nuances of the data, and make the correct choice as to what to do about it.
You lose more of that, the further you go down the list.
And in fact, for (4) to be useful, you would have to spend a lot of time to help put together the rules and logic that drives the data cleansing process.
In my experience, clients have frequently underestimated this task, and end up migrating bad data into the new system, and never get around to really finishing the task.
If you want the maximise the value from your new CRM system, you need to spend the time to do this properly,
Good data is like oil, a bit messy in its raw form, but with the righ tools and process to extract and clean it, it can be turned into immense commercial value. Give me the mo-ney 🤑
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