But you have to trust either way
Most of our experiences using Geomarketing solutions end up requiring a position of trust.
After all, there's no way to fully validate what's happening behind the screens: whether the databases are consistent, intact, or even if the privacy promises of your analysis are actually being fulfilled.
If you use geolocation platforms, it is likely that you are delivering valuable information in exchange for a service, under the promise that all this data is protected, encrypted, free from manipulation and misuse.
However, how can you be sure that the supplier is actually fulfilling what they promise?
- Code and data are black boxes, you don't have access to what's going on behind the scenes.
- Manual verification is not feasible, databases have billions of information cells.
- It's impossible to know if each data collection or projection point is error-free.
Most vendors are honest, but there are situations where companies can fail without even knowing it, applying rules that distort data or using models they don't fully understand.
Mistaken business decisions are the worst consequence. If you act based on misrepresented data, intentionally or unintentionally, your strategies and investments can fail disastrously.
The importance of “trust” in data
Many talk about software security; but in the end, most of the negative consequences fall on The data.
Virtually all digital operations require some level of faith in the good faith of a third party: from the hardware manufacturer to software developers and data providers.
The objective is not to become paranoid, but to adopt measures that minimize blind trust:
- Perform tests and validations on your own
- Choose suppliers that are recognized and have a history of good reputation.
- Follow the community, see if there are frequent discussions about security or if there are reports of malpractices in the company's history.
The final message
Even with sophisticated tools, there is still no solution that eliminates the need for trust in the software and data vendor.
The best you can do is to make that trust more evidence-based, less absolute, and subject to verification.
At the end of the day, to trust or not to trust is a matter of balancing benefits, risks, and guarantees.
If someone says they have “a miracle solution” that requires any validation, be suspicious.