Dirty data is simply an indirect way of describing data that's inaccurate or incomplete in some way. Since data is nothing more than the facts, if hoteliers are not receiving accurate information, their data is misleading them, or termed “dirty.”
Dirty data can include inaccuracies in reservations data such as how many rooms are on the books, competitor pricing data or website data, including regrets and denials.
This blog is adapted from our whitepaper Strength in Numbers: Unlocking Data for Actionable Insights. Download your free copy today.
There are many ways in which your data can become dirty, including:
- Technological faults
- Human error
Sometimes there are bugs in technology that translates the transactional database into a report, for example. Other times human error occurs or a human process is broken. For instance, hotels often have the same customers reflected multiple times in their database. In addition, old or outdated data can mislead hoteliers.
In the case of dirty data, hoteliers must figure out how to make sure that their data is showing an accurate reflection of reality or they’re often forced to make assumptions on how bad data might be influencing the facts. Multiple levels of assumptions almost guarantee inaccurate analysis.
The challenge for hotel revenue leaders is to be almost maniacal about ensuring the data they’re relying upon is accurate. Only with trusted, accurate data do hoteliers have the foundation and confidence to drive new marketing and pricing strategies.