What Does it Mean to Have Clean Data?
Data is a popular topic in the vacation rental space today. As technology continues to advance, it relies more and more on data to provide the cutting-edge experiences that property managers expect. For a service like a PMS system to function as intended, it must house what we call “clean data”. That means the data is accurate and duplicate-free. It should also be as comprehensive as possible.
For example, importing reservations into your new software is moot if there are no rates, cleaning fees, or guest contact details. To have clean data you must first determine if there are any errors in the data and understand how they can be corrected. It’s important to cleanse your data to ensure your systems are working to their full potential and error-free. You can also capitalize on your high-quality data to book repeat guests. Sophisticated software programs like CiiRUS make this easy!
Advantages of Having Clean Data:
- Clean data eliminates major errors and discrepancies from manual handling and puts relevant data into one system. Many property managers without an all-in-one PMS store data in multiple systems, often with overlapping, conflicting results. Unifying guest records, reservations, cleans, owner accounting and the rest of the operation in one system will lead to cleaner data integrity.
- The productivity of employees will increase. Clean data frees your staff from the possibility of errors and discrepancies since a unified system allows them to do their jobs from one platform. When staff is multi-tasking across platforms, there is a wide margin for error, which can be eliminated through cleaning.
- The result of clean data trickles down to guests. A unified system (one data set) leads to smoother processes and more accuracy, which leads to happier staff, which leads to a better service ethic, which leads to happy guests with problem-free stays. How many times has a cleaner or maintenance vendor shown up to an occupied home due to poor data-keeping?
- An all-in-one platform can leverage data from across your organization to boost success in other departments. For example, keeping reservation data in the same system you use for marketing allows you to target repeat guests with unique promotions that pertain to their last stay, preferred traveling season, and more. Targeting guests with data that applies to their unique circumstances will increase your chances of securing their repeat business directly.
Steps to Clean D
- Start by looking at the systems you have and asking questions. Are you experiencing fragmented data? Are you using multiple overlapping platforms? Can they be unified? Are they compatible? If not, seek out an all-in-one PMS like CiiRUS to unify those disparate tools into one clean platform.
- Remove unwanted duplicate values and irrelevant
data fromyour operation. Do you have multiple records of the same guest from separate reservations? Using a CRM or an all-in-one PMS will help you de-duplicate theserecords; you can succinctly track and book repeat guests. Are you connectedto the same channel by more than one means? You may be connectingvia a channel manager but also maintaining a second account via iCal. Unify these with one API feed to your software and eliminate double bookings.
- Simply proofread. Fixing structural errors that
may haveoccurred from manual handling of data can make a substantial differencein all areas, especially in bookkeeping. Such structural errors liketypos, inconsistent capitalization, and mis-categorizationmay seem trivial, but over the years can add up to massive discrepancies that are harmfulto your business.
- Having a grasp on missing data and understanding how
to handlethem sufficiently is key. For example, if property data is missing, what effects will this have on your success? The Property Assistant in CiiRUS shows you a visual representation of your home’s data completion in aneasy-to-read graphical format. Each of the required data points to successfullyadvertise each home is shown with a status, adding up to an overallpercentage of data completion. Quickly root out areas with missing dataand correct them on the spot without any guesswork.