This post is also available in:
Cleaning your customer database consists in checking each data to make sure that the information is still valid, and that it does not exist in duplicate. It is an essential background work to communicate with your customers, to keep them loyal, and potentially to carry out marketing campaigns.
How to do it? Which data to keep? And how to detect erroneous data without spending too much time on it?
Experience gives you the best practices to clean your customer database and keep it up to date easily.
Why clean up your database?
Open the “Contacts” application on your phone and scroll through the list. Do you see duplicates, old contacts that are certainly no longer up to date, others with information that you know is wrong? Now you know what “polluted” data is.
On your phone, it is already not practical, so imagine the same phenomenon on your customer database…
Exchanges with your customers are important: their data is therefore essential.
It is not practical to realize, when sending an email, that the information on your customer file is obsolete. Outdated information wastes your company’s time and money, but it also wastes sales opportunities because of incorrect lead information, undelivered emails and inaccurate forecasts.
A clean contact list shows only one entry per contact and all information is grouped under each entry: name, mailing address, email address, phone numbers, etc., and, of course, everything is up-to-date! No more duplicates or inaccurate information.
What data should you keep?
Are you able to collect and track all the customer information you need? Are there outdated or incomplete data in some of the fields in your kardex? Do you have a lot of duplicate data? Is the information from the various customer contact points all in one place?
Analyzing your database to clean it up can quickly become overwhelming and time consuming.
Make a list of all the data fields you collect.
Review all the data and determine once and for all which data is really useful to you: Identify which data is necessary for operational exchanges with your customers (their consumption habits and preferences can be very useful to improve the customer experience!), transaction management (address, banking data, etc.) and the segmentation of your database (business or leisure stay, couple or family, etc.)
Then determine which ones you are missing.
Throw away the rest!
The different types of data
This is data collected at each stage of the customer journey (purchases, dates, type of product, etc.)
This data measures interactions with your hotel (newsletter subscription, click-through and email opening rates, NPS scoring, etc.)
This is data related to customer profiles, or personas (type of customer, reason for stay, age, nationality, etc.)
This is contact data that provides useful details, both in B2B and B2C. It includes telephone contacts, postal addresses, emails, bank details, call center feedback, satisfaction surveys, etc.
In general, this data comes from direct interactions with the people concerned. It completes the available information and is used to improve your services.
Detecting erroneous data
What is considered bad data, and how to detect it?
What is erroneous data?
Let’s take the example of an important piece of data: the email address.
If the address is incorrectly filled in at check-in, or even not retrieved, it can sometimes present problems of incompatibility between the source of collection and the final database. For example: “Gérard” becomes “GÃ©rard”.
We also talk about obsolete data when people change company, email or phone address, move, etc.
Emails provided by OTAs
There is a case of erroneous data very particular to the hotel industry: the “Alias” emails provided by OTAs like booking.com.
Too many hoteliers are still surprised when they discover the poor quality of their database and the customer data that is actually usable.
More than 90% of your kardexes display an email address. How many of them are OTA emails? How many have a typo? How many are not up to date? How many are duplicates? And the 10% that don’t have contact information, why?
Finding and removing duplicates
Many PMS still generate duplicate kardex for several reasons:
Syntax and spelling, often related to human errors in data entry.
The same customer can give different details from one source to another.
A corporate customer who books a first time with his professional email, and another time with his personal email.
In the case of a group that does brand communication and whose clientele visits several establishments in the hotel portfolio.
Imagine having to sift through your entire database to detect who is who, no you won’t, or at least not on a regular basis.
The main interest of a CRM is to be able to create “matching criteria” in order to centralize all duplicates on a SINGLE view of your customer profiles.
How to keep your customer database clean and up to date?
It is necessary to have a clear policy to identify your customers, to share the information in your database, and then to be able to exploit the data.
This structuring and nomenclature work guarantees the stability of your customer information.
It is useless to have all the possible existing data, if they do not lead to any concrete decision.
It is essential to clearly define your needs in order to determine the list of data that you need to collect and process.
Do this exercise by asking your teams, and you will obtain a complete list of the data necessary for the strategic development of your business.
Once you know what data is important for your development, you need to know whether or not it exists in your operational environment.
If it does not, structure your sources of supply and the tools that work to support this information flow.
Beyond retrieval and storage, you need the ability to process this data quickly and efficiently.
Use a CRM tool to help you transform each piece of data into a reliable, centralized and up-to-date knowledge base, and of course in an automated way.
The “witness” data
This is similar to monitoring a small portion of your database: your best customers. This is called enrichment.
You can check and update your customer data online (LinkedIn or other social networks, public information and directories)
Add to this the history of your customers over the longest possible period (the RGPD allows to store data up to 3 years): number of stays, amount spent, consumption habits, tastes and preferences, services and extras most often booked, frequency of stays, loyalty program, ratings and comments, etc.
A more detailed knowledge of the customers in your CRM database will increase your chances of conversion by conducting personalized and effective marketing campaigns.
Filters and segmentation
Learn how to segment.
Set up advanced levels of personalization to create your profile lists.
Don’t limit yourself to just differentiating your customers between FR and ENG.
Create cross-referencing criteria such as:
Single guests + Single room + BB rate + Check-in Tuesday to Thursday + Check-out Wednesday to Friday + OTA booking channel + Having made at least 2 stays.
In order to detect which customers are corpos, leisure, recurrent, occasional… And what reasons could push them to come back.
Propose them to join your loyalty program through a mailing that specifically addresses this particular segment.
And make sure that these lists are dynamic and updated with each customer’s stay.
Another filter can also be used to maintain this database and to develop customer loyalty: the “2 years already” filter, which detects customers who have not come back and/or have not responded to your offers for 2 years.
You can also create filters in order to detect customers who no longer open your newsletters where they used to read them all recently, in order to prevent the loss of a loyal customer, or simply to check if he has not changed his email address.
These filters allow you to have a quality and long-lasting database.
Backups and updates
Remember that your data will lose quality over time.
In addition to the CRM tools that do most of the work of keeping and updating data, do a cleanup of your database at least once a year.
Remove from your mailing lists all contacts for which you know the data is no longer valid.
Make sure that the people unsubscribed from your newsletters are really unsubscribed (this will prevent you from having a bad image of spammer)
Take out all your profiles with “Alias” emails from OTAs to try to contact them by another means (social networks, sms if no usable email, etc.)
There you go 🙂 Now you have an idea of how to keep your hotel database clean and up to date ! Good luck 👍🏻