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How to Clean the HubSpot Database for Higher ROI

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How to Clean the HubSpot Database for Higher ROI

Inbound marketing involves a great capture of data from our followers and potential customers that occurs especially in the conversion phase, a stage in which a large part of the records are obtained by requesting user data, so that they can access to a content offering.list_altIndex of contents
Why clean a database? Some wrong data that you can find in yours
How does data inconsistency affect us and what are the benefits of solving it?How to clean your database in 5 steps
How to clean the database out on a technical level?
After this, in addition, in the qualification that is carried out in marketing automation through lead nurturing and lead scoring , data processing is also essential:A record with basic data can be completed by progressive profiling with intelligent form systems.
The information we have from a contact should be used to personalize the content of the web, your browsing experience and the communications we make with this contact. This is achieved thanks to the what is united kingdom phone number of lead nurturing.
We also use contact information to assign you a score that lets us know how interesting you are on a business level. We achieve this by implementing lead scoring in our database.
For these reasons, having a good quality of data in our database is very important externally (in communications and interactions with the records) but also internally, to correctly segment and classify the database .It is also necessary to take into account that the databases are shared with the different teams that make up a company, such as the marketing, sales and customer service team, so having a consistent data set will allow to increase the effectiveness of the company and facilitate the alignment of the different departments that compose it. Remember it!

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Also, when there are high levels of erroneous data, it is necessary to clean the database to avoid business problems. Through the use of specific tools and strategic techniques, it will be possible to solve the problems caused by inconsistent data.Why clean a database? Some wrong data that you can find in yours
There are different types of errors in databases that can affect the proper functioning and credibility of a company. We explain some of them based on Betting Email List examples:Example 1: Imagine that you receive an email that greets you “Hello, Marta” instead of “Hello, Marta”The user who receives this presentation in his email may think that he is dealing with an unprofessional company, and makes it very clear that behind the email there is a robot and that it is automated.Although this is evident in many cases, it continues to impoverish the user experience and damage our conversion rates and our reputation.Example (simulated) of name in badly capitalized email:clean database miscapitalized nameAnother case could be that I received an email that contains the text “… I will explain to you how we can help Inbound cycle SL …” instead of “… I will explain to you how we can help Inboundcycle …”. You could also come to think that it is an email made with little care and extracting our contact information from unverified sites or with low quality data.Example 2: Imagine that you are a B2B company and you are in the registration phase, so you need to know the job title of your contacts to decide if they are qualified or not.If you ask this information with an open field, some possible options to refer to the same concept could be:COO
Chief Operations Officer
Director of operations
Etc.
This fact makes the segmentation and analysis of the database difficult, causing errors and duplications, as you can see in the following image:clean database inconsistency job titlesImage Source: Hubspot BlogHow does data inconsistency affect us and what are the benefits of solving it?
Poor data quality means big costs for companies. Specifically, according to a Harvard Business Review study, it cost $ 3.1 trillion in 2016. Yes, this is $ 3,100,000,000,000, to give you an idea. That is not little, right?The main reason is that it generates inefficiency and requires an investment of time and resources to correct it.

Why can data inconsistency happen?
The user fills in a form on our website carelessly or with errors.
People on the sales team add contacts to the database or CRM based on the best information they can find.
The marketing department adds data for each contact with the progressive creation of profiles.
It is common for sales to make various connections with contacts, and, therefore, to update the profile of these contacts as they learn more about them during phone calls.
These data inconsistency issues affect many departments, especially if they are integrated. It is one of the main problems of department alignment: things that affect one of them also affect the rest.You can see it represented in the following image:database cleanup Hidden data factory
Adaptation and translation of the HubSpot Blog schemaIn the event that the marketing and sales departments are perfectly aligned, it is very important to have this data consistency:If the sales team does prospecting, to identify and attract new customers and registrations, it is essential that all data is entered into the database following the same format and with the same rules.If, on the contrary, each commercial records the information with different criteria (for example, Mexico City, Mexico DF, Federal District …), it will be impossible to correctly segment and make communications directed only to the people of this city.On the other hand, it could happen that users enter wrong data, with spelling mistakes, with different formats … in the forms. If they are not reviewed and validated by the marketing department, business processes can be hampered and inefficiencies added. And we don’t want that, right?Quiz HubSpot – barIf there is no system created in the marketing department for the creation of forms or there is no data validation in them, in most cases these inconsistencies can appear in the database.Some common examples you might come across are …Word capitalization problems : for example, someone writing “maria perez” instead of “María Pérez”.Problems with the format of phone numbers , postal addresses or dates: 97 845 95 54 or 978459554 or +34978459554, for example.
People who register multiple times with different emails.
Different ways of entering the same information : this can also happen from the marketing data collection forms, such as the example of Mexico City that I explained to you previously.
One case in which this problem is magnified is in data imports into a CRM. This can be due to different causes:

Capture of records using external tools.
Records that come from events or fairs (offline capture).
Manual introduction due to commercial or social selling actions.
Incoming calls from people actively contacting the company.
Database purchases.
In these imports it is very difficult to control the quality of the data from each of the sources, and fixing it manually is a very inefficient task. I assure!

In a study in which we participate in collaboration with Insycle and Databox, it is shown that there are many reasons to import data into a CRM, such as the existence of other systems, records that come from events and offline sources, etc.

cleanup database reasons uploading contacts

Image Source: Insycle.com

To solve it, we have different tools that can help us to do it automatically and much faster . And while it is impossible to have 100% consistent data, we can take steps to maximize its quality.

Here are some benefits of doing so:

You get a better user experience.
It reveals more efficiency in business processes.
Ensures better ROI by being able to segment marketing campaigns more effectively.
How to clean your database in 5 steps
If in our CRM or contact database we have problems and inconsistencies like the ones we have just seen, taking measures will help us to have greater control over the data and get much more out of it . It is worth the effort!

These are the steps we should follow to solve it:

Step 1. Format phones, capitalize names and format postal addresses and emails
The fact that a person enters their data incorrectly is probably the inconsistency that we will find most frequently, although it does not mean that it is a bad record.

Nor do we have to limit the introduction of data in the forms because it would lower the conversion. It is best to perform a database cleanup and normalize the error later.

Inconsistencies to solve:

Capitalize first and last name.
Format phone numbers. We have to consider it especially if we are going to use the phone number to make calls automatically from the CRM. In this case we have to adapt the format to which the calling tool is going to use.
Postal addresses and postal codes: they must always be in the same format.
Format of email addresses: although it may seem incredible, sometimes there are users who do not enter their emails with the usual format “[email protected]”. We can find it with the format “nombre-at-dominio.com”. If it is not resolved properly, it is very possible that a large part of our emails will bounce and this will affect our reputation.
Take a look at the example when doing it with Insycle:

clean database format data
Image Source: Hubspot Blog

Step 2. Remove unwanted spaces and characters
In this case we refer to the situation that occurs on some occasions, when some people press the space bar involuntarily, so blank spaces are introduced in the fields that can alter the formats. It may also be that someone enters two spaces instead of one between two words.

As for unwanted characters, they appear sometimes, as some systems cannot reproduce certain characters: Ã, ¢, â, ê.

Step 3. Consolidate and normalize to improve filtration.
To carry out this motion for a resolution, we go back to the example we have seen above about jobs. Sometimes, a person can write their position in the company in different ways (for example, CMO or chief marketing officer …) or there may be different nomenclatures that refer to the same functions (for example, chief marketing officer or marketing director ).

Another field in which duplications are incurred is in the business sector. For example, different ways of indicating something similar would be the retail or retail sector.

This problem can be solved by identifying all the possible values ​​that we have in the database and unifying them . To prevent this situation, it is also a good solution to ask what type of fields it refers to, by using drop-down lists with closed answers.

Step 4. Eliminate low-value contacts and redundant data.
Although they are not errors or inconsistencies, it can help us to have a more refined database. With low value contacts it does not mean that they are of no use, simply that they are not the ones that the sales team is going to prioritize.

For example, we can also delete email addresses that have bounced, people who have unsubscribed from communications, free emails if we are a B2B company, etc.

Step 5. Remove duplicates.
It usually happens in the case of imports, where several contacts are created that refer to the same person.

This situation is very inefficient at a commercial level, since we may be updating the two contacts separately and when we realize this it is necessary to unify it, being able to find duplicate information.

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How to clean the database out on a technical level?
Surely you wonder how you should clean the database to execute the previous steps in your business. Is that so?

Well, one way to do it, especially in the case of imports, is to have a professional specialized in the use of Excel who is in charge of separating fields that are together (name and surname, for example), eliminating duplicates, etc.

In addition to the human factor, there are tools that allow you to do all these functions quite automatically and very easy to use.

An example tool of this type of tool to clean the database is Insycle . Here are four things about her!

It is one of the tools that HubSpot recommends to carry out these functions, since it has a direct integration for cleaning the database.

Insycle can work in the case where it is needed …

Spot data cleansing
Periodic cleaning
Continuous cleaning
It allows to make cleaner imports and to validate the contacts to avoid duplicates, and to have a better filtering and manipulation of data, which will help us to have a much cleaner and more efficient database.

Day-to-day marketing and sales actions involve entering a lot of data, and if we are not aware of it, it may be done incorrectly, thus generating inconsistencies in our database. Does it sound familiar to you?

These inconsistencies make us work inefficiently, worsen the user experience, and also lower the performance of our marketing campaigns.

In the case of imports, in addition, the problem multiplies, so it is essential to regularly analyze our database and take certain measures to improve the quality of the data.

As you have seen, tools like Insycle can help us make this process much easier. So I ask you: have you carried out any data cleansing recently? How did you solve it? I await your impressions in the comments section!

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