No one likes clutter.
Whether it’s in your office, your house, your email inbox, or in your CRM, clutter can happen quickly - and it can make you feel unorganized, unproductive and out of balance.
This is especially true when it comes to your CRM database. However, a messy database doesn’t just make your data feel cluttered - it can also have a tangible negative impact on your business’ effectiveness and your bottom line.
An unorganized CRM can:
- Keep you from properly tracking your customer interactions
- Make you waste valuable employee time sifting through inaccurate or duplicate customer contact information
- Increase your risk of alienating or failing to contact an important lead
Here, we break down the different types of cluttered “bad data” that you should look out for in your CRM and discuss how to avoid these common mistakes.
Where Does Bad Data Come From?
Companies constantly receive valuable data - including customer contact information, advertising data, sales information and customer support data - from various third party sources. If this data is organized and accurate, it can give you a well-rounded understanding of your customers and their interactions with your business. This allows you to build your business plan around your customers’ needs and follow up with the leads that are most likely to be converted into sales.
However, this data can very easily become unorganized and cluttered. Most often, this happens because your data isn’t standardized, meaning that it isn’t all being inputted in the same format. When this happens, you get problematic “bad data” including:
One common type of bad data that sits in your database is duplicate data. This can happen for a variety of reasons. For example, you might have a lead sign up for your service multiple times with their emails or street addresses - and your CRM has separate records for each one. The possibilities are as endless as the extent of human error.
On a small scale, this problem is manageable and relatively easy - albeit time-consuming - to fix. In the big picture, though, it could have serious implications. Every duplicate record that you have to deal with in your database increases the amount of time required to sift through data and fix it, thereby reducing your internal bandwidth and your ability to follow up on leads.
If you want to avoid this, you have to address your duplication problem at the source. This means going through your entire database, discovering where the duplicate records are coming from, and standardizing their format. To further simplify the process, you can even create a drop-down menu that limits data entry options, therefore ensuring that your data never becomes incorrectly inputted again.
Another common form of bad data is incomplete information. This also happens all the time. Say you meet a lead at an event - they seem really interested in your company, but they’re in a hurry so they fill out your form with their email address, phone number, and company name, but forget to put down their name.
Again, if this were a one-time incident, it would be fairly easy to research the missing information and fill in the blank. However, on a larger scale, it can become a much more time-consuming and difficult problem to overcome.
This too could have some very negative business implications. Without complete information, any automated marketing tools that you have, such as sending more personalized emails to your contacts or separating contacts by lifecycle stage, are going to have trouble performing their functions. As a result, you may not be able to contact or separate your leads correctly - if at all - which means you’ll likely miss out on an opportunity to convert them into an opportunity.
In addition, incomplete information could keep you from understanding large-scale insights like which markets to focus on, what leads are most likely to convert into opportunities, and what companies you should pursue. With these kinds of problems, you risk alienating and losing potentially profitable leads.
It’s simple: the older your data is, the more likely it is to be inaccurate and, for all intensive purposes, useless. This is especially true of your CRM data. If your data is no longer valid - say a customer support specialist forgets to update a customer’s information or a customer changes their phone number and doesn’t tell you - then you won’t be able to follow up with that contact or accurately analyze the information at hand.
Here’s a common use case: your CRM shows that you have 10,000 leads in the Boston region, but, in reality, 1,000 of those leads have moved to new cities. If you don’t have this new information, you are likely going to draw incorrect conclusions about the health of your business in that region and make bad judgment calls about how you should proceed with your marketing ventures. For example, if you think that they all live in the same neighborhood, you may put up traditional ads in that part of town or set up Facebook Ads for their time zone.
These mistakes can be costly, and such inaccuracies can make the value of your data plummet.
When to Get Help
If your house is especially messy, you might call in some reinforcements and hire someone to help you tackle the problem. In certain cases, the same strategy should be used for the bad data in your CRM.
So what kind of help can you get?
An effective solution is a data integration service like Xplenty. In general, these services will help you quickly and accurately organize your data in one centralized location.
As a data delivery company, Xplenty works by facilitating your data movement so that you can streamline your data and maintain a clean, organized database. With over 100 integrations, Xplenty allows you to quickly and efficiently connect all of your relevant sources without using your company’s internal resources or having to write in the code. In addition, you can choose exactly what you want from each source, when you want it integrated and how you want it delivered.This freedom and precision means that all of your data will be properly connected, synced and up-to-date and all times, avoiding all of the the “bad data” problems above.
When your data is clean and organized in this way, you’re better able to run analytics and get a clear sense of exactly how well your business efforts are working - which means that you never have to worry about how much money you are losing to a messy database again.
If you can handle all of these tasks independently, great! If not, we can help! Schedule a call with one of our experts today for more information.