Here's a shocking statistic:
Poor quality data reportedly costs businesses $9.7 million per year 😱
What's worse, the nature of the problem means that you probably don't even know if it's affecting you.
Getting the Right Data
Data is a huge part of what makes modern marketing and selling techniques possible, and that's why we all keep contact data records.
However, not just any contact data will do.
You need quality data if you're going to make a positive impact on your business, and that's where contact data quality management comes in.
This term refers to the process of monitoring and controlling the quality of your contact data - data that is:
Mistakes are a given when dealing with any kind of written information. Things can always get mixed up, and now that we type everything out instead of writing it by hand, typos are a common occurrence.
Either of these issues can seriously complicate any potential use of the data: how are you supposed to get an email out to someone whose email address you only have a misspelled version of, or perform proper analytics with two profiles that have had half of their information switched around due to a mix-up?🤔
A duplicate entry is also considered an error, since only one of those two or more entries actually represents a contact you can use.
Of course, a seeming duplicate entry may actually be two separate entries with a completeness problem, as described above.
If you do manage to build complete profiles and find that this isn't the case, you'll need to delete one or the other to keep your data quality management consistent.
For example if you had one customer listed in your database 5 times, you may accidentally send them the same marketing materials 5 times.
Even if there were no typos or other errors made during the initial input process, contact data needs to be reviewed regularly in order to keep on top of any changes that might have occurred since your last check.
While things like age change predictably and things like gender are unlikely to change at all, vital bits of information like a lead's email address will almost certainly change fairly frequently and may cause trouble when you attempt to contact the person.
Other things like physical address, phone numbers, income range, marital status and education level may also shift over time, and any one of these criteria usually has a significant impact on how you market to a person.
Without constantly updating your contact profiles, you'll still be operating with the old information as your guide, leading to potential hold-ups and missteps.
Estimates say that each individual business' collected data decays in accuracy (and thus in value) by at least 30% per year; in some cases this decay can reach a staggering 70%. Let this issue go for too long, and you'll have nothing useful left in your records.
In order for data to be useful, your entire set has to have the same number of filled-in fields (or as close to it as you can get). This ensures that all profiles can be easily compared and that all contacts can receive the same level of attention when a potential sale is on the line.
With empty fields present, certain variables cannot be analyzed (you couldn't find the median age of your contacts, for instance, if many of them did not have an age entered into your database), and some of the helpful personalization techniques described above are not possible.
It's this kind of clarity that makes it extremely important to gather as much data as you can.
Even if you're not sure about how you will use some of these attributes right now, you may very well decide that you really want to implement some new strategy that requires this type of data at some point in the future. 45% of top companies are currently prioritizing personalization in their sales and marketing efforts, and in order to do that, they'll need as much information about their contacts as they can get.
Not only do complete profiles enable uniformity, but ironically, they also help to ensure that each contact's profile remains unique.
If you have several Mr Smiths listed for a given area and only a few of them have enough data entered to differentiate them, it's tempting to think that the ones without much to go on might just be duplicates. However, the truth is that you simply have no way of knowing whether these are all separate people or not with the information you have. Just in case, you would have to treat them all as separate profiles, potentially wasting worker's time if they are indeed just duplicates.
Non-productive data-related dead ends like this are actually thought to take up about 27.3% of a sales representative's time (a loss which costs a business about $32,000 a year on average)
Proper contact data quality management would uncover and resolve this issue before it started to have such tangible effects.
Avoiding conflicts like this requires following a standardized format to which every contact profile conforms, allowing differentiating data points to become apparent while still keeping profiles comparable.
Now that you know what quality data looks like, you probably want to know how you can get some for yourself.
It all starts with a thorough approach right from the beginning.
Collecting data after the fact is always harder than gathering as much of it as you can with each new contact that comes in.
If you prioritize data collection up front, you'll start with more complete profiles that already give you a wide array of information to work with.
From that point on, it's all a matter of keeping up with things.
You'll need to go over your entire contact database on a regular basis, checking every bit of information to ensure it is still correct and filling in any gaps you find.
There are tools available to help you do this, but they will usually still require quite a bit of human oversight to make sure they catch everything.
Data quality management can often uncover data that you might not think to look for yourself, and they will almost always do a better job than you of keeping your list in tip-top shape - after all, it's their entire job, while you probably find yourself wearing many hats while at work.
If you're not confident in your ability to keep your contact data quality at a high standard, consider investing in data quality management services to assist you. You'll recoup far more in retained revenue than you'll spend to do this in virtually all cases.
Only Active Management Gets Good Data
It may not be an issue on many people's minds, but competent contact data quality management is one of those behind-the-scenes things that can uncover great potential revenue growth.
Understanding what makes quality data is the first step toward a database that will keep your sales and marketing endeavours functioning at peak efficiency.
Check out this article to know the exact number and to find out the 6 characteristics for great contact data quality.
We will take a deeper look at why data quality management matters and some of the specific things it can bring to the table.
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