Best Practices of Data Cleansing and Enrichment for Marketing Strategy

Is Your Data Dirty?

Don’t look now, but your data may be dirty. And that dirty data could be costing your business thousands of dollars. You’re not alone, though. One recent study concluded that at least 25% of the average B2B database is “dirty.” On one level, data decay is inevitable. In fact, 20% of all street addresses and 18% of telephone numbers change in a given year, while anywhere from 25% to 33% of your email addresses will be outdated within the same period. Over the next hour, 58 different business addresses will change, 11 companies will switch names and 41 new businesses will hit the market.

What happens if you let your data erode? Duplications, inaccuracies and inconsistencies can lead to wasted marketing efforts, misinformed decisions, product returns, a poor experience for your customers and, ultimately, lost revenue. In fact, Experian estimates that companies waste about 12 percent of their revenue thanks to dirty data. That’s a loss of $600 billion a year for companies in the United States alone. How much is yours losing by relying on unclean data?

What is Data Cleansing and Enrichment?

Data cleansing is the process of identifying these little income thieves and kicking them out, leaving you with clean, actionable data that works for your business instead of against it.

Data enrichment goes a step further, taking your raw data and shaping, enhancing and improving it so you can stay one step ahead of the game.

Best Practices for Quality Data:

Let’s face it — cleaning data is necessary, but it isn’t fun. It doesn’t have to be miserable, though, especially if you do it right. Here are some best practices you can use today to clean your data quickly and relatively pain-free.

Plan Before Planning and Then Plan Some More

Before you dive headfirst into an unmanageable pile of data, you need a plan. First ask yourself what data is the most critical to your marketing efforts. As a for instance, let’s look at a Customer Information File. If your marketing strategy relies primarily on email campaigns, you’ll want to plan to focus your initial efforts on email addresses. The same is true for other fields, depending on your marketing plan — job titles, industries, roles, phone numbers, revenue and more.

Be 100% sure that your data fits (or will fit) into the defined, organized boxes you have for it. If you’re not sure, run a test. Collect a small set of data that’s typical for your business and plug it in. You might be surprised at how things take shape. If problems pop up, you’ll know exactly where they lie and how to fix them going forward. This will save you untold pain down the road.

Create Multiple Worksheets

To stay organized, you’ll want at least four worksheets — one for Raw Data, one for Currently Cleaning, one for Cleaned Data and a fourth for Analysis. Having four separate sheets gives you a clearer picture of your dataset in different stages. If an error arises, you can trace it back to point where things went wrong. You wouldn’t want to do your cleaning in the same worksheet where you store your data, right?

Decide on a Standard

Here’s one of the biggest reasons data gets dirty: there’s no standard way to record a piece of data, so one employee records it one way and another records it different way. When you go to sort the information, you have a mess on your hands.

So, the next step is to decide on a standard format and stick to it. Should dates be recorded 12-Oct-2018 or 10/12/2018? Should addresses be divided into different columns or be recorded in the same cell? Should decimals be rounded up to the nearest one, two or three places? Should number signs be used? Once you’ve decided on a standard format that works best for you, create a cheat sheet for yourself and your employees for reference.

Tackle Common Errors

If you’re starting with a fresh data set, you can incorporate all the previous tips and it should be smooth sailing. Unfortunately, if you’ve inherited dirty data, you’re going to have to give it a good scrubbing. To start, look for some of these fixable errors:

Find duplicates in your data and root them out. With duplicate entries in your CRM, you could be marketing to the same customer or prospect twice, which costs you more and could potentially have a negative effect on response rates.
Incorrect Date Formats. As we touched on before, mixed date formats can wreak real havoc with data. Sort and scan to find anomalies and make sure they’re corrected to a standard format. Integrate normalized attributes in a pick list so that every selection is consistent.
Incomplete Data. Incomplete data could mean records are missing altogether or it could mean attribute values of a record are not present. Either way, filling in those blanks will give you a more complete picture. Thankfully, these omissions can be simple to spot, especially with the sorting tools that come with most spreadsheet programs.
Expired Data. With data decaying at such a high rate, much of your “dirtiness” comes from data that is no longer valid. Examples may include data that refers to expired events or customer contacts that are no longer available.
Spelling Errors. One of the most common mistakes in data entry is spelling errors. If you’re using Excel or a spreadsheet format, running a spell check is a relatively quick way to catch issues.
Multiple Representations. Employees may have tried to save time by abbreviating certain words. Also, differences in capitalization, adjective genders and spacing can arise when you have several people working in your data sets. Even minor variances can cause huge problems down the road.

Add Quality Checks

Now that you’ve populated your missing data, thrown out old records and removed duplicates, save yourself the headaches and make sure they don’t come back. Here’s how:

Stay Consistent. Make sure everyone who has access to your spreadsheets or data program knows and practices the naming conventions and format standards you’ve adopted. Print out a cheat sheet or keep instructions within the sheet itself so they are always front and center for reference. Consider locking cells or requiring values be chosen from a pre-defined pick list. Define user roles and make sure the only people with access and editing privileges are the ones who absolutely need it.
Verify All Incoming Data. If your data comes from customers, double check the accuracy. Have your team double and triple check that the information is fresh, valid and not a duplicate.
Schedule Maintenance. Just like tidying your home, keeping your data clean requires a regular schedule of maintenance. If you let it go for too long, the job becomes unmanageable. At regular intervals, program time to go through your data for a routine cleansing.

Why is it Important for my Marketing Strategy?

Of all the things you do to make your business a success, cleaning and maintaining your data may seem like a low priority. It shouldn’t be. Here’s why:

It Leads to Innovation. The former president of HP, Carly Fiorina, once said that “The goal is to turn data into information, and information into insight.” We’d take it a step further — data turns into information, information turns into insight and insight turns into innovation. With clean, enriched, accurate data on your side, you don’t have to rely on guesstimates and intuition to make decisions about your company’s direction.
It Builds a Better Marketing Plan. Without reliable data, the time, money and effort you put into your outbound strategies could be squandered. With it, you’ll gain insights that help you efficiently target your audience with promotions, coupons or ads to encourage purchasing. Moreover, you’ll be able to see relevant trends in your marketing strategy such as what’s working, what’s not working and what could work with the proper attention.
It Helps Understand Customers Better. When it comes to running a productive business, knowing your customers comes in at a close second to having a great product. Armed with relevant, usable data, you can keep track of how they buy, when they buy and why they buy, and that can mean the difference between a loyal customer and one who hits “unsubscribe.”

How EnableVue Can Help

We live in a period that many people call a data revolution. Or, as expert Gary Cokins phrased it, we are “drowning in data, but starving for information.” We get it: managing your data can feel like a full-time job (it is) and devoting your workforce to it can seem like a waste of precious resources (it is).

EnableVue can help you stop drowning in a sea of data and let you direct your valuable time elsewhere. Our cutting-edge techniques and years of experience in the industry means we can intelligently cleanse anomalies and enrich your data so you can see it for what it is: information to make you more efficient, give your customers a better experience and, ultimately, lead to more conversion of products on your site.