How many resources, including time and money, do you devote to software? If the total isn’t at least equal to what you expend on data, you may have checked your priorities at the door. Your data is almost always a better investment.
Not that a commodity like software isn’t important. It helps with infrastructure, data access, and data quality. But it’s just a means to an end. After all, you invest in software to access data, and the quality of data differentiates your business from the competition when doing market research.
Let’s say, for example, you sell to businesses. Every decision you make starts and ends with your customers. The only way to know these customers — and I’m talking really know what makes them tick — is through all the data you’ve gathered over the years.
If that data gets contaminated by the killer D’s of data — duplicate, dirty, or dead records — every part of your business will slow down. And being that all businesses are now information businesses, you can’t let anything plague your data. It’ll kill your bottom line.
Untangling the Rat’s Nest
Unfortunately, most companies take on a more reactive approach when dealing with the rat’s nest that data can become. They want to rid their businesses of the pests without ever determining which of the killer D’s has infested their data. Here’s how to break them down:
- Duplicate records. Most business systems refer to accounts by name. But doing so can leave data open to duplicates. One person could write out a company’s full name, while another could enter its abbreviation — and the variations go on from there. Given enough time, you could end up with 17 instances for that same company.
- Dirty records. Businesses often assume that data collection tools provide concrete data. But these tools come from people, and people are prone to mistakes. If you capture the wrong address, company size, revenue, or other value, you’re working off dirty records, and those “actionable insights” quickly become half-baked.
- Dead records. Simply put, a dead record is one for a defunct company. Keeping those in the mix does nothing to drive business and could actually hurt the health of your data as a whole. Looking at a data set of 200 businesses in which half no longer exist makes projecting into a game of chance.
You need to have protection around data. Instead of referring to companies by name, wouldn’t a better option be referring to a globally known, free, and open standard-using URL? More and more companies are conducting business online, so it only makes sense to differentiate them this way.
Plus, you can easily ping them for signs of life. If you get a 400 error, it’s a good indication that a company has shuttered its doors. The time has come to knock it off your list.
Erecting these standards often comes down to your company’s mentality. If its focus is simply on software, the standards won’t be as strong as they would with a focus on data. Data drives innovation, and the majority of the most successful companies have made this transition already — or they’re at least well on their way.
The Woes of Infestations
Obviously, you expend more time and money by focusing on the wrong companies with the wrong outreach efforts. A company of five doesn’t require the same resources as a company of thousands, and dirty records could send you barking up the wrong tree — or trees, at that.
Working off duplicate or dirty records could also damage your credibility. Customers demand more personalized interactions with brands when doing company research, and incorrect data could highlight how ill-informed you are about your customer base. Someone in his 20s doesn’t necessarily need an email for a walk-in tub.
Besides wasting time and money or hurting your credibility, any one of the killer D’s can cause you to incorrectly set global sales territories or forecasts. This not only creates internal strife with people fighting over particular areas, but also can lead to senior executives setting unattainable goals for their teams — talk about positioning your company to become a dead record itself.
Exterminating the Pests
Though the killer D’s will vary by company, ensuring business intelligence data is the best it can be is almost always the same. The following is often a good place to start:
1. Change your mindset. Thinking of data as a side issue does your company no good. If there’s a problem, a solution should be your main focus. Cloud software has taken away anyone’s excuse for not using software. Now it’s time to invest in data, and you’ll reap the rewards.
2. Clean your rat’s nest. Starting with a URL and expanding out with company name, address, and phone number, you rid your data of duplicate, dirty, and dead records. It improves the integrity of your information. Layer in a data backbone by accessing a resource of millions of company URLs.
3. Keep it clean. Keeping data clean or alive is all about creating very specific safeguards around it. Institute a framework or mode of operation for your data. If a record hasn’t been touched for a certain number of days, revisit it. Is it a duplicate of another entry? Does it contain all the necessary values? Is it still in operation? Just implement rules to keep your data clean.
Think about how much more efficiently your business would run if you had perfect data. Your salespeople would no longer waste time in the dirt. And your company could completely avoid having multiple salespeople reach out to the same prospect in an organization, which makes your company lose credibility.
Instead of eliminating the conditions that led to the infestation in the first place, don’t be like many companies and look for a quick fix. You don’t want to just clean house, sweep up any excrement, and go about business. Look for the hole that has obviously worked its way into your foundation in order to keep your data clean.
What’s your company doing to ensure your data hasn’t become a rat’s nest?