As any business pundit would tell you, a successful business venture requires two base ingredients: a polished idea followed by an impeccable execution. Miss any of the two and you are destined to fail. Remember Google Plus? A good idea, to be sure, but ultimately doomed by the shaky and slow execution from Google. Then there’s the alternative scenario, such as MoviePass, which had a brilliant execution but still failed due to a fatally flawed idea. There are of course other factors like resilience, innovation, customer satisfaction, etc. but they are all supplementary.
As these examples attest, there is no cookbook for creating successful business ideas. Even when you do hatch a brilliant business idea, the execution is a very dynamic process that relies on numerous factors including competence, strategy, experience, and others. The latest addition to that list? Data. Tune into any business leader or executive and they will consistently use terms like “data-driven X”. Be it marketing, sales, talent acquisition, or any other internal operations, data is now the key to executing any business plan.
Here is the interesting part – if something is data-driven, it can go either way. For instance, if you use data-driven marketing, good data could lead you to potential clients while bad data such as inaccurate contact info will lead to wasted effort (such as in the form of bounced emails, etc). The point is, if you make your decisions based on data, the quality of the data ultimately determines the competence of your decisions. The key question: is there such a thing as good and bad data? And what exactly constitutes bad data? Since we are limiting our discussion to the B2B sphere, it’s fairly simple to define.
Bad Data
Database management systems prescribe 3 C’s to ensure data quality: Consistency, Completeness, and Correctness. To simplify, data across the database should be consistent in terms of information and format, should contain no missing fields, and should be correct. Any database that fails to meet any of these properties is considered bad data.
Easy, right? Not when you factor in the impact of crowdsourcing and data decay. If you collect the same data (say, contact number of a person) from three different sources, they might yield different results, leaving you baffled as to which one is correct. Hence, the issue with inconsistency. Alternatively, people may switch jobs, change numbers, companies may shut down, downsize, and so forth between the time they enter your CRM and the time you reach out to them. That’s referred to as data decay, which has major implications for data correctness. Make no mistake – your data will keep changing. And unless your database keeps pace with it, it doesn’t take long for good data to turn bad. According to reach, even if you have 100% accurate data at this very moment, more than a quarter of it would go sour within a year.
So what’s the problem with bad data? As it turns out, a lot! Here are just a few of the highlights:
Squandered Resources
If you have bad b2b contact data, your sales reps will be calling the wrong people, emailing incorrect addresses, and a significant portion of your sales and marketing team’s time will be spent finding the correct information. This is the time they could have used to talk to potential clients and close deals.
Reputational Damage
Mass advertising, when done wrong, is called spam. If you are working with bad data, most of your emails will be reported spam. Your calls will be answered by irritated people. Not only is it a waste of your time and resources but it also causes reputational damage in the long run. You don’t want to be the company everyone hates because they keep receiving irrelevant marketing emails and calls.
Degraded Morale
If a sales rep makes a hundred cold calls and fails to hold even a single legitimate conversion, he or she is bound to feel frustrated. The same goes for marketers who launch extensive campaigns but fail to garner significant results. Often overlooked is the fact that their performance was directly influenced by the quality of data they had. Bad data yields bad results and by extension, leaves the entire sales and marketing team frustrated.
On the other hand, good data enables businesses to take the right decisions, optimize operations, and judiciously allocate resources to maximize productivity and profits.
Now if you add all that up, it seems pretty evident that great business ideas and strategies are only a part of the equation. No matter how innovative or groundbreaking your products are, you are going to need quality data to be able to precisely target your prospective clients. B2B enterprises in particular grapple with the challenge of acquiring reliable contact data as they often target a very small and niche clientele.
If you wish to know what good data is and what goes into building a reliable and robust database, you can read more about it here . If you want to try our data, request a demo of SalesIntel now!
