Who are the prospects that are the ‘right fit’ for your business? Your organization has probably spent a great deal of money and time to try to answer this question. In that effort, you have collected details and information involving job title, industry, and company size. Even with all that information, you are keenly aware that your sales rep can have a prospect that seemingly fits neatly into your buyer persona and still end up not being able to close a sale? Why is that?
The answer is that there’s more that goes into lead scoring than just finding a ‘fit’. If you score leads solely based on fit, you may know who is qualified but still not know who is ready to talk to your salespeople and who isn’t.
By the time a lead lands at your website, they’ve already done 60% of their research online. When you fail to track the activities that a lead performs before they start engaging with your brand, you’ve already missed out on being able to be involved in the first half of their research process.
This creates a major blind spot in your lead scoring system and ends up giving the sales team a lot of work to catch-up on when they finally discover the lead.
How do you identify data blind spots?
An organization may use one of the many data analytical tools available in the market, but they won’t give you good results if your data blind spots are not taken into account.
The first thing to keep in mind about blind spots is generally the factors you didn’t take into account because you did not know, or think, to consider them.
Secondly, when business analysts talk about blind spots in data, dark data comes into the picture.
Dark data, also known as an “unclassified data”, is information that is not put to use for analytical purposes or any other reasons related to business.
If you are unaware of how much dark data your company has, where it stores it, and what kind of information it entails, then that unawareness could cause a blind spot – A business can possibly run into big problems if their unclassified data and the blind spots in it are ignored.
Thirdly, natural human behavior can also cause a data-specific blind spot. If people already expect a particular conclusion, especially one that supports their hypothesis, then they start ignoring data that does not meet their expectations. This phenomenon is called “confirmation bias” and falling into a confirmation bias trap leads to yet more blind spots. Whenever you look at data, ask yourself these two questions: “can I interpret this in another way?” and “am I missing on something?” Forcing yourself to think critically steers you clear from the blind spots your mind is subconsciously trying to create.
A growing number of organizations now see great values of information that are contained within these data blind spots. The key reason is that it enhances a business leader’s ability to make smarter decisions since much of these data points provide good insight into past decisions.
Companies have started realizing that these non-traditional data sources are growing at an exponential rate and have now become the language of business for various organizations.
Flobile can fix it!
Flobile can fix your data blind spots and increase productivity and sales by 200% with technology automation and strategy built on solid data compiled by our team of dedicated data scientists.
With most third-party data lists, the quality of the information is a complete unknown. Prospect data governance can consume a lot of resources, time, and money to maintain. With Flobile, there’s no guesswork. Thanks to the AI-driven data scientist-developed verification technology.