In sales—especially in today’s ultra-competitive digital age—data accuracy is everything. On the plus side, just remember a time when a salesperson reached out to you, and you realized (perhaps with somewhat of a shock) that this person really understood you and your issues. On the negative side, just remember the last email you received, from which you could tell the sender knew absolutely nothing about you. Data accuracy tends to run the gamut from one extreme to the other. Obviously the more accurate it is, the more effective it will be, with an increased likelihood of a closed sale and shut-out competition.
For the future, machine learning is going to have an enormous contribution to data accuracy. Machine learning allows a computer to learn without being explicitly programmed. It works by searching through large volumes of data and identifying patterns; the patterns can then be applied to what has already been learned, and to new data. Pattern recognition will play a major role In day-to-day processes, with recognized data patterns triggering the next logical process.
I personally have been working with pattern recognition for almost 20 years—in fact, my company worked with the first pattern recognition system. It consisted of algorithms that correlated patterns, so the system actually learned and became smarter.
In a future article in this series we’ll be examining the subject of anthropology—the study of humankind—in more detail. But here I’ll just touch on the fact that there is a lot of misunderstanding of what humans can do.
Humans can be lazy. They forget things, and neglect to complete processes. This is unlike a process in a computer—when it runs, it runs all the way through to completion. But a human can be easily side-tracked. You might have noticed that it can be difficult to have a meaningful dialogue with someone on a single topic, that makes it all the way to a conclusion with no diversion. One stray thought or comment can derail the conversation to a totally different subject.
Human beings are the real problem in most accidents. A human can blank out mentally and run a red light causing a serious injury. Even the serious issues with Boeing 737 jets that have been in the headlines in the last few months were traced back not to computer error but humans making assumptions.
Because of these and other human failings, computers will, in the near future, take over many processes, because they can do so without deviation and mistakes. If there is a bug in computer programming, it can be rapidly fixed, which is not so easily done with a human; a human has a will which you cannot simply override.
We know, as discussed in our last article, that everything in the future will rely on data. And it’s not just data, but the completeness of the data.
Decisions made with inaccurate data lead to errors. Therefore the next major step we need to make with automation is the correction and completion of data by machine, through machine learning. Unlike a human, a machine cannot lie, does not forget, and completes information.
Data Capture and Leads
Completeness of data is not just for the use of salespeople in improving the user experience—it is also needed to round out and improve the quality of leads as they enter into your CRM system. You need to know if a lead is valid or not, and where it comes from. Additionally, you want more than just the data the person entered in a form, so it should be automatically enriched. You want to know where this prospect stands in the company, what their connections are, if they are a decision-maker (or, if not, what their relationship is to a decision-maker). This kind of data will shortly be available within just a few seconds.
Data will consist of, but will certainly not be limited to, communication tracking, blocked call tracking, email tracking, and much more, and will exist in reports as well as being available directly.
For the Reps
Data capture through automation won’t simply be for leads, but also for existing customers. Automatically you’ll know if there are changes in an account, and how much they’re using your product or service. You’ll know right away if the customer has some sort of issue, informed by your tech support ticketing system, and automatic alerts will be generated.
Overall from a company perspective, you want to provide sales reps with immediate insight, giving them the power to understand what kind of conversation they should have with the customer or prospect the next time they speak.
You can see how much of an effect machine learning is going to have in many areas of sales. We need to have this advantage because the world is so complicated—accurate data is a must-have for our processes.
In the end, a CRM system is a (albeit well-designed and fancy) container for customer and prospect knowledge and data. The CRM system is only as effective as the quality of the data it contains.
And the only way to close a majority of sales—and to truly shut out the competition—is with completely accurate data.