You need two things to operate a classification system: data and a grading standard. As we mentioned, data is gathered from first-, second-, and third-party data providers.
A grading standard is a way to translate the facts and figures of data into something workable. A very simple grading standard can categorize intent data into marketing or sales information. In this case, a signal that involves uae whatsapp number somebody downloading a white paper – and while doing so, entering their contact info – will be sent to marketing. This can lead to a follow up in the form of emails that notify the prospect of new white papers.
On the other hand, if the signal is categorized as sales, a different treatment follows based on data insights. Let’s say that the data point has been classified as a strong buying signal, like a direct contact filling out a demo request. This goes to sales, where they might arrange a pre-demo call to figure out the prospect’s needs.
One interesting crossover between the “NLP” interpretation of intent classification (see above) and sales intent classification is the ability to immediately exploit very recent contacts. Normally, an automated intent classification system reviews the data and sends a report to sales and marketing, perhaps once a day. But an NLP-based system can be set up to go a step further by recognizing high potential leads.
