But in most companies, the task of defining MQLs falls to one person who comes up with relatively arbitrary characteristics—and those go on to constrain the whole organization. Instead, MQL criteria should be set by sales and marketing, who work together to identify proven indicators that a lead is likely to buy from you. Working with Sales to Reverse Engineer Lead Qualification So how should you define an MQL to avoid these problems between marketing and sales and MQL vs.
SQL miscues? It’s simple: Marketing teams should work with sales to figure out the best definition of an MQL. That is, the criteria you use to define and score MQLs should be pulled directly from the end of the sales process. That happens by reverse engineering the buyer’s journey to find common characteristics and patterns in who’s likely to buy and who isn’t. You can get a good sense of some important lead qualifiers by looking through your CRM for patterns.