mql and sql statistics

Sales: Are You a King or a Pawn?

Sales Benchmarks that help you look in the mirror

In sales we get caught in our little bubble, judge ourselves against our quota, and the success of our peers internally. But how do we rank against the world? How can I use broad benchmarks to see how individuals or teams rank broadly? Here are some broad global sales metrics we can all use as a litmus test for broader improvement and goals. Note: I know that each industry varies, as does target market from a customer size perspective, and for example purposes, these are enterprise software SaaS metrics.

  1. Marketing(MQL) to Sales(SQL) – How are your sales and marketing teams working together and are they in sync? The percentage of leads that go from Marketing Qualified Leads (MQL) to Sales Qualified Leads (SQL) is a key metric that should be tracked and honed. The average for SaaS companies is an MQL to SQL conversion rate of 15-20%. Note: Some organizations have an intermediary step, Sales Accepted Leads (SALs) when they have dual functions – SDR and AE. MQL – SAL is typically around 45%, and SAL to SQL is typically 60+% if you separate the functions.
  2. Sales Qualified (SQL) to Opportunity – Once that bad boy gets accepted and further vetted by inbound sales, how many are further qualified and promoted into an opportunity? A good Sales Qualified Lead (SQL) to Opportunity conversion rate is 50%.
  3. Opportunity to Close – The biggie…you are handed a lead, it’s been qualified and vetted, and the true sales and close process begins. How many of those qualified leads that become opps actually close? Best-in class-organizations have a close rate of 30% on qualified opportunities.

So how does your process compare? This is an oversimplified model, and there can be other steps, depending how you outline your inbound process, the lead source, etc. The above example is for the best case, SEO leads from a website. In another post I’ll expand on a broader process for more complicated orgs.

close rate, saas stats, sales conversion rates, sql

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