Decreasing rejection rate with enrichment, targeting and alignment

Steve and his team at Google Chrome Enterprise were tasked with generating MQLs to send over to their sales team to follow up on. At the time, the team had ramped up their lead generation - buying leads from multiple vendors.

Only to find that a huge percentage of them - around 87% - would be rejected, not converting to SQLs. This was abnormally high for the business, so it was quickly highlighted in a monthly pipeline review meeting.

There were a number of elements to the solution that Steve and his team implemented:

1) Redefine the ICP, which could then be translated back to the vendors supplying the leads.

Steve said:

“Our vendor had been sending over a bunch of bad leads, but it wasn’t their fault because we gave them a really broad description of the ICP.”

This meant going back to the drawing board and redefining exactly who they wanted to bring in. 

For example, the job titles they wanted to get. Which was mid-level decision makers, IT managers for example. Not CTOs or anyone more senior, as they wouldn’t be involved in the purchasing of Chromebooks.

2) Setting up proper governance over what leads made it through. 

In other words, setting up rules in systems meaning that only leads with full contact information (not just HQ reception numbers!) would be considered an MQL.

3) Alongside this, the team focused on enriching the leads that they received to ensure the information they had was the most up to date as possible.

4) Finally, the last piece of the puzzle was to tighten up the rejection reasons recorded from the sales team.

Prior to the new adjustments being made, the majority of rejections were recorded as ‘couldn’t connect’ because the reps couldn’t reach the prospect. 

On the surface, that meant they called the rep 12 times but they never answered the phone. But when this data was investigated, it was revealed that the rep had called an 1800 number - so of course they hadn’t been able to reach a decision maker.

Another common rejection reason that was often used was ‘not qualified’ but this didn’t offer any real insights as to why they weren’t qualified. For example, was it the prospect saying they didn’t have the budget? 

Instead, reps were trained on how to properly log reasons why they couldn’t get hold of prospects and why they were rejecting prospects so this data could be better used to monitor performance.