Finding the buyer who could say yes
This company had built data most of its market couldn't produce, and it sold that data as fixed-fee pilots to large organizations that took a long time to decide. In our first two months we changed the buyer, the pricing and how the team tracked deals. The new buyers were investors who use the data to price a deal, and they signed annual contracts. Pipeline grew about tenfold in seven months.
Data and analytics company // Client story
10x
pipeline in seven months
Open pipeline when we stepped back from the hands-on work, against where it stood when we started.
€75K
new ARR in one quarter
Annual contracts signed in a single quarter, after pricing moved from one-off pilots to yearly terms.
15
old stages, one pipeline
About 15 stages across two pipelines became one pipeline, with conversion rates between the stages.
Where the work started.
The product was strong, and the team could explain every part of it. Their first buyers liked it and had no deadline to buy it, and each sale was a one-off pilot with its own price. The CRM had about 15 deal stages across two pipelines, and half the deals had no value entered. Nobody could say what the pipeline was worth.
//buyer_and_pricing
From pilots to annual contracts
Their first buyers valued the data and had no deadline to buy it. Investors did. When you're pricing a deal, better data changes what you'll pay, so it affects returns directly. We aimed the sales work at those investors, then at the most active of them. The pitch now opens with the deal in front of the buyer, and the science comes second. We also dropped fixed-fee pilots and priced on annual contracts. Buyers took to it, and €75K of new contracts signed in one quarter.
//pipeline_review
Flagging the guesses in the forecast
Half the deals in the CRM had no value entered, so any forecast was partly a guess. We gave each of those deals a default value and a checkbox that says so. The total became usable, and everyone could see which numbers were guesses. We also merged about 15 stages into one pipeline. The weekly review now covers only the deals with no next step or two quiet weeks, so the meeting is short and spent on the deals that need help.
//sales_training
Twenty calls before changing the script
Two bad calls are usually enough to make a team drop a new script, so we agreed up front to run it on twenty real calls before judging it. Before those calls, the team rehearsed against two researched buyer personas, in rounds with a different mood each time, so a gruff answer on a real call wasn't a surprise. We also handled replies to the CEO's outreach twice a day and went through the best and worst messages with the team.
What the team was left with.
The company sells annual contracts to investors who use its data to price deals, and its pipeline is about ten times what it was. The team works from one pipeline with stages everyone uses, a forecast that marks which numbers are guesses, and call guides short enough to read before a call.
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