Is your hit rate too low?
Are your sales people running after opportunities they will not win?
Do you think your sales process and sales people are not as efficient and effective as they could be?
Qualification of sales opportunities is important
Many businesses, especially solution businesses, are often characterised by multiple buying influences and long buying cycles, which increases the importance of accurate and effective sales forecasts and opportunity qualification. How do you measure the quality of a sales funnel? How do you pick and choose the “right” sales opportunities to focus on?
To increase quality in marketing and sales, one must know what kinds of inputs are allowed to enter the sales process, i.e. which opportunities sales people (and the rest of the organisation) should work on. Typically, companies rely on experienced salespeople to judge whether a sales opportunity is a good fit. No Go decisions are rare and at the same time, the hit rate is low. This means that the salespeople run after business they will not win and sales is creating lots of waste instead of value.
Companies can no longer trust the judgment of the individual salespeople, especially without a criteria. There are generic opportunity qualification tools such as BANT, but they are generic and produce average results. A single model cannot be applied across industries with accurate results. Data and fact based approach is proven to improve results and help focus on the right sales opportunities. We’ve come up with data driven approach that creates very accurate results.
Data-driven approach to opportunity qualification
We start the process by identifying what the characteristics of very good sales opportunities are. Typically, these qualities can be identified in one or two workshops with the sales management and senior salespeople. These might include information regarding the timing, such as if the company was the first or last provider to hear about a specific opportunity. They could also be about how well the company knows the customer’s decision-making process, or if they know where the need is coming from in the customer organisation. We’ll formulate these as questions and start to collect data.
All of these characteristics are grouped into four key areas:
- Is this an opportunity for the customer?
- Is the customer going to act on it?
- Is this opportunity a good fit for us?
- Can we win?
Once we have sufficient amount of data, we’ll analyse the data to identify which questions predict winning and which predict losing.
Case study – One of our customers was able to achieve the following results:
They executed 200 sales opportunities with the qualification criteria and collected data. They won 50 opportunities and lost 150 opportunities, so the hit rate was 25 %. The average sales cycle length is 6 months and the average sales opportunity value is tens or hundreds of thousands.
Based on the analyses, we were able to identify some qualification questions that predicted losing and some that predicted winning. Sales people started to use these qualification questions early on in the sales process, helping the organisation to pick and choose the “right” sales opportunities.
Average hit rate is 25 %. The best qualification question is able to predict 67 % chance of winning.
This is important, especially if your sales cycle length is many months or even years, and if you need to have more than one person working on the opportunity.