What factors should be taken into account when scoring?
The basis for quality scoring is compliance with ICP. For a B2B company, such criteria may be:
Industry;
Marketing budget;
Techstack.
Once you have clearly defined your ICP, setting up quality scoring becomes much easier.
How to Develop a Scoring System
At Dashly, developing a scoring system starts with identifying list of albania phone number strong questions. A strong question is one that shows a significant difference in conversion to sales across different answer options. It’s important to understand which attributes or actions of leads are most closely associated with successful deals for your company.
To determine a strong question, it is best to first turn to sales, because they are the main source of knowledge about the lead. They are the people on the front lines and usually know the customer's needs best.
They involuntarily accumulate this database of scoring questions.
It was sales that prompted a subtle, powerful question in one of the pilots: “What games does your child play?” Sales said that users who answer that their child plays Minecraft or Roblox convert better.
Or for B2B, these are questions from the BANT (Budget, Authority, Need, Timing) approach to lead assessment. Yes, such questions can be asked directly in the quiz and quickly qualify leads.
The second way to learn more about leads is marketing questionnaires, research, etc. Although in our practice this is not so common.
Third, brainstorming. Take the client's profile and understand who they are, why they contact us. But we still advise you not to make things up out of your head
But in reality, the questions should be simple and straightforward. Even questions about money. Yes, for many, the topic is quite painful. In one of our pilots, 30% of users dropped out of our quiz precisely because of the question about money.
In the past, we tried to figure out how to get around this. We asked questions like, "How often do you have to make hiring decisions?"
But we have found that the simplest formulations work best. And yes, many will drop off at the question about earnings. But those who answer it will give us a clear signal of their readiness to buy.
Next, based on historical data on closed deals, we assign points depending on the conversion prediction for strong questions. The higher the probability of a purchase, the higher the score.
Through iterative data collection and analysis, we compile powerful questions and answers that predict ABCD segments (tiers) of leads.
The final stage is testing and adjusting the scoring system. We launch it, analyze how the scores correlate with real conversions, and make adjustments.