What is Lead Score ?
Lead score is the likelihood that the Lead would generate business. The higher the lead score it is more likely to give business. Lead score depends on various factors and could vary from company to company or even how a Sales Person thinks about it.
Lead Score in Vtiger
In Vtiger there is no defined criteria for Lead Scoring. In Leads module we have a picklist which defines a lead as Hot,Warm, Junk etc.. This is completely based on the intuition of the Sales Person. There might be criteria which he is not considering, but they are effecting the lead conversion.
Some of the criteria normally considered are the frequency of emails exchanged, if the Lead has subscribed to a certain newsletter, age, gender, previous products bought etc..
In Vtiger we can setup workflows with conditions like if age is between a range, gender is male/female, email field is empty or not, if belongs to certain country, has opted out of email or not etc.. We could set the execution to every time the Lead is modified. Based on this we can have “update fields” kind of task and which updates the lead score as warm, hot, junk etc..
But this is not accurate and do not help much. As there are various important criteria which could not be put in workflow conditions like freq. of email exchanged, website visits, no. of downloads etc..
But, do you need Lead Scoring ?
The fact is, lead scoring is not a must have thing for all business. Sometimes it could become a waste of time for your team. According to reports only 36% of B2B marketing teams have setup lead scoring mechanism.
Few of the question which you must ask yourself before implementing Lead Scoring are:
- do you have enough data? Lead scoring is comparative. It has to evolve over time based on previous scoring.
- how good is your data ? are you collecting right data from your contact forms and other lead sources? is the data collected relevant to your business.
- are you getting enough leads? lead scoring would be waste if you have only few leads coming in which could be handled easily by your team.
Whatever the scenario might Lead Scoring is time consuming and needs to be monitored and evolve. Various criteria have to be tried and experimented to make out which one is comparatively more accurate.
Predictive lead scoring
With the evolution of BigData and Machine Learning, it is becoming more easier to automate your Lead Scoring and to get more accurate results. Predictive Lead Scoring is based on your historical data. The more the data. more accurate the results.
Traditional lead qualification is subjective, with a lot of guesswork around how many points to assign to various behaviors, specific job titles, etc.. Each Sales person has different perspective for a given Lead.
Predictive lead scoring is complete science and depends on Machine Learning. It could identify patterns in your data and make out which factors correlate with won deals. This factors then could be used to build data-models and then to predict the lead score. This could help even to uncover hidden Hot leads, which have been ignored earlier due to false scoring.
Machine learning in today’s world has reached to an accuracy of ~86%. Now you can yourself decide which is more good Tradition or Predictive Lead Scoring.
Should you implement Lead Scoring for your business ?No Fields Found.