According do Forbes, Predictive Lead Scoring will be one of the major Marketing Trends in 2019, but it's not for everyone! Find out if it is for your business and use it to your advantage.
Yes, it is possible to have too many leads. Yes, it is possible to have too many MQLs, and yes! It is possible that these high values at the top and middle of the funnel do not reflect on your turnover. It may be because there are not enough resources to respond to all the leads, or simply because the qualification is not being very selective. Truth is: the money you invested needs to be monetized.
Marketing Automation offers us several tools to qualify leads more efficiently, namely Lead Scoring. In a Traditional Lead Scoring process, there is a numerical assignment of points to certain characteristics and behaviors of your leads. For example, opening an e-mail can be worth 5 points, clicking on a CTA can be worth 10 points, qualifying for one of your Buyer Personas can be worth 30 points, and so on.
However, these scores are attributed by humans and, in fact, humans make mistakes. It's in our nature! We evolved, therefore, to a Predictive Lead Scoring methodology, where data is incorporated with machine learning technologies that evaluate previous results in your CRM (other leads with similar characteristics and scores) to improve your Lead Scoring.
Take a look at these 3 HubSpot tips to decide if it's time to implement a Predictive Lead Scoring model.
1. Do I have enough leads?
Lead Scoring can be implemented in any business, but it is more valuable to companies with large volumes of leads and few resources. On the other hand, you may even have a good volume of leads, but if your business is still taking its first steps, you certainly will not have enough information to implement an effective Predictive Lead Scoring model. Focus first on knowing your leads and understanding what they have in common, qualification wise.
2. Are my Sales and Marketing teams aligned?
The Predictive Lead Scoring process does not end with lead qualification. The result of each lead (whether it's closed business or not, whether it took more or less time, if it resulted in more or less return) will serve to inform the software and feed the machine learning for the improvement of the score. On the other hand, if your sales force does not continue the SQL qualification procedure, there is clearly a lack of alignment between the marketing and sales teams that you will have to solve first.
3. Do I have enough data?
Predictive Lead Scoring needs an overwhelming amount of data on qualified leads, disqualified leads, customers, etc. Yes, it is also possible to feed your Lead Scoring over time with more leads and more data, but if your database is still too small, wait until you learn more about your buyer.
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