According to Forbes, Predictive Lead Scoring will be one of the biggest marketing trends of 2019, but it’s not for every business! Find out if it’s right for you and how you can use it to your advantage.
Yes, it’s possible to have too many leads. Yes, it’s possible to have too many MQLs, and yes! It’s possible that these high numbers at the top and middle of the funnel aren’t translating into revenue. This could be because there aren’t enough resources to respond to all the leads, or simply because the qualification process isn’t selective enough. The truth is that money is being invested, and it needs to be put to good use.
Marketing Automation offers us several tools to qualify leads more efficiently, namely Lead Scoring. In a traditional Lead Scoring process, numerical points are assigned to certain characteristics and behaviors of your leads. For example, opening an email might be worth 5 points, clicking a CTA might be worth 10 points, qualifying as one of your buyer personas might be worth 30 points, and so on.
However, these scores are assigned by humans, and, as we know, humans make mistakes. It’s human nature! We’ve therefore evolved toward a predictive lead scoringmethodology, where data is integrated with machine learning technologies that evaluate past results in your CRM (other leads with similar characteristics and scores) to refine your lead scoring.
Check out these 3 tips from HubSpot to decide if it’s time to implement a predictive lead scoring model, and be sure to review the 5 Best Practices for Lead Scoring as well.
1. Do I have enough leads?
Lead scoring can be implemented in any business, but it’s most valuable for companies with high volumes of leads and limited resources. On the other hand, you may have a good volume of leads, but if your business is still in its early stages, you certainly won’t have enough information to implement an effective predictive lead scoring model. Focus first on getting to know your leads and understanding what the qualified ones have in common.
2. Are the marketing and sales teams aligned?
The Predictive Lead Scoring process doesn’t end with lead qualification. The outcome of each lead—whether a deal was closed or not, whether it took more or less time, or whether it yielded a higher or lower return—will inform the software and feed the machine learning model to refine the score. On the other hand, if your sales team does not follow through with the qualification process for SQLs, there is clearly a lack of alignment between the marketing and sales teams that you’ll need to resolve first.
3. Do I have enough data?
Predictive Lead Scoring requires an overwhelming amount of data on qualified and unqualified leads, customers, etc. Yes, it’s also possible to gradually feed your Lead Scoring system over time with more leads and more data, but if your database is still very small, wait a bit and take the opportunity to learn more about your buyer personas.
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