One of the core benefits marketing automation delivers to any organization is better prioritized and qualified leads for the sales team – at least that is how it is suppose to work.
Debates about the quality and “sales worthiness” of marketing leads are not a new thing in any organization. Using technology to bridge this gap and create shared understanding seems like a great thing, but getting there can be a whole different matter.
Long before technology enters the discussion, there needs to be a shared definition of what a “sales qualified lead” is and is not. Keeping these qualification criteria front and center not only adds discipline to the process but helps target and focus lead generation programs to acquired those types of prospects.
Once this is in place and there is a baseline level of quality for all leads, now it is time to better prioritize, engage, and close new customers. Using a marketing automation system to aid this prioritization effort is key and lead scoring functionality is how to do it.
If you have invested the time, effort, and energy to develop, test, and tune a point-based lead scoring model in your marketing automation system that does actually prioritize the best sales leads for your sales team then congratulations, you are in a select group of power users. Doing this properly requires a thorough understanding of what has actually contributed to a conversion and the buyer’s journey a prospect took to get there.
If you are like the other two thirds of companies using marketing automation systems, you have either tried this and abandoned it or started down the path and simply gave up. How many points for the pricing page? How many points for a demo request? What happens if they unsubscribe? The questions (and scenarios) go on and on.
There is a better way.
Enter predictive lead scoring and automatically scoring and prioritizing sales leads based on the behaviors they are exhibiting. No points to assign, no models to get consensus on, no opinion based debates between sales and marketing about what constitutes a good lead.
How does it work? Predictive lead scoring simply takes a look at the prospects that have progressed through the sales process and have either become customers or were expected to become customers (forecasted). It then looks at all the actions and events associated with that prospect – the web pages they viewed, how engaged they were in email campaigns, what events they attended, what content they consumed, etc. and finds “look alikes” in the database. These are the ones who are most likely to become your customers and need sales engagement.
The data informs the prioritization and is constantly updated based on the day to day activities of marketing and sales teams.
Adding predictive lead scoring to the mix uses data to align sales and marketing teams and delivers on one of the core promises of marketing automation – prioritized sales leads, more efficient sales teams, improved conversion rates, and, most importantly, more revenue which will deliver the lead scoring benefits for marketing.