Marketing’s job as a lead generation engine has changed. It’s no longer good enough to provide sales with just any leads; providing ultra-qualified leads that are sales-ready is now the imperative. Models based on past behavior and engagement help marketers more effectively qualify leads, but even these traditional engagement-driven models have become unreliable in a world of ever-changing and complex buying situations. Marketing and sales are at a constant tug of war, pulling against each other when in reality both teams want the same thing: quality leads that have a high propensity to buy.
A recent report from Gartner indicates that more and more companies are utilizing predictive technologies to combat this problem, specifically through predictive lead scoring. Predictive lead scoring combines traditional data models from lead management and marketing automation systems and combines them with third-party and proprietary data systems, ultimately helping companies see higher conversion rates with more targeted, sales-ready leads.
Let’s face it: the growth of marketing-qualified leads (MQLs) only matters if it leads to coinciding revenue growth. Instead of simply generating as many MQLs as possible, leading marketing and sales teams today are much more focused on converting these MQLs into active sales opportunities (and ultimately closed deals). Predictive scoring can help marketers streamline this part of the conversion process by utilizing advanced data models to determine which leads are most valued by the sales team, and more importantly, which leads have a higher propensity to buy.
The rapidly growing trend of Account-Based Marketing has aimed to retarget marketing’s efforts at key accounts or groups of accounts to get qualified, high-value prospects in the door. Predictive lead scoring can serve as an ideal tool to enhance account-based efforts by prioritizing leads from key accounts and more quickly moving them to sales. To make account-based marketing work, however, it’s essential for all stakeholders to be involved in the process. Sales teams need to communicate which accounts to target and why, content creators need to determine proper messaging and positioning for every target individual, and lead generation specialists need to ensure they are focusing their campaigns in a hyper-specific way.
In addition to prioritizing the right leads, predictive signals can provide lead generation specialists with insights and data that can help to adjust and fine tune nurture campaigns to fit these unique indicators. Content creators can also utilize these insights to help create more refined and targeted messaging, while sales teams can use the insights to create more contextually relevant sales presentations. Predictive signals, in sum, help account-based marketing teams anticipate and scale hyper-specific messaging in high-value accounts to increase revenue.
On top of revenue generation, integrating predictive scoring into your account-based strategy yields huge ROI. According to ITSMA, account-based marketing is one of the highest value marketing tactics in terms of ROI—and Gartner has noted similar findings from its clients using predictive scoring systems. Specifically, those using predictive lead scoring today have seen glaring improvements in .
Predictive technologies are becoming a necessity in the realm of account-based marketing. According to a report from Forbes Insight, only 15% of marketers indicated using predictive technologies for two or more years, but 83% indicated that they planned to increase their investment in 2016. Ensuring your sales and marketing engine is investing in predictive technologies–for your lead generation strategy, account-based efforts or both—may prove to be the best way to stay ahead of the game and gain a competitive edge.
