According to Forbes, 50% of B2B Sales teams miss their quotas.

The reason they can’t deliver, of course, is that your team (Marketing) isn’t bringing in the volume and quality leads that they need to hit their numbers. But those guys are lazy, right? Maybe they’d be closing if they’d stop complaining and actually follow up on the precious leads you’ve worked hard to attract and nurture. With this proverbial boxing match constantly at play, nobody wins.

It’s a longstanding rivalry that presents both a challenge and opportunity. If the above scenario doesn’t sound familiar to you, congratulations… you’re the minority. If you’re like most, as a B2B marketing leader, you feel this pressure on a daily basis. Salespeople resent you because you’re not giving them what they need to do their job. You feel you are and may throw even more budget and attention at demand gen, to both increase volume and cover your ass. Everybody needs to stop and take a breath.

When Sales and Marketing unite around agreed upon goals and responsibilities, everybody can stop focusing on what the other department is doing wrong, and start focusing on killing it in their respective fields and work towards company goals. In this post, we’ll outline three ways that predictive Marketing analytics can bring Sales and Marketing together, and drive more revenue.

1. Create a common customer view.

Sales and Marketing need a shared understanding of what drives a prospect to buy. The B2B buyers’ journey is complex, but with visibility into which channels, campaigns, and activities are most likely to move prospects along the path to purchase, Sales and Marketing can develop a common understanding of prospect motivations. Unfortunately, this marketing performance data generally lives in automation systems (Marketo, Eloqua) and Sales interactions are tracked in CRMs (Salesforce). These siloed data sources make it difficult to craft a complete customer profile.

Predictive marketing analytics can help integrate data between disparate platforms to create a common customer view and track interactions all the way along the buyers’ journey.  As a result, Marketing can more intelligently craft their programs and understand which themes are resonating most with prospects. When a lead is ready to advance to Sales, Sales already has a complete prospect profile—by understanding the triggers that advanced that lead—and is able to target messaging to address a prospects’ unique needs.

2. Develop shared definitions/goals with revenue waterfall visibility.

Lead scoring technology has been pivotal in helping organizations track, score, and route leads between Marketing and Sales. The problem, however, is that traditionally Marketing defines when a lead is qualified (MQL) and ready to move to Sales. On the same note, Sales traditionally defines what characterizes an SAL (Sales Accepted Lead; a lead that Sales has accepted and is committed to) and SQL (Sales Qualified Lead; a prospect this is likely to buy). Because of this, Marketing may not always understand what exactly Sales considers great lead, and is stumped when they don’t see an SAL advancing as quickly as expected.

Predictive Marketing analytics gives marketers a complete view of the entire revenue waterfall—from first touch to conversion, and everything in between. With full visibility into lead progression along the purchase path, marketers can understand which activities are necessary to deem a lead Sales-ready and, based on historical performance, anticipate how quickly they can expect a lead to move from stage to stage. With this knowledge, you can build data-backed Service Level Agreements (SLAs) to keep everyone in check and ensure everyone’s holding up their end of the bargain.

3. Predict pipeline and revenue.

B2B Marketing generates lots of activities, but Sales doesn’t always see the connection between the activities and revenue. This is generally because Marketing activities tend to be far more complicated with multiple touchpoints, stakeholders, and buyer scenarios. Without the ability to see which Marketing activities contribute to revenue, it becomes impossible to optimize campaigns, and effectively forecast how and when leads will translate to pipeline and Sales.

Predictive Marketing analytics can attribute campaign touch to leads at every step of the buyers’ journey—not just first or last interaction. Data science is then applied to predict which leads will translate to pipe/revenue, and when. With this knowledge, marketers can automatically identify revenue levers, and adjust programming as needed, to ensure that Sales will get the quantity and quality of leads that you’ve committed to. In turn, if Sales’ ability to convert doesn’t align with forecasted revenue, you can identify exactly where there’s tension in your funnel, and correct kinks in the system. For example, you may find that in fact you’re both “doing your jobs,” but you’re missing your targets because you weren’t aligned: you’re generating great mid-market leads, and your sales VP has built a great enterprise sales organization; or that the C-level message resonates in EMEA but the Director-level message works better in NA.

The Twelfth Round

While Sales-Marketing alignment may still seem like a pipedream to some, technology is helping both functions improve performance and efficiency by granting visibility into activity across the entire revenue waterfall. With these insights, Sales and Marketing can stop fighting against each other and instead, work together, to deliver the one-two punch that turns prospects into customers.