Lead fatigue can be summed up as the result of marketing automation working too well, delivering too many leads that sales cannot prioritize and CRM cannot provide insight into.
Picture this: You are in the marketing department and you've been mandated to create more inbound leads. You and your team create remarkable content to engage your target audience. Before you know it, leads begin coming in so fast that your inside sales team can't keep up.
This is lead fatigue, and it's a real thing, thanks to marketing automation's effectiveness.
So, what happens when marketing automation works too well?
Just a decade or so ago, companies began to invest heavily in marketing automation, and the leads started pouring in. However, marketing leaders weren't recognized for their efforts supporting the sales team. When the content used to fuel a marketing automation system works too well, it results in countless leads passed to the sales team, the majority of which go unseen, largely due to sheer volume. Lead fatigue sets in and suddenly, low response rates, incomplete lead scores, and poor lead qualification become the operational norm.
The sales team is left on its own to follow up with the leads, but doesn't know how to handle them due to an absence of context. Many sales professionals will search up to 15 different sources prior to placing a call to create this context, eventually becoming overwhelmed by the amount of data available.
In many cases, sales teams will end up ignoring the leads because they don't know where to start. If they do reach out, the conversion rate is poor, because they aren't sure how to prioritize the leads, nor do they know how to properly engage them and communicate the value proposition.
According to a recent survey we did with CSO Insights, 47 percent of sales professionals believe the quality of leads generated by marketing needs improvement. But are they looking for improvement, or prioritization?
Many marketing organizations have turned to lead scoring to bridge the gap between marketing-generated leads and sales--to cut down on the "noise makers" and surface the prospects with the highest propensity to buy. However, while lead scoring does identify the best and worst leads, it leaves a lot to be desired.
Enter Big Data
The new era of sales and marketing is less about the raw data and more about insight. The best sales and marketing organizations are beginning to apply predictive analytics to all that is knowable about customers and prospects, identifying patterns and serving up those insights to their sales reps. To avoid missing the window of opportunity with marketing-generated leads, marketers should consider big data strategies to optimize their lead generation efforts.
There is an immense amount of data available online that can be analyzed to determine buyer intent. Instead of passing over leads once they reach a certain score or threshold, a big data strategy could help marketers identify which leads are most likely to purchase a company's products or services based on a set of inputs rather than a simple lead score.
As an example, if your contact at a company has downloaded several whitepapers and watched a few videos, a lead score may indicate that he or she is ready to be reached out to by a sales rep. But what if you knew that that company just declared bankruptcy? How likely is that company to invest in new products or services? It doesn't make sense to dedicate resources to that lead because it is unlikely to convert.
After implementing a big data strategy, one of our customers was actually passing off fewer leads to its sales team. At first glance, this would be viewed as a failure. However, the leads that were passed over were converted at a higher rate, and marketing was able to cut the volume of leads sent to sales by nearly 50 percent--only sending the prospects likely to convert.
Big data and predictive analytics can help any company with lead strategy, taking scoring and prioritization to the next level and identifying new opportunities to bridge the sales-marketing gap once and for all.
Amanda Maksymiw is the content marketing manager for Lattice Engines, a big data for sales and marketing company in Boston. She is responsible for setting and managing Lattice's content marketing and social media strategies including creating, producing, and publishing engaging content.