When you change your lead scoring and lead delivery using predictive analytics, don’t forget to train sales reps to think different as well. It’s well-known that salespeople don’t qualify leads, they disqualify them. The more leads provided, the faster leads seem to get disqualified and bounced back in the holding queue. Reasons could be due to lack of data (such as invalid or no phone number), bias (“can’t possibly be a large enough deal”), or simply attitudes (“the more I close out, the sooner I will find something that works”). This approach churns through leads, resulting in significant cost of acquisition and processing resources – both human and machine. If your reps’ closeout rate is 50%, your net cost is twice the initial cost! Marketers and sales leaders often respond by finding ways to deliver a greater number of qualified leads faster. Predictive models are often used to score and deliver ideal prospects from a larger universe into outbound lead gen programs. Predictive models increase productivity and the ROI of achieving specific outcomes such as getting appointments or sales, moving newly-acquired customers into repeat customers, and improving cross and upsell. But caution: predictive models may produce leads with characteristics that are …Read More
Tag Archives: outbound calling
What to do when your sales reps think good leads are bad
Inside sales teams are at it every day, making thousands of calls to prospects, seeking an appointment or a sale. They are given scrubbed lists with contact names, job title, phone numbers and a good luck pat. On the back end, managers track calls, appointments and sales. The cycle continues when reps deplete their assigned leads and it starts over again. There are times when this well-oiled prospecting machine can under-deliver – and you may not be aware. But there are easy fixes. Here we explore three cases, and discuss how to overcome these challenges. TESTING NEW MARKETS: When looking at sales data, you may find strong traction among companies that don’t fit the best customer profile — or at least what the rep thinks is the best profile. This finding is usually uncovered by in-depth profiling, micro-segmentation or modeling analysis. These customers may not be among the largest customers, but you find that they purchased numerous units of products that fit specific needs. As an example, say you are selling technology products, and religious institutions are not known as leading technology buyers. But recently we came across a church buying hundreds of iPads for one of its programs. This is opportunistic entry into a market if other religious institutions have similar programs. What you can do: …Read More