Snap Chart

Where Lead Generation Goes Wrong, and How to Right a Faltering Process

Many CRM systems are bloated with poor-quality data and unqualified names.

Snap Chart

Where Lead Generation Goes Wrong, and How to Right a Faltering Process
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Look inside the CRM system of an industrial company and you’ll probably find that a significant share of leads haven’t been worked on, or even examined, by the salesforce. Of the leads that sales reps have pursued, a large share likely have been disqualified. Many companies struggle to record, manage and track leads effectively, but the lead generation process can be strengthened.

For example, one large B2B company found that its salesforce worked on only about half of all leads generated, and fewer than 15% of the worked leads became active, for a paltry 1% final conversion rate. A survey of sales reps revealed two main reasons for the gaps: poor data quality and insufficient prequalification. The company used software to improve data quality and install an artificial intelligence–based qualification algorithm. The algorithm prioritized leads in each postal code, which informed more effective territory coverage. The new model helped sales reps double conversion rates relative to cold calls.

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