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Lead scoring

Challenges

Lead scoring is a sales and marketing methodology for ranking ‘leads’ or prospects to determine their sales-readiness and potential value to the business; the score helps determine which prospects to engage with, how and when in the buyer’s journey.

A major challenge in lead scoring is capturing sufficient rich behavioral insights into each prospect to drive a meaningful score. Without high-quality behavioral data, many lead scoring approaches resort to basic ‘Lamb or Spam’ techniques or crude rules-of-thumb. Poor lead scoring approaches hamper marketing effectiveness and sales efficiency.

Opportunity

Effective lead scoring starts with identifying the prospect across all of their touchpoints, channels and devices. Having uniquely identified the prospect, the next step is to start capturing as much behavioral ‘signal’ from the prospect as possible – which pages they have visited, their progress through a trial experience, even how far down a whitepaper or how far through a tutorial they reached. This behavioral data can then be used to calculate an accurate rules-based score for the prospect. Moving beyond this, predictive lead scoring replaces the hard-coded scoring rules with machine learning, to generate a predictive model based on the behavioral data. With predictive lead scoring, we can identify high-value prospects earlier in the buyer’s journey, and our lead scoring can learn as new patterns of behavior are uncovered.

Why Snowplow

Snowplow provides you with incredibly rich and granular behavioral data across multiple platforms (including web, mobile and AMP) – both in your data warehouse and in a real-time event stream. Snowplow also provides you with a rich set of user identifiers allowing you to resolve diverse anonymous usage into a single prospect as soon as they have completed your call-to-action.

Putting this all together, you can custom-build the lead scoring system that makes sense for your business and your buyer’s journey. You can even create a lead-scoring system that learns from its mistakes via machine learning techniques.

Most lead scoring systems will be based on crude determinations of customer value. With Snowplow, you can implement Single Customer View alongside your lead scoring and use a 360° view of your customer and their lifetime value to drive the correct scores for future prospects.