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Use Case

Lead Scoring

Automate scoring of leads based on where the lead is in the funnel, expected value, and how the lead was acquired.

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Business Problem

One of the main roles of marketing is to generate leads and send them to sales to close. But not all leads are equally ripe for closing and if sales receive too many poorly qualified leads too often, it leads to tension between the departments. Lead scoring helps defuse that tension by ranking leads according to criteria that indicate the prospect’s readiness to purchase. It reduces noise in the qualified leads (QL) pool and ensures that sales route the lead according to pipeline goals.

For lead scoring to work, marketing and sales must arrive at a model for defining a qualified lead, including agreement on the data points that go into the model. The problem is that data points such as demographics and number of website visits could come from multiple sources and their relative importance could be in constant flux. Marketing and sales can spend months or entire quarters trying to identify the most useful data points and even longer massaging the data in spreadsheets.

Alteryx Solution

A company with a medium to high volume of leads can’t process and score them all manually. Automated workflows perform the lead scoring by collecting signals from a variety of sources and ranking the signals according to the company’s criteria.

With Alteryx, you can:

  • Automatically pull in engagement and demographic lead data from multiple sources. More data sources mean more flexibility as lead scoring process matures and scales.
  • Apply a rules-based model directly within a workflow, eliminating need to outsource analytics to a third party. This dramatically reduces costs and improves turnaround for lead scoring process.
  • Once lead scoring rules are applied, you can automatically push leads back into database or Customer Relationship Management (CRM) platform to apply prioritization business rules, as well as provide daily reporting on generated leads.

Lead Scoring Designer Workflow

Lead Scoring Workflow

1- Prep/Blend:

Gather data from multiple input sources (MAP and CRM) related to lead engagement and demographics

2- Variable transformation:

Flatten and transform data to create relevant/impactful variables for lead scoring

3- Lead Scoring:

leverage machine learning models to determine which leads are most ready to enter the buying cycle

4- Output Reporting/Sharing:

Push lead score and supplemental information back into MAP and database to support lead SLA creation and follow-up as well as reporting of number of qualified leads generated each day

Additional Resources

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Starter Kit for Salesforce

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Starter Kit for Marketing Analytics

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Lead Routing

Transform Your Analytics

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