Augmented Lead Scoring

Well known San Francisco based enterprise company built a lead scoring engine to predict the propensity to buy and personalize their sales efforts.

Software
Sales
170,000

rows of data

2 days

time to value

86.3%

prediction accuracy

+11%

increased conversion

Background

Determining the value of each lead, including likely future conversion and spending, is a vital factor in deciding where to aim personalized sales efforts. Conversion models determine the likely revenue each individual customer will generate over the entire relationship and time it takes to convert them. Allowing sales reps to focus their efforts on those likely to be most revenue generating eventually closing deals faster.

The company's Growth team was looking to build predictive models for lead conversion & scoring. However, they were not AI experts and in-house AI team were already backlogged in several requests.

Consultancies didn’t were tough to find as no one understood the business well. Lead scoring plug-ins on their CRM were never accurate. That’s when they turned to Obviously AI.

The Solution

The company conducted extensive market research and chose Obviously AI’s predictive analytics platform for their needs. 

The Growth team used Obviously AI’s platform to train a model by using historical data of won / lost accounts and answered the following questions:

1. Which leads are most likely to convert in next 3 and 6 month window?
2. Created what-if scenarios to model how leads are likely to convert.

The Results

The company increased conversion rate by 11%.

Obviously AI’s platform allowed the Growth team to build the AI model within 2 days, versus 3 months waiting time proposed by their in house data team, and at a significantly lower cost.

Most notably, the company empowered its existing non-technical team with the capability of building state of the art AI predictive analytics models, without the need for an on-call data scientist.

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