Spot your best leads

Dagic uses predictive analytics to discover best opportunities to improve your sales team’s productivity and increase sales

Poor quality leads steal your sales team’s finite time and energy

No buying intent
Poor fitment
Stale leads
Competitors

High quality leads get buried between poor quality leads

Too many poor leads adds pressure on the salesreps
Delayed first contact significantly reduces the probability of conversion
Some of your potential leads might need persistent follow ups
Subtle opportunity indicators are hard to discover

Difficult to spot anomalies

Not finding sales errors when they occur are hard to fix and will lead to business loss
Sales rep's skill gaps can lead to negative outcomes

Predictive lead scoring

Lead forecast

Dagic uses machine learning models to learn conversion patterns from your customer's data (e.g. demographics, firmographics, demo usage, engagement metrics etc). The trained model is used to predict the conversion probability of your leads and categorize them as hot, warm and cold opportunities. This will enable you to reach your best a.k.a hot leads faster.

Know about your leads

Lead insights

Lead name

Category

Score

Insights

HDFC Bank

hot

97.0

from chennai banking tried demo

Kotak mahindra

warm

77.0

avg call engagement 8.5 mins referral

City union Bank

cold

31.4

inbound 2 channels did not try demo
Dagic explains the top factors influencing the lead prediction, so your reps will be equipped with additional insights when they talk to the leads. Dagic also computes a look-alike score by matching leads with your customers helping the sales reps to prioritise better.

Spot anomalies when they occur

Anomalies

Lead name

Salesrep

Score

Anomaly

Pipedrive

Anish Kumar

98.1

marked as no fitment

Zoho CRM

Kathy Walker

7.0

marked as prospect

Close.io

Kathy Walker

92.1

did not attempt to reach enough times

Alerts the managers real time about the anomalies so that they can coach effectively and reduce business losses.