Prioritize prospects: Lead scoring

How to prioritize the hottest prospects?

GOAL

Adapt the treatment of the leads according to the imminence of the act of purchase.

ACTIONS

For hot leads, proposal for immediate recall, priority processing of requests for information, proposal for exchange via the Chat.

For the medium term leads, information proposal, attempt to recover the email address, breeding.

PREDICTIVE SCORING

Using the DataLead module and its algorithms by integrating navigation data (number of pages visited, time spent, web browsing ...), the geographical origin of the connection and the origin of navigation of the client.

DataHub AfterData: integration of data on habitat type and standard of living.

RESULTS

  + 28% conversion rate
  - 42% recall after a competitor purchase

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Predict customer appetite: product recommendation

How to increase the number of contracts per customer?

GOAL

Develop multi-equipment rate and option sales.

Limit the commercial solicitation of customers by only communicating on offers with a strong palate.

ACTIONS

Weekly up-selling campaigns targeted at customers with a peak of appetite for a product and no more than a coefficient of solicitation.

Scoring of the optimal communication channel.

For sales consultants, alert (push product) directly on the customer record in the CRM.

PREDICTIVE SCORING

Use of the DataSell module and its algorithms by integrating the socio-demographic data of the customers (anonymized), the sets of the customer interactions and the contractual data.

DataHub AfterData: Exploring data on the probability of marriage and birth.

RESULTS

  + 20% up-selling
  - 16% of the attrition rate

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Anticipate customer termination

How to limit the starting rate to competition?

GOAL

Decrease the number of terminations suffered.

ACTIONS

Loyalty campaigns: email and / or phone.

For sales consultants, alert directly in the CRM.

PREDICTIVE SCORING

Use of the DataChurn module and its algorithms by integrating the socio-demographic data of the customers (anonymized), the sets of the customer interactions and the contractual data.

DataHub AfterData: exploitation of data on the probability of change of vehicle and the risk of moving.

RESULTS

  - 21% of the attrition rate

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Identify frauds

How to automatically detect suspicious behavior?

GOAL

Identify market abuse early.

Limit false positives.

Historise precisely the instruction of the fraud.

ACTIONS

Real-time analysis of all transactions.

Detailed explanation of each criterion suggesting fraud.

Alert and reporting by mail.

PREDICTIVE SCORING

Using the DataFraud module and its algorithms to analyze the investor profile, the behavior of each value and the unusual variations.

DataHub AfterData: exploitation of financial news and Euronext daily quotations.

RESULTS

  97% detection rate
  Less than 5% false positives

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Sales forecast

How to anticipate orders and production?

Sales forecast conditions production, storage, and orders. Overestimating sales leads to losses and storage costs. Underestimating sales represents a shortfall and a risk of loss of customers.

Artificial Intelligence algorithms AfterData can predict quantities sold through promotional campaigns, market trends, competitive actions, weather and history of consumption.

Potential ROI: 20% decrease in forecast errors and 30% decrease in unsold inventory

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