Predict every behavior

Remarkable customer experiences produce remarkable customers.

Likelihood to buy, convert, churn, and more

How likely is the customer to exhibit a behavior or take an action that you’ve seen before?

Docs →

Docs

# LEAD SCORING
# First register your data to produce event streams
curl https://api.faraday.ai/datasets --header 'Authorization: Bearer $YOUR_API_TOKEN' --json '{
  "name": "Signup",
  "identity_sets": {
    "shipping": {...}
  },
  "options": {
    "type": "hosted_csv",
    "upload_directory": "signup_data_files"
  },
  "output_to_streams": {
    "signup": {
      "data_map": {
        "datetime": "created_at"
      },
      "value": "total"
    }
  }
}'

curl https://api.faraday.ai/datasets --header 'Authorization: Bearer $YOUR_API_TOKEN' --json '{
  "name": "Transaction",
  "identity_sets": {
    "shipping": {...}
  },
  "options": {
    "type": "hosted_csv",
    "upload_directory": "transaction_data_files"
  },
  "output_to_streams": {
    "transaction": {
      "data_map": {
        "datetime": "created_at"
      },
      "value": "total"
    }
  }
}'

# Now organize your customer data into cohorts
curl https://api.faraday.ai/cohorts --header 'Authorization: Bearer $YOUR_API_TOKEN' --json '{
  "name": "Leads",
  "stream_name": "signup"
}'
curl https://api.faraday.ai/cohorts --header 'Authorization: Bearer $YOUR_API_TOKEN' --json '{
  "name": "Customers",
  "stream_name": "transaction"
}'
# Next, declare your prediction objectivesfalse
curl https://api.faraday.ai/outcomes --header 'Authorization: Bearer $YOUR_API_TOKEN' --json '{
  "name": "Likelihood to convert",
  "attainment": "$CUSTOMERS_COHORT_ID",
  "eligible": "$LEADS_COHORT_ID"
}'
# And finally complete your pipeline to deploy
curl https://api.faraday.ai/scopes --header 'Authorization: Bearer $YOUR_API_TOKEN' --json '{
  "name": "Lead scoring",
  "population": {
    "include": [
      "$LEADS_COHORT_ID"
    ]
  },
  "payload": {
    "outcome_ids": [
      "$LIKELIHOOD_TO_CONVERT_OUTCOME_ID"
    ]
  }
}';

Dynamic prediction

Timeline matters

Patterns that predict behavior in the early stages of a customer journey eventually stop working and new ones take over. Only Faraday uses time-linked model ensembles to tell the true story.

Example UI from the Faraday dashboard the performance of a propensity outcome

Algorithmic freedom

We'll pick the algorithms so you don't have to

Faraday will detect and select the best tool for the job, from time-tested classics to cutting-edge GenAI.

Example UI from the Faraday dashboard showing the top predictors for a given propensity outcome, along with directionality

Everything you need to predict customer behavior, built-in

All the power, flexibility, and data you need to ship fast.

Built-in consumer data

Humans included.

Get more accurate predictions—and avoid the dreaded cold-start problem—with 1,500+ consumer attributes on nearly 240 million adults.

Browse included traits →

AI safety

Predict wisely.

Explainability, privacy, bias management, and transparency: find your balance between power and fairness.

Responsible AI with Faraday →

Automated feature engineering

Got data? We'll use it.

In addition to its built-in consumer data, Faraday can find patterns in whatever first-party data you have for even more accurate predictions.

Using first-party data →