To be able to know which of your leads and prospects are most likely to buy your product is to have the leg up on your competitors.
The most effective way to predict likelihood to buy is with machine learning. You can take people just like that lead or prospect you're looking at–similar hobbies, income, lifestyle, and more–and use their historical actions to predict whether or not your they'll take that leap and convert.
Faraday makes predicting likelihood to buy for both individuals and geographies intuitive & easy, and delivering it to any channel in your stack a breeze.
With likely buyer predictions in Azure SQL, you'll give your team the ability to focus on only those people that are most likely to buy, meaning time is never wasted on bad fits.
Follow the steps below to get your likely buyers predictions into your Azure SQL account.
In this guide, we'll show you how to:
- Organize your customer data into cohorts
- Describe predictive models for likely buyers with outcomes
- Deploy likely buyers predictions to Azure SQL using Pipelines
You'll need the following cohorts available in your Faraday account:
- A cohort representing your customers — or create one first
- Azure SQL — or create one first
Now you'll create the prediction objective(s) necessary to complete this use case with Faraday.
Outcomes use machine learning to predict whether or not people will exhibit a certain behavior.
Let's make an outcome for likelihood to buy.
- In the navigation sidebar, choose Outcomes.
- Click the New outcome button.
- Fill out the form:
- Click the Save outcome button.
Faraday will do some magic in the background, so you can proceed with the rest of the instructions. When your outcome is done building, you'll get an email, and you can review your outcome.
Now you'll configure the pipeline that deploys your predictions to azure_sql_server.
- In the navigation sidebar, choose Pipelines.
- Click the New Pipeline button.
- Fill out the form:
- Click the Save pipeline button.
Your pipeline will start building in the background. You can proceed immediately with the next set of instructions.
- In the Deployment area, find the Azure SQL module and click Add.
- Fill out the popup:
- Provide the specified parameters for Azure SQL.
- Click Next.
- Choose the Hashed option.
- Click the Next button.
- Expand the Filter section of Advanced Settings
- Click Add payload filter
- From the dropdown, choose an outcome from the list
- In the dropdown on the left, choose Greater than or equal to
- On the right, enter the value 86.
- Click Add another condition.
- In the dropdown on the left, choose Less than or equal to
- On the right, enter the value 100.
- Skip the "Advanced Settings" by clicking the Finish button.
- Click the Finish button.
- Click the Test deployment button and confirm the results meet your expectations. Faraday will finish building your pipeline in the background. When it's done, you'll get an email—return to the pipeline and click the Enable pipeline button to activate it.
With your pipeline deployed, your likely-to-buy scores are loaded into Azure SQL Server and ready to be plugged into your favorite marketing activation platform, where you can kick off a campaign to target only the best fits.
🔒 It's a best practice to permanently delete any file that contains personally identifiable information (PII) after use. Any deployment from Faraday that is unhashed contains PII, and should be deleted after uploading it to your destination for security purposes.