Funnel Analysis and Conversion Metrics in SQL

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Funnel analysis crops up everywhere. It can be used to analyze success of sales and marketing teams, a customer's progression through a website, or the efficiency of a recruiting pipeline. A famous example in the startup world is David McClure’s AARRR (pirate) framework for product metrics. In general, it is a useful approach to analyzing just about any process that involves multiple steps and attrition.

Some Example Data

Let’s walk through an example involving some mock sales data. In our sales model, we have the following progression of events:

1. Lead - a potential client has been identified
2. Marketing Qualified - the marketing team has determined that a potential client is a good fit, based on broad characteristics
3. Sales Qualified - the sales team has determined that potential client is a good fit, based on conversations with the client
4. Negotiated - the sales team has discussed pricing and features with a potential client
5. Customer - the sales team has closed new business with client
6. Renewed - the client has renewed their contract for the next period

The particulars of a funnel can vary. In the actual Salesforce schema, you will likely be looking at the “opportunity_history” table, and examining steps with names like “contacted,” “qualified,” and “won.” What is most important to making this model work is that the expected value of a client increases as they progress down the funnel, while the raw number of clients decreases.

We’ll use a table with the following fields:

1. account_id - a unique identifier for client accounts
2. date - date on which an event occurred
3. event - type of event, from the above progression