Revenue Engine Analytics - Part II

In Part I we concluded that three things matter about a revenue engine:

1. Power

2. Efficiency

3. Reliability

Power is thrust.

Is there enough prospecting going on? Are we creating MQLs on the back of that? Is sales accepting and working these leads? Are we generating enough pipeline and forming a funnel? Is the funnel moving fast enough?

All a question of force and thrust. All a matter of effectiveness.

Efficiency measures how resource hungry the engine is. Do you need 50 initial meetings to write up a single good opportunity? Are the MQLs and SALs so far apart in conversion % (and widening) that you need to intervene?

Reliability tells us how consistent the operating profile is. If your pipeline generation month-to-month looks like this, you have a consistency problem:

• January: $1.2M

• February: $150K

• March: $75K

• April: $250K

• May: $1.4M

• June: $150K

This chunky discontinuous flow will cause problems down funnel.

The same problem happens all across the revenue engine — lead generation, lead conversion, opportunity generation, pipeline development… not executed optimally and consistently to ensure a high-performance revenue engine.

What Are We Measuring?

Agreeing on clear definitions before measuring anything is vital for successful revenue intelligence implementation in your company.

Here are the key definitions you and your team should discuss and align on:

Core Financial Metrics

• Revenue: The total income generated from sales of goods or services.

• Bookings: The total value of new contracts signed in a specific period, even if revenue recognition hasn't started yet.

• Billings: The total amount invoiced to customers in a given period, even if payment hasn't been received yet.

• Annual Recurring Revenue (ARR): The value of recurring revenue normalized to a one-year period. Crucial for subscription-based businesses.

• Customer Lifetime Value (CLTV): The predicted total net profit from the entire future relationship with a customer.

• Customer Acquisition Cost (CAC): The total cost of acquiring a new customer, including marketing and sales expenses.

• Churn Rate: The percentage of customers or revenue lost in a specific period.

Sales Pipeline Metrics

• Lead: A potential customer who has shown some interest in your product or service.

• Marketing Qualified Lead (MQL): A lead deemed more likely to become a customer based on certain criteria (e.g., engagement with marketing materials).

• Sales Qualified Lead (SQL): A lead further qualified by the sales team as a potential customer ready for direct sales engagement.

• Opportunity: A qualified lead that has entered the sales pipeline with a potential deal value.

• Win Rate: The percentage of opportunities that result in closed deals.

• Sales Cycle Length: The average time it takes to close a deal from the initial opportunity stage.

• Average Deal Size: The average value of closed deals.

Additional Metrics

• Upsell/Cross-sell Rate: The percentage of existing customers who purchase additional products or services.

• Net Promoter Score (NPS): A measure of customer loyalty and satisfaction.

• Quota Attainment: The percentage of sales reps who achieve their sales targets.

Once these definitions are agreed upon, ensure you have a system in place to accurately track and measure these metrics. Then, you can leverage this data to gain insights, make informed decisions, and drive revenue growth for your company.

Now we can start analyzing the performance (and health) of our revenue engine.

How Are We Measuring?