Product Management Financial Impact — the six variables that matter

As a product manager, you have two masters to serve. On one hand you need to be adding value to customers by solving real problems. Everyone knows this. On the other, you are in the business of making money. Everyone knows this too — but what does that actually mean?

This means that you need to sustain a proportionate focus on building and optimizing your business model. Which in turn means that you need to think about and make decisions explicitly for the purpose of driving the operating economics of your company. Thinking just in terms of customer features is not enough.

Every product manager knows they should be making great products for their customers. If you aren’t meeting a customer need, you aren’t creating value. But most PMs don’t, or can’t, articulate a clear rationale about what business impact their feature priority choices will achieve

If you ask a product manager “why are you building this feature” inevitably you will hear some form of “because it meets some important customer need”. Right answer! If you ask again though, “why this feature” — as in why this particular one over the others that are also meeting worthy customer needs — you will probably hear something about prioritized roadmaps based on breadth of impact or ease/speed of development —also correct!

But…what you ideally should hear is “because it meets this important need and it will affect our business in this important way. A vague notion that it will help sales or lift NPS isn’t enough. You need to do the work to understand how and why some product initiative is a good investment.

I’m not suggesting that every feature has a business case behind it. Far from it. Detailed business cases for every decision is a waste of time and creates a false sense of precision and inevitability. But what I am suggesting is that epic-level capabilities have an articulated connection to some important economic lever of the business — and that there is some logic and a basis for believing that it will indeed have some affect. In other words your articulation should be a hypothesis: We believe if we do X, then Y will happen, and the impact will be Z.

Some companies do a pretty good job of clearly connecting feature building to business objectives — especially those that have an OKR oriented approach. But I think we can all agree that most software companies don’t do this well at all. They blindly build from their backlog with only the occasional glance at their pricing, feature packaging, selling motion, support efficiency, commercial terms, and other levers that affect the operating economics of the business.

Background: The Essential Metrics

Knowing these big six metrics will give you the starting framework for understanding your company’s business model and seeing where you can/should focus product investments.

As a product manager, the first step to making good decisions is understanding terminology and knowing why certain metrics matter to an enterprise SAAS company. You should be intimately familiar with all these terms and, off the top-of-your-head, know where your company is right now. Here’s a test for all you CEOs — go talk to a few PMs and ask them for your company’s specific number for each of following six metrics. I bet you’ll be disappointed in what you hear.

Now obviously, direct-to-consumer, hardware products and transactional business models have very different economics and associated metrics and B2B SAAS. This article was written with a typical enterprise model in mind — that’s what I know best — but the general concepts still hold regardless of your industry.

The following items are what I consider to be the most essential drivers. You may think that because they are macro level that nothing you do will directly or meaningfully affect them. That is partly true — these are whole-company kinds of things and that there are a million exogenous variables that are outside one one person or team’s control. But it is important to recognize that a series of incremental improvements do matter, and the way to tackle macro problems is to unpack and drill deeper until you get to an actionable level. I will touch on that a bit more after this section.

Annual Recurring Revenue (ARR)

For most B2B software companies, today’s measure of success is best thought of as building an asset in the form of future revenues. This is measured by ARR which perhaps the single most important SAAS performance metric.

ARR is the value of contracted recurring revenue normalized to a one-year period. It excludes one-time items, like implementation fees and professional services. This one measure is so important because it serves as the baseline around which future planning is done — it affects how you think about raising capital, setting headcount, and budgeting. ARR growth rate is the strongest indicator of momentum, which directly influences your company’s valuation multiple.

Gross Margins

Gross Margin is a measure of the profitability of your actual software offering and provides a floor around which you need to manage your operating expenses. Gross margins are highly sensitive to (a) pricing and packaging (b) mix of SAAS and service revenues and (c) achieving economies of scale.

A typical at-scale SAAS company has ~75% margins, which is one of the reasons why investors love these businesses. Once you’ve reached scale, then you could argue that there’s not much optimization to be had, nor much movement in the number over time — and therefore not a useful metric. I won’t argue that point. But for companies and business models that don’t have sustained high gross margins, then this metric should be something to worry about.

EBITDA

Earnings before interest, taxes, depreciation and amortization is a proxy for cash-flow generated by day to day business operations. This is a common profitability metric that excludes items that are affected by financing choices and other ‘non addressable’ items.

The sum of ARR growth rate and EBITDA margins is often referred to as the Rule of 40. For example 20% annual growth with 20% margins = 40. This is an rough equalizer for companies at different stages of maturity (growth maximization versus profit maximization), but a rule-of-thumb is achieving 40 or more is the threshold for high-performance.

You may hear terms like Adjusted or Cash EBITDA — if so, then these figures also exclude one-time items which otherwise might cloud the picture of what the business looks like on a steady-state basis (e.g., deferred revenue, non-cash comp, acquisition related and other one-time exceptional costs).

Customer Lifetime Value — CLV

CLV measures the expected operating profit per customer over their lifetime with your company. CLV is very sensitive to (a) churn and (b) one-time items.

Averages can be misleading for all the key metrics but especially this one. Even if overall numbers look solid, there will be many instances of individual customers who have a negative CLV. This is often a sign of bad discounting practices or those with chronic support problems/dissatisfaction. Likewise those clusters with exceptionally high CLV may have some instructive use cases where they are willing to pay a premium.

CAC Payback

Cost of acquisition (CAC) measures selling-motion efficiency and the CLV/CAC ratio is the most important measure of your overall go to market strategy. This measures the return on investment of sales and marketing efforts and allows you to determine if our growth strategy is working efficiently.

Often there is a lag in the time your sales and market spend translates into in-market results, so it isn’t uncommon to look at prior quarter spend compared to this quarter’s sales. I also like to look at sales/marketing spend per prospect and the prospect to sales conversion rate — to get a sense for how much you directly spent on each new customer and how much was wasted spend.

Net Revenue Retention

Net Revenue Retention is a key metric in any subscription business as it indicates the quality of product and ongoing service you provide. This measure looks at your existing customer base and subtracts revenue from lost customers as well as downsells (i.e., customer stays but changes to a lower-priced offering) — and then adds back up-sells, additional users/licenses and price increases to your existing customer base.

Top performing enterprise SAAS companies have a 120%+ NRR. This means they would continue to grow even if they didn’t acquire any new customers.

Account level churn is also a key metric to look at in conjunction with this as there may be pockets of customers who leave you all together (clearly a serious sign that warrants analysis)

Knowing these big metrics alone will go a long way toward having a sense for how you can affect the business. However, I am sure you recognized that these measures are interrelated and overlapping — basically different aggregated views on same set of underlying details. That is why I like to drill down another layer or two into what I call the drivers of operating economics when evaluating product investment alternatives.

Also, you may have noticed I didn’t put NPS on this list. NPS is an important thing to monitor, but in itself it is not an economic outcome for the business. Rather it is a measure that will have a correlation with or be a leading indicator of the underlying drivers that manifest themselves ultimately inside these big six metrics.

Operating Economics

Identify product investment objectives by decomposing operating economics into operational metrics. The end result is a tree of key drivers, and if the epic you are building doesn’t address one of these directly — ask yourself again why you are building it. You may still have good reasons but make sure you can articulate what they are.

When I say operating economics — I define it as the underlying variables that make up this equation: unit economics times volume drivers — for both net-new and existing customers.

For every operating metric we’ve talked about you can decompose it into a unit * volume equation. Sometimes units refer to price, sometimes costs. Volume sometimes refers to customers, sometimes to transactions.

The key is to look for the customer behaviors that influence unit cost/price or activity volumes — and that is where you make the product connection.

A feature should solve a need → which affects their behavior → which in turn connects to our business by moving some unit or volume variable.

For example, when looking at CAC Payback you start with expected total contribution of a customer over their lifetime and match that with average sales and marketing cost per customer (e.g., we are spending $1 to make $2).

Using our unit and volume framework, CAC Payback starts with yearly customer margin (unit) times avg years lifespan (volume) divided by spend per customer (unit) times number of customers (volume). Each of these variables can be decomposed further: For example, yearly margin is broken down into initial deal size and annual residuals. Initial deal size is made up of the mix of service and software fees. The initial software fees are a function of which package they chose and what discount they received. And so on…

The useful end of the tree is when you start to describe things in terms of customer decisions and preferences. This is where product management comes in.

For example, if CAC is an issue for your company and you are choosing what to build, you should be thinking about things like: Will this cause customers to gravitate towards a bigger day 1 pricing plan; Will this help customers make purchase decisions quicker; Will this help or hinder prospects to self-educate and go through lower cost marketing funnel themselves; etc. There’s a long list of possibilities.

It is worth reiterating, I don’t recommend you start with you company’s income statement and use that to go feature hunting. You should always start with a mindset of solving real customer problems — that establishes the universe of options. Your company’s operating economics profile is what should guide priorities and approaches from within that universe.

I have no doubt that the extra work to connect your feature planning to the economic drivers is worth it. You’ll make better decisions, you’ll have a basis for explaining why you chose one thing over another, and ultimately it will show up in your company’s results.