Long-term profitability is the only growth metric that matters

It's time to change how you measure success

Your company’s one metric that matters (OMTM) shouldn’t be return on investment (ROI), return on ad spend (ROAS), net promoter score (NPS), brand affinity or one of the other sophisticated-sounding acronyms marketers use to gauge success.

Your company’s one metric that matters should be long-term profitability.

Put another way, your business should be singularly focused on how much money it can return to its owners, investors and shareholders. Sounds obvious, right?

You’d be surprised: A majority of Fortune 500 and Silicon Valley startup marketing budgets aren’t optimized for long-term profitability.

Instead, budgets are often optimized for secondary or upper-funnel metrics. Besides tracking ROI, ROAS, NPS and brand affinity, many marketers monitor key performance indicators (KPI) like net revenue, customer acquisition cost (CAC), cost per thousand (CPM) and brand recall — none of which directly correlate with long-term profitability.

In fact, many brands’ marketing departments frequently omit the word “profit” all together from the line items and KPIs in their monthly performance reports.

A good way to think about the futility of the KPI status quo is the following fictional scenario, which reflects the marketing and advertising playbooks of a shockingly large segment of American businesses: Main Street Shoes spends $100 on a Facebook ad campaign to promote a new line of sneakers to Jack and Andrew. As a result of the retailer’s Facebook ad campaign, Jack and Andrew each spend $100 to buy new sneakers.

By nearly all conventional KPIs, Jack and Andrew are equally valuable consumers. But, through the lens of long-term profitability, Jack and Andrew represent strikingly different values to Main Street Shoes.

That’s because Jack lives five minutes from Main Street Shoes, buys new shoes twice a year and spends three hours a day scrolling through his Facebook feed. Andrew, on the other hand, lives one state away from Main Street Shoes, buys new shoes just once every 18 months and only spends one hour a week scrolling through Facebook.

As a result, Jack and Andrew have substantially different lifetime values (LTV), a metric calculated by examining customer demographics, psychographics, geography and buying behavior. In terms of LTV, Jack — who lives closer to Main Street Shoes, buys shoes more often and goes on Facebook more frequently — is exponentially more valuable than Andrew.

Armed with this individualized data, Main Street Shoes can now optimize its Facebook advertising for LTV by increasing its willingness to pay (WTP) for people who look like Jack, instead of people who look like Andrew.

Within a few months, Main Street Shoes will realize a profit because of its decision to optimize for long-term profitability and LTV instead of short-term returns.

The benefits of optimizing for long-term profitability and LTV aren’t just hypothetical. At WITHIN, the performance branding company I founded, we separate ourselves from our competitors because, more often than not, our competitors are looking at the wrong KPI.

As a result of our reputation for profitably scaling businesses, brands like Nike, Shake Shack, Spanx and Hugo Boss, among other Fortune 100 companies and VC-backed startups, have chosen WITHIN to manage their North American performance marketing budgets.

One brand we partner with, subscription coffee service Trade, has been an exemplar of adopting long-term profit optimization.

After examining Trade’s customer data, we found that customers who used a Chemex to brew their coffee had 50% higher LTV than those who brewed with a French press. After cross-referencing Trade’s customer data with a third-party shop, we also found that, all else equal, men had a 20% higher LTV than women.

As a result of these insights, we increased our WTP for men on Google, Facebook and other ad platforms by 20% relative to women and, through the creation of custom conversions, were able to optimize media mix toward website visitors more likely to use high-end brewing equipment. Profits soon climbed.

At the same time, Trade incorporated our data analysis to learn how and why its user experience led to widely disparate customer LTV’s. By improving the website experience for lower LTV users (i.e., sourcing coffee better suited for French press brewers), Trade was able to sell more subscriptions at larger profit margins.

Another way we boosted Trade’s long-term profitability was by offer-testing discounts for first-time customers of 15%, 30% and 50%. Using Facebook ads, we offered 15% discounts to some customers, while offering 30% and 50% discounts to others.

Over time, we discovered clear patterns in the data: Customers who received the richest offer, 50%, had the highest conversion rate and lowest CAC, but also the lowest LTV. In other words, 50% discount recipients were more interested in the discount than the coffee. Without discounts, they churned.

The 15% discount, on the other hand, didn’t drive enough demand.

The 30% discount, we realized, was the sweet spot for maximizing net profit. The CAC’s were tolerable and the LTV was nearly as good as the 15% cohort.

Had we simply measured ROAS or CAC, Trade Coffee might have continued to advertise 50% discounts — since that offer generated the most sales at the lowest cost.

Instead, we partnered with Trade to optimize for LTV (which subsequently grew by 200%) and profits soared.

Like we did with Trade, we analyzed the long-term buying patterns of the e-commerce pet food company PetFlow to optimize their marketing and advertising programs for LTV and long-term profitability.

PetFlow sells dog and cat food, a highly competitive, commoditized industry with razor-thin margins. To maximize profitability, we analyzed the profit margins of every brand and product on PetFlow’s website, as well as how competitive the market was for those brands and products.

We then cross-referenced the margins and competitiveness ratings with PetFlow’s customer buying behaviors, including whether buyers signed up for auto-ship subscriptions.

We turned that data into a matrix of combinations, which has since allowed us to predict the LTV of every PetFlow customer at the moment they make a purchase.

After a new customer checks out on PetFlow, their data is passed through an LTV-prediction algorithm and into Google and Facebook’s advertising platforms. This way, Google and Facebook can allocate ad spend in real-time toward the most profitable Google search terms and Facebook audiences. Just like with Trade Coffee, PetFlow’s customer LTV and projected long-term profitability has soared.

In the hyper-competitive world of pet food, where companies regularly go out of business, optimizing for LTV has allowed PetFlow to not just survive, but thrive.

It’s important to maintain strong data analysis principles when you start diving into your customer data, as the wrong interpretation can do just as much harm as the right interpretation does good. However, we’ve never conducted an analysis that didn’t reveal a window of opportunity. Over time, those opportunities add up.

It’s time for the rest of the advertising and marketing industries to apply these same lessons to their companies and clients. Until then, they are leaving money on the table by using outdated KPIs that don’t directly tie into their most important business health metric: long-term profitability.