What You Should And Shouldn’t Be Measuring To Determine Success

Marketers who aren’t sure of what they’re measuring are building on a shaky foundation.

What You Should And Shouldn’t Be Measuring To Determine Success
[Photo: Flickr user Sonny Abesamis]

Mistaken measurements can have disastrous effects.


NASA engineers failed to convert from English to metric measurements in 1999 and lost the Mars Climate Orbiter. Polar explorer Falcon Scott miscalculated how much food his crew would need on their 1910-1912 expedition to the South Pole and never returned. Whether you are embarking on an exploration or trying to grow a business, measuring correctly is key.

One of the greatest challenges facing marketers today is knowing what to measure. The digital revolution created a flood of data that has the potential to yield valuable insights–if it is managed and measured effectively.

Unfortunately, most marketers fail miserably on this count. But there are a number of best practices they can use to get the most out of their data.

1. Product-market Fit

There are an infinite number of ways to splice and dice data. Do you measure pageviews? Leads? Conversions? Engagement? Likes? The first step is to figure out what metrics your company relies on to survive and succeed and the ones it doesn’t. This will differ depending on the stage of a company.

For example, early stage companies should be focused on identifying product-market fit. A good strategy is to identify three to five actionable metrics that lead to conversion, and bear down on those.

Angel Investor Dave McClure defined these metrics as “acquisition, activation, retention, referral, and revenue.” Basically, which metrics reveal how you attract new users, whether they use the product, keep using the product, tell others about the product, and finally, generate revenue.


These metrics aren’t the same for every product, but activation and retention are the most useful when looking at product-market fit. Activation could mean creating a first photo gallery for one company, and an app download for the other. Retention can be gauged by anything from number of shares per month to recurring payments.

Once these metrics are identified, companies should create a plan that measures results versus goals. It is also important to track those trends over time, and calculate how progress in each individual metric impacts the overall business.

2. Revenue-centric Marketing

Companies that have already achieved product-market fit should be focused on the ultimate goal: how to generate the most revenue in the shortest amount of time.

Seventy-seven percent of CMOs at top performing companies indicate that this is their most compelling reason for implementing automation. Marketers should focus on metrics that directly contribute to the sales pipeline, conversions, revenue, and profits.

Knowing what to measure is really about asking the right questions. How do we generate more quality leads? Where do the most valuable leads come from? What increases the lead-to-conversion ratio? What shortens the sales cycles? How do we increase our win rate?

The best way to do this is to work backwards. Companies should look at their happy, paying customers, and then “reverse engineer” the revenue cycle to figure out what got them there. This enables marketers to track and respond to which campaigns generate the highest quality leads. It also enables them to identify which metrics lead to the greatest ROI. If 100 new website visitors don’t ultimately lead to revenue, it is not a valuable metric to measure. If lead nurturing programs lead to a 12% boost in revenue, they should be expanded.


Simply put, revenue-centric marketers should look at metrics that reflect value, reach, conversion, velocity, and return. This means looking at what drives the best demand and how to properly score and prioritize leads. It means understanding the customer acquisition to cost.

If opportunities are getting “stuck” in the funnel, it means figuring out the best tactics to increase their conversion. It also means ensuring that the entire organization is on the same page, and committed to the same metrics and goals. Marketing and sales teams have to work together to optimize their results.

3. Measuring The Right Things

Part of knowing what to measure is knowing what not to measure. Marketers too often go for “vanity metrics,” such as social likes, that stroke their egos. These may look impressive, but they aren’t related to core business objectives.

Another common measurement mistake is to focus on quantity instead of quality. This often happens with sales leads. The number of leads in your sales funnel is not important if they are not converting, and an endless succession of low-quality prospects can quickly cause tension between marketing and sales teams.

4. The Proverbial Needle

Data has completely transformed the way businesses operate. Marketing used to be more of an art and depend on intuition. Now in today’s data-deluged world, it is more of a science. Any marketer that hopes to succeed has to make data and analytics an integral part of their strategy.

But a large gap exists between recognizing the importance of data and effectively leveraging technology in order to get the most out of it. A whopping 85% of business-to-business marketers using marketing automation platforms in 2014 feel that they’re not using them to their full potential. Sixty-one percent of marketing leaders cited collecting and managing data as their top business challenge, and 59% identified human error as the primary cause of poor data quality.


Marketers that don’t know what to measure are searching for a needle in a haystack, except they don’t know what they are searching for.

Fundamentally, understanding what to measure boils down to understanding the business itself. You have to know who your ideal customer is, why and how they use your product, and what will keep them doing so. These are things every marketer should know.

Sifting through the deluge of data requires focus of vision and a clear sense of purpose. When considering what metrics to measure, only one question matters: does this have a substantial impact on the business? If the answer is yes, it’s worth paying attention to. Everything else is just hay.

Doug Camplejohn is the CEO and founder of Fliptop, a leader in Predictive Analytics applications for B2B companies. Before Fliptop, Doug founded two companies, Mi5 Networks and Myplay, and also held senior roles at Apple, Epiphany, and Vontu.