Everything is measurable in marketing

Leadership must commit the time, people and resources to measure what they ask for.

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One of the most frequent cliches in marketing analytics is that there are things that simply can’t be measured. People will say, “Well, you can’t measure some stuff. It’s intangible. There’s no way to measure branding, the impact of public relations or any more complex forms of measurement.”

To which I say: That is patently untrue, completely false.

Everything in marketing is measurable, from top to bottom, from brand to customer satisfaction to purchases — you can measure 100% of marketing. People mean that not everything in marketing can be measured because they don’t have the budget and resources to measure what they care about.

They can’t measure using the resources available to them, whether time, personnel, hard dollars, or organizational skills. Some organizational constraints prohibit them from measuring effectively, but those constraints are not the same as saying something can’t be measured.

So, let’s clarify these two questions about any given metric to be measured.

First, is it worth measuring or not? If the answer is yes, but only up to a certain point because of resource constraints —and those resource constraints prevent you from a complete measurement — then the actual answer is no. Your organization has decided that it’s not worth measuring that metric to the level of investment needed, no matter how important we think it is as marketers.

For example, something like brand strength is measurable, but it’s expensive to measure. As a result, people will say, “You can’t measure the strength of a brand.” That’s untrue — brand strength is measurable, but companies are unwilling to invest the time, money and people needed to measure brand strength effectively.

The second question we have to ask is whether we can collect the data needed to measure effectively. The further up the marketing operations funnel, the more challenging measurement becomes from a data availability perspective. Revenue? Sales? Those are metrics the CFO can provide, and they’re as certain as anything in business can be. We have total control over those systems and the ability to measure them thoroughly.

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Online and offline measurement

Marketing automation makes it straightforward to measure sales qualified leads and marketing qualified leads. Further up, we have digital traffic, which is also relatively easy to measure — web analytics, individual channel analytics like Facebook, LinkedIn, YouTube, etc. These systems provide robust data that tells us what’s happening on those channels.

Offline traffic is where we start seeing resource and financial costs begin to escalate. Things like foot traffic in stores need hardware like foot counters, cameras, aisle counters, even technologies like beacons and WiFi triangulation — but it’s still measurable. For other out-of-home and offline measurements, there are hybrid response tracking methods.

For example, when you send someone a piece of direct mail, there should be a unique, tagged URL and a custom phone number tied to that piece which allows you to measure its performance. This is another area where underinvestment causes problems; offline direct marketing is measurable but has higher costs. If you send out a postcard with AcmeMarketing.com and no other form of tracking URL, you’ll be unable to measure the impact of that piece because there’s no tracking to disambiguate it from other traffic sources.

The same is true of channels like terrestrial radio. If a radio host says, “Go visit AcmeMarketing.com,” you’ll have unattributed traffic, the origin of which you can’t determine. Compare that with the radio host saying, “Go visit AcmeMarketing.com/spotify” or “Go visit AcmeMarketing.com/KNBC,” you’ll get trackable responses. It won’t be perfect; some people will remember AcmeMarketing.com and nothing else, but it’s substantially better than nothing (especially if it’s tied to a promotion).

Let’s talk about brand next — brand awareness and brand strength. This is the layer of marketing where things like awareness spending, brand campaigns, and public relations operate, and it’s the layer that people often say can’t be measured. The reason, of course, is that measuring brand strength is very expensive compared to other metrics.

There are a few metrics around brand strength: low-cost digital metrics such as branded organic search – when customers search for our companies, products, and services by name. Still, otherwise, brand strength requires classical market research techniques.

These are techniques like focus groups, one-on-one interviews with current and prospective customers, customer shadowing — when researchers accompany customers in their homes and offices to observe their behaviors and see how they make decisions.

Other techniques include surveys and panels, incredibly powerful methods for measuring brand strength by asking people, “What is your intent to purchase a blender in the next 90 days?” or “Was your intent to purchase a firewall in the next 90 days?”

Why is market research so expensive? First, you must conduct enough research to obtain a statistically relevant sample size. Second, particularly for B2B marketing or complex sales, if the decision-makers are senior folks in their organizations, it may take considerable time and expenses to reach them. You’ll be springing for many steak dinners and rounds of golf to get in touch with them.

Again, this doesn’t mean your brand is unmeasurable with that specific audience — it just means your organization may be unwilling or unable to invest to the level necessary to obtain the information.

Dig deeper: How marketers can measure success

The value of measurement

Data analysis is the final hurdle that leads people to say, “X can’t be measured in marketing.” The data needs to be brought together and transformed into a single model, typically an attribution model. This is the domain of techniques and disciplines like exploratory data analysis, data science, statistics and machine learning. We take all these data points and inputs and then transform them into a coherent model with sophisticated techniques like uplift modeling, propensity scoring, and multiple regression to determine what works.

So, to review: a metric is strategic if an organization provides the time, people, and funding to measure it. If the organization does not, then it’s not a strategic measure. That doesn’t mean it can’t be measured — it means the organization doesn’t value it enough to measure it.

Everything in marketing is measurable, but executives and stakeholders must commit the time, people and resources to measure what they ask for. If they don’t, then it’s our obligation as marketers to push back on them and ask for the resources to measure it properly — and tell them when they’ve underinvested and thus no valid measurement is available.

Marketing attribution and predictive analytics: A snapshot

What it is. Marketing attribution and predictive analytics platforms are software that employ sophisticated statistical modeling and machine learning to evaluate the impact of each marketing touch a buyer encounters along a purchase journey across all channels, with the goal of helping marketers allocate future spending. Platforms with predictive analytics capabilities also use data, statistical algorithms and machine learning to predict future outcomes based on historical data and scenario building.

Why it’s hot today. Many marketers know roughly half their media spend is wasted, but few are aware of which half that is. And with tight budgets due to the economic uncertainty brought about by the COVID-19 pandemic, companies are seeking to rid themselves of waste.

Attribution challenges. Buyers are using more channels and devices in their purchase journeys than ever before. The lack of attributive modeling and analytics makes it even more difficult to help them along the way.

Marketers continuing to use traditional channels find this challenge magnified. The advent of digital privacy regulations has also led to the disappearance of third-party cookies, one of marketers’ most useful data sources.

Marketing attribution and predictive analytics platforms can help marketers tackle these challenges. They give professionals more information about their buyers and help them get a better handle on the issue of budget waste.

Read Next: What do marketing attribution and predictive analytics tools do?


Opinions expressed in this article are those of the guest author and not necessarily MarTech. Staff authors are listed here.


About the author

Christopher Penn
Contributor
Christopher S. Penn is an authority on analytics, digital marketing, marketing technology, data science, and machine learning. A recognized thought leader, best-selling author, and keynote speaker, he has shaped five key fields in the marketing industry: Google Analytics adoption, data-driven marketing and PR, modern email marketing, marketing data science, and artificial intelligence/machine learning in marketing. As co-founder and Chief Data Scientist of Trust Insights, he is responsible for the creation of products and services, creation and maintenance of all code and intellectual property, technology and marketing strategy, brand awareness, and research & development. Penn is a 2020, three-time IBM Champion in IBM Analytics, a Brand24 Top 100 Digital Marketer, an Onalytica Top 100 AI in Marketing influencer, and co-host of the award-winning Marketing Over Coffee marketing podcast. Prior to co-founding Trust Insights, he built the marketing for a series of startups with a 100% successful exit rate in the financial services, SaaS software, and public relations industries. His work has served brands such as Twitter, T-Mobile, Citrix Systems, GoDaddy, AAA, McDonald's, and many others. Penn is an IBM Watson Machine Learning Certified Professional, a Google Analytics Certified Professional, a Google Ads Certified Professional, a Google Digital Sales Certified Professional, and a Hubspot Inbound Certified Professional. He is the author of over two dozen marketing books including bestsellers such as AI for Marketers: A Primer and Introduction, Marketing White Belt: Basics for the Digital Marketer, Marketing Red Belt: Connecting With Your Creative Mind, and Marketing Blue Belt: From Data Zero to Marketing Hero, and Leading Innovation.

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