The rise in ad blockers and super apps in mobile-first markets make Asia unique when we think about advertising measurement. However, despite advertising’s technological advancements, we have never addressed the legacy measurement challenges that persist.
A quantifiable feedback loop is the backbone of improving consumer perception and actions toward a brand—the goal of advertising.
Measurement helps distinguish the best creatives, placements, and audiences so brands can optimise their campaigns and improve success. Determining success can only be done through setting a goal and leveraging analytics and measurement to compare against it.
Having worked for both agencies and tech brands, I know one of the key challenges is that the options for measurement can be overwhelming. There are so many acronyms that fall into the measurement bucket, from CPA to CTR and ROAS to CPM.
It’s an arduous task for marketers and media agencies to isolate the best metrics to define success, so let’s talk about why it’s necessary first.
The importance of measurement
There are three primary goals for media measurement:
- Budget justification
- Budget allocation
- Continual improvement.
The rationale and audience behind each of these is different and requires different reporting metrics. For example, if you plan to ask your chief marketing officer for additional budget, you will need metrics that highlight which channels provide the most efficient cost per acquisition (CPA) metric.
In other cases, it will be important to prove that for every dollar spent, there is exponentially more return on investment for the company, that is, return on ad spend (ROAS).
Advertising measurement is flawed
The holy grail of measurement is ‘scaled utopia.’ This refers to a direct link between a marketing message being seen and a purchase or action being performed. However, being able to attribute each advertising dollar to a direct conversion isn’t as simple as it sounds. So why is this so hard to measure?
In digital marketing, I boil the difficulty of measurement down to ‘the four Vs of data’:
- Velocity: speed with which streaming data is generated
- Volume: scale of data (in terabytes and petabytes)
- Variety: sources of structured, semi-structured, and unstructured data, requiring algorithms to process
- Veracity: trustworthiness of the data.
As IBM puts it, the veracity of data is the uncertainty of data. The more variety of data an organisation has, the greater its veracity. This is why measurement is so difficult: we have a deluge of data which grows daily, making it challenging to navigate and find valuable insights that can directly lead to an outcome. Adding to the complexity of managing the volume, velocity, and variety of data, measurement must happen in real time to be relevant.
The challenge with click-based metrics
A key flaw in digital advertising measurement is the focus on clicks as a success metric. Consumers are usually online for a purpose—to read content, shop, or socialise. When they’re browsing on a website, they’re not usually in a mindset to leave by clicking on an ad to go to another page. Accidental clicks account for almost 38% of all clicks on static banners and 13% of all rich media clicks.
Asia has a reliance on clicks as the primary metric for measuring success. Not only are click-based metrics ineffective in determining the true success of a campaign, they also exacerbate the region's ad fraud problem—$17 million (US) is estimated to be lost to ad fraud every day in APAC.
Increasing levels of digital ad spend has made the category a prime target for ‘fraudsters,’ who lure marketers into buying fraudulent inventory that deliver high click-through rates, but a lack of business growth. These misunderstood success metrics drive marketers to focus on quantity over quality, meaning they end up overlooking the threat of fraud.
While clicks are an easy metric to report on, in reality chances are nearly all the clicks you’re getting are not generating real revenue or interest.
Bad incentives lead to bad outcomes
The incentives you set—how you measure things—directly impacts the participant’s behaviour inside an economic system, and you end up with unintended consequences.
To describe reward-based incentives that lead people to exploit the system to cash in, economist Horst Siebert coined the term “the cobra effect.”
When Delhi was overrun with poisonous snakes, officials offered a bounty on cobra skins. This crowdsourcing strategy worked well—until some realised they could breed snakes for their skins. The new industry was successful, but when the cobra infestation didn’t abate, the authorities caught on and stopped paying. The breeders released all the valueless snakes, making the snake population even worse.
Likewise, click-based metrics started out with good intentions but have led to an increase in fraud and a decrease in value for marketers.
The best approach? Use a cohort of metrics
Good measurement involves weighing the pros and cons of the different approaches, establishing clear methods to reduce bias, and choosing metrics that set the tone and incentive for every part of your marketing supply chain. I recommend using a cohort of metrics to measure campaigns:
The epitome of digital measurement success
Every metric you look at, every audience you try to reach, every methodology you use—they must all be evaluated as part of a cohort.
By first establishing a core set of metrics instead of focusing just on clicks, you can see a wider picture and make informed choices. Only if those incentives truly align with the outcomes you’re looking for will you come close to finding measurement success.
To understand attribution and incrementality methodologies that savvy marketers employ, look for the next installment in this two-part series: “Finding digital measurement success, part 2: Attribution and incrementality.” You can also read the first two installments in a three-part series on being “ruled by the click”: “You Can’t Measure Display With a Yardstick or Clicks” and “Phishing for Clicks.”
Sonal Patel is managing director for Southeast Asia at Quantcast.