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Attention analytics aims to accurately measure how much attention a customer is paying attention to a marketing or advertising initiative.
Attention is a metric that Nudge measures to enable marketers to see how customers are engaging with them.
This post includes:
- What is attention analytics?
- What are attention metrics?
- Why are attention metrics important?
- Common attention metrics
- Common metric comparisons
- What attention metrics can you use on programmatic?
- What are the best practices for attention metrics?
- Is attention correlated to conversion rate?
- What is a good attention benchmark?
- How do you measure attention?
What is attention analytics?
Attention analytics is the process of measuring and getting insight from consumer attention. Often on digital experiences such as advertising, websites or content.
In an attention economy, most brands are moving to understand attention on a deeper level and what it means for how they engage with consumers.
Consumers are a mouse click or a swipe, from competing digital options, so brands must ensure they create engaging experiences, that deliver on consumers needs. Without attention measurement in place, that would be very hard to do.
Why is attention strategically important?
If someone walks in to a shop and leaves straight away, were they a customer? The analogy we like to give is, in a shoe store, the more time you spend with an attendant, the more likely you are to buy something. And that’s how you should think about your measurement, it takes time and consumption to deliver value.
Measure attention rather than ‘time on page’ Time on page, which looks at the time gaps between link clicks, so means it is sampled data. It misses all those that read the content and hit the back button. Which can distort your data.
Attention looks at every user, and how long they are active on the content. From Nudge data, we know that attention is linked to conversion rate. Which makes sense, the more time you actively spend on creative the more likely you are to take the action which the content was built for.
And this metric works across video and audio too, letting you better allocate between the types of media. When you think about consumption of the content, look at: Scroll percentage or video completion rate; is the average user actually consuming enough of your content?
Ideally, the average person is consuming at least half of what you’ve produced.
What are attention metrics?
Attention metrics are measures of consumer attention in different digital experiences. These metrics are used in advertising and marketing teams, as well as product or digital experience. These metrics seek to understand how the customer is paying attention to a piece of creative or experience. In turn, enabling marketers & advertisers to find areas of improve and allocate their investments accordingly.
Advertisers need to be attentive to the methodologies behind how attention is measured.
- Is it a sample of the consumers who engaged, or every user?
- How often is the data collected in a session?
- Is there any rounding in the final measurement?
- These can impact the accuracy and fidelity of the attention data collected.
Why are attention metrics important?
They take existing measurement a step closer to reflecting the actual experience of the end user. And aid advertisers in making better decisions based on that.
Nudge has found that attention is correlated to conversion rate, that is, the more attention an experience gets the higher its conversion rate is.
Common attention metrics
Depending on the environment and type of creative, common metrics are:
- Attention, engaging in the experience.
- In-view, is the content in view on the screen
- Viewable impressions, impressions that met a threshold of being in view.
- Scroll depth, average scroll or scroll speed, using on page activity as an understanding of attention.
Nudge as an analytics platform collects attention metrics, to give a better view of how consumers are engaging with experiences. The data is sliced against other variables, like traffic source, URL, device and more. You can even see ‘attention thresholds’, how many people say for 5 seconds, 10 seconds etc.
Example of attention analytics dashboard:
Common metric comparisons
Click through to see how each metric compares.
What attention metrics can you use on programmatic?
For programmatic ads, there are two areas of attention metrics to consider.
- Pre-click attention.
- Post-click attention.
Pre-click attention is how long is the ad within view before engaging. This helps to understand if the population of customers seeing the ad are reading or watching the ad. Which will be a pre-cursor to a change in brand engagement.
Post-click attention looks at how customer that click through engage. If the customer is well primed from the ad, they should have high attention after clicking. This is useful for gauging the quality of a traffic source.
Programmatic advertisers can also use UTM parameters, to see the quality of multiple variables on programmatic. From placement, to publisher, to creative.
Attention metrics are also helpful for identifying the quality of the destination – and whether it is performing. It is hard for programmatic advertising to perform well if the landing page itself is a low performer.
What are the best practices for attention metrics?
Attention is like any other metric, in that, it is what you do with it that counts.
For improving attention metrics, you want to look at:
- Does the experience match the expectation of the customer that has clicked through?
- The experience, does it load fast, is it intuitive, are customers engaging with it or dropping off?
- The traffic sources, or context, for which customers are coming from? Can you reduce accidental clicks? Or fraudulent clicks.
- Attention is a high value metric that gives that feedback loop from populations of customers.
Is attention correlated to conversion rate?
More attention is correlated with an improved conversion rate.
Attention won’t solve conversion problems but can help duct tape over them. Improving the conversion rates. But what it does mean is, if you can’t change other variables, optimizing to attention can help you maximize performance.
For example, adjusting the traffic mix, to those that are driving the most attention.
A good analogy, is a food demonstration at a supermarket. The more time people spend watching the demonstration, the more likely they are to convert. That food demonstration is unlikely to change. But how people get to the food demonstration might, someone could be outside handing out flyers, promoting the food demonstration and priming customers. So those that come along, do spend longer.
What is a good attention benchmark?
For post-click engagements, that is when a user arrives on a destination.
For the average webpage or piece of content, about 48 seconds of attention is a good benchmark.
For homepages or navigation pages you would see this go down. For longer form content, you would expect this to go up.
How do you measure attention?
Install javascript on your digital experience, that will then measure, second by second, the attention your experience is getting. Whether it is a website, ecommerce, content, the same principles apply. Nudge provides these sorts of metrics, to help you make better decisions using attention.
- Attention by each URL
- Attention by each traffic source
- Attention by time of day
- Attention by device
And even a breakdown of attention, with how many people stay for 5 seconds, 10 seconds and other increments.
Nudge enables you to get customer insights with ease, diving straight into how customers are engaging, what they’re paying attention to, where they’re coming from, on what devices. And then it makes analysts jobs easier by synthesizing the data into insights, so you can get from insight to action faster.
Other methodologies can use a panel, and opt-in- eye tracking using the webcam on a device. These can be useful for big campaigns and where analysis is needed between pieces of creative.
For in-ad attention measurement, these measures are increasingly available direct in your DSP.
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