UK based, Kantar Media, recently published its annual global study of major trends and innovations impacting media and communications planning for advertisers through the eyes of the consumer. They surveyed 5,000 “connected consumers” over 18 years old from the US, UK, Brazil, France and China.
The study looked at how consumer attitudes toward advertising and media are evolving, ad blocking and selective ad blocking, relevance in media and many other interesting topics. The below specifically looks at the takeaways from the second chapter that focuses on the impact of ad avoidance and what advertisers can learn from online consumer behavior.
When it comes to ad relevancy, 65% of consumers surveyed agree that they have seen an increasing amount of advertising online that is relevant to their interests. This, no doubt, has a lot to do with advancements in programmatic technology, including artificial intelligence, geo-fencing and better data access. On the surface, this lone data point is encouraging to advertisers. It looks like interest targeting has improved over time.
That said, 72% of consumers surveyed agree they see the same ad repeatedly and that it’s too repetitive. This speaks to advertisers’ overuse of the same creative and content and suggests there’s still some ways to go to make consumers happy with our online advertising.
Lastly, 40% of respondents agreed that they prefer to see advertising that is relevant to their interests. A similar study done the year before by Adlucent showed 46% of US respondents shared that personalization in advertising reduces irrelevancy. That study equates personalization with interest relevancy.
The takeaways and implications below come directly from the study and have been slightly edited for a US audience:
Takeaway 1 – It hasn’t gone away – ad blocking remains at a similar level to 2017.
Implication – Improve the value exchange for the consumer (be useful, be entertaining) to persuade consumers to stop avoiding advertising.
- In 2016 there was a lot of buzz and concern regarding ad blocking. At the end of the year I predicted that adoption would level off because they were getting too aggressive and blocking non-ad content, too. This study confirms that prediction. Adoption of ad blocking software is flat. If advertisers focus on providing value in their content by making it helpful and/or entertaining, perhaps we’ll see a decline in adoption.
Takeaway 2 – Significant numbers of consumers ‘selectively block’ – a practice that includes paying a premium for ad free environments on selected platforms.
Implication – Don’t put a “square peg in a round hole.” Take care over repurposed TV content, ensure sufficient adaptation for the intended media form.
- Consumers who upgrade their freemium model to the paid version of Pandora, Spotify, YouTube, etc. may not consciously be making the decision to eliminate ads. However, some probably are. The implication above is spot on – don’t expect to take a 30 second television commercial and add it as pre-roll on YouTube. Why? Because users’ experiences and expectations are different across channels. Advertisers must be cognizant of this and plan creative accordingly so freemium models are more palatable to consumers.
Takeaway 3 – Amongst the core reasons for blocking are poor creative, a lack of relevance, contextual inappropriateness and inaccurate chronology in the placement of the ads.
Implication – All parties across the media industry, agencies, research companies, media vendors, must recognize that more needs to be done to regain consumers’ acceptance of online media. Everyone has a role to play in achieving this.
- A lot of the above complaints are produced by advertising-holdovers that still deploy click-bait tactics and don’t rely on the advanced AI interest targeting available today. They quite frequently use poor creative, too. Most of this is coming out of the direct response and affiliate advertising space. In many ways, they’ve spoiled it for the rest of us. However, this is changing.
Takeaway 4 – Consumers crave relevance; the industry is still struggling to deliver on the promise implicit in online data.
Implication – Ensure better integration between what is said in ads online, and where, when and how it is said.
- The problem (opportunity) with online data is that there’s so much of it. The industry calls this big data. Big data are amounts of data so large that it’s very difficult or nearly impossible to derive actionable insights without a robust team of data scientists. That’s where AI comes in. Machine learning is only as good as the data (and amount of data) it consumes. The more structured and unstructured data AI has access to the deeper the insights it can provide. AI is the key for advertisers to deliver relevance.
The second chapter of Kantar Media’s global study reaffirms what many of us already knew. As marketers we need to make relevancy in our advertising a top priority. How is this accomplished? By focusing on quality creative that’s tailored to appropriate channels, targeting based on consumer interests, maximizing the value exchange pre and post-click, and harnessing big data insights using AI technology. This isn’t something coming down the pipe in the future. The technology to truly achieve relevance in advertising is available today and consumers are clamoring for advertisers to use it.