Advertising solutions that rely on Big Data can still deliver good user experiences. In publishing, the Catch–22 is that readers generally want great quality content but for free. The publishing industry’s solution is ad-supported content which has a pretty simple proposition:
- Site visitors have the benefit of that content in exchange for slices of their attention.
- In return, advertisers pay publishers for the exposure to those visitors.
- In this way, publishers can pay for all the costs associated with producing more great quality content.
Unfortunately, this seemingly simple model is under threat because visitors are increasingly using ad blockers to block annoying or offensive ads. There are a number of reasons for this, none of which are insurmountable.
The short version is:
The problem isn’t advertising, it is bad advertising.
In my article I quoted Professor Jeff Jarvis in his column in the Observer titled “Advertising Doesn’t Have to Irritate, Intrude, Lie, Cheat and Generally Suck”. He listed a number of reasons why “advertising sucks” and there are a few key themes:
- Advertising is frequently irrelevant;
- Advertising is a blunt tool that has no insight into changing consumer behavior after initial targeting;
- Advertising solutions intrude on people’s privacy; and
- Advertising is often poorly designed and lacks compelling content.
The last issue is solved by creating better content for better designed ads. The first three issues can be resolved with smarter implementations of Big Data solutions and I’ll explain why below.
Big Data informs smarter targeting
Big Data uses personal and anonymous data to learn more about consumers and that data is gathered when consumers interact with connected technologies on their journeys across the Web. It is also informed by the signals people send when they interact with various services and platforms that indicate their intentions.
Before Big Data became feasible, advertisers resorted to educated guesses about how to target consumers with their ads.
Better targeting makes ads more effective because they are more relevant.
Why consumers don’t like Big Data
When advertisers and publishers gather data in secret and use it in surprising ways, they scare consumers who then look for ways to block data collection, usually using ad blockers.
Unfortunately, modern sites contain a growing number of tracking scripts and tools that dramatically slow down the user experience and increase the amount of data consumers use. This is a bigger problem on mobile devices which are fast becoming the dominant platform. It’s no wonder that mobile adoption of ad blockers is growing so rapidly.
More responsible data practices will lead to more trust
The key to resolving the impasse between consumers, on one hand, and publishers and advertisers on the other hand, is to give consumers more insight into what personal data publishers collect, along with how and why they use it. This is a big step towards earning consumers’ trust and persuading them not to use ad blockers.
Another important step is for publishers to discuss the impact ad scripts have on site performance with advertisers. DigiDay interviewed Ars Technica’s editor-in-chief, Kevin Fisher, about how Ars addressed site performance issues:
“When ad scripts aren’t loaded, page speed is in the milliseconds, whereas the standard is more like three seconds.” With ads loaded, that’s a bit higher. “We often have to go back to agencies when we have performance issues where the ads are slowing pages. I’m often surprised to learn that people making the ads aren’t aware of the performance issues of these ads,” he added.
Building better user experiences with Big Data
Irrelevant ads create a poor user experience. Poor user experiences, in turn, incentivize consumers to use ad blockers or, worse, switch to competing sites.
So, how can publishers create better user experiences using Big Data? To begin with, it is crucial to be more transparent with consumers about –
- what data publishers and their partners collect; and
- what publishers and their partners do with that data.
One of the most common ways of disclosing this information is by using a clear privacy statement (Disclaimer: we are not lawyers so please consult with your lawyer about what is most appropriate for your business). Make sure your privacy statement is accessible to consumers and follow recommended best practices for your region and industry.
Make relevant offers
Big Data offers advertisers the opportunity to deliver relevant offers to consumers. In turn, this enables publishers to deliver a better ad experience and engage more meaningfully with consumers. Imonomy’s in-image solution, for example, uses a machine learning algorithm based on a potent mix of large datasets. Our technology analyzes users’ behavioral history and insights into impressions received. It then anticipates their potential value to publishers and advertisers as well as which offers would be most relevant to those consumers.
Publishers, advertisers and consumers need not be in conflict when it comes to delivering personalized ads that offer consumers what they are looking for. When publishers and advertisers adopt more responsible Big Data use practices, everyone wins –
- Consumers receive more great content they want, see ads that are more helpful and enjoy an improved user experience;
- Advertisers pay for ads on publishers’ sites that deliver value to them; and
- Publishers earn more ad revenue that supports the production of even better content.
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