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The Future of Machine Intelligence in Mobile Advertising: Building Trust between Consumers and Their Mobile Devices

Written on
Sep 5, 2014 
Author
Martin Rugfelt  |

According to a recent eMarketer report, global e-commerce sales are expected to increase this year by 20.1% to $1.5 trillion – a growth stemming from what the research is largely attributing to sales on mobile devices. While these numbers are hugely impressive, they do not come as a surprise — marketers have been aware of the growing m-commerce trend in the past several years. Simply being aware of this trend and having a presence within m-commerce does not equate to mastering the magic formula of how to accurately target and sell to our customers to optimize success on the platform.

The magic formula lies within machine intelligence and big data analytics. Many marketers today still do not fully understand the concept or the benefits, while others are already beginning to explore opportunities with this technology to provide relevant advertisements and product recommendations for their customers. It will be those organizations that begin to employ these intelligent algorithms that will both better understand their customers, as well as for these customers to trust and rely on their devices for intelligent recommendations.

Creating Accurate Customer Profiles

Every marketer’s dream come true is to know what their consumers want, when they want it, and how they want to consume it, even if that is a bit invasive. In today’s world, that’s a lot to ask, but we are getting closer to this goal with machine intelligence gathering more types of information to create accurate customer profiles.

With what some are now calling this the “data opportunity”, we can gather data to better predict what our customers may want or need. Rather than simple segmenting and providing customers with a massive amount of spam (in the form of pop-up ads, e-mail ads, text messages, etc.), in the future we will be able to tailor data-driven advertisements to what the end user actually wants to see. If ads are relevant, and predictive of what a consumer wants, it can actually be seen as helpful, rather than invasive.

Utilizing Virtual Assistants to Provide Personalized Advertisements and Recommendations

Most consumers are undoubtedly familiar with the virtual assistants of today like Apple’s Siri, Microsoft’s Cortana, and Google’s Google Now. However, the virtual assistants of the future will go further both in terms of voice capabilities and functionality, and will be an incredibly important tool for marketers to explore utilizing. At the core, virtual assistants provide an intelligent service to users: whether it is a narrow voice powered search function or a complex shopping assistant, or other services.

Many marketers have found that in-app advertisements on mobile devices provide a difficult challenge in terms of user experience and advertisements conversion. However, by incorporating machine intelligence within virtual assistant devices, there is an opportunity to build this bridge by using good targeting then enabling a stellar user experience as the ad frequency can be reduced.

By using machine intelligence, virtual assistant apps are able to utilize data to understand and remember the customer’s behaviors and preferences and effectively build up a rich profile. This enables them to offer a great service to their users. As the device creates that profile of the end-user, it has a strong opportunity to break through the barrier to providing relevant information. Rather than spamming the user with information, because the virtual assistant has knowledge about what the customer wants and needs, this device achieves the perfect balance – and is then able to provide incredibly targeted advertising. By doing so, the end-user experiences a much more seamless interaction with their device, and the amount of advertisements that they receive can be reduced. For the marketer, lower frequency and better targeting will in the end improve click-thru rates significantly, which increases the value of the advertising.

In turn, consumers will use one application (the assistant) to consume what they now consume on many separate apps: social media, e-mail, news, shopping, calendars, and more.

Building Trust in our Apps

A lot of the current methods of advertising and marketing on mobile services fail in their execution because consumers ignore the adds – it’s obvious the content they are viewing is advertising—and either it’s completely irrelevant, or they’ve been provided with so much “spam” in the past that they have learned to tune out advertising messaging. Machine intelligence serves to combat the underlying issue behind this.

Once virtual assistants prove to consumers that the advertisements they receive from their virtual assistants are both useful and relevant, consumers begin to build a trust with that device. By providing relevant data to the end users’ preferences, needs and wants, advertising in small doses then creates a much larger impact in the mind of the consumer. Machine intelligence employs filters and algorithms that are able to provide these relevant advertisements.

Keys to the Future

While these technologies have so far only begun to be explored by early adopter brands and technology companies, they will provide keys to the future for advertisers. Virtual assistants will not only become a tool that customers will use in their everyday lives, but something that they trust, rely upon, and develop a relationship with. However, this will only happen as we continue to develop intelligent machine algorithms and then learn over time how to best apply this knowledge to mobile users. Marketers that begin to explore this technology now will have a competitive advantage over their competitors who may still be exploring outdated methods to reaching their customers.





Expertmaker's CMO Martin Rugfelt is a mobile Internet entrepreneur focused on Artificial Intelligence, machine learning and big data business development. He has been involved in several startups working with projects like the semantic web, mobile search, location based services and communities with focus on mobile opportunities. Previous positions include Director for Product Development at Orange Group, Director for Business Development at GoldenGekko as well as leading roles in Framfab, Wezap, Simpay. Martin also serves on the board of Expelytics AB a life science data analytics and EDC/eCRF solutions provider.

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