The internet of things (IoT) is a phrase coined to describe the proliferation of devices, sensors and software that has been created in recent years and have the ability to capture, record or send information in an automated way.
While the technology already exists or is under development in several industries, such as large IT companies, advancements in internet speeds and the growth in connected consumer technologies is making IoT much more common. It also has the potential to deliver real benefits for the marketing industry, including better data collection, management and consumer targeting, as some sources are already estimating it generates $1.1 trillion a year for the global economy.
Data collection has traditionally been time-consuming and highly manual. Historically in marketing, for example, data could only be collected on the results of a campaign by looking at financial or consumer impact results, for example, sales, costs or brand awareness, and consulting with quantitative research, including track-based and one-off studies, to judge the efficacy of a particular strategy. While there have been significant advancements in the availability of data, there is still much more work to be done to ensure accuracy, as the information will often be collected using a range of formats and structures. This then requires a high degree of human interaction to guarantee consistency across datasets and deliver actionable recommendations and insight.
This is the point at which IoT can be a powerful tool for the marketing industry. By creating structures that enable regular automated capture, collection, screening and delivery of data, set against comparable metrics, marketers can access regulated information that can help them to not only judge results accurately but to plan and monitor campaigns more effectively. Many advertisers are taking steps to make their data capture and housing more effective so they can target users across complex markets, all of which is possible thanks to the available datasets created through IoT enablement.
The benefits of IoT don’t just rest on using it to collect data, it can be used to support campaign modelling too. Rather than requiring large amounts of human input to ensure it is statistically accurate, IoT-delivered data is easier to input into modelling tools as it can be managed in such a way to compare sets from across a range of sources. However, to be really valuable those models need to be accurate and have predictive power too. By combining IoT and machine learning – a form of artificial intelligence that enables computers to learn without the explicit programming – marketers can access powerful tools that offer deep insight. This is because once designed and deployed, the modelling software can learn as it generates more outputs, constantly re-calibrating itself to deliver increasingly reliable analysis based on comparable and regulated data.
Machine learning-based models have the potential to and are already beginning to revolutionise the marketing and advertising industry. New technologies such as programmatic, though still niche, are becoming more prevalent within advertising and already contributes to 40% of display ads served in Europe (IAB). The associated targeting capabilities to reach different audiences across media and at the right time and place is enabling marketers to be significantly more focused in how they reach their audiences. It also brings benefits for publishers and media owners, who can sell ad space online based on real measurements of users accessible through a range of touchpoints.
While the data and analytics capabilities are impressive, they’re nothing if they can’t help marketers make an actual decision about where to place their campaigns based on legitimate predictive intelligence. It’s at this point that IoT and the associated new technologies can be truly powerful for marketers. Having reliable data that can be fed through accurate modelling software and can predict the result of an ad placement with a high degree of certainty can make a real difference to the campaign’s success. For example, if the model recommends placing 20% of the campaign budget on TV, 30% out of home and 50% online, that can make an appreciable difference to ROI if previous campaign budgets were to be structured differently. If the marketer can then repeat the simulation during the campaign, using live data, they can see how other factors are affecting results and adjust budget accordingly, they can take steps to improve the ROI, all of which is only possible through integrated IoT-based services supported by accurate capture and analytics.
In future, these technologies could even begin to automate the decision-making process. For example, if a placement is made regularly to a known audience on Twitter, automating the process could free up the marketing teams to focus on making larger decisions that require more human input, for example in developing creatives and the communication strategy.
IoT is a powerful tool for the marketing industry, but one that is only just starting to be exploited for its potential. The access to better quality data and modelling through machine learning is already starting to make a difference, but the real value will come from enabling more effective decisions to be made, whether by machine or man
By Luiz Chaves