Most discussions that extol the virtues of using the mobile device within a marketing context start by describing the mobile phone as the most personalized device. Statistics seem to fly out of the woodwork describing the time a user spends on his or her device, the percentage of users that sleep or use the facilities with the mobile phone present, and how the device is just as important as the air that one might breathe or the food that is consumed. This makes a great story for the mobile marketing and advertising industries. The best practices for taking advantage of the personalized nature of the devices, however, have yet to consolidate around a single methodology.
One reason for the lack of a standard set of proven guidelines is that all vendors want to ensure that any recommendation submitted has competitive differentiation. But in holding back on guidelines, we might be doing a disservice to the progression of our core mobile marketing values: dynamic targeting and dynamic creative.
This column is not going to compare and contrast these campaign tactics. Both solutions have a role within the personalization of mobile campaigns. They take advantage of the personalization opportunity in a very similar way. They are just typically implemented by providers participating in the mobile ecosystem, all coming at the solution from a different perspective. Is one approach better than the other? It really doesn’t matter. When either approach is implemented correctly, all parties will prosper.
Art and science often come together in the planning, design, and execution of successful mobile campaigns. When they do, it is because the consumer is matched with an offer that was exposed within an advertisement that takes advantage of the data and analytics technologies available in the industry. Creating media buying rules that can utilize technology to identify the right customer for a specific advertisement or utilizing technology to create rules to determine which advertisement to show are both forms of real-time personalization in mobile advertising. These approaches will likely improve campaign performance, because the providers will be using machine learning automation to optimize based on engagement (or lack of).
In addition to providing a better experience for the consumers, deploying these rules will allow for mobile ad tech suppliers to be more selective when making the decision to expose a brand to a potential customer without having to make compromises to ensure delivery at the promised scale.
Brands should be encouraged to provide a personalized experience and have multiple advertisements available for mobile campaign execution. Each advertisement should be sufficiently unique and potentially highlight different brand or product values. Lastly, those involved can remain engaged during the campaign by identifying patterns of consumers and advertisements that make for a successful match and apply those learning across other channels.
Aaron Epstein is the Vice President, Business Development at Voltari, a company that develops predictive analytical solutions for the mobile space. Voltari optimizes mobile advertising campaigns from the start, learns and improves automatically in real-time, and provides insights. Aaron oversees the introduction of new products to the marketplace — managing key relationships for the company, related to product development and new lines of business. Look for his post the fourth Wednesday of every month.