Two Consumer Research Studies That Can Help Boost Your Mobile Advertising

Mobile AdvertisingMarketer predicts that by 2017, the spending of various brands on mobile advertising will amount to $36 billion. That staggering amount of money that is continuously being spent on mobile advertising may be reason enough for you to believe in its effectiveness at generating sales.

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However, don’t make drastic steps just yet. Before you unleash a torrent of banner ads on the browsers of your potential customers’ mobile devices, know how best you can leverage mobile advertising first. You should know that your product type is a crucial factor that determines whether or not mobile advertising will work as a marketing technique. Also, you should keep in mind that mobile users are not like typical consumers–meaning, they are not easily impressed by gimmicky ads.

Which Product Types Are Suitable for Mobile Advertising

If you sell toothbrushes, for example, then forget about launching a mobile ad campaign for your product. You’ll just end up wasting your marketing budget and your time. A toothbrush marketed through mobile ads is likely to flop in terms of sales, according to the results of a study undertaken by researchers from the Columbia Business School. The study looked into American consumer survey data culled from close to 40,000 respondents and more than 50 product representations in various mobile ads.

In a paper that was published in a 2014 issue of the Journal of Marketing Research, Yakov Bart, Andrew Stephen, and Miklos Sarvary explained that mobile ads are effective when they are used to market these two types of products: those whose use is deemed practical and important and those whose purchase involve painstaking decision-making. A washing machine is a perfect example of the former product type, while a family sedan exemplifies the latter product type. According to the findings of the three researchers, mobile ads don’t work when selling products that are bought only for pleasure (like a fancy watch) and items that are considered by consumers as less risky purchases. Examples of the latter type are toothbrushes and movie tickets.

Another useful conclusion from the study made by the Columbia Business School researchers has major implications for advertisers who use multiple marketing channels. It has been demonstrated that a mobile ad is effective as a form of reinforcement to preexisting marketing efforts to sell products whose purchase requires long, careful thought. Consumers who rationalize whether or not to pick up a certain model of a family car, for example, spend an inordinate amount of time considering other options. And in that time, they are exposed to a variety of traditional marketing materials–yours and those of competing brands. Miklos Sarvary said that the strength of a mobile ad is not to introduce new information into the minds of consumers, who have already learned so much about the product they are planning to buy. A mobile ad is far more potent when a consumer has already seen the same product being touted in ads from other media platforms. In short, use other marketing channels first to advertise your product, and then finish off with a sleek mobile ad display.

Why Gimmicky Mobile Ads Are Likely to Fail

You may be sorely tempted to design gimmicky ads to catch a person’s attention as he views content through a small touchscreen display, but don’t give in to that knee-jerk impulse. Mobile users tend to be more tech-savvy compared to average consumers, so your flashy, gimmicky ads will fall short of enticing them. This is according to the findings of a study made by Penn State University researchers.

Resist the temptation to design mobile ads that are based on gimmickry like running a free-prize draw or showing a time-sensitive offer. It is very likely that majority of mobile users will develop a negative impression of your product.

Penn State University researchers S. Shyam Sundar, Bo Zhang, Mu Wu, Hyunjin Kang, and Eun Go polled 220 participants and tested them with four mobile sites. Their findings were presented in April 2014 at the Association for Computing Machinery’s Conference on Human Factors in Computing Systems.

this article is written By K. Ong