funmobility.com annie cai, jane wu, akshay...

funmobility.com Annie Cai, Jane Wu, Akshay Shah | 1

ABOUT FUNMOBILITY FunMobility is an all-in-one solution for creating, targeting, launching, and tracking mobile rich media advertising. We’ve taken a complex process—one that has traditionally required multiple vendors and special technical expertise—and brought it all under a single point solution

MOBILE AD INDUSTRY STATISTICS The mobile advertising industry is expected to grow 300% to 14 billion over the next five years. It is the fastest growing advertising industry due to a push from the success of geotargeted campaigns and in-app advertising.

Currently, smartphone usage in teens is expanding exponentially. Now, about three in four (74%) teens ages 12 - 17 say that they access internet through their phones regularly. By comparison, only about 55% of adults are “mobile internet users.” The teens are the ones directly affecting the growth of mobile advertising.

OUR PROJECT We researched the mobile behavior of individuals in the millennial population (born 1980’s to 2000’s, or ages 14 to 34). We wanted to know how they used their cell phones and their behavior towards different types of mobile advertising.


OUR METHODS

HOW DID WE CONDUCT THE SURVEY? We used two techniques to connect with our target audience: field studies and the social media campaign.

Field Studies: We performed field studies in shopping malls around Pleasanton to gather data from a broad age group. We asked shoppers to give us 2 minutes of their time to finish a quick survey.

Social Media Campaign: The bulk of our survey data came from the social media campaign. It was split into two parts:

Facebook Promotion:

We shared a two posts on the FunMobility facebook page with the survey link, and advertised it to a random audience of people ages 14 - 34 over the course of three days.

The two posts are shown below, and have a combined audience reach of over 30,000 people:


Direct Messaging:

In addition, the three of us also directly messaged people in our Facebook friend networks. The return rate on the “direct messaging campaign” was close to 100%. Just about everyone we messaged finished the market research survey.

Both of these tactics combined gave us an audience of over 100 people.

HOW DID WE ANALYZE THE DATA? The Survey:

● We used targeted questions based on the previous answers of participants, to get a more in depth perspective of individual interests.

Post-Survey Data Analytics:

● We found similarities between groups of people and their choices by running all or data through Python code. Based on this, you can find relationships between a certain gender and how they interact with mobile devices or advertisements.

More details on Data Analytics is below in the “Data Analytics” section.

DEMOGRAPHICS

LOCATION:

The majority of the survey participants lived in the Alameda County region in the cities of Pleasanton, Dublin, and Livermore. They are all fairly affluent communities.

AGE:

The survey participants were 14 to 34 years old.


DATA: BASIC

BASIC QUESTIONS: (answered by everyone)

1. Which age group are you in?

--------------------------------------------------------------------------------3. What device do you primarily use?

2. What gender are you?


SMARTPHONE/TABLET SPECIFIC QUESTIONS: (answered by those who primarily use a smartphone/tablet)

4. How often do you use your smartphone/tablet everyday?

--------------------------------------------------------------------------------6. What do you think of mobile coupons/ads that save you money?

5. How often do you use the mobile apps for the stores you usually shop at?

--------------------------------------------------------------------------------7. What do you think of ads on social media apps and store apps?


BUYING BEHAVIOR QUESTIONS: (answered by everyone)

8. Which most greatly affects your buying behavior?

--------------------------------------------------------------------------------10. In the last 6 months, how many times have you bought something after you saw a mobile ad?

9. Which most greatly affects your buying behavior?


FINAL QUESTIONS: (answered by everyone)

11. What type of ad most appeals to you?

12. How would you react to ads that were more interactive?


DATA: LINKS & SIMILARITIES CONNECTION 1:

CONCLUSION: The most significant correlation seen in this graph is that 40% of females prefer banner ads whereas only around 9% of men prefer banner ads. More specifically, men tend to prefer video ads over static ads.


CONNECTION 2:

CONCLUSION: In terms of industry, men and women differed greatly on what ads they prefer to see. 17% of men tend to enjoy receiving ads for electronics, whereas only 4% of women feel the same way. On the other hand, 50% of women tend to enjoy clothing and apparel ads-- significantly more than the 4% of men who prefer clothing ads.


CONNECTION 3:

CONCLUSION: A large majority of females (19%) preferred to receive ads through email, followed by Social Media sites, and online shopping sites. Most males wanted to receive ads through TV and through email. The two least preferred platforms of receiving ads were In game, and SMS. This makes sense, because both parties do not want to be distracted in gaming, and because a majority of the population considers text messaging as a fairly private method of communication.


CONNECTION 4:

CONCLUSION: A large majority of smartphone users (23.5%) preferred to get their ads through email. In addition, 15% of smartphone users chose to receive ads social media sites, and 13% wanted to receive ads through TV. On the other hand, more than 12% of computer users prefered to see their ads on the TV, and another 9% wanted to receive ads through social media.


CONNECTION 5:

* Note: The computer data was not available for this chart because we were only looking at the answers of smartphone users* CONCLUSION: From this chart, we can conclude that the best way to incentivize Social Media users (67%) is through a price discount (20%) or through free items (20%).


CONCLUSION To wrap up with a broad conclusion, we looked at a combination of all the graphs. From this data, we can conclude that a specific ad campaign targeted towards women would be most effective if it was banner ad about apparel, distributed via email or through social media. On the other hand for men the ad should be a video about electronics sent on email or seen on TV. We also found that a large majority of smartphone users preferred to get their ads through email and that computer users prefered to see their ads on the TV followed by through social media. In addition, the best way to incentivize mobile users to click on ads would be a price discount or free items.

MORE INFORMATION

See the website for more interactive charts:

funmobilityresults.weebly.com

We composed the 20-question survey and collected answers from 100+ people. The spreadsheet of our raw data can be found here:

https://docs.google.com/spreadsheets/d/17-NiYA5GnlKVa7ubmeF5qNT6GM2VadljGmNPujyGdYE/edit?usp=sharing

and a chart view of our data can be found here:

https://docs.google.com/forms/d/1ZktNbIjB3RCKNfuNkYhFbhDudh6ix8BDcFtSf7kkckY/viewanalytics






SKILLS LEARNED

● Creating a relevant and targeted survey ● Learned the most effective survey promotion methods ● Learned what incentivized people to click on Facebook posts ● Website building through weebly ● Google Spreadsheet and Surveys ● How to code python using Sublime Text ● Running Python code + HTML in Highcharts to create interactive high charts ● Learned how to host and run items through Weebly

VISIT FUNMOBILITYRESULTS.WEEBLY.COM FOR ALL RESULTS

FUTURE IMPROVEMENTS

● We tried to leverage free survey hosting sites that had limited functions, such as redirecting certain questions.

● Because of our time restraint on the project, we did not get a very wide scope of people to take our survey. For example, most of our survey-takers were in the 14-17 age group.

● We did not have enough time to organize a visit to local colleges to ask college students to take the survey.

● Some questions could provide more accurate data if asked as a scalar/rating question rather than a multiple choice question.

● We could have asked more questions about what makes someone more or less inclined to click on an ad. These longer-text based questions would have required the audience to spend more time taking the survey, but would give us better, personalized data.

OVERALL, THE PROJECT WAS EXTREMELY SUCCESSFUL

THANK YOU


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