4 Ways to Improve the Efficiency of Mobile Ad Spend with Data-driven Insights

Improve Mobile Engagement with Machine Learning Blog_image.jpgAs an advertiser – and especially a digital marketer – it’s safe to assume that a day doesn’t go by where you’re not concerned about the quality of your mobile ad spend. You may even begin to wonder whether you’re spending too much.

According to the BIA/Kelsey Industry Watch report, mobile ad spending in the U.S. will grow from $33 billion in 2016 to $72 billion by 2021. In addition, there’s an eMarketer report published in November 2016 showing that digital ad spending surpassed TV ad spend for the first time in 2016.

The report goes on to state that mobile comprised 63% of digital spend last year, or $45.95 billion in advertising. This outlay is projected to nearly double in the next three years, surpassing $86 billion by 2020.

Okay, so you’re probably not spending too much.

However, based on these numbers, it’s safe to assume that increasing the overall efficiency and ROI of your mobile ad spend will be a main priority for many marketers in 2017 and beyond.

Here are 4 ways mobile advertisers can optimize their digital ad spending.

1. Collect Data Points Indicative of Mobile Lifestyle Behavior

The above referenced BIA/Kelsey Industry Watch report indicated that mobile marketing and advertising is optimized when taking advantage of the unique features of smartphones such as the smaller screen size of these devices and their valuable ability to capture usage behavior.

For example, smartphones can provide information on app usage, location, dwell-time, frequency and wireless network connections (Wi-Fi, cellular, etc.), to name just a few. With this insight, advertisers can promote the right products to the right person at the right time and place.

Of course, while location-based targeting and mobile native strategies certainly are a step in the right direction, more can be done to boost the effectiveness of mobile ad spend including the use of Big Data strategies.

2. Utilize Data Mining Techniques

One example of how Big Data can be valuable is through the use of data mining. This gives you the ability to analyze and determine key attributes that can be correlated to the desired user action, in particular, mobile ad click-through.

For example, an advertiser could discover that a consumer is 3X more likely to convert if they visit a specific location 3 times a month for a duration of 10 minutes each time (dwell-time). In this scenario, the likelihood of a conversion doubles when a consumer meets all the above criteria along with connecting to Wi-Fi on at least one visit.

3. Take Advantage of Machine Learning to Program and Scale Mobile Ad Campaigns

Big Data strategies such as data mining and machine learning have the potential to transform mobile advertising. By identifying valuable patterns and relationships within large data pools indicative of future behavior, mobile advertisers will know how to build campaigns to maximize conversions.

Equipped with this intelligence, future campaigns can be improved to maximize scenarios that lead to high conversion rates. With machine learning, high-conversion campaigns can be identified and programmed automatically with no human intervention.

4. Put it All Together, Rinse…Repeat

As with most things in the mobile world, it’s all connected. It’s hard to do one thing without the other. In this case, collecting the data points identified above is only one piece of the puzzle. Combined with data mining and machine learning, it has the potential to truly optimize your mobile ad spend.

However, it doesn’t stop there. Practice continuous data collection, data mining, and machine learning to iterate and improve your mobile ad campaigns. The predictive accuracy and effectiveness of these techniques will only improve as your data set grows.

Has your company used Big Data to improve the ROI of its mobile strategy? If so, how? We’d love to hear from you.