What indicators affect the effectiveness of mobile advertising
The mobile advertising market occupies a very important niche along with the mobile app market. As they develop, so does mobile marketing. To assess its effectiveness, there are many metrics that help determine engagement, conversion rates, and other criteria for the effectiveness of mobile advertising.
It is essential to determine the percentage of detected and blocked fraudulent app downloads in relation to their total number. The formula to help calculate this metric is expressed as: the number of fraudulent installations refers to the total number of inorganic installations.
A metric such as ARPU, or average user revenue, demonstrates how much income an average user brings in on average. It takes into account data on impressions and interactions with ads, subscriptions, and paid downloads. The formula for calculating the metric involves the ratio of revenue for the period to the number of users who have interacted with the advertising message over the specified time period.
The average revenue per paying user (ARPPU) is a metric that shows the approximate revenue received from one paying user over a certain period. To calculate ARPPU, you need to divide the revenue generated by the application by the total number of users who pay internally.
The average session is also an important metric. It is a metric that allows determining the average time people spend in the app per session. With the help of this metric, it is possible to determine how many users are engaged and how many are less active. To calculate the metric, you need to divide the number of sessions by the number of active users.
To determine the profitability of a particular advertising campaign, use the Return on Ad Spend (ROAS) metric by dividing revenue from users by the amount of money spent on marketing.
The Click to Install (CTI) metric allows you to determine the ratio of users who clicked on an ad and took the targeted action of installing a mobile app after viewing it. To calculate the index you need to divide the total number of downloads by the number of clicks.
CPI metric clearly shows the price that the advertiser pays for the installation of the application. To obtain the value, you need to divide the advertising costs by the number of installations for a certain period of advertising campaigns.
CPA shows how much a target user action costs the company. Another useful metric for marketers is CPM – the actual cost per thousand impressions. It is used to determine the effectiveness of an advertising campaign in terms of coverage of the target audience.
Lifetime Value (LTV) determines the revenue per user who installed the app over a certain period. The formula by which LTV is determined is expressed as revenue generated since a certain installation date/number of users who installed the app on that date.
Cost per click (PPC) shows the cost per click on an ad. The formula for calculating this metric is ad spend/number of clicks.
Retention Rate (RR) measures how many people started using the app again in a given period of time. The formula for RR is the number of active users during the date interval after installation/the number of people who launched the app for the first time during the same interval.
A metric such as repeat purchase frequency (RPR) shows how many people have made multiple purchases in more than one session, which demonstrates a higher LTV. Calculated as follows: the number of purchases from existing users divided by the total number of purchases.
Return on experience (ROX) determines how successful the customer’s experience of interacting with a specific channel of the company’s promotion has been. The formula: benefit (revenue)/value of experience (software, services, labor) x 100%.
Finally, remarketing conversion value determines the percentage of remarketing conversions compared to all marketing conversions. The formula is the number of remarketing conversions/number of marketing conversions.
Marketers can use these formulas to simplify the evaluation of the performance of marketing campaigns during marketing strategy or hypothesis testing.