Mobio for Ecommerce & Retail

Cumulative dynamics

The volume of online orders is growing by an average of 20-23% from year to year. What is the actual basis for the objective long-term planning of advertising activity and its budgeting.

An exception to the cumulative trend is 2020, which was driven by the covid-19 pandemic.

Ratio of orders Desktop vs Mobile (+ APP)

The proportion of online orders by platform is almost identical, which serves as an additional reason to focus directly on the aggregate dynamics in forecasting, however, the share of app is not so significant, but the calculation is from year to year.

Shopping: Android vs IOS

Conditional income per user

Based on the volume of user income and the proportion of the purchase rate on IOS and Android,
we can conclude that, on average, in the category, IOS users have a significantly higher average check (45% higher) and, most likely, higher purchasing power.
What makes both the adaptation of advertising activity and the possible adaptation of the economy relevant
within individual OS

The total purchase volume between the axles is almost identical, IOS has a slightly higher volume (4%)

Total revenue from iOS users is 45% higher than Android users

Share of purchases by platform

APP: LTV within a quarter

Conditional income per user

This statistics serves as the basis for the formation of a long-term user cohort of 30 days and additional accounting for pending orders

The largest growth naturally falls on the first month, however, the second and third months are also characterized by continued consumer growth, however, in a smaller volume.

During the first quarter, there is a stable growth in product consumption

Average check per category

Average checks vary greatly from category to category.

Understanding the average check in a category will allow you to prioritize areas of work and maximize the cost-effectiveness of an advertising campaign at the start.

Advertising ecosystem architecture

Ecommerce & Retail Cases

Attracting potential buyers to your online store

Received reference CPOs for each channel. During seasonal periods, CPO was reduced by 40% and the conversion to purchases doubled. We identified the most successful product categories in terms of attracting new users. We set up the use of deep links to increase user loyalty, launched campaigns with a product feed and dynamic remarketing, which allowed us to reduce the CRR indicator from the planned one.

Results:

Before launching the advertising campaign, we paid a lot of attention to setting up tracking analytics, threw all the events through the funnel. We connected traffic from sources ASA, Facebook, MyTarget, Yandex.Direct and Google Ads; compiled a categorization for creatives according to the product matrix, audience segmentation, analyzed key queries to compose a semantic core.

Mechanics:

Announce the release of a new OBI application. Search for effective channels and the formation of benchmarks for CPO. Scaling results while maintaining a working CRR.

Task:

Comprehensive promotion of mobile applications of an online store

We attracted more than half a million users to a mobile application with a cost that is 2.5 times lower than the planned one and a subsequent decrease in the СRR indicator by 2 times from the planned one.

Results:

Conduct text and visual optimization of application pages. Next, build a cost-effective purchase of mobile traffic in Facebook ads, Google UAC, MyTarget, Tiktok ads, Apple Search ads and Yandex.Direct channels. Development of a large number of creative concepts in accordance with the seasonality of products and promotions.

Mechanics:

Conduct ASO events. Attract a large number of new users while maintaining the planned СRP indicator.

Task: