There are all kinds of apps in the app store. Startups are coming up with apps compatible with smart devices across all major platforms to reach a larger audience and their quest for traction and user engagement is evidently visible.
Businesses are aggressively marketing their mobile apps to increase user engagement.
Web marketing is the mother of the new-age mobile marketing. It channelises strategies towards marketing to the audience on smart devices. Mobile marketing turns out to be effective when marketers advance from a conventional approach and act on the mobile moment of a user.
To cash on the mobile moment of a user, one must know the exact position of the user with respect of his product lifecycle journey. The latest technology that helps act on the mobile moment of a user is mobile marketing automation. Mobile marketing automation uses software to execute, manage and automate mobile marketing tasks and processes.
There are four stages that a user undergoes though a product life cycle:
- Installing App
- Finding/ Viewing Product
- Add to Cart/ Wish list / Share
- Product Purchased
Marketing efforts can be targeted according to the user’s position in the product life cycle:
- Advertising app to drive downloads.
- Push notification about relevant or searched products.
- Notifications about availability of products or services searched.
- Discounts/ freebies / offers available on products in cart/wish list.
Knowing which phase a user is in his product life cycle is instrumental is targeting relevant and result-oriented marketing efforts to enhance user engagement. Data driven analytics will help target marketing efforts where they are needed the most.
Authentic analytical data helps track behavioural trends of a group of users within a given period of time is known as ‘Cohorts’. Cohort analysis is a subset of behavioural analytics that derives relevant data from any given e-commerce platform, application or online game. It sorts users and divides them into relevant groups to aid analysis.
These related groups, or cohorts, have one or more common characteristics or experiences within a given time-span. Cohort analysis helps direct marketing efforts towards a relevant segment of users.
Different cohorts study user behaviour, similarity, and difference in activity of users. It is a functional method to compare users by time and way they were acquired or lost.
For example, if a notification is sent to a group of 100 users, marketers can sort and identify users who purchase that product on Day1, Day2 and Day3 and similarly those users who view the product and add it to cart or wish list, and those who do not view the product at all.
With the help of these cohorts, relevant marketing efforts can be channelised towards these specific groups i.e. sending discount codes, freebies or offering loyalty points to those who have added the product to cart of wish list to lure them into purchasing the product.
How Cohort Analysis Helps
Cohort analysis enables apps with information about the users that view/buy products and those customers that leave or uninstall the app. Intelligent insights backed by cohorts can help address such problems, giving your business an edge over competitors, more downloads, better engagement and sales.
Reliable data can be secured to target marketing using funnels too. Funnels are built with a conversion action (an end result) in focus and a series of actions leading to the conversion action over a period of time.
A funnel depicts the purchase journey of a user from beginning to the end.
For e.g. Step 1 – Installing an app. Step 2 – Navigating between different sections of the app. Step 3 – Looking for a product. Step 4 – Adding product to cart or wish list. Step 5 – Buying.
Funnels are a reliable tool to analyse trends but they can miss out on fine variations that indicate drop-offs or time bound trends. Most marketers prefer studying funnels as collective data comparing them by standard properties like platforms, gender and city to spot trends that they can otherwise overlook.
With the help of funnels marketers can engage in email campaigns or push-notifications that are relevant to a larger group like marketing an event in a particular city or a beauty product to the female users.
Marketing a new mobile app efficiently, driving downloads, and user engagement is a challenging task for most marketers, startups and developers.
Effective marketing backed by data-driven metrics can be instrumental in the growth and success of an app leading to better sales and ROI.