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How To Keep App Users Coming Back?

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How To Keep App Users Coming Back?

For the vast majority of apps, user acquisition is considered to be just a small aspect of the entire app marketing. For app marketing, the more important thing is maintaining user retention and user engagement. According to most studies, the vast majority of users just stop using an app within a maximum of 3 months after downloading.

So, what are the tried & tested ways to ensure app retention? How to retain app users for maximum time? Here we explain some helpful tips.

Ensuring smooth onboarding

To make app users engaged, it’s critical to offer a lean and smooth onboarding process. The principal way to do this is to establish the value proposition and prevent unnecessary attributes. When you hire remote developers from India, you can get their huge experience in creating superior onboarding experience. Remember, providing too much information to a first-time user can prove to be a barrier to user retention.

Here are some onboarding tips.

  • Just give focus to one key value proposition of the app while communicating with first-time users.
  • For users landing on an app-only, highlight the key app features and help new users quickly understand how they can use the app.
  • When asking users to provide information, explain why you need this and how it can add value to their user experience.
  • Make the onboarding quick to allow users to do what they need to do with the app.
  • Optimize the signup process to make sure users can finish with this as soon as possible. Allow social login and guest login options.

Use retargeting campaigns

After downloading and using the app for some time, many app users who just stopped using it can be won back easily by carefully orchestrated retargeting campaigns. Retargeting should be given a key focus for a mobile app development company in Illinois with limited outreach. Such retargeting campaigns can help reengage the inactive users and bring back their interest in the respective app.

Here are some tips for doing this.

  • Get help from an analytics tool to detect inactive users.
  • Make a lucrative campaign offer for these users.
  • Bring them important app updates and the latest happenings and offerings from the app.

Make use of push notifications effectively.

It is important to keep track of user engagement through an Activity Feed. This can keep the app users still engaged when they are using the app. But when the users are not using the app, the most effective way to bring back the inactive users is using push notifications.

There are times when even a small nudge can make a player get back to the game with the same gusto or enthusiasm. Session in the game. In the case of other apps also, push notifications in various measures can be helpful to get back customers. The core idea behind such retargeting through notifications is to bring back their interest in the app by making them remember the good things they had as a user.

Push notifications are particularly used very creatively by game apps to bring back the players. For example, an app like Fancy Dogs makes use of push notifications to allow their players to see the new things in their activity feed. As there are too many apps, it is often important to make users remember where they have left off an app.

Ensure ease of sharing content and inviting other users

The app should also help users incorporate their social circles and near and dear ones to boost user loyalty and user retention. Moreover, when the users have their friends and family on the app, they can continue chatting with them without switching to other chat apps. The huge success of games like PubG can mainly be attributed to this integrated chat feature.

Apart from integrated chat and social messaging features, an app also needs to extensively use the Social Invites feature as part of the referral marketing strategy. By easily inviting their friends and family through social invite features, their participation and engagement with the app also increase substantially.

Personalized user experience

Finally, the personalized user experience remains a key aspect of the app engagement strategy. Personalization in the context of mobile apps is basically about providing a user experience that perfectly aligns with the user’s needs and expectations.

There are several many ways to achieve this personalization. You can always begin by adding the user’s name and personal details to address them very personally.

Every aspect of the user experience can be tweaked with personalized attributes. You can even personalize push notifications with messages curtailed to audience requirements, preferences and tastes. This personalization through push notification messages and other attributes can be best achieved by incorporating data-driven insights corresponding to user behavior, location, etc.

A most common way to use personalization is to send user-specific messages based upon the user’s location. Apart from location, other considerations can also be brought in to personalize communication-based upon user context. Personalized app communication just sends the right message when users are in need of any of the app features or offerings.

Conclusion

According to most studies, the vast majority of apps and mobile game apps just lose the majority of the users after three months of downloading the app. This mostly happens because most of these apps lack a robust retention and engagement strategy. This is one crucial area where we need to focus on ensuring that app users return and continue using the app.  

If you don’t want to meet the same fate and want to achieve optimum user retention, always focus on the same before considering new user acquisition with priority. The more you keep users coming back and spending more time every session, the fewer chances for churning and losing users.


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YouTube Ad Specs, Sizes, and Examples [2024 Update]

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YouTube Ad Specs, Sizes, and Examples

Introduction

With billions of users each month, YouTube is the world’s second largest search engine and top website for video content. This makes it a great place for advertising. To succeed, advertisers need to follow the correct YouTube ad specifications. These rules help your ad reach more viewers, increasing the chance of gaining new customers and boosting brand awareness.

Types of YouTube Ads

Video Ads

  • Description: These play before, during, or after a YouTube video on computers or mobile devices.
  • Types:
    • In-stream ads: Can be skippable or non-skippable.
    • Bumper ads: Non-skippable, short ads that play before, during, or after a video.

Display Ads

  • Description: These appear in different spots on YouTube and usually use text or static images.
  • Note: YouTube does not support display image ads directly on its app, but these can be targeted to YouTube.com through Google Display Network (GDN).

Companion Banners

  • Description: Appears to the right of the YouTube player on desktop.
  • Requirement: Must be purchased alongside In-stream ads, Bumper ads, or In-feed ads.

In-feed Ads

  • Description: Resemble videos with images, headlines, and text. They link to a public or unlisted YouTube video.

Outstream Ads

  • Description: Mobile-only video ads that play outside of YouTube, on websites and apps within the Google video partner network.

Masthead Ads

  • Description: Premium, high-visibility banner ads displayed at the top of the YouTube homepage for both desktop and mobile users.

YouTube Ad Specs by Type

Skippable In-stream Video Ads

  • Placement: Before, during, or after a YouTube video.
  • Resolution:
    • Horizontal: 1920 x 1080px
    • Vertical: 1080 x 1920px
    • Square: 1080 x 1080px
  • Aspect Ratio:
    • Horizontal: 16:9
    • Vertical: 9:16
    • Square: 1:1
  • Length:
    • Awareness: 15-20 seconds
    • Consideration: 2-3 minutes
    • Action: 15-20 seconds

Non-skippable In-stream Video Ads

  • Description: Must be watched completely before the main video.
  • Length: 15 seconds (or 20 seconds in certain markets).
  • Resolution:
    • Horizontal: 1920 x 1080px
    • Vertical: 1080 x 1920px
    • Square: 1080 x 1080px
  • Aspect Ratio:
    • Horizontal: 16:9
    • Vertical: 9:16
    • Square: 1:1

Bumper Ads

  • Length: Maximum 6 seconds.
  • File Format: MP4, Quicktime, AVI, ASF, Windows Media, or MPEG.
  • Resolution:
    • Horizontal: 640 x 360px
    • Vertical: 480 x 360px

In-feed Ads

  • Description: Show alongside YouTube content, like search results or the Home feed.
  • Resolution:
    • Horizontal: 1920 x 1080px
    • Vertical: 1080 x 1920px
    • Square: 1080 x 1080px
  • Aspect Ratio:
    • Horizontal: 16:9
    • Square: 1:1
  • Length:
    • Awareness: 15-20 seconds
    • Consideration: 2-3 minutes
  • Headline/Description:
    • Headline: Up to 2 lines, 40 characters per line
    • Description: Up to 2 lines, 35 characters per line

Display Ads

  • Description: Static images or animated media that appear on YouTube next to video suggestions, in search results, or on the homepage.
  • Image Size: 300×60 pixels.
  • File Type: GIF, JPG, PNG.
  • File Size: Max 150KB.
  • Max Animation Length: 30 seconds.

Outstream Ads

  • Description: Mobile-only video ads that appear on websites and apps within the Google video partner network, not on YouTube itself.
  • Logo Specs:
    • Square: 1:1 (200 x 200px).
    • File Type: JPG, GIF, PNG.
    • Max Size: 200KB.

Masthead Ads

  • Description: High-visibility ads at the top of the YouTube homepage.
  • Resolution: 1920 x 1080 or higher.
  • File Type: JPG or PNG (without transparency).

Conclusion

YouTube offers a variety of ad formats to reach audiences effectively in 2024. Whether you want to build brand awareness, drive conversions, or target specific demographics, YouTube provides a dynamic platform for your advertising needs. Always follow Google’s advertising policies and the technical ad specs to ensure your ads perform their best. Ready to start using YouTube ads? Contact us today to get started!

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Why We Are Always ‘Clicking to Buy’, According to Psychologists

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Why We Are Always 'Clicking to Buy', According to Psychologists

Amazon pillows.

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A deeper dive into data, personalization and Copilots

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A deeper dive into data, personalization and Copilots

Salesforce launched a collection of new, generative AI-related products at Connections in Chicago this week. They included new Einstein Copilots for marketers and merchants and Einstein Personalization.

To better understand, not only the potential impact of the new products, but the evolving Salesforce architecture, we sat down with Bobby Jania, CMO, Marketing Cloud.

Dig deeper: Salesforce piles on the Einstein Copilots

Salesforce’s evolving architecture

It’s hard to deny that Salesforce likes coming up with new names for platforms and products (what happened to Customer 360?) and this can sometimes make the observer wonder if something is brand new, or old but with a brand new name. In particular, what exactly is Einstein 1 and how is it related to Salesforce Data Cloud?

“Data Cloud is built on the Einstein 1 platform,” Jania explained. “The Einstein 1 platform is our entire Salesforce platform and that includes products like Sales Cloud, Service Cloud — that it includes the original idea of Salesforce not just being in the cloud, but being multi-tenancy.”

Data Cloud — not an acquisition, of course — was built natively on that platform. It was the first product built on Hyperforce, Salesforce’s new cloud infrastructure architecture. “Since Data Cloud was on what we now call the Einstein 1 platform from Day One, it has always natively connected to, and been able to read anything in Sales Cloud, Service Cloud [and so on]. On top of that, we can now bring in, not only structured but unstructured data.”

That’s a significant progression from the position, several years ago, when Salesforce had stitched together a platform around various acquisitions (ExactTarget, for example) that didn’t necessarily talk to each other.

“At times, what we would do is have a kind of behind-the-scenes flow where data from one product could be moved into another product,” said Jania, “but in many of those cases the data would then be in both, whereas now the data is in Data Cloud. Tableau will run natively off Data Cloud; Commerce Cloud, Service Cloud, Marketing Cloud — they’re all going to the same operational customer profile.” They’re not copying the data from Data Cloud, Jania confirmed.

Another thing to know is tit’s possible for Salesforce customers to import their own datasets into Data Cloud. “We wanted to create a federated data model,” said Jania. “If you’re using Snowflake, for example, we more or less virtually sit on your data lake. The value we add is that we will look at all your data and help you form these operational customer profiles.”

Let’s learn more about Einstein Copilot

“Copilot means that I have an assistant with me in the tool where I need to be working that contextually knows what I am trying to do and helps me at every step of the process,” Jania said.

For marketers, this might begin with a campaign brief developed with Copilot’s assistance, the identification of an audience based on the brief, and then the development of email or other content. “What’s really cool is the idea of Einstein Studio where our customers will create actions [for Copilot] that we hadn’t even thought about.”

Here’s a key insight (back to nomenclature). We reported on Copilot for markets, Copilot for merchants, Copilot for shoppers. It turns out, however, that there is just one Copilot, Einstein Copilot, and these are use cases. “There’s just one Copilot, we just add these for a little clarity; we’re going to talk about marketing use cases, about shoppers’ use cases. These are actions for the marketing use cases we built out of the box; you can build your own.”

It’s surely going to take a little time for marketers to learn to work easily with Copilot. “There’s always time for adoption,” Jania agreed. “What is directly connected with this is, this is my ninth Connections and this one has the most hands-on training that I’ve seen since 2014 — and a lot of that is getting people using Data Cloud, using these tools rather than just being given a demo.”

What’s new about Einstein Personalization

Salesforce Einstein has been around since 2016 and many of the use cases seem to have involved personalization in various forms. What’s new?

“Einstein Personalization is a real-time decision engine and it’s going to choose next-best-action, next-best-offer. What is new is that it’s a service now that runs natively on top of Data Cloud.” A lot of real-time decision engines need their own set of data that might actually be a subset of data. “Einstein Personalization is going to look holistically at a customer and recommend a next-best-action that could be natively surfaced in Service Cloud, Sales Cloud or Marketing Cloud.”

Finally, trust

One feature of the presentations at Connections was the reassurance that, although public LLMs like ChatGPT could be selected for application to customer data, none of that data would be retained by the LLMs. Is this just a matter of written agreements? No, not just that, said Jania.

“In the Einstein Trust Layer, all of the data, when it connects to an LLM, runs through our gateway. If there was a prompt that had personally identifiable information — a credit card number, an email address — at a mimum, all that is stripped out. The LLMs do not store the output; we store the output for auditing back in Salesforce. Any output that comes back through our gateway is logged in our system; it runs through a toxicity model; and only at the end do we put PII data back into the answer. There are real pieces beyond a handshake that this data is safe.”

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