Connect with us
Cloak And Track Your Affiliate Links With Our User-Friendly Link Cloaking Tool, Try It Free

MARKETING

Software Development Trends and Benefits to Keep an Eye On

Published

on

Software Development Trends and Benefits to Keep an Eye On

Trends fluctuate or evolve throughout time. Whatever field you’re in, what’s popular right now won’t last long. When it becomes obsolete, it will either be replaced with something better or there will be significant improvements to prior trends. It is vital for every organisation to stay current with industry trends in order to ensure that their customers have the best (and most recent) experience possible and that the firm does not fall behind in the race.

The same will be seen in software development going forward in 2022, as with every other industry trend and developers will need to keep an eagle eye on these developments. Your existing procedures may become obsolete in the not-too-distant future. Software development firms must be aware of these software development trends and well-informed on what they bring and how they intend to reform the present procedure. Being aware of these patterns also allows businesses to strategize appropriately throughout software development.

Trends in Software Development and their Advantages:

  • AI and Machine Learning Are Becoming More Relevant: Artificial Intelligence and machine learning are no longer regarded as specialist technologies accessible solely to a few high-end organisations. They are applied by businesses of all sizes and from all major industries. These technologies entail analysing large amounts of data and teaching machines to think like humans. As Artificial Intelligence and machine learning act as extensions of their personnel, this provides additional support to enterprises.

Predictive analytics has proven to be one of the most effective applications of AI and machine learning. Organizations utilise these technologies to evaluate their customers’ behaviour and predict their actions in a calculated manner. When it comes to acquiring sales data from multiple clients and determining their preferences, the use of AI algorithms is likely to grow.

  • Putting Cybersecurity First: The significant transition to internet platforms, particularly in this pandemic era, has revealed weak links in digital environments. Cyber-attacks have recently increased in frequency and severity and if not handled with the highest care and attention, may lose businesses millions of dollars. Here are some of the biggest cybersecurity trends that will likely have an impact on the world in the coming year:
    • 5G: It is certain to have a significant impact on connection, particularly in more isolated places that have previously experienced connectivity challenges. 5G is expected to make communication and cooperation more efficient and effective.
    • Breach of the Clouds: As a result of the COVID disaster, numerous firms across many industries have shifted to cloud-based technologies.
    • Cybersecurity Insurance: As the number of users of digital tools and platforms grows, they will want their data to be secure and to be reimbursed in the event of data loss.
    • Combating Cyber-Attacks: Organizations all over the world are likely to deploy automated cybersecurity platforms that safeguard the privacy and security of their sensitive data and are opting for software development services.
  • Increased Internet of Things Integration: Because of its ability to collect massive amounts of data from sensors, process it, and filter it through cloud networks, IoT is already being actively used in a variety of industries. The usage of IoT provided enterprises with low failure rates, great security, and insignificant data transformation delays. It is also possible that corporations will employ it to streamline remote work.
  • The Big Data Industry Is Growing Consistently: According to technology experts, there are more bytes on the planet than stars in the sky! The importance of big data is only going to grow with each passing year. It is just a matter of time before firms begin to optimise technology to improve their day-to-day procedures.

Here are the two primary areas where big data is expected to succeed in the coming year:

  • Computation in Memory: In-memory computation can be viewed as an alternate method of accelerating business analytics. The most obvious advantage of this technology is the ability to process data in real-time.
  • Augmented Reality and Analytics: As a result, the time it takes to clean and prepare your data is significantly reduced. Augmented analytics will allow firms to gain daily insights from their tools while saving data scientists a significant amount of work. Any reputed firm providing software development services can support this.
  • An Increase in the Development of Progressive Web Apps: Today’s app users are unwilling to wait for the platform to download for an extended amount of time. We live in an era of immediate pleasure. Progressive web apps (PWAs) are significantly faster and lighter to download over the internet. The user experience is not affected because the services provided by them are identical to those provided by native programs.

When it comes to developing these apps, the procedure is faster and less expensive than constructing traditional and native applications. This is due to the fact that these programs do not require various versions or devices.

  • Java and JVM Will Remain Favored Technologies: Java has carved out a position in the IT industry since its introduction into the realm of software development in the mid-1990s. It is considered as one of the world’s most powerful programming languages, allowing developers to create and deploy highly responsive programs across numerous platforms.

It offers a lot more to offer developers and users, such as high stability, high flexibility, automatic memory allocation, a large number of open-source libraries, widespread use in Android app development, and much more.

  • Increased Use of Cloud-Based Applications: Finally, the increasing popularity of cloud-based applications is a trend that will undoubtedly continue in 2022. Organisations all over the world have been migrating away from traditional storage systems and toward cloud-based platforms since the COVID disaster. Given the rapid digitisation of corporate operations across all industries, it is safe to predict that more enterprises will join the ranks of organisations moving to cloud-based platforms in 2022.

Conclusion:

These are some of the 2022 software development trends. With a greater grasp of these trends, businesses can guarantee that any software they develop is future-proof and that they do not fall behind in the race.


Source link

Keep an eye on what we are doing
Be the first to get latest updates and exclusive content straight to your email inbox.
We promise not to spam you. You can unsubscribe at any time.
Invalid email address

MARKETING

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

Published

on

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!

Keep an eye on what we are doing
Be the first to get latest updates and exclusive content straight to your email inbox.
We promise not to spam you. You can unsubscribe at any time.
Invalid email address
Continue Reading

MARKETING

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

Published

on

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

Amazon pillows.

(more…)

Keep an eye on what we are doing
Be the first to get latest updates and exclusive content straight to your email inbox.
We promise not to spam you. You can unsubscribe at any time.
Invalid email address
Continue Reading

MARKETING

A deeper dive into data, personalization and Copilots

Published

on

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.”

Source link

Keep an eye on what we are doing
Be the first to get latest updates and exclusive content straight to your email inbox.
We promise not to spam you. You can unsubscribe at any time.
Invalid email address
Continue Reading

Trending