MARKETING
Top 10 SaaS Application Trends You Need to know in 2022
Software as a service model has gained immense popularity in the past few years. It offers cutting-edge solutions in a wide range of industries. SaaS application development model provides a lot of cost-effectiveness and flexibility making it an amazing option for business models and industries. Currently, there is huge competition among SaaS products. As per the latest report by DevSquad, SaaS spending across companies of all sizes will reach $500 billion by 2023.
To gain a competitive edge SaaS application development companies are adopting modern technologies. In this blog, we will discuss the top 10 SaaS application trends you need to know in 2022. But before that, it is important to understand what is SaaS and how popular it is. So let’s get started.
Table of contents
◰ What is SaaS?
◰Some popular organizations that use SaaS
◰ Top 10 SaaS Application Trends
- Artificial Intelligence
- Machine learning
- Low code popularity
- Micro SaaS
- Vertical Saas
- SaaS analytics
- Focus on Mobile
- Migration to PaaS
- Data Security
- White labeling
◰ Conclusion
What is SaaS?
Saas or software as a service is a method of software delivery in which software is accessed through an online subscription rather than installed on individual computers. This process saves a lot of time spent on installation and maintenance. It allows us to access applications from anywhere and anytime using the internet. Some of the significant advantages of using SaaS are enhanced scalability, highly cost-effective, time-saving, fosters high security, and a lot more.
SaaS is used by top organizations like Salesforce, Zoom, Slack, GSuite, Hubspot, Shopify, and Netflix. As per the latest reports by DevSquad 80% of the businesses plan to make all their systems SaaS by 2025. Software as a service has a really promising future and it will continue to grow further. So till now, you have got a clear idea about SaaS now let’s move to the next section and discuss the top 10 SaaS application trends in 2022.
Top 10 SaaS Application Trends
Now we have explored the key characteristics of Software as a service. Now is the time to dive deeper into the top ten SaaS application trends. So let’s get started.
- Artificial Intelligence: Artificial intelligence is deep-rooted in the veins of our society. As per the latest reports by Gartner that customer satisfaction is expected to grow by 25% by 2023 in an organization that uses Artificial Intelligence. AI innovations will empower organizations across industries to gain deeper insights and understand the needs of their audience. So Artificial Intelligence will boom the SaaS landscape in a variety of ways, enhancing the key characteristics of the SaaS development model across the globe. When AI is combined with SaaS it helps to obtain better value from customers, automate services and enhance security.
- Machine learning: The second forecast for SaaS application trends in 2022 is Machine learning. Machine learning is a subset of Artificial intelligence that is used to automate responsiveness in applications. The latest innovations in ML will empower businesses to automate significant parts of internal operations. It will improve internal collaboration through more sophisticated models. Machine learning is currently one of the fastest growing segments and a hot SaaS trend for 2022.
- Low code or no code: It is another big evolution in the software industry. These platforms put complex application development in an almost finished state. Applications that can be developed using low code frameworks vary from simple mobile applications to complex enterprise applications. It is an excellent SaaS solution for developers as they can use their unique code with drag-and-drop functions to build applications.
- Micro SaaS: Micro SaaS products just focus on one type of service offered by service providers. It can be software, an extension, a bill payment system, or anything just focusing on one solution. These smaller tools can be easily managed at a low cost. With reduced cost, the profits will increase as work will be done at a lesser price. It has helped small tech industries in product development without any errors. That has led to the growth of these companies in the long run.
- Vertical Saas: The fifth forecast in SaaS trends for 2022 is Vertical SaaS. It is customizable and targets customers within a specific niche. Organizations that are looking for specific customizations will find vertical-SaaS to be a very cost-effective option. It provides amazing benefits like enhancing business value, improving data governance, and helping to explore new niches.
- SaaS analytics: It is the process used by industries to analyze user experience across all touch points. The analysis is used to increase customer engagement and enhance their revenue. SaaS analytics tools help you to fully understand the customer experience.
- Focus on Mobile: As per the latest reports, 83.37% of people have smartphones today which accounts for 6.64 billion smartphone users in the world. This clearly manifests that mobile is promised land for SaaS development. Business owners are increasingly running their businesses from smartphones. Therefore, SaaS companies need to create and improve mobile applications for services and tools.
- Migration to PaaS: PaaS stands for the platform as a service. Another fascinating SaaS trend that we can expect in 2022 is SaaS migrates further toward PaaS which empowers businesses to build custom applications. The advantages of using PaaS have enhanced scalability, security, and agility. With organizations like Salesforce and Box migrating towards PaaS we can expect to see this trend gaining more and more popularity in the coming years.
- Data Security: Data breach is one of the biggest issues that companies are facing in today’s era. Due to the increased use of the internet, hacking into someone’s system is really easy. Data security is really crucial and companies are willing to pay a huge sum for their security. As per the reports by Fortune Business Insights the global information security market is expected to reach $366.1 billion in 2028. So SaaS development companies can create SaaS products that are aware of online threads and find a solution to overcome those issues. It will be quite challenging but it is one industry where these products will thrive more.
- White labeling: Another forecast in SaaS trends for 2022 is white-label SaaS products. These products are designed to have no branding when sold to clients. The clients can further add branding to resell it to the customers. It is great for businesses that can easily sell products but lack the technical skills to build them. Another advantage of using a white-label SaaS is that businesses don’t have to invest heavily in the beginning. This makes white quite appealing to small businesses.
Conclusion
These 10 trends mentioned above will shape the SaaS landscape in 2022. Many developments have evolved in past years paving the way for new concepts that will take the industries to new heights. These concepts will transform the face of business intelligence in the coming years. These SaaS development industry trends will promise a progressive future for the country. SaaS options are now regarded as really affordable and convenient options across industries. As these digital transformations will grow globally the SaaS development industry will get stronger which provides a smarter and simpler future for all. I hope that you found this helpful!!
MARKETING
YouTube Ad Specs, Sizes, and Examples [2024 Update]
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!
MARKETING
Why We Are Always ‘Clicking to Buy’, According to Psychologists
Amazon pillows.
MARKETING
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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