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How can Blockchain Benefit IoT (Internet of Things)?

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How can Blockchain Benefit IoT (Internet of Things)?

The blockchain is an open, distributed ledger. It allows the tracking of digital currency transactions without the need for central recordkeeping or external validation. The blockchain is primarily used in cryptos like bitcoin and Ethereum.

However, it also has the potential to be used in other industries as well such as IoT. Since it can cut costs and provide a secure mechanism for sharing data, companies are now tapping into this disruptive technology to improve their business processes. Blockchain and decentralized technologies, in general, can help to improve the IoT with regard to data security and privacy by providing a distributed ledger of transactions.

As we progress into a digital future, we will see more and more data collected. It is important that data is collected in a secure manner that protects users’ privacy. This is where blockchain comes into play. At its core, blockchain technology provides a distributed ledger of transactions that can be used for virtually any type of transaction – from cryptocurrency trading to asset management.

Benefits of Blockchain and IoT

Blockchain is a distributed ledger that enables machines to autonomously transact with one another. Combining this with IoT allows for secure and reliable systems that can accept multiple sources of information while also needing relatively little overhead in terms of energy, power, and space.

The IoT and blockchain are two terms that are getting more attention in the business world. This is because they have a lot of potential benefits. For instance, the blockchain can tell you how reliable your smart devices are, and it can also help them track how they’re communicating with one another.

Blockchain, a decentralized platform, creates architecture that allows for interconnected devices. However, this same structure can become problematic if an IoT device loses its network connection and needs assistance from other devices in the decentralized architecture.

An IoT platform that is built to be decentralized in nature will require more configuration on your part. However, it will be easier for them to run on a blockchain-based network due to being compatible with it.

Blockchain and IoT in Cyber Security

The data is growing in size and the number of people who are willing to share their personal data with companies keeps increasing. This is because they don’t want to miss out on opportunities or feel left behind in the process of personalization.

The big data security issue keeps on getting more complicated as well. Digital marketing has evolved quite a bit in recent years, and it’s becoming increasingly important for companies to protect their customers’ privacy, especially when it comes to sensitive information like their social media content.

Blockchain imposes high-level security by authorizing and authenticating encrypted device-generated data. With a distributed & decentralized ledger, the storage of data is spread across millions of devices within their network. Blockchain technology is providing decentralized control for IoT devices & networks. This means that if anyone component in an IoT device fails, the blockchain will still be able to operate with that specific component offline.

IoT platforms provide numerous opportunities for attackers, as they often have poor server architecture and lack robust access control. DDoS attacks are becoming increasingly common and can disrupt normal traffic to connected devices by overwhelming them, or by surrounding their servers with more than the number of potential victims. Using blockchain technology, IoT networks and devices can be protected from botnet-driven DDoS attacks which can easily pass even through security software like Avast Antivirus for Android. Blockchain technologies spread over many devices at once making these systems massively more secure than conventional methods.

How Blockchain and IOT can Help Improve Product Development Life Cycle

Blockchain technology is the backbone of cryptocurrencies like Bitcoin and Ethereum. It is able to provide a unique identity to anything that has an identifier. It can help improve the product development life cycle by providing complete transparency, traceability, and audibility. This will allow the industry to review the data more efficiently and quickly.

With blockchain, companies can also develop new co-created products which are more beneficial for both parties involved in the process.

The Ways Blockchain and IOT Can Help with Supply Chain Management in the Automotive Industry

Blockchain technology can help with supply chain management in the automotive industry. It is less expensive, faster, and more transparent.

The ways blockchain can help with supply chain management in the automotive industry are found in two areas – transportation and inventory. Blockchain technology helps to reduce costs, save time, reduce theft, avoid counterfeits, and improve transparency.

There are still challenges that companies need to overcome before incorporating innovative technologies into their operations. These include making sure that there is no downtime or loss of data when integrating new technologies into their systems. It is also important for companies to work closely with their suppliers so they can understand how blockchain works in the automotive industry and how it supports business objectives.

Conclusion

In this article, we have seen how blockchain can be integrated with IoT. We have seen the use of blockchain as a secure and transparent platform for IoT devices.

In conclusion, we can see how blockchain is providing a secure and transparent platform for IoT devices. For users, it allows them to connect their personal data and personalize their experience with brands on an individual basis. The future of blockchain-IoT integration is going to be a global revolution that will change the world in a positive way.


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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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