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MARKETING

4 Personalization Trends in Marketing [2022 Data]

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A 2021 Mckinsey & Company report found that 78% of consumers are more likely to make repeat purchases from brands that personalize. Nearly 80% are also more likely to refer their family and friends to these companies.

As we know, personalization is the name of the game in customer experience nowadays. In this post, we’ll dive into key personalization trends you should know in 2022.

Demand for personalization is increasing.

According to Twilio’s 2022 State of Personalization Report, 62% of consumers say a brand will lose their loyalty if they deliver an un-personalized experience, up nearly 20% from 2021.

Another report by Zendesk suggests that customer experience is more important to consumers now than it was before.

personalization trends in marketing: Zendesk report shows that half of consumers say customer experience is more important to them than it was a year ago

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This uptick in a need for personalization didn’t just start recently, it grew in part due to the pandemic in 2020. This was a time of uncertainty that forced most consumers indoors and online for an extended period of time.

The Mckinsey & Company report reported that 75% of consumers tried a new shopping behavior during the pandemic. Consumers are seeking more valuable experiences from the brands they engage with.

In fact, the same study revealed that over 70% of consumers now expect personalization and are frustrated when they don’t find it – making personalization a must-have for today’s brands.

Online personalization is prioritized.

According to a 2021 Zendesk report, 65% of customers want to buy from companies that offer quick and easy online transactions.

The report also found that online companies are outperforming, with ecommerce brands leading in consumer engagement.

Here’s why: Online offers many more opportunities for personalization than in-person. You can target users to see your ad then follow them through their journey, as they discover your products and consider purchases.

personalization trends in marketing: a visual display of online vs. offline personalization during each stage of the buyer's journey

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In-person, customers typically see generic displays followed by generic store experiences. Meanwhile, brands are unable to collect any data regarding items customers viewed and considered unless there was a purchase.

With these obstacles, many brands find it easier to personalize their marketing efforts online.

Omnichannel is the main way forward.

Only 35% of companies feel they are successfully achieving omnichannel personalization, up 13% from 2021 – according to Twilio’s 2022 State of Personalization report.

With consumers now actively engaging across multiple channels, effective personalization depends on an omnichannel approach that meets consumers where they are, not where brands expect them to be.

One 2021 report by Vonage revealed that 26% of consumers are very likely to stop buying from a business if they can’t switch between communication channels.

However, McKinsey & Company notes some roadblocks to a seamless omnichannel strategy. Here are the two main ones:

  • Traditionally, digital and customer-facing channels work independently so changing requires interlinking software and hardware.
  • It involves changing the customer journey flow, which involves retraining staff and updating the process.

While these aren’t minor challenges, they can be addressed with the right team and resources.

Companies will prioritize first-party data as privacy concerns mount.

With the end of third-party cookies and the recent data privacy laws, brands have had to pivot their approach to collecting data. This shift has caused a domino effect, impacting personalization strategies.

According to Twilio’s 2022 State of Personalization Report, 37% of brands exclusively use first-party data to personalize customer experiences, a six percentage point increase compared to 2021.

Why? The first reason is higher quality data, according to 54% of respondents. The report shows that accurate data is a particular challenge for brands, keeping them from fully implementing personalization strategies.

Other reasons include better privacy and easier management.

Collecting first-party data enables companies to make better decisions more quickly and integrate their systems more easily for a seamless experience – for both marketers and consumers.

Key Tips About Personalization

  1. Customization is not personalization. Customization is explicit, while personalization is implicit.
  2. You can achieve intent-driven personalization by understanding what people engage with on your site.
  3. Never forget that no matter how much technology changes, the key to great marketing is having an in-depth understanding of users.
  4. The future of marketing is in making websites, products, or experiences personal in a deeply meaningful way.
  5. The personalization of search results offers an opportunity to increase your visibility for really relevant searches.
  6. The potential to engage customers contextually based on a need and serve that in real-time will drive mobile devices as they become payment vehicles.
  7. Personalization has moved beyond segmentation to algorithmically-driven content.
  8. Personalization is about leveraging what you can from individuals when they come to your inbound customer touch-points.
  9. Don’t think about the different groups you want to market to. Think about the power of one and how to reach that person in the most customized and creative way.
  10. The three-step approach to personalization is: listen, educate, and engage.
  11. Think in terms of customer-centric recommendation engines rather than company-centric selling engines.
  12. Personalization is about creating a natural conversation between companies and customers.
  13. The three keys to balancing personalization and privacy are company transparency, consumer choice, and accountability.
  14. With personalized ads, the goal is to reach the highest point of relevance at the lowest sense of intrusion.
  15. Instead of thinking of data privacy as a limitation, consider that what needs work might be the value proposition.
  16. Marketers can get too focused on the details and forget to focus on the most important aspect: relevancy.
  17. Personalized marketing is not just for customers and prospects – it can affect change within an organization.
  18. We’ve moved from opt-in, permission-based, and customized address fields in personalization to online relevant conversations that engage and excite.

Editor’s Note: This post was originally published in Dec. 2021 and has been updated for comprehensiveness.

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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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