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37 Holiday Shopping Statistics & Key Marketing Insights [2023]

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37 Holiday Shopping Statistics & Key Marketing Insights [2023]

Beyond the fun festivities, the holiday season is an incredibly significant time for both businesses and consumers alike, shaping economic landscapes year after year. In this post, we’ll discover how the art of gifting fuels retail sales and steers supply chains. We’ll also highlight the impact of online vs. in-store shopping as well as key seasonal sales for brands (Prime Day, Black Friday, etc.)

From the early-bird shoppers who meticulously plan to the last-minute buyers looking for a steal, we’ll dive into the interesting ways consumers interact with the market in the months leading up to the festivities. Let’s unwrap the top statistics behind the most anticipated shopping season of the year.

 

Check out our webinars covering the 2023 Playbook for Q4 and Holiday Success.

 

The Most Important Holiday Shopping Statistics for 2023

 

Let’s dive into the key holiday shopping statistics that are shaping how we shop in 2023.

 

Holiday Consumer Spending Statistics

 

  • Consumers spent $211.7 billion online over the 2022 holiday season , an increase of 3.5% year over year, per Adobe Analytics (Source).

 

  • Roughly 30% of shoppers gear up to kick off their holiday shopping as early as October or even before (2022 holiday shopper study).

 

  • 57% of consumers will begin holiday shopping on or before Thanksgiving (Source).

 

  • Just 15% of consumers plan to wait until December to begin holiday shopping (Source).

 

  • 60% of U.S. holiday shoppers plan on spending more than $250, with 10% planning to spend more than $1,000. (2022 Tinuiti Holiday Shopper Study).

 

 

  • The top influences for holiday purchase decisions include: Price (50%), sales or discounts (22%), free shipping (13%), fast shipping (7%), BOPIS (4%), easy returns (4%) (Tinuiti 2022 Holiday Shopper Study).

 

  • When making last minute gift purchases – 58% go in store and purchase, 39% get physical gift cards, 24% BOPIS, 23% get electronic gift cards, 21% will order products online even if it means a late gift, 15% will buy supplies to make a gift (Tinuiti 2022 Holiday Shopper Study).

 

  • As of 2021, 60% of consumers have reported using a Buy Now Pay Later (BNPL) service (Source). 

 

  • In 2022, consumers prioritized smaller purchases, with 72% stating they spent under $200 on a mix of holiday gifting and everyday essentials (Source). 

 

  • Across the 2022 holiday season, consumers spent a total of $1.14 trillion online globally and $270 billion in the U.S. (Source).

 

  • In 2022, holiday season retail sales grew by 4.8% YoY, following two years of surging retail and ecommerce growth. We expect a similar gain of 4.5% for the 2023 holiday season (Source). 

 

  • On average, 46% of global consumers preferred Buy Now Pay Later (BNPL) in comparison to a quarter of consumers who said they would opt for credit cards (Source). 

 

  • Households earning over $150K actually plan to spend 21% – almost $327 more – than they did last year on holiday purchases (Source). 

 

  • Shoppers look at social media for inspiration during the holiday season with 56% of Gen Z respondents saying they look at TikTok and  38% of Boomers check out Facebook (Tinuiti 2023 Holiday Report).

 

 

Online Holiday Shopping Statistics

 

Online shopping has essentially become a holiday tradition of its own. In our digital age, more people are turning to their screens to find the perfect gifts, making online shopping a dominant force in the holiday season. Let’s check out some of the top online shopping stats. 

 

  • 62% of shoppers plan to “buy mostly online” (Source).

 

  • Paid search remained the biggest driver of sales for retailers, with 29% of online sales attributed to that channel. Direct web visits (19%), organic search (17%), affiliates/partners (16%), and email (15%) were also major drivers (Source).

 

  • According to a September 2022 survey, more than half of GenZ consumers in the U.S. expected to buy more online and in-store this holiday season than last year (Source). 

 

  • 75% of respondents to our Holiday Survey said they will do at least some of their gift shopping on their phone (Tinuiti Holiday Study, 2021).

 

  • Only 14% of customers plan to shop online only (Tinuiti 2022 Holiday Shopper Study).

 

  • 70% of online shoppers foresee making purchases on their phone, 31% on tablet, 55% on desktop, and 8% using voice assistant devices (Tinuiti 2022 Holiday Shopper Study).

 

  • 85% of Gen Z plans to use a phone or tablet to holiday shop compared to 87% of millennials (Tinuiti 2022 Holiday Shopper Study).

 

  • 86% of shoppers will holiday shop on Amazon, 60% on Walmart.com, and 47% on Target (Tinuiti 2022 Holiday Shopper Study). 

 

  • Roughly 57% of U.S. consumers plan to shop online during the holiday season (Source). 

 

  • More than 80% of shoppers 40 and under will use their phones to find gifts, as will 66% of those over 40 (Tinuiti Holiday Shopping Report, 2021). 

 

In-store Holiday Shopping Statistics

 

While online shopping dominates, don’t count brick-and-mortar stores out. Let’s explore key statistics that shed light on the popularity of in-store shopping during the holiday season. 

 

  • 85% of holiday shoppers plan to do at least some of their shopping in-store, the majority saying they will first check availability/stock before going to stores. (Source)

 

  • Only 8% of customers plan to shop in store only with 39% majority online and some in store (Tinuiti Holiday Shopping Report, 2021).

 

  • According to a survey, in both 2021 and 2022, 43% of shoppers in the U.S. planned to go to stores (Source). 

 

  • 47% of respondents stated that they plan to make their holiday purchases at a department store (Source). 

 

  • 44.1 million people are expecting to shop exclusively in stores on Super Saturday (Source). 

 

  • More than 122.7 million people visited bricks-and-mortar stores over the 2022 Thanksgiving holiday weekend, up 17% from 2021 (Source).  

 

Black Friday, Cyber Monday, & Early Prime Day Statistics

 

From the frenzy of Black Friday and Cyber Monday to the anticipation of The Prime Early Access Sale, these events set the stage for incredible deals and mark the beginning of a shopping extravaganza. Let’s check out some of the top statistics for these major shopping holidays. 

 

  • 28% plan to start shopping on Black Friday or Cyber Monday (Source).

 

  • Cyber Monday 2022 was the largest retail ecommerce sales day in U.S. history with consumers spending $11.3 billion online—a 5.8% increase over 2021 (Source). 

 

  • 29% of Prime Early Access shoppers used the sale to purchase holiday gifts. Of those who purchased gifts, 69% say they completed less than half of their holiday shopping, and 95% say they’re likely to shop on Amazon again for additional holiday items in the next three months. (Source).

 

 

  • Consumers spent a record $9.12 billion while online shopping last Black Friday, which tracks more than 85% of the top 100 U.S. online retailers. That’s an increase of 2.3% over a year ago (Source). 

 

  • U.S. retail sales on Black Friday rose 12% year-over-year (Source). 

 

Conclusion

 

Preparation is the cornerstone of holiday success for brands. Understanding the intricacies of consumer behavior, harnessing the power of seasonal sales, and embracing the surge of online and in-store shopping can make all the difference in your bottom line. If you need assistance in getting prepared for the fast approaching holiday season, we can help. Contact us today and make sure to check out our webinars covering the 2023 Playbook for Q4 and Holiday Success.


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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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