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Who thinks you’re customer-driven, you or your customers?

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Who thinks you're customer-driven, you or your customers?

Here’s a fun weekend exercise. Round up 10 marketing executives and ask them if they consider themselves customer-driven. I would bet that nine out of 10 would say yes, and the other person would explain that they focus on other things which eventually benefit the customer.

The importance of the customer is so significant that most of the marketing buzzwords are about them — customer journey, customer experience (CX), customer insights, and so forth. Any marketing book is bound to include a chapter on why you should be obsessed with the customer.

However, who is validating all of this customer focus? Is it your team or your customers? It’s easy to think that you’re putting the customer first while making it harder for them to buy from your brand. Let’s look at what it really means to be customer-centric.

The reality of being a customer

It’s hard being a customer. Why do we keep coming across hurdles to purchase the products or services we want if we are so important? Think of the examples where buying was a frustrating experience.

You apply for a job by uploading your resume, and you’re then asked to enter the very same details on the next screen. You try to file an insurance claim, and suddenly, it’s impossible to get someone on the phone. Your flight is canceled due to COVID restrictions, but it takes two hours to reach customer service.

Recently, I was staying at a Hilton in Miami. I had a long day of traveling, and I couldn’t figure out how to turn on the lights for the life of me. Luckily, the Hilton sent me an SMS confirming everything was in order. I replied that I couldn’t find the light switch for the lights. They replied that they were unable to help me with this request. This idea was designed with great intention but poor execution.

Every day we face similar challenges when interacting with businesses. I imagine that every marketing team constantly talks about how important their customers are and then makes them go through unnecessary hoops. Would you put your mother through this kind of service?

Closing the reality gap

When working with marketing teams, I tell them they can close the reality gap by doing one simple thing. They should open their notebooks or laptops and get ready to take notes as the instructions are somewhat complex. Ask the customer.

I hear you! You’re already asking the customer, right? Apart from poor service, we are now bombarded with customer satisfaction surveys. The Hilton could not help me, and they also wanted me to fill out a survey to know how they did. Is anyone actually reading these survey responses?

Let’s dispense with vanity metrics like NPS. It’s interesting to know that someone is a promoter, but how does that improve the service? Marketing teams need tangible feedback. You can get that in three ways.

1. Shop the business as a regular customer

Airlines executives will book a first-class flight to see first-hand the “customer experience.” However, first-class is a different world than the economy. They should look at economy class and board last to see what most customers go through.

Marketing teams need to know what an “average” customer actually sees and not just focus on the 1% experience. Flying first class is amazing in any airline. Flying economy in some airlines feels like punishment. 

2. Quality over quantity in feedback

I worked with a company that would always call customers to get their feedback. Calling doesn’t scale, but you’re bound to learn more from a few calls than from reading thousands of surveys—if anyone reads them at all.

Technology has made it easier to get feedback, but teams don’t need quantity, they actionable insights. Designing experiences for real people is easier than creating them from random data points. 

Despite my expertise in data, I constantly tell teams that they need to look beyond the data points. Real people are hiding underneath all of their charts. Talk to them.

3. Get an outside perspective

Services like secret shoppers are beneficial because you can get unbiased feedback. You might overlook specific details because of your familiarity with your product or service. 

I recently used a self-checkout machine, and the grocer ran into critical issues because someone tried scanning an orange instead of typing in the number. The customer could shut down three out of the four machines with the same error. I can’t imagine scanning an orange is an obscure or unexpected customer action.


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Don’t forget the baby

One popular comedy trope is when parents “forget” their baby and drive off without them. I imagine this sketch resonates more with non-parents than people who have encountered something similar. 

In customer experiences, you need to avoid “forgetting the baby,” aka the customer. It’s easy to get caught up in what you could do and forget if the customer even cares about it. It’s nice to develop an app with all the bells and whistles but do the customers even need it?

Costco’s fast-food menu is an excellent example of customer-first thinking. The prices have barely changed in years, the food is delivered quickly, and purchasing is easy. Costco does not add complexity where it’s not needed. 

Despite growing to behemoth levels, Amazon still delivers packages on time. It’s cool to purchase anything from one place, but the core promise is a painless buying experience. It’s easy to refund items, and they arrive on time. That’s what the customer cares about.

Putting customers at the center will continue to attract headlines. Companies will claim that they are now focusing on the right variables—though it’s unclear what they were focusing on before. Teams need to ensure that these aren’t just words on a wall. Someone needs to consult the customers to hear what they think about your efforts.


Opinions expressed in this article are those of the guest author and not necessarily MarTech. Staff authors are listed here.


About The Author

Ruben Ugarte is the global expert in Decisions, Strategy, and Data and author of the Data Mirage and Bulletproof Decisions. He helps executives at the most innovative medium and large enterprises find their hidden treasures and use them to dramatically boost performance, increase profitability, and make their teams world-class. He has done this across five continents and in three languages. His ideas have helped hundreds of thousands of people make better decisions.


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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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