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For a Better Customer Experience, Make Your Buying Process Less Efficient

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For a Better Customer Experience, Make Your Buying Process Less Efficient

We ordered Domino’s pizza last weekend.

I know, I know. But hang with me for a moment.

Do you know the scene in the movie Reality Bites where they order Domino’s pizza and Lelaina, played by Winona Ryder, asks, “Do they take checks?”

The last time I ordered Domino’s, that movie was a year old. That’s right. It’s been 28 years.

In the mid-1990s, apps, websites, and pizza trackers didn’t exist. Someone would hang a Domino’s magnet showing its menu on your doorknob, and you’d take it inside and attach it to your fridge. On that menu was … wait for it … pizza. Large or small. 11 toppings. Thick or regular crust.

In 1995, ordering Domino’s pizza was an inherently efficient transaction. I called, ordered the number of pizzas, and specified the toppings. Thirty efficient minutes later, the pizza arrived at my door.

Domino’s became known for that – average, efficient pizza.

@Robert_Rose delivers a #ContentMarketing lesson after he orders @Domino’s pizza for the first time in 28 years via @CMIContent. Click To Tweet

So last week, after three neighbors said we were “missing out,” we ordered Domino’s. I approach the 2023 experience with a 28-year-old expectation for the Domino’s customer experience – an average, efficient pizza.

Domino’s iPhone app stepped up on the “efficient.” The menu has expanded to include chicken, tater tots, sandwiches, pasta, salads, and desserts plus five pizza crust options, but the app got me through all those choices efficiently. I ordered a few pizzas and went a little wild by ordering the cheesy tater tots (don’t judge). The GPS-suggested delivery address was spooky in its accuracy, and away my order went.

Less than 30 minutes later, Domino’s average, efficient pizza and tater tots arrived at my door.

Meh.

The ‘right’ way to buy

When I shared the experience with the friends who recommended Domino’s, they scoffed. “You didn’t do it right,” they said. “You have to customize and always ask for double cheese. You need to add garlic. The basic tots are fine, but the cheddar bacon tots are killer.”

I was fascinated. They indicated the “meh” experience was somehow my fault. I had manifested the suboptimal experience because I didn’t take enough time to order.

I don’t necessarily disagree. But my experience with Domino’s is a great lesson for B2B marketers who facilitate complex sales.

Can friction be a good thing?

Over the last 20 years or so, marketers have worked hard to reduce or remove friction in the buying process. You may have implemented digital technology that said it would “remove the friction from the customer journey.” You’ve streamlined your websites, thinned the product pages, and provided sales enablement scenarios so tightly scripted as to eliminate any ability for a sales rep to “read the room.”

But B2B products and services are complex. Your many “toppings” and “sides” can differentiate your solution or at least make it more contextually valuable to a customer. For example, “marketing cloud” and “marketing hub” technology products offer so many choices. Whether it’s HubSpot, Oracle, Salesforce, or Adobe, their clients haven’t a clue of all the components in the complete package.

Balancing the B2B customer’s journey presents a challenge: How do you offer customized choices without overwhelming the customer?

You introduce friction that may slow down – or pause – the buyer’s journey and provide value that ultimately enhances their overall experience.

Introduce friction to slow down buyers so they appreciate customized choices without being overwhelmed, says @Robert_Rose via @CMIContent. Click To Tweet

I’ve seen a few successful methods used by B2B companies.

Use content-generated data to tailor and prioritize

Many B2B companies use first-party data to get personal rather than to help them target a solution for the person. They focus on the data fields that capture the who and almost ignore the buyer’s why or what.

A smarter B2B content marketing strategy tags data with attributes so you can refine the suggested solutions or highlight unique features that will prompt the customer to pause and become aware of that unique combination.

Default feature packages can differentiate

I learned this lesson the hard way. As the CMO of an enterprise web content management company, I believed one of the greatest features was our flexible approach to content translation and localization. Our customers couldn’t dream up a scenario that we couldn’t meet. We thought it removed friction because if a customer asked, “Can you handle our translation and workflow process,” we would confidently say, “Yes.” However, the brand continually lost customers to solutions with only one translation and localization method.

It turns out customers – on the whole – sought an alternative because they were dissatisfied with their translation and workflow process. They wanted to learn the competition’s default way of doing it rather than make their existing technology bend to their perceived bad process.

By recommending options with verbiage, such as “many customers choose this,” “recommended for you,” or even “editor’s choice,” you slow the customer’s decision, but you also provide easier ways to make their decision.

Sustained audience engagement: Marketing after the transaction

What I call the “dead zone” presents a fantastic opportunity for B2B content marketers to slow the process. The dead zone occurs after the customer says “yes” to your solution and before and/or during delivery and implementation. Emotions run high on both sides. Remember, the endpoint for marketing and sales is the beginning point for the new customer. So the elated sales side usually says, “Leave the customer alone. Don’t slow things down.” While the buyers, though usually happy, can be uneasy. They may lose the “new-car-smell” happiness well before they use the product.

Slowing down by adding friction to this process can actually help. During the dead zone, thought leadership can sustain engagement. Experiences can help the customer get ready, learn, prepare, and generally understand how they can get the most out of what they just bought.

More than upselling the vinyl mats or undercoating for the new car, valuable content marketing experiences enhance the customer’s experience to prevent second thoughts or a lack of enthusiasm when recommending the brand to their peers.

Slower can be easier

Your overall goal should not streamline the buyer’s journey so efficiently that you miss opportunities where the customer could benefit from a pause. In my Domino’s experience, the app was remarkably efficient. It took me through identifying the delivery location and scheduling a delivery time before it even asked what I wanted. Then, the super-efficient configurator zoomed me through the process. Pizza. Big. Thin Crust. Pepperoni and Onions. Tots. Checkout. Done.

Your overall goal should not streamline the buyer’s journey so efficiently that you miss opportunities where the customer could benefit from a pause, says @Robert_Rose via @CMIContent. Click To Tweet

When I selected the first three attributes, it could have replied, “Whoa, did you know that many of our customers in your area say ‘double cheese’ really makes their pizza special?” What if it recognized I hadn’t ordered in a while and offered a welcome-back special, using the most popular orders as a default? I would have had to pause to learn about that package, but perhaps I would have purchased more.  Or maybe I would have made more enjoyable choices.

Remember, sometimes your customers don’t know what they want exactly or have preconceived notions that don’t match the optimal experience. You and your major competitors may offer almost the same thing. But you can differentiate by slowing down the buying process to make it easier for the customers to understand the combinations that make your solution better for them.

As you double down on creating more valuable customers who stay longer and evangelize more loudly, remember it’s better to slow down and delay the right decision than speed up the wrong one.

It’s your story. Tell it well.

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Cover image by Joseph Kalinowski/Content Marketing Institute



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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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