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Getting marketing, sales and operations aligned

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5 tips for building customer trust during the supply chain crisis

This is the second part of a two-part article. The first part is here.

Online shopping is like magic to the customer. Click on a few links, and the purchased item appears on your doorstep in a day or two — thanks to the supply chain.

For the online retailer, it is anything but magic. Unseen by the customer is the network of manufacturers, shippers and warehouses that meet demand with supply. For the most part, online retailers have a physical process to manage, and the outcome of all this is inventory — the stuff they must keep lying around, waiting to be bought.

Hopefully that wait is not too long, as having stuff lying around is a cost. Retailers are not mind readers, but they have some sense of what customers want, based on data about past purchases. They have been pretty good at delivering the goods.

All that goes down the drain when the unpredictable happens. The COVID-19 pandemic delivered a good thrashing to the existing system. Online retailers must reconsider how they calculate inventory, so that they are not stuck with too much stuff — or too little. That will take teamwork and require some
organizational flexibility. And it matters — a lot — to the marketing teams that must stimulate demand but not over-promise.

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 Read next: The Brooks Group on building customer trust while the supply chain is in crisis

Getting your departmental ducks in a row

Indeed, an important factor in taming unpredictability lies in aligning your sales and marketing efforts with your inventory. That advice is easy to write but challenging to implement. Large companies have the resources to achieve alignment. Smaller businesses may lack the scope and the time, being too busy
selling…and growing.

“A typical sales guy says, ‘just buy it, whatever it is’. A marketing guy will say ‘buy what is promoted.’ Operations and inventory will say ‘just buy what is there’,” said Mark Hart, chief operating officer of Pollen Returns, a pick-up service for e-commerce businesses. What each unit sees as a “win” is different. All must agree on expectations, he noted. There must be a reasonable target to shoot for. Missing the target is okay, he said, so long as the team is willing to learn from mistakes instead of pointing fingers.

“The reality is that the best marketers can’t tell operations…what the customer will buy or like,” said Dave Emerson, SVP for global e-commerce at Sekologistics, a global freight and delivery firm. “They take a bit of a punt. They sell through, or sell out, or are left with a shit ton of stock.”

Each department can appear to be working at cross-purposes. Marketing can be too focused on the future, while sales may not be paying attention to funnel and conversion percentages at each stage, explained Russ Sharer, Chief Sales Officer for The Brooks Group, a sales training and leadership consultancy.

And operations? They may be reducing production to minimize risk because they have their doubts about sales and marketing. “It is actually a big deal in most companies that the incentives for the three groups often are contradictory,” Sharer said. Combined forecasting meetings should bring the three together, where they must show their work and defend their plans.

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Building the supply chain buffer

So, you have the data, and you’ve got the alignment. What is this supposed to add up to?
Creating a supply chain buffer.

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Firms need to know how much stock they have on hand, and when to reorder. Again, no crystal ball can give you that information. But if they get this right, then can build a shock absorber into their supply chain that can offset the shock of the unpredictable.

“The concept of supply chain buffers is not new, but the pandemic has reflected the importance of these buffers across the supply chain,” said Matt Garfield, Managing Director in FTI Consulting’s retail and consumer products practice. “Essentially, buffers are designed to absorb uncertainty within the supply chain.”

The buffer is “typically sized based on demand variability.” Garfield continued. “The greater the variability in demand, the larger the buffer. In the most basic terms, we are adding safety stock and/or safety capacity across the value chain.”

Maintaining high inventory used to be the buffer, but it has its risks. “You’re trading off more capital tied up in inventory,” said Carter Armstrong, CMO of e-commerce fulfilment firm ShipBob. There is the risk of not selling through, plus storage costs. “We’ve seen more brands adopt a ‘drop’ style approach, where they introduce limited quantities of a product that sells out quickly” he said. Firms can “set inventory reorder point notifications to alert your team when inventory hits a certain unit threshold that indicates it’s time to create a new purchase order (at the SKU level), working in lead times.” Armstrong said.

“Smart brands will retire products that are very slow-moving in favor of focusing on profitable, best-selling products.” Armstrong continued. “Keeping a close eye on inventory turnover and the velocity at which your products are sold can be very eye-opening (usually favoring a slimmer SKU count or product catalog).”

Firms can develop plausible “worst case” scenarios that they can plan for, within their means. It pays for a company to be nimble, having the capacity to react to sudden increases and drops in sales, Hart said. Say the team decides it will budget for a sudden 25% drop or 200% spike, then it must plan to accommodate such swings and budget accordingly, he explained.

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Flexibility can be obtained with a two-supplier strategy, Sharer said, “splitting the business something like 80/20. I’d also make sure I paid on time and maintained a good relationship with their key leaders. When supply is tight, one thing suppliers do is try to improve the ‘quality of their revenue — larger orders, predictable payments, better margins.”

In short, the supply chain buffer is created by “spending money on inventory or capacity in anticipation of some future spike in demand,” Hart said. He offered this checklist:

  1. Start understanding the true cost of carrying inventory or capacity.
  2. Understand the cost of aligning or anticipating demand.
  3. Agree on how much to spend.
  4. Maintain ongoing monitoring and adjustment.

“This is not ‘one-and-done’ or ‘set-and-forget,’ said Hart. “This is a living, breathing process.”

 Read next: How logistics and the supply chain impact customer experience


About The Author

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William Terdoslavich is a freelance writer with a long background covering information technology. Prior to writing for MarTech, he also covered digital marketing for DMN.

A seasoned generalist, William covered employment in the IT industry for Insights.Dice.com, big data for Information Week, and software-as-a-service for SaaSintheEnterprise.com. He also worked as a features editor for Mobile Computing and Communication, as well as feature section editor for CRN, where he had to deal with 20 to 30 different tech topics over the course of an editorial year.

Ironically, it is the human factor that draws William into writing about technology. No matter how much people try to organize and control information, it never quite works out the way they want to.

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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.”

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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.”

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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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