Connect with us

MARKETING

Here’s how startups and small companies should build their marketing stacks

Published

on

As a startup founder in the martech industry, I’m routinely asked by other founders what should be in their marketing stack. It was also a topic of discussion during a birds-of-a-feather session at the MarTech Conference. It would be nice to respond with “acquire these ten products, and then you’ll be all set,” but unfortunately, that’s not how marketing works. Many factors impact product selection: marketing objectives, budget, composition and skills of the marketing team, and the market and competitive environment.

Startups are very different from established companies from a marketing perspective. They have no established brand position, limited personnel and little to no budget for technology. They may be entering uncharted territory by defining a new market category or jumping into an already crowded space with well-established competitors. So, where to begin?


Get the daily newsletter digital marketers rely on.


Marketing objectives

You can’t be successful in building your tech stack without first creating well-defined marketing objectives. You should have 3-5 high-level achievable objectives for the year (no more, or you’ll drive yourself insane). They should be aligned with the company’s business objectives and current position in the market (don’t set an objective for market leadership when you have no product or no revenue – it’s not achievable nor believable).

Here are some guidelines.

Advertisement

If you are entering an already established market category, your first objective should be related to positioning and differentiating the company and creating brand awareness. Creating a new market category should be about market education and socializing the new category. Do not create a new category if you don’t have to. I’ve done it twice under duress, and it requires a huge investment in market education and hard work to ensure that there is a line item for your product in your customer’s budget. In addition, if you define a new category and remain the only company in that category it is not a category. It is just a marketing description.

Your second objective should be related to the most important thing you need to do in the coming year, e.g., drive leads, revenue, launch a product, etc. You can customize your objectives to support your particular goals. As you write your objectives, you should identify the metrics that will define success for each objective so that you can quantify what you are trying to achieve.

Technology requirements

When you are clear on your objectives, you can then define how you will achieve those objectives in a marketing plan. Content marketing will be a large component of your marketing plan for most startups because it is cost-effective and impactful. With your marketing plan in hand, it becomes straightforward to build a technology plan. You need to look at each component of your marketing plan and define where you need technology to support each component and what you need the technology to do.

Experienced marketing operations professionals will be the first to tell you to start by defining what the technology needs to do before determining what type of technology you need. Don’t start with a technology shopping list, e.g., CRM, email platform, analytics, etc. Even though you may instinctively know that you need a CRM system to satisfy a need to manage contacts, to select the right one for your environment you need a clear definition of what it needs to be able to do for you. Continuing with CRM as an example – besides managing contacts, do you need it to send emails individually and to lists? Do you need it to create a pipeline structure in a specific way? What sort of reports do you need to generate? Does it need to give you the ability to create landing pages? With a comprehensive list of needs in hand, you can identify the types of technology required in your stack, and in many cases, you may find that one type of technology addresses multiple needs.

Cheatsheet

It’s important to do the work noted above, but as a starting point, I can confidently say you’ll most likely need the following components in your stack:

  • Source of lead data.
  • CRM to manage contacts.
  • Email platform or marketing automation system (note: some CRMs will provide you with enough of this capability to get you started).
  • A variety of content creation and management tools.
  • An analytics platform (could be as simple as Google Analytics).
  • A social media management platform.
  • Productivity and collaboration tools.

The work defining functional needs will be vital in selecting the right vendor for each of these categories. As you think about functional requirements, don’t forget to think about which pieces of your stack will need to integrate with one another frequently, which will dictate your vendor options.

Choosing the technology that’s right for you

Once you’ve determined the type of technology you need in your stack, two critical factors in choosing the right vendors for your environment are cost and skills. Most startups are budget constrained, and marketing technology frequently follows programs and people when it comes to the budget. That’s the bad news; the good news is that numerous excellent products are free, cost very little or offer significant discounts to startups, so you should get what you need within your budget constraints. And, remember you are not selecting technology that will be in place forever. As a startup, get what you need for the immediate future.

Advertisement

By nature, startups move fast, and startup employees generally perform multiple functions. Your team members must become “jacks of all trades,” leaving little time to master complex tools. Finding tools that are easy to implement and use is critical. Not every tool will be intuitive, and your team may need some new skills to leverage them properly. Invest in training. There are free programs and webinars as well as courses that charge for participating. You’ll get a great return by empowering your team to keep learning.

What next?

If you follow the guidelines above, you’ll have no trouble building your initial stack, and you’ll establish good discipline around technology selection at the same time, which will serve you well in the future. However, recognizing that some of you are under a lot of pressure and want to know what to put in your stack, I’ll share two things:

1) My company’s martech stack, which is continually evolving as we test and try new things.

2) The most popular tools in use by businesses with less than 100 people, which we’ve extracted from the aggregated data on our stack management platform:

Heres how startups and small companies should build their marketing
2022 MarTech replacement survey2022 MarTech replacement survey

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


About The Author

Heres how startups and small companies should build their marketingHeres how startups and small companies should build their marketing

Anita Brearton is founder and CEO of CabinetM, a marketing technology management platform that helps marketing teams manage the technology they have and find the technology they need. A long-time technology marketer, Anita has led marketing teams from company inception to IPO and acquisition. She is the author of the Attack Your Stack and Merge Your Stacks workbooks that have been written to assist marketing teams in building and managing their technology stacks, a monthly columnist for CMS Wire, speaks frequently about marketing technology, and has been recognized as one of 50 Women You Need to Know in MarTech.

Source link

Keep an eye on what we are doing
Be the first to get latest updates and exclusive content straight to your email inbox.
We promise not to spam you. You can unsubscribe at any time.
Invalid email address

MARKETING

YouTube Ad Specs, Sizes, and Examples [2024 Update]

Published

on

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!

Keep an eye on what we are doing
Be the first to get latest updates and exclusive content straight to your email inbox.
We promise not to spam you. You can unsubscribe at any time.
Invalid email address
Continue Reading

MARKETING

Why We Are Always ‘Clicking to Buy’, According to Psychologists

Published

on

Why We Are Always 'Clicking to Buy', According to Psychologists

Amazon pillows.

(more…)

Keep an eye on what we are doing
Be the first to get latest updates and exclusive content straight to your email inbox.
We promise not to spam you. You can unsubscribe at any time.
Invalid email address
Continue Reading

MARKETING

A deeper dive into data, personalization and Copilots

Published

on

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.”

Advertisement



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.”

Advertisement



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.”

Source link

Advertisement



Keep an eye on what we are doing
Be the first to get latest updates and exclusive content straight to your email inbox.
We promise not to spam you. You can unsubscribe at any time.
Invalid email address
Continue Reading

Trending