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Don’t miss out on what your customers actually want

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Don’t miss out on what your customers actually want

Dont miss out on what your customers actually want

We’re told hindsight is 20/20. But hindsight doesn’t always tell you where you need to go. In fact, when it comes to research, it only tells you where you’ve been. On the other hand, Foresight research tells you where you need to go, sets you on the right path, and lets you continually check-in to make sure you are always headed in the right direction.

“Foresight research allows you to get quick feedback about what your customers want right now,” Feedback Loop CEO Rob Holland said. “It gives you the ability to rapidly innovate, test a hypothesis, get feedback, make another decision, test that decision, get more feedback, and do that all very, very quickly, so you can stay on track.”

Marketers looking to plan their next ad, message or campaign traditionally have relied on hindsight, or legacy, research. They look at how things have performed in the past to inform what they do in the future. But traditional legacy research is expensive and time-consuming, and it gives you a snapshot of just one moment in time, which by the way, is already behind you. It may have little to do with what’s in front of you.

We know of what we speak. Feedback Loop’s crackerjack marketers recently undertook a revamp of our digital presence. As the effectiveness of agile, iterative, foresight research for marketing became crystal clear, so did the tangible results of our campaigns.

“We would’ve been completely wrong.”

Jolene Pierangeli was surprised. A seasoned marketing consultant, she was charged with overseeing Feedback Loop’s marketing changes. As was her usual practice, she looked at previous ad campaign history and website traffic to gather data to use in planning the company’s website redux.

“Typically, in marketing, you look at how banner ads or display ads perform in other locations,” Pierangeli said. “You take into account personas and the demographics for your audience. Then you use that data to make assumptions and decisions based on what you know — but that legacy data isn’t necessarily right.”

Feedback Loop exists to provide rapid consumer feedback, so Pierangeli didn’t have to rely solely on that legacy data. She did what Feedback Loop tells its clients to do: She tested.

Marketing designer Michelle Baker created mock-ups of two new website designs. Option A had a clean white background, using graphics to add some color. Option B had blue elements and a darker blue background. Based on the legacy data they had, as well as the popularity of white-background websites, Pierangeli and Baker were certain their audience would prefer Option A. They did an A/B test using the Feedback Loop platform.

To their surprise, respondents favored Option B.

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In addition to testing the color, layout, and user experience for the website, they tested whether to use clickable dropdowns, so all text information would be accessed by clicking buttons. 

“Personally, I like to interact with websites that way, and I thought other people would, too,” Baker said. They used the Feedback Loop platform to test their hypothesis that users would prefer a cleaner experience that would encourage them to click through to get the specific information they wanted. 

Again, Pierangeli and Baker were surprised. The overwhelming response to the test was that users wanted everything to show at once — no clicks needed — because they didn’t want to have to do any extra work to get information.

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“That was not a behavior or a response we thought we were going to have,” Pierangeli said. “I realized you can use as much data as you want from previous campaigns, but you’re going to be missing out on what consumers actually want. In our case, we want product professionals, marketing professionals, research professionals, UX, and innovation teams to find the website useful and easy to navigate.

“All the data we had from other channels and the historical information — from a few months ago to a few years ago — did not tell us this. We didn’t learn this until we tested the different layouts, the different colors, the different ways text was presented. I was surprised. I’ve been doing this for a long time — a really long time — so you’d think I’d have a fairly decent understanding of what consumers would want. I have an understanding of target personas and what’s important to them. That’s why we do persona exercises. But without using Feedback Loop, we would’ve been completely wrong.”

The new blue website launched on February 14, 2022. Since then, Feedback Loop has seen traffic increase — and that doesn’t even include repeat users. The number of new website visitors doubled.

“In a week, we got a month’s worth of lead guarantee.”

On the heels of the website’s success, Feedback Loop launched a content syndication program. The company handling the promotion said it should take a month to reach Feedback Loop’s guaranteed lead goal. 

Before launching the promotional ad, Pierangeli and Baker tested the advertising and messaging for their promotion using the Feedback Loop platform. For the ad, targeted at both marketers and product teams, Baker created one version using a cartoon treatment and one using screenshots. The majority of the audience-tested chose the screenshot version. That’s the one they launched.

Feedback Loop got their entire lead guarantee in one week.

“In a week, we got a month’s worth of lead guarantee, which is great because that gave us the entire month to nurture them. We were able to use the time we saved by testing to nurture those leads and then start converting them,” Pierangeli said. They’ve converted 30% of those leads to MQL — so far.

For the next iteration of the ad, targeted at marketers, Baker tested three concepts with the Feedback Loop platform: one with cartoons, one with screenshots, and one with a combination of both. The third option — a combination of styles — was chosen by 46% of respondents, so that’s the ad they’ll be launching. 

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“As a designer, before I started testing concepts, I never really knew how an audience would react to what I was creating,” Baker said. “Using the Feedback Loop platform lets us target exactly who we want to target, and the more data we have, the better the end results will be. Now, when I create something, going in blind is pointless since I have the ability to know what the audience prefers before we ever launch.”

“You already know going into it what your consumers want.”

The lessons she learned by using Feedback Loop for Feedback Loop changed how Pierangeli looks at marketing campaigns.

“When marketers build out a campaign plan, they typically build out a first draft, revision time, second draft, final draft, then launch date,” she said. “Unfortunately, a lot of times after a launch, the campaign does not perform and deliver the number of leads or MQLs or conversions to opportunities that marketing needs to build the lead funnel and help sales convert. That means marketing will have to go back and add new content to their campaign or do other types of activities. Basically, they’ll have to do more work in order to get to their goal.”

By building rapid consumer research into marketing processes early on, marketers can save themselves and their teams hours of work down the road and, potentially, prevent failure of a launch. Testing in the Feedback Loop platform only takes a couple of hours, and it can de-risk decisions, whether it’s what color to put on your website or what messaging to use for a promotion. You don’t have to wait weeks or months for traditional research methods to produce insights that are already in hindsight when you finally get them. A little foresight goes a long way toward ensuring you launch successfully.

“You need to bring in the voice of your consumers to have true data to make your marketing campaign successful,” Pierangeli said. “Then you can launch with confidence and know you’re going to get what you’re trying to get, whether it’s a number of leads or delighting your customers or a higher conversion rate. For all the things you are being held accountable for, you improve your chances of success by testing in advance.

“It’s OK to be wrong. But you need to understand that, even though you may have been doing this for years, even though you may have the most well-written persona until you actually ask your potential customers what it is they want, you really don’t know.” 

Still skeptical? Don’t take our word for it, try Feedback Loop yourself for FREE!


About The Author

Dont miss out on what your customers actually want
Feedback Loop is the research platform that marketing teams rely on to test products, messages, and ideas directly with target consumers before bringing them to market. Fast-growing companies and established market leaders like Ad Council, AARP, Experian, Swiss Re, Travelers and Best Buy trust Feedback Loop to validate market fit quickly, create stronger products and messages, and launch confidently. The company’s technology allows business users to conduct rapid concept testing, early-stage discovery, and qualitative feedback at scale so that they can make decisions based on data, rather than subjective opinion.


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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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