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10 Ways to Use AI for Better Ads

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10 Ways to Use AI for Better Ads

In our recent post about OpenAI’s ChatGPT, we unpacked what the tool is and how it works, and why we don’t see its popularity as a threat to search engines like Google. In this post, we’ll be diving further into the OpenAI Playground, and how PPC marketers can use that tool along with ChatGPT to save time on research, ideation, execution, and more.

The Playground is a basic UI built on top of OpenAI’s API. OpenAI has recently added ChatGPT to their API. When accessing ChatGPT through this UI, users have the ability to customize the model being used for each query (or continuation of the “conversation”) as they progress through their work.
 

How to Write ChatGPT Prompts

 
When working with tools like ChatGPT, it’s important to be as clear as possible in what you ask, and how you ask it. As you write prompts for ChatGPT to work with in retrieving and displaying the information you need, remember that you are giving instructions in a more direct way than you might if conversing with a colleague.

While another person may have contextual insight into what you’re really looking for with your question, tools like ChatGPT take language more literally, tailoring their response to the information you explicitly provide in your request.

ChatGPT will consider every element of your ask, so don’t give generic prompts. The more information you provide the tool in your prompt, the better it will be able to generate what you’re looking for in its response.

Example: Let’s assume you’re using ChatGPT for dinner inspiration…

  • Generic prompt (least likely to return what you’re looking for): Give me 10 recipe ideas for a home-cooked dinner
  •  

  • Slightly better prompt: Give me 10 recipe ideas for a home-cooked dinner with squash as the primary ingredient
  •  

  • Even better prompt: Give me 10 recipe ideas for a vegetarian home-cooked dinner that I can make in an air fryer in 20 minutes or less with squash as the primary ingredient

See here and the examples below for more information and inspiration on crafting strong prompts.
 

How to Start Using the OpenAI Playground for PPC Marketing

 

To get started with the OpenAI Playground, create an account using your personal email address at https://platform.openai.com/. Once you’re logged in, navigate to the Playground page to access the interface and begin making requests.

screenshot of open ai playground

The right-hand sidebar provides some options for different modes and GPT submodels, as well as Codex models, which are primarily used for generating code. The Complete mode is selected by default, along with the text-davinci-003 model. The other models within the “Complete” mode are typically faster and cheaper but are also less advanced, so they may be viable alternatives depending on the nature of your needs. ChatGPT can be accessed via the Chat mode and is what we used for the examples below.
 

OpenAI Playground Tokens and Settings

The billing model for using this service is constructed around the concept of tokens. Each new user gets $18 of free credit (900K tokens) that can be used during their first 3 months from sign up; after that, it’s $0.02 for every 1,000 tokens.

There is a token counter in the footer of the Playground display which can help you keep track of how many tokens you are using. 1 token is approximately 4 characters (or 0.75 words), with token usage measured against both your prompts and the responses.

You can limit the number of tokens that can be used in a response by toggling the Maximum length slider on the right hand sidebar, which is set to a 256-token cap by default. If you make an inquiry that requires an elaborate response, you may see the response get cut off before completion; in this case, it may be helpful to increase the Maximum length.

There is a maximum of 4,000 tokens that can be used in a single “request” (single session), i.e. a series of questions within the same Playground. Once you’ve hit that limit, all you need to do is delete your earlier prompt questions and answers, or save them as a “preset” before moving on to a new prompt.

open ai playground screenshot with arrow highlighting button to save your preset

Note: The use of tokens is required in the OpenAI Playground, but not when using ChatGPT natively. As of the time of this writing, ChatGPT is still free to use. A paid version of ChatGPT with advanced features and benefits is also available—ChatGPT Plus.
 

OpenAI Playground and ChatGPT Temperature

open ai playground screenshot highlighting where you can adjust the temperature

The Temperature setting controls randomness; lowering the temperature results in less random completions. As the temperature approaches zero, the model will become deterministic and repetitive. For most PPC purposes, we recommend a temperature range of 0.6-0.8 as optimal.
 

10 Ways PPC Marketers Can Use GPT to Improve Workflow Efficiency

 

“In terms of use cases, there are many different ways in which people working in all industries, and all fields of expertise, can lean on tools like ChatGPT and the OpenAI API to improve their efficiency and automate certain redundant tasks. This technology can help with smaller, repetitive tasks, such as breaking down a long document into a bullet point summary. However, when it comes to critical thinking and understanding the implications of things, I would be very cautious about over-relying on AI.”

Portrait of Josh O'Donnell
Josh O’Donnell, Sr. Strategist, Paid Search at Tinuiti

A couple of important things to consider before diving into our examples below:

  1. ChatGPT/GPT language models training data cuts off in 2021. They do not have any knowledge of current events, and cannot accurately respond to questions about such topics. ChatGPT is not aware of things like who won the big game last night; it is not even aware of what day it is.
  2.  

  3. ChatGPT/GPT language models do not have access to the internet or any other kind of external data retrieval; they can only answer questions based on the knowledge acquired from their training data. They cannot verify facts or provide references, only generate responses based on their own internal knowledge and logic.

 

1. Keyword Research

Whether you work on the Paid Search side of marketing, or the organic side, you know how important (and time-consuming) thorough keyword research can be. One of the most important rules of marketing is to know your audience—which includes knowing what they want, and how they search for it—and the OpenAI Playground can help you find those answers faster.

Sample Scenario:

You’re just getting started building a new PPC campaign for a client that sells running shoes. To kick off your initial keyword research, you want to get an idea of which related keywords are being searched most often. You want a Top 20 keyword list, and GPT can generate a list for you to help you get started.

The prompt: Provide me with a list of 20 running shoe keywords for google ads, list them in descending order based on expected search volume in the United States.

The result:

screenshot showing how open ai playground can help with keyword research

Note that since OpenAI enables you to continue the “conversation” beyond your first query, we also asked it where it got the returned information from (above photo); it’s always important to consider the source when relying on AI-generated responses. This is a good example of why it’s important to take the outputs with a grain of salt, using them as inspiration to get you started, but not the finished product.
 

2. Competitor Research

Comprehensive competitor research and analysis is a crucial part of a marketer’s job, helping inform and guide their campaigns. However, just like keyword research, this is also an ongoing, time-consuming process.

When you work in a complex space—or your products or services are part of different spaces—it can sometimes feel overwhelming to assure you’re accounting for everything and everyone. The OpenAI Playground can help make short work of initial research in a variety of ways.

Below, we showcase the results provided by three different prompts aimed at unpacking competitor insights instantly…

Sample One: Ask for a list of top US competitors ranked largest to smallest with accompanying website URLs to get ideas for custom audiences, messaging, and product positioning.

screenshot showing the results when asking open ai tool for a list of top running shoe companies in US ranked largest to smallest with website URL

Sample Two: Ask objective questions about your competitor and their product.

screenshot showing results when asking open ai playground to describe advantages of a competitor product compared to another product, including which is more geared toward price-conscious consumers

Sample Three: Ask about pain points for competitor products, and use that info to inform your own product messaging & marketing strategies.

example of using open ai to uncover competitor pain points
 

3. Generate Ad Copy

In the below examples, we used the URL of the ad’s landing page to help inform the suggestions from ChatGPT, providing character limits in our prompt to help direct the output. If your original result doesn’t meet your expectations, continue to sculpt with additional follow-up prompts. GPT cannot access these web pages in real-time, but it can use the context from the URL structure to inform the output.

example of using open ai playground to help with ad copy headline ideas

example of using open ai playground for help with writing google ads descriptions

“It’s more of a utilitarian thing, where you provide the tool with the data, and ask it to manipulate that data for a better output. One example is to provide it with a web page, and ask it to generate some ad copy based on the URL text; it can provide fifteen or twenty options within seconds. I would never recommend simply taking those headlines and pasting them into an ad, but you can now start off your project with a list that you or a teammate can garner inspiration from, and strategically refine or tweak to fully optimize. This gives the practitioner more time to spend on critical thinking, with ChatGPT taking away the more mundane elements of the task.”

Josh O’Donnell, Sr. Strategist, Paid Search at Tinuiti

The copy itself should be quality, but the important aspect of parity between what you’re saying on the ad and what’s on the page can be efficiently solved for.
 

4. Translations of Copy & Headlines

In the example below, we asked ChatGPT to translate the 5 English language ad copy options generated above into Spanish. Additional options currently available include French and Japanese translations.

example of using open ai playground for copy translation
 

5. Answer Questions on Demand

Similar to ChatGPT, the OpenAI Playground can also be used for Q&A purposes. Just remember that answers can only be generated based on the tool’s current knowledge.

screenshot of Q&A information from open ai website

Source: https://platform.openai.com/examples/default-qa

This can be especially helpful during calls with clients when you need a fast and simple answer to keep the conversation moving forward.
 

6. Simplify Complex Concepts

When talking about digital marketing with other practitioners, we know our audience ‘speaks the same language’ and certain questions, concepts, or outcomes need no further explanation. However, those same complexities aren’t always as easy to communicate to newer team members or clients.

Even when our day-to-day contacts are digital savvy, they often have to convey information to those higher up the chain in their organization who might not be as familiar with the lingo, or even why certain things they’re highlighting matter.

For scenarios like these, OpenAI’s Summarize for a 2nd grader feature can prove especially helpful. Once you have the foundation laid out, you can add more color and context to paint the fuller picture without worrying the basics would be glazed over.
 

7. Generate Product Descriptions & Names

Working with accurate, well-optimized product names and descriptions is one of the most essential elements of effective marketing. Strong, descriptive names and product information help search engines and users alike in uncovering the items that will be most relevant to their needs.

screenshot from open ai website showcasing how their product name generator works

Source: https://platform.openai.com/examples/default-product-name-gen

While names and descriptions will always require a human touch for proper refinement, tools like ChatGPT and the OpenAI Playground can provide a great starting point to build from.
 

8. Parse Unstructured Data

The OpenAI Playground makes it easy to organize long-form text into a table format. Simply specify a desired structure, provide a few examples to work from, and enjoy the time saved.

screenshot from open ai website showing a prompt for parsing unstructured data

Source: https://platform.openai.com/examples/default-parse-data

screenshot from open ai website showing a response from a prompt asking for structured data

Source: https://platform.openai.com/examples/default-parse-data

 

9. Call Summaries & Follow-Ups

Call summaries are an important aspect of keeping organized and ensuring everyone working on a project is clued into plans and discussions, even if they weren’t part of the original calls. Putting together these comprehensive, valuable recaps can sometimes take as much time as the call itself, but GPT can help.

Below, we asked GPT to write a follow-up email based on a call summary.

screenshot of response when asking GPT to write follow-up email based on call summary
 

10. Convert text from first-person to third-person

We have found this feature especially helpful for turning our own notes into actionable steps someone can follow when shared. For example, if you want to share steps for completing a process with a team member or client, you can type naturally using “I” language to convey those directions. You can then quickly convert the text to third-person, adjusting as necessary for optimal clarity.

Screenshot from Open AI website showing how third-person converter works

Source: https://platform.openai.com/examples/default-third-person

 

Conclusion

 
The capabilities of advanced tools like OpenAI’s Playground and ChatGPT can make short work of mundane tasks, help quickly generate ideas and direction, and ultimately save us all time to focus on the elements of marketing and advertising where our expertise and strategic insights can truly shine. If you’re interested in more under-the-hood information about how ChatGPT works, check out Stephen Wolfram’s breakdown of ChatGPT. Also see here for additional application options, or reach out today to learn more about how our Paid Search team can bring your PPC advertising results to the next level!
 

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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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