TikTok launches new ad performance measurement tools

TikTok has launched two new ad performance measurement tools:

  • Cross-Channel Partners – which analyzes how ads perform across different online platforms and touchpoints before a purchase is made to understand their overall impact.
  • Lift Partners – this assesses the effectiveness of ads on brand metrics, sales, physical store visits, and viewership for shows or media.

Given that conventional last-click attribution models fail to capture four out of five purchases attributed to TikTok, these new features are designed to offer marketers improved insights into the effectiveness of their campaigns on the social platform.

Why we care. A clearer understanding of the customer journey reveals the returns from your advertising investments, empowering you to make informed decisions about your ad spend moving forward.

Cross-Channel Partners. This feature analyzes the impact of TikTok ads across various marketing touchpoints before a purchase is made. It focuses on two key areas:

  1. Multi-touch attribution: This involves measuring the effectiveness of TikTok advertising across digital touchpoints. It provides marketers with a deeper understanding of the customer’s path to purchase, helping them identify the most effective channels to achieve their goals.
  2. Post-purchase survey (PPS): This survey-based tool integrated with e-commerce stores, helping advertisers understand how customers discover their product/brand and gathers attitudinal metrics (how customers feel about your product). By using the voice of the customer as a source of truth, PPS helps advertisers to gain a more complete view of attribution, contributing to a deeper understanding of advertising impact.
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Lift Partners. Lift partners gauge the impact of TikTok advertising, focusing on four main areas:

  • Brand lift: This uses an engaging, in-feed polling experience to measure the impact of ads on brand lift metrics like Ad Recall, Awareness, Attitude, and Favorability.
  • Sales lift: Determines how effective advertising is in driving both online and offline sales, especially
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Top 26 AI Marketing Tools to Grow Your Business in 2024

The use of artificial intelligence (AI) in marketing has hit the mainstream. You would be hard pressed to find companies—big and small—that don’t use top AI marketing tools to promote their brands or businesses.

If you’re a blogger, an e-commerce entrepreneur, or an affiliate marketer, taking advantage of AI-powered marketing tools should be a part of your business game plan. With it, you can run and put together an effective marketing strategy that would allow you to hit your goals faster.      

What is an AI Marketing Tool?

An AI marketing tool is a software or platform that uses artificial intelligence technology to create automated decisions. These decisions are based on collected data that’s analyzed and interpreted together with the market trend. The goal is to develop a marketing strategy that anticipates the buyer’s next move. 

All of this is done in real time without the intervention of an actual human. It’s this capacity to make automated decisions at lighting speed that makes AI marketing tools for business so formidable.


Best AI Marketing Tools You Should Be Using Today

Top

ai marketing tools

2024

Jasper.ai

Price (Monthly): $40 for Starter (20,000 words) / $82 for Boss Mode (50,000 words)

Best Features:

  • Content Generation
  • Tone of Voice Settings
  • Machine Learning
  • Plagiarism Checker
  • Customizable Templates

Once known as Conversion.ai, Jasper is an advanced AI marketing tool intended to create high-quality ad copy, emails, landing pages, articles, or social media posts. This tool uses the GPT3-model developed by OpenAI to write human-sounding text. It also has built-in templates for AIDA, Feature to Benefit, PAS, and Before-After-Bridge Framework. All you need to do is add your brand name or product, and it will generate the copy for you. 

E-commerce shops can also produce product descriptions using this powerful AI. It can generate Amazon product bullet points

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Google plans RISC-V Android tools in 2024, wants developers to “be ready”

Google plans RISC-V Android tools in 2024, wants developers to “be ready”

Google

Android is slowly entering the RISC-V era. So far we’ve seen Google say it wants to give the up-and-coming CPU architecture “tier-1” support in Android, putting RISC-V on equal footing with Arm. Qualcomm has announced the first mass-market RISC-V Android chip, a still-untitled Snapdragon Wear chip for smartwatches. Now Google has announced a timeline for developer tools via the Google Open Source Blog. The last post is titled “Android and RISC-V: What you need to know to be ready.”

Getting the Android OS and app ecosystem to support a new architecture is going to take an incredible amount of work from Google and developers, and these tools are laying the foundation for that work. First up, Google already has the “Cuttlefish” virtual device emulator running, including a gif of it booting up. This isn’t the official “Android Emulator”—which is targeted at app developers doing app development—Cuttlefish is a hardware emulator for Android OS development. It’s the same idea as the Android Emulator but for the bottom half of the tech stack—the kernel, framework, and hardware bits. Cuttlefish lets Google and other Android OS contributors work on a RISC-V Android build without messing with an individual RISC-V device. Google says it’s working well enough now that you can download and emulate a RISC-V device today, though the company warns that nothing is optimized yet.

The next step is getting the Android Emulator (for app developers) up and running, and Google says: “By 2024, the plan is to have emulators available publicly, with a full feature set to test applications for various device form factors!” The nice thing about Android is that most app code is written with no architecture in mind—it’s all just Java/Kotlin. So once the Android RunTime starts spitting out RISC-V code, a lot of

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Google Keep’s Android app is getting formatting tools and version history

Good news for Android-toting Google Keep users: you’re finally getting the text formatting options the app has so desperately needed for years. Google announced this week that the ability to bold, italicize, and otherwise transform text in your notes is rolling out now, and you should start to see it in the app soon. (I don’t have it yet, but Mishaal Rahman and a few others actually spotted the feature ahead of its official launch, so it seems to be coming fast.)

The new Keep features are more in the “should have been here all along” category than they are shiny new things, but they’re still a welcome addition to the app. And actually, Google has been paying an unusual amount of attention to Keep recently: users got a new homescreen widget earlier this year, and you can now open multiple Keep windows at a time on your device. Google’s also slowly rolling out version history so you can see all the changes you’ve made to your notes over time.

Keep is, if you didn’t already know, an excellent note-taking app. It’s fast, available on Android, iOS, and the web, and it manages to be both extremely simple and quite clever. Paste a link into a note, and the card reformats as a rich preview so you know exactly what it is. A single-line note just looks like a Post-it, but a longer note looks more like a document. You can draw in a note; you can record audio in a note; you can set reminders in a note! And because this is a Google product we’re talking about, it’s all searchable and accessible in the sidebar of a bunch of other Google products.

The new formatting options make Keep even more powerful — while still being super simple.
Image:

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Google to Add Bard AI Tools to Android, Home Virtual Assistant in Chatbot Push

Google will soon release a version of its virtual assistant that is powered by the company’s Bard artificial intelligence technology, helping users handle more complex tasks.

The new offering, called Assistant with Bard, will be available in a test phase shortly and then roll out to the general public in the coming months, the company said Wednesday. The release will equip the Assistant, which helps users of Android and Google devices complete tasks and find information, with some of the capabilities of Bard, a chatbot that is the company’s answer to OpenAI’s wildly popular ChatGPT.

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Watching the detectives: Suspicious marketing claims for tools that spot AI-generated content

A common trope crossing the science fiction and mystery genres is a human detective paired with a robot. Think I, Robot, based on the novels of Isaac Asimov, or Mac and C.H.E.E.S.E., a show-within-a-show familiar to Friends fans. For our purposes, consider a short-lived TV series called Holmes & Yoyo, in which a detective and his android partner try to solve crimes despite Yoyo’s constant malfunctions. Let’s take from this example the principle – it’s elementary – that you can’t assume perfection from automated detection tools. Please keep that principle in mind when making or seeing claims that a tool can reliably detect if content is AI-generated.

In previous posts, we’ve identified concerns about the deceptive use of generative AI tools that allow for deepfakes and voice cloning and for manipulation-by-chatbot. Researchers and companies have been working for years on technological means to identify images, video, audio, or text as genuine, altered, or generated. This work includes developing tools that can add something to content before it is disseminated, such as authentication tools for genuine content and ways to “watermark” generated content.

Another method of separating the real from the fake is to use tools that apply to content after dissemination. In a 2022 report to Congress, we discussed some highly worthwhile research efforts to develop such detection tools for deepfakes, while also exploring their enduring limitations. These efforts are ongoing with respect to voice cloning and generated text as well, though, as we noted recently, detecting the latter is a particular challenge.

With the proliferation of widely available generative AI tools has come a commensurate rise in detection tools marketed as capable of identifying generated content. Some of these tools may work better than others. Some are free and some charge you for

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