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  • How Brands and Agencies Are Experimenting With ChatGPT From Copywriting to Chatbots | Patrick Kulp - Adweek
  • ChatGPT might change advertising — but it won’t revolutionize it | Chris Kelly - Marketing Dive ... Even though its unlikely to upend the ad world any time soon, the buzzy conversational AI model could prove useful for savvy marketers
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Meta’s AI Advertising Tools

• [https://www.searchenginejournal.com/meta-introduces-new-ai-tools-for-advertisers/497805/#close Meta Introduces New AI Tools For Advertisers

Meta rolls out AI ad features to boost creativity and productivity for advertisers after positive tests. | Matt G. Southern - Search Engine Journal]

Meta is rolling out the following three tools to advertisers:

• Background Generation: Allows advertisers to automatically create multiple backgrounds to complement their product images.
• Image Expansion: Seamlessly adjusts image sizes to fit different ad formats like Facebook Feed or Instagram Reels.
• Text Variations: Generates multiple versions of ad copy using the advertiser’s original text. The AI highlights product features and suggests text to better reach target audiences.

Lead Scoring

• Automated Scoring

Lately

• Lately

Your unique voice. Tailored to your unique audience. At scale.

Lately's AI learns any brand or individual voice and the exact content that will convert your target audience, delivering higher social media performance for sales and marketing teams across the globe. And by higher, we mean waaaaay higher. Lately AI is a social media post generator that uses artificial intelligence to learn any brand or individual voice and the exact content that will convert their target audience, delivering higher social media performance for sales and marketing teams across the globe1. Lately AI’s artificial intelligence studies what your social media audience wants to watch, hear or read and then builds you a custom writing model, based on what it learns. Then it uses that writing model to automatically repurpose any longform video, audio or text into dozens of pre-tested social media posts, based on what it learns.

NLP -Based Brand Awareness and Market Research

It’s difficult to develop actionable business strategies when you don’t know how customers feel about your brand. By using Sentiment Analysis and getting the most frequent context when your brand receives positive and negative comments, you can increase your strengths and reduce weaknesses based on viable market research. NLP-based software analyzes social media content, including customer reviews/comments, and converts them into insightful data. Natural Language Processing (NLP) Use Cases For Business Optimization | Ilia Iorin - MobiDev

How Does This Algorithm Work?

1. Analyze an entire list of comments and classify them using a Sentiment Analysis model.
2. Get the most frequent words and phrases from both positive and negative comments.
3. Perform market research based on the data collected.

Based on this algorithm, it is possible to assign a value to the output information. This value might be considered as a positive, negative, or neutral emotion. Marketers can use this data to make more informed decisions in their marketing strategies and campaigns.

NLP-Powered Competitive Analysis

Most founders will conduct competitor analysis and research when starting a business. This task enables them to better understand their market, competitors, customers, and other important details about their industry. There are dozens of tools available to help entrepreneurs monitor their competitors. NLP-powered engines like Zirra simplify the process for automatically building a competitive landscape. When Zirra analyzes something, it gathers a list of companies and ranks them from zero to one. This rank shows how closely these companies are related to each other using a multimodal semantic field. The algorithms solutions like Zirra create the list of companies by scanning the Internet for articles and putting the data into an NLP module that closes out semantic relationships between companies. Natural Language Processing (NLP) Use Cases For Business Optimization | Ilia Iorin - MobiDev