How will artificial intelligence help deliver traffic?

Publication date: 12 Feb 2024

Artificial intelligence, or neural networks, is the new internet reality. It seems to be everywhere: not only intelligent support bots are waiting for us, but also AI in search results, email clients and optimization of advertising costs. With more services and opportunities emerging every day, it’s time to understand what to work with and how to use it.

In the new 3SNET article, we’ll look at how neural networks can be used to build an analogue of a media buying team and effectively send traffic to betting and gambling.

Neural networks are mathematical models that are capable of learning. The development of neural networks began in the last century and has continued into the present day.

But on 30 November 2022, everything changed: that’s the date of the public release of ChatGPT. The release of ChatGPT attracted so much attention because a chatbot could now write code, create text, translate information, give accurate answers and participate in brainstorming sessions. The ChatGPT could understand the context of the dialogue and improve answers, look at information from different angles, etc. It remains the most popular language model. According to Reuters, the number of active ChatGPT users reached 100 million in February 2023.

One year later, in February 2024, Similarweb estimates that the traffic to the chat.openai.com site is already 1.6 billion people.

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Neural networks are a great tool, everyone can benefit from them and make their work easier. Nevertheless, it is necessary to evaluate and verify the answers of chatbots in a reasonable way. All information should be checked and tested, preferably with the participation of experts in the chosen field.

  • For example, in May 2023, attorney Stephen Schwartz of Levidow, Levidow & Oberman used the bot’s prompts to build a line of defence. In court, Stephen recklessly presented case law that Chat had made up. In doing so, he set himself and his client up for failure.

Firstly, the “memory” of some neural networks is limited to the information available at the time they are activated.  In other words, the AI learns and trains on the data of the entire Internet, but only on the data available at the time of release. For example, the first version of ChatGPT was limited to knowledge up to 2022. The latest version of the chat was released on 27 September 2023. It is therefore pointless to ask neural network assistants about events that happened after that date.

This is more likely to be the case with generative artificial intelligence neural networks or large language models. In everyday life, we call them “virtual interlocutors” or “chatbots”.  They need very precise, detailed queries – prompts. Let’s look at some examples.

AI Prompt Examples for Affiliate Marketing

Here are some prompts that media buyers can use with ChatGPT:

  • Evaluate the effectiveness of targeting strategies for [product name] on [platforms] and suggest optimizations.
  • Find the most effective keywords for [name]’s advertising campaign using [tools].
  • Suggest improvements to [name]’s ad creative based on performance analysis.
  • Evaluate the performance of [name]’s landing page and suggest changes to increase conversions.
  • Identify the best countries for media buying for [name of product] and justify your choice.
  • Compare cost per click (CPC) on different platforms for [name of campaign] and suggest optimizations.
  • Review competitors’ advertising strategies in [niche name] and highlight successful approaches.
  • Suggest new traffic sources for [name] campaign based on trends and data.
  • Propose budget optimization strategies to increase the ROI of the [name] campaign.
  • Formulate several alternative headlines for the [name] ad and identify the best one.
  • Identify the most profitable targeting for [name of product] and propose scaling strategies.
  • Evaluate the effectiveness of [name]’s retargeting strategy and suggest improvements.
  • Determine the optimal time to show [name] ads given the target audience.
  • Suggest audience segmentation strategies for the [name] campaign and justify choices.
  • Propose a plan for scaling the successful [name] ad campaign to new markets.

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How do neural networks help with copywriting?

Text chatbots are the best option for writing code, text and generating ideas.

For example, the 3SNET team uses Bard to write summaries of recent sporting events. We also use chatbots to generate ideas and descriptions for YT doorways, content for white doorways and ideas for semantics. GPT allows you to create a Telegram bot for use in media buying as an autoresponder.

Here’s a list of the best neural networks for text generation:

Some links to tools may not be available. It depends on the country you live in, usually you have to find a way to get access. This way is different for each neural network, we suggest you use Google search.

  • One of the most popular services is ChatGPT.
  • Google Bard.  While this material was being prepared, it became known that Google is replacing the Bard neural network with Gemini. In the near future, the company will launch Gemini Ultra, its most powerful model to date, with a large number of languages. However, this version will be a paid one – $20 per month.
  • YandexGPT, which is used in the Alice voice assistant, among others.
  • GigaChat is a neural network model with different capabilities from Sber.
  • Poe platform with access to 4 neural networks simultaneously: ChatGPT, Claude, Sage and Dragonfly.

The main rule when working with GPT models is that success depends on a correctly formulated prompt. Remember that neural networks understand the context of the conversation. The longer you communicate with it, the better it will understand you and offer more appropriate options. You should use different tools, compare results and develop unique techniques for working with them. An unconventional approach is half the battle in the creative space. Besides, many AI services already have built-in add-ons and ready-made templates, the main thing is to search well.

How to choose AI-enabled tools for image-on-demand generation

Stable Diffusion is used by many services and websites. It is a software that converts the prompt text into an image according to the request. The system works on open source principles, so the web is full of different modifications and generators in a certain style.

Midjourney works on the big language and diffusion model, with the AI creating illustrations based on textual prompts. The bot is online, requires no installation and runs through a browser. It is available in Russian, English, German, French, Spanish and Portuguese. 15 images per day are free.

DALL-E is a neural network from OpenAI, the developers of ChatGPT. It generates high quality images based on text descriptions in English. Several parameters can be used to create unique content: colour, theme, style.

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AI applications: what are the possibilities?

From a broader perspective, AI is already being actively implemented in all areas of life. New versions of software are being released with a built-in generation line.

For instance, generative design using neural networks has recently become available in Photoshop. New versions of Photoshop have introduced advanced artificial intelligence technologies that significantly improve image processing. AI helps to automatically improve the quality of photos, removing noise, correcting colour defects, and enhancing sharpness and detail. Machine learning also enables Photoshop to automatically enhance objects in photos, improve portrait shots, and provide new tools and features for creative editing.

Notion AI is a service from Notion that is built into the application. You can use it 10 times before it becomes a paid service. It can create a table or text content. Notion AI helps by providing the ability to automatically create UI mockups based on set parameters, allowing for quick prototyping and saving design time. Likewise, it can help to automatically generate code based on given parameters, speeding up the development process and reducing the chance of errors. Notion AI can also be used to analyze code and identify potential vulnerabilities and bugs.

Useful neural networks for traffic capture: 3SNET Recommendations

On behalf of the 3SNET editorial team, we recommend other tools that use AI:

DeepL Translator for taking intonation into account when translating. It has an AI editor function. It supports 32 languages. Useful for creating accurate prompts. After all, many neural networks and artificial intelligence services only work in English. The translator can also help to check the content, taking into account the GEO.

Sider is a sidebar with built-in GPT, image generator, and Claude and Gemini models. It works directly in the browser, and the basic version of ChatGPT 3.5 comes with up to 30 free requests per day.

Veed.io is an advanced AI video editor. The coolest part is the multiplayer mode, like in Figma. Add annotations, stickers and other elements for catchy videos. Automatically resize videos from one format to another. One of the most exciting features is the translation of Youtube videos into text, although the free version is limited to 10 minutes.

waifu2x is a tool for improving image quality. It is a bit complicated to deal with artefacts, but it does support the webp format.

Zyro is a similar tool to the previous one. It only accepts images with a resolution of up to 750×750, increasing to 2500-3000 pixels. It also has many other features.

Topaz is a paid AI photo and video editor. Improves quality, offers editing options and solves turnkey tasks.

SnatchBot is a platform for creating and deploying chatbots. It allows users to create bots to communicate with customers, automate tasks and provide information. SnatchBot also has natural language processing models that, when combined with machine learning tools, enable the creation of chatbots that can analyze user intent.

What neural networks are you using? What tools are you missing? Any ideas? Share your information!

What is the need for neural networks in media buying?

The use of neural networks is gradually becoming a new standard of work in the digital environment. They allow you to receive and implement new ideas. Artificial intelligence can check spelling or write a completely new text, generate an image on demand or improve an illustration, help select information or create an assistant to answer questions.  Code, spreadsheets, writing – the possibilities of AI, although limited, are very impressive.

The main advantage of neural networks is that they are assistive tools that can take over some of your current tasks, freeing up time for the creative process. Communicate more with colleagues and friends at work, ask for actual schemes of operation and interaction with neural network utilities. Through trial and error, you will be able to understand what specific actions should be taken at any given time.

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