Boost your Marketing Game with Conversational AI in a Post-Cookies World

Google has announced that it will phase out the usage of third-party cookies in Chrome by the end of 2024, joining a growing list of browsers that have discarded the dreaded tracking technique.

Soon when cookies will be out of the picture, you will need a new tactic to track down user behaviour to keep your marketing game on. You must circle back to contextual marketing and leverage conversational AI to make the most out of it.

Before diving deep into it, let’s first understand what cookies and contextual marketing are.

What are Cookies?

Cookies are small codes added to your web browser when you visit any website. These codes contain information that enables the web to store your actions, log-in information and other activities, such as shopping cart content etc., to cater for you with a customised experience. Advertisers make the most of this information by identifying the right target audience for their ad.

What is the Cookie-less Web?

A cookie-less web is an environment where websites and web applications do not use cookies to store user browsing history or behaviour information.

A cookie-less web can be better for user privacy and security since it limits the amount of personal information stored and shared between websites. Furthermore, a cookie-less web can also improve website performance and reduce page load times since cookies are not transmitted between the client and server. This can result in a faster and more efficient browsing experience for users.

On the contrary, with cookies, third-party advertisers and other entities can track users’ online behaviour and target them with targeted adverts. As a result, this might be a major hindrance to your marketing path. How can you provide a personalised ad experience to the user? That is achievable with contextual marketing.

What is Behavioural and Contextual Marketing?

Behavioural and contextual marketing are two related but distinct approaches to targeting and engaging with customers.

As the name suggests, behavioral marketing involves tracking customer behavior. Behavioral marketing uses information such as browsing history, IP addresses, and cookies to create a comprehensive user profile and then personalize adverts appropriately.

Contextual marketing, on the other hand, involves targeting customers based on their current context or situation. This could include location, time of day, and device type, the website you are on. For example, you’re reading a shoe-related blog and notice a Nike or Adidas ad coming up on the screen. This is nothing more than contextual marketing, in which user data is not monitored to advertise but they are put on websites or pages related to the material the user is browsing.

Conversational AI and Contextual Targeting

Behavioral and contextual marketing aims to deliver customers more relevant and personalized marketing messages. Behavioral marketing relies heavily on cookies for data, while contextual marketing does not. This makes contextual marketing a need of the hour. Contextual marketing is advertising where the ads are targeted based on the web page’s content or the user’s search query context. When contextual targeting and conversational AI are used in conversational marketing, it yields more valuable results for the business.

How to leverage conversational AI in Contextual Marketing?

To leverage conversational AI in contextual marketing, businesses can take the following steps:

• Identify the right channels: Businesses should identify the most relevant channels to their target audience that can be used to deliver a conversational AI experience. This may include messaging apps, chatbots, or voice assistants.
• Develop a conversational strategy: Businesses should develop a strategy for engaging with users through conversational AI, including the types of questions and prompts used to gather data about the user’s context and interests.
• Gather data: Businesses should use conversational AI to gather data about the user’s current context and interests, such as their location, device type, or current activity. This data can be used to deliver more targeted and personalized experiences.
• Deliver targeted content: Based on the data gathered through conversational AI, businesses should deliver targeted content or offers relevant to the user’s current context and interests. This may include targeted ads, personalized recommendations, or exclusive offers.
• Measure results: Businesses should track the results of their conversational marketing efforts, including engagement rates, conversion rates, and other key performance indicators. This data can be used to refine and improve future campaigns.

Leveraging conversational AI in contextual marketing requires a thoughtful and strategic approach. By using conversational AI to engage with users more naturally and conversationally, businesses can gather valuable data and deliver more targeted and personalised experiences, even without cookies.

Benefits of Conversational AI in Contextual Marketing

Conversational AI can be a powerful tool for contextual marketing by providing personalised and targeted messaging to customers based on their preferences and context. Here are some ways conversational AI can be used in contextual marketing:

• Chatbots for personalised recommendations: Chatbots can use conversational AI to analyse a customer’s preferences and context to provide personalised recommendations for products or services. For example, a chatbot can recommend products based on a customer’s viewing page.
• Sentiment analysis for personalised engagement: Sentiment analysis can analyse a customer’s emotional state based on their interactions with a website or chatbot. This can be used to personalise messaging and offers to improve engagement and customer satisfaction.
• Voice assistants for personalised experiences: Voice assistants, such as Amazon Alexa or Google Assistant, can provide personalised experiences for customers. For example, a customer can use a voice assistant to order groceries based on their purchase history or receive personalised product recommendations.
• Predictive analytics for targeted messaging: Predictive analytics can be used to analyse customer data, such as purchase history and browsing behaviour, to predict future behaviour and provide targeted messaging and offers. For example, a customer who frequently purchases products on sale can be targeted with messaging and offers related to discounts and promotions.

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Conclusion

Marketers face a significant challenge with Google and other search engines discarding cookies to protect users’ privacy and data. Cookies were deployed to store user behavioural data and to target adverts to the appropriate audience.

On the other hand, contextual targeting gathers information about customers based on their contexts, such as their location and the website they are visiting, without hampering their privacy. With contextual marketing, you may establish a dialogue with the consumer using conversational AI bots. You may then employ conversational marketing to turn the user into a lead.

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