AI marketing: How to use this powerful new technology for your next campaign
According to Price Waterhouse Cooper (PwC), artificial intelligence (AI) would create over USD 15 trillion for the global economy by 2030 and increase local economies by 26%. (1) But what about AI’s commercial potential?
AI offers almost unlimited marketing uses, like customised content generation, task automation, and data analysis, but it also poses concerns. Key definitions, advantages, use cases, and a step-by-step approach for incorporating AI into your next marketing campaign are below.
What’s AI marketing?
AI marketing uses data collecting, data-driven analysis, NLP, and ML to give consumer insights and automate important marketing choices. Today, AI is employed more than ever to create content, improve consumer experiences, and improve results. Before picking an AI tool, organisations should research the various AI marketing apps and how others utilise them.
Marketing AI use cases
More companies are using AI to better their social media, email, and content marketing. Here are some ways companies are using AI to meet marketing goals.
Content generation:
OpenAI’s generative AI platform ChatGPT launched in November 2022, sparking a wave of new AI use cases. AI can generate blogs, marketing messages, copywriting, emails, subject lines, video subtitles, website text, and other targeted content for marketing teams, saving time and money.
Audience segmentation:
AI intelligently and effectively segments customers by attributes, interests, and behaviours, improving targeting and marketing campaigns, customer engagement, and ROI.
Customer service chatbots:
Marketers are researching ways to use AI chatbots to improve customer care. These bots may engage with clients at every stage of their experience, answer issues promptly, and boost customer happiness once trained.
Programmatic advertising:
Programmatic advertising automates website and app ad placement. AI has greatly improved programmatic advertising by leveraging client history, preferences, and context to offer more relevant advertisements with greater conversion rates.
SEO:
Using AI to improve SEO helps marketers improve page ranks and strategy. AI helps marketers produce and optimise content for new standards.
E-commerce:
AI is helping businesses enhance their e-commerce and digital marketing by automating jobs, streamlining workflows, and analysing consumer wants and buying behaviours.
The pros and cons of AI marketing
AI for marketing has pros and cons, like other emerging technology. Organisations that have never utilised AI are naturally wary about preserving the quality of the vast data sets needed to train AI and complying with the field’s increasing privacy standards. But companies who invested in an AI marketing solution suited to their requirements are reaping several benefits.
Benefits
Better decision-making: Marketing teams using cutting-edge AI solutions may observe the results of their marketing efforts in real time and adapt their strategies. AI marketing solutions use ML algorithms to generate plans, analyse data, and propose actions based on sentiment analysis from previous customer data faster than people.
AI marketing technologies may help marketers find meaningful insights from campaign data in real time, improving marketing ROI. The same techniques may also determine the best media purchase channels and ad placement depending on customer behaviour. Modern AI marketing solutions assist stakeholders maximise campaign ROI.
More precise KPIs: Digital campaigns create more data than people can handle, making marketing success measurement challenging. Marketers may use AI-enhanced dashboards to track the performance of their tactics and identify areas for improvement.
Customer relationship management (CRM) improvements: AI technologies automate mundane CRM processes like customer data preparation, helping marketing teams enhance their CRM programmes. They may also detect at-risk clients, decrease human error, and personalise customer messaging.
More valuable consumer data insights: Many marketers struggle with the volume of data accessible when designing a campaign. Machine learning (ML) systems can analyse massive volumes of client data in seconds to anticipate it. It analyses data to predict client behaviour, recommend personalised content, and identify trends in massive data sets for marketers.
Challenges
Train AI solutions: AI needs extensive training to learn new tasks, much as humans. For instance, you must spend time and money training an AI system to engage consumers. This application requires a lot of consumer preference data and maybe data scientists with this training.
Monitoring data quality and accuracy: AI solutions are only as good as their training data. No matter how powerful a tool is, its answers and conclusions will be poor if its training data is inaccurate and representative.
Privacy laws: AI is educated on personal consumer data, thus they must be observed. Companies using AI for marketing must comply with consumer data rules or face penalties and reputational harm. HFS Research reports that media coverage of botched AI installations has raised pressure for regulation in Europe and North America.
Step-by-step AI marketing strategy guidance
Five steps to successfully integrate AI into your next marketing strategy.
First set goals
Setting objectives and expectations is the first step to using AI in marketing. Assess prior campaigns’ successes and failures and suggest how AI might enhance future outcomes. After stakeholders agree, choosing an AI system and setting relevant KPIs will be easy.
Step 2: Find talent
Data scientists and engineers with AI, machine learning, and deep learning backgrounds are rarely on marketing teams, yet their experience is needed for AI marketing. Organisations can engage data scientists and engineers or pay a third-party vendor to train and manage their AI marketing tool to handle this issue. Both techniques offer pros and cons, mostly according on an organization’s investment level.
Step 3: Follow data privacy regulations
One of the major hurdles for AI marketing solutions is using consumer data for training and deployment without breaking privacy rules. Organisations must protect consumer privacy and security during training or risk steep fines.
Step 4: Assess data quality
The accuracy and relevance of data taught on an AI marketing tool determines its performance. AI solutions educated on data that doesn’t correctly reflect consumer intents won’t deliver relevant customer behaviour insights or strategic suggestions. Enterprises may guarantee their AI solutions help them reach marketing programme goals by prioritising data quality.
Step 5: Pick your solution.
Organisations choosing an AI solution have several platforms and capabilities. If they’ve followed the previous four steps setting goals, employing the proper people, and guaranteeing data quality and accuracy the last step picking the correct tool should be easy.
AI marketing tools
The best AI marketing tools use AI and ML to improve customer experiences and give marketers quick, accurate information. IBM Watsonx Assistant, a market-leading conversational AI platform, lets organisations develop voice agents and chatbots that organically interact with consumers and solve their problems.
