6 Ideas to Leveraging Artificial Intelligence Technology for Marketing
McKinsey & Company says that artificial intelligence (AI) applied to marketing has the potential to discover up to $2.6 trillion in new business value. Using AI in marketing has become one of the most important digital marketing trends, and the ways of applying this technology to marketing tasks are promising:
- Discovering insights with predictive analysis
- Automating advertising
- Creating content and promotions
- Providing excellent customer service
- Personalizing sales efforts
- Optimizing product price
1. AI-Based Predictive Analytics and Insights
The problem with data is that there is too much of it. To discover valuable insights requires analyzing enormous amounts of data. This challenge is an impossible task for any number of humans to manage without using AI. However, when using AI, an expert team can accomplish superb results.
Salesforce reported that marketers increased their use of AI tools from about 24% in 2018 to 84% in 2020. Marketing predictive analytics comes from analyzing data collected over many marketing campaigns to identify the consumer behaviors that drive conversion patterns (sales) and catalog consumer preferences.
One powerful AI application of this type is using machine learning (ML) for demand forecasting in retail operations.
Marketing optimization comes from using AI that has significant ML analytical power. This strategy allows an organization to formulate a solid marketing strategy while allowing for any existing constraints, such as budget limits and privacy policies.
Using AI properly increases a marketing campaign's return on investment (ROI) while improving the customer journey and developing effective customer touchpoints.
The days of sending bulk emails to all your customer lists are over. A company may discover it makes more sales by not sending bulk emails to customers on the mailing list and sending a personalized message instead.
Compared to traditional marketing analytics, which is prone to human error, AI-based marketing analytics is proving to be vastly superior. Using AI augments and enhances analytics by automating many processes.
Here are the benefits of AI-based predictive analytics:
- Using ML with AI develops more robust data models over time.
- Better and more useful insights come from the collected data.
- Insights integrate across various data platforms.
- Accuracy increases for marketing predictions.
2. AI for Advertising Automation
AI combined with ML applied to Big Data is used in planning advertising campaigns, allocating advertising spending, and analytics so that advertisers can improve decisions and maximize ROI. AI is used in advertising at every level, from ad creation, campaign planning, audience targeting, and ad spending. Machine learning is used in major ad platforms. ML algorithms in the core of Google Ads predict if a user will click on an ad, analyzing their browsing and search history.
Here are the benefits of using AI for advertising automation:
- Accurately identify audience segments.
- Efficiently and effectively personalize marketing messages.
- Use ad creatives that each audience segment will respond to positively.
- Easily test multiple ad-campaign variations.
- Improve ROI and ad-campaign performance.
- Optimize ad spend in real-time, at scale, automatically.
3. AI for Content Creation and Promotion
AI stands for artificial intelligence. It could be more reasonably described as augmented intelligence because the best use cases for AI are where the AI does things that humans cannot do as well to augment human efforts. But what about AI replacing humans?
The World Economic Forum predicted that AI would cause up to 85 million humans to lose their jobs by 2025.
AI for Text Creation
AI will replace low-quality writing, and it is already doing this. Many newsfeeds are AI-driven with human editing to finetune the results. In comparing AI vs. human writing, AI is currently lacking because AI does not understand emotions and strategy and is poor at fact-checking. AI does not have empathy and cannot understand a brand's essence.
However, using AI for search engine optimization (SEO) is very effective. The three most popular AI content tools are Jarvis, Frase, and Surfer SEO have many useful features, however they don’t remove the need to have a human editor involved in content creation.
AI for Image Creation
Another AI tool that is useful is text-to-image generation. An example of this type of tool is the Dall∙E project.
Using generative adversarial networks (GANs), the AI system creates new images based on an extensive library of images that the AI can access. The developers used ML to train the system with multiple models.
The use cases of GAN technology include, but not limited:
- Logo Synthesis: Creating a unique logo derived from other images.
- Facial Features: Creating human faces with specific features.
- Image Upscaling: Maintaining the quality of an image when scaling it to be larger.
- Image Improvement: Improving low-quality images and substituting things or replacing missing stuff in photos.
AI can address many challenges that photographers face. For example, sometimes you need to be able to make images sharper, making them clearer and more detailed. Artificial intelligence tools can reduce the efforts of creators to fix blurry photos and achieve better results in a shorter time.
4. AI-Based Customer Service
Using AI chatbots to solve the most frequent customer service questions improves the user experience while cutting costs. One goal of customer service automation is to reduce time spent on repetitive activities. AI tracks customer behavior patterns and can improve customer service response times.
One of the most widely-used applications for AI in customer service is the natural language processing of text and speech. AI can also give insights into customers' interests, sentiments, and reactions to major events. AI-driven decision trees can message customers at the correct time based on a customer's interaction with touchpoints.
AI also helps provide greater personalization in customer interactions. For example, you can personalize the shopping experience based on customer likeness or preferences. The use of artificial intelligence allows you to customize the content of your website for each specific user. According to a report from Epsilon, 80% of customers are more loyal to brands that provide them with a personal touch. Personalization of services can increase customer engagement as well as increase conversion rates.
With the help of AI, customer support specialists have the opportunity to get real-time insights about a specific customer in order to better understand their needs and expectations. AI-based tools can quickly and easily analyze large volumes of data and provide you with easy-to-read reports. Based on this information, сustomer support agents can make more informed decisions and make offers more relevant to each client.
Finally, using AI technology helps reduce the costs of customer services. AI can not only help automate repetitive tasks, but it also provides high levels of customer support across multiple communication channels. Typically, a customer support team receives a huge number of incoming calls and many of them are routine requests that virtual assistants can handle perfectly. With AI-based tools you can optimize the time of your agents, automate workflows and pay more attention to the most difficult issues and cases.
5. AI for Sales Personalization
Forrester reports that 80% of American consumers will give personal information for a personalized shopping experience. AI-driven personalized ads help an organization establish relationships with its customers and engage in a marketing conversation that builds brand loyalty.
AI uncovers unique patterns on a highly-individualized basis on a greater scale than humans can achieve. McKinsey & Company report that about 65% of organizations using AI-personalization tools see increased sales.
AI-personalization is not simply dropping in the correct first name in a "Dear somebody" bulk email. Instead, it creates a marketing conversation that consumers appreciate.
Powerful applications of AI-personalization include:
- Hyper-personalization: Shaping content specifically for each customer.
- Targeted Messaging: Message content derives from profiles and events.
- Ad Targeting: Showing more relevant ads to a target audience.
- Product Recommendations: Rule-based algorithms intelligently present products for consideration as alternatives, up-sells, and add-ons.
- Personalized Websites: Dynamically changing what displays to a web visitor based on their past behavior.
- Customer Sentiment: AI applications can tell a customer's emotional state and understand when a customer is truly satisfied.
6. AI for Pricing Optimization
Knowing how much a customer is likely to pay for a product, and understanding how this relates to profit goals, is a great asset for any company. Artificial Intelligence can help you optimize prices to meet both your business needs and customer expectations. Many factors affect price, including competition, seasonality, events, and more. It is really difficult for a human to react quickly to all these events and make changes to the pricing strategy. AI makes it fast and easy.
Using AI-based price optimization systems allows you to constantly track different patterns affecting pricing. Here are some examples of data that AI can analyze to optimize prices:
- Market trends
- Competitor's prices
- Customer activity
- Purchase history of a specific customer
- Customer reviews, etc.
With AI you can not only make smarter decisions but also automate some pricing rules. Based on the algorithms you put in place, the system can select the best prices in real time. Thanks to this, you can implement a variety of strategies that are suitable for your business. For example, you can adjust prices in such a way that they are always $10 lower than competitors, or increase the price as demand for the product grows.
Conclusion
In any competitive industry sector, not using AI in the most effective ways possible is a serious strategic mistake. The 16% reported by Salesforce who are not yet using AI for marketing and others not yet fully using it will soon be left behind by their competition.
If an organization embraces the innovation in AI technology by using these methodologies, there is a significant positive result for the vast majority of enterprises. Consumer expectations are quite high, especially when it comes to customer service and personalization.
Using these AI-driven solutions gives a company a competitive edge and improves the customer experience.
