Artificial intelligence (or AI) is already changing how we think about marketing. AI technology can optimize and accelerate many marketing tasks, improving customer experience and driving conversions.
You’re likely already using an AI-powered solution as part of your enterprise marketing strategy. Many marketers don’t understand the value of AI and machine learning over traditional, non-intelligent marketing software.
You’re not alone if you still need to be on the bandwagon or just thinking about jumping in. It’s a considerable investment and can seem daunting when considering complex concepts such as machine learning algorithms.
Improved Personalization and Recommendations
Marketing messages are changing how consumers interact with them. Traditional marketing methods such as direct mail and media advertising are no longer as effective.
This is because today’s consumers expect marketers to tailor messages based on their location, demographics, or interests. Non-personalized marketing may be ignored or not received by many.
Accenture reported that more than 40% of consumers changed brands because of a lack of trust and poor personalization. Companies that provide personalized customer service are 43% more likely to purchase from them.
Personalized marketing messages are more popular with consumers. Experian data shows that personalized subject lines make emails 26% more likely to be opened. Marketo also found that 79% of respondents to a global survey said they only open emails with personalized subject lines if they are specific to past interactions.
AI allows marketers to personalize communications at an individual level rather than targeting a generic group of people as they did in the past.
The technology predicts customer behavior using intelligence gleaned from past interactions. This allows marketers to send marketing communications and content that convert leads into sales most effectively.
The personalized recommendations offered by sites like Amazon and Netflix will be familiar to most people.
These recommendation engines have evolved and can be astonishingly accurate for users who have been using the service for a long time. Amazon, for example, has a record:
Every purchase you have ever made
History of product browsing
These are the addresses where you have lived and worked.
You’ve always wanted items
You’ve seen TV and heard the music.
Apps that you have downloaded
You’ve left reviews and product ratings
You’ve used devices to download ebooks or watch movies.
All the questions Alexa has asked if you have an Echo
This information can be used to make product recommendations based on your past purchases and interests.
If you have previously purchased a printer, Amazon recommends buying cartridges and paper. You might find baby clothes and toys in your recommendations if you have ordered prenatal vitamins and stretch mark cream.
This is all powered by DSSTNE, an AI framework that has been made open-source software to enhance its deep learning capabilities.
Gartner predicts, however, that although 90% of brands will employ some form of marketing personalization before 2020, many will not be able to create optimally personalized content.
AI is the answer to improving personalization as well as producing better content. Machine-learning algorithms allow marketers to create hyper-personalized customer experiences by analyzing customer data.
Discounts are a surefire way of increasing sales. However, some customers will purchase with a smaller discount or no discount.
Artificial intelligence can dynamically set product prices based on demand, availability, customer profiles, and other factors. This allows you to maximize sales and profit.
The website camelcamelcamel.com allows you to see dynamic pricing in action. It tracks Amazon product prices over time. A graph shows how the price fluctuates based on popularity and season.
This is dynamic pricing at work.
Chatbots for Customer Service
Facebook Messenger, WhatsApp, and other messaging apps are becoming popular for customers to reach companies. However, ensuring that the accounts remain staffed with customer service representatives can be costly.
Some companies are using chatbots to answer customer questions and give instant responses at all times of the day and night. Chatbots can be programmed with pre-recorded answers to common questions and the ability to redirect the conversation to a human agent for more complex queries. This reduces customer service time and makes it easier for agents to handle more personal discussions.
Chatbots such as Siri, Google Assistant, and Cortana are becoming more familiar and even preferred to real people. AI language processing algorithms have advanced significantly in recent years. This makes it possible for machines in customer service and sales roles to replace human agents.
Chatbots can be more cost-effective than having more people handle inquiries. They also can do so in a more efficient, sometimes even more human way. Chatbots are always polite, friendly, and engaging, unlike humans.