12 Advantages & Uses of AI in Digital Marketing

Artificial intelligence (or AI) is already changing the way we think about marketing. AI technology can optimize and accelerate many marketing tasks, improving customer experience and driving conversions.

If you are involved in enterprise marketing There’s a good possibility that you already use an AI-powered solution in your Martech stack. Many marketers are still unaware of the advantages of AI and machine learning over traditional marketing software.

You may not be fully on board yet You’re not alone if you are thinking of dipping your toes into the water. Investing in technology is a major commitment. It can also be daunting when it’s backed by complicated concepts such as machine learning algorithms.

1. Improved Personalization and Recommendations

Marketing messages are changing in 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 to them 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 that brand promotions are more likely to be opened if the subject lines are specific to their 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 at the most effective times.

The personalized recommendations offered by sites like Amazon and Netflix will be familiar to most people.

These recommendation engines have evolved over time 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 on.
• All the questions Alexa has asked if you have an Echo

This information can be used to make product recommendations based on your interests. Past purchases and other people who bought the same products as you.

If you have previously purchased a printer, Amazon will recommend that you purchase 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.

2. Dynamic Pricing

Discounts are a surefire way of increasing sales. However, some customers will purchase with a smaller discount or no discount.

Artificial intelligence can be used to dynamically set prices for products 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 the Amazon product prices over time. A graph shows how the price fluctuates based on popularity and season.

Have you ever tried to find a flight only to return home and buy another one? It was only a few days later that it was discovered that it had gone up by a few hundred dollars. This is another example of dynamic pricing at its best.

Originally published on The Tech Trend