6 Ways Artificial Intelligence Will Shape Your Digital Marketing Strategy

 

Artificial intelligence is currently revolutionizing the business world — and it’s just as quickly transforming virtually every element of digital marketing.

For marketing leaders, the growth of artificial intelligence (AI) means less guesswork and more efficiency. Marketers should expect to use AI in guiding and implementing every element of their marketing strategy — from the initial research stages to carrying out automated media buys and providing targeted customer service.

Explore the 6 ways artificial intelligence have already begun and will continue to transform digital marketing:

1. Messaging & Brand Voice

In the past, marketers have used research, combined with trial and error to determine the best way to communicate with target markets. With the introduction of artificial intelligence, that guesswork is starting to drastically decrease.

Artificial intelligence gives computers the ability to learn just about anything, including the ability to reason and to use language to formulate original ideas. Computers will soon be able to predict everything about the buyer, including buying patterns, viewing patterns, age, location, as well as the ideal voice, tone and dialect for the buyer.

Through AI, computers will be able to combine strategic reasoning with countless data points. With this information, they’ll be able to formulate the appropriate voice and tone to properly communicate with the potential buyer, making guesswork obsolete.  Voice and tone are already being used in popular voice robotic applications, such as Alexa and Siri. But, they are just the tip of the iceberg when it comes to advanced, AI-fueled brand communication. 

2. Content Strategy

While AI likely will not be able to write a personalized opinion column, AI is already beginning to formulate sample social media messaging, political articles, quarterly earnings reports and financial services data.

During the 2016 U.S. election, Washington Post created narrative templates for stories and included key phrases for a variety of different outcomes, and then hooked Heliograf, a cutting edge AI software application, up to VoteSmart.org, a data source. From there, the software identified relevant data, matched the phrases in the template, and then went ahead to publish the data. For content marketers, this technology will eliminate trial and error in content creation. Marketers will be able to create a template, plug in keywords and formulate content that is relevant to their target market. 

In addition to content creation, AI allows marketers to target content promotion. Through formulating overlapping buying patterns, AI applications can serve website visitors specific content that is highly relevant to their interests based on purchasing history. In the future, this information will be used to personalize website algorithms and automated email content, formulating articles relevant to the customer based on data.

3.  Ad Targeting & Programmatic Media Buys

With ad targeting on platforms such as Facebook, LinkedIn, and Google AdWords, there’s never been an easier time to niche target various markets, and ad targeting is only going to get easier, more specific and more accurate within the next few years.

Not only will targeting be more specific, but also machines will drive which media buys would be most effective for businesses, automatically. This is a relief for both marketers and businesses who often need to spend thousands of dollars in test campaigns.   

Marketers have already begun utilizing AI for media buys; computers are more effective in processing large amounts of data using various algorithms to optimize buys and improve campaigns. Computers can also handle more campaigns than the average human, setting up and monitoring 5,000 to 10,000 campaigns in the time a human can do six to 10. 

Lingerie brand, Cosabella has already experienced the benefits of programmatic media buys, as explained by Ad Exchanger. Cosabella replaced their ad agency with Albert, an AI software platform. After just three months with Albert, they saw a 336 percent increase in return on ad spend. By Q4, revenues increased 155 percent and the brand saw 1,500 more transactions year-over-year. In the first month alone, costs decreased by 12 percent and returns increased by 50 percent. 

4. Targeted Lead Scoring 

Rather than requiring the sales team to call all leads, propensity models generated by machine learning can be trained to score leads, allowing the sales team to establish how likely a lead is to buy. To begin scoring leads, a training data set is developed, containing a number of descriptive features that relate to a target feature. From there, the algorithm is applied to the data set, creating a prediction model. This can then be applied to predict if the customer is likely to convert and then can be used to influence the business strategy, either manually or programmatically. While these programs currently require a large amount of data, less data will be needed in the future.

Overall, this allows sales teams to focus their time and energy on qualified leads, rather than having to use energy on leads with low propensity to buy.     

5. Chatbots

Chatbots work by mimicking human intelligence to interpret consumer’s questions and solve issues for said customers. Facebook has already begun working on the use of chatbots for brands, having them work as ambassadors of sorts. Chatbots will be able to answer questions for customers, and likely will even be able to predict the proper voice and tone of use in the future, per the individual customer.

A Denver-based company, OneReach is a leader in the use of bots for personalized company communication, allowing companies to build their own bots. From there, OneReach integrates the bots into popular platforms, such as Facebook, Slack, Twitter, Salesforce, Skype, etc.

6. Dynamic Pricing

Currently, coupons and promotions are essential to all forms of e-commerce purchasing but offering continuous promotions can hurt a business’s bottom line.

Dynamic price optimization through machine learning can help boost sales by correlating pricing trends with sales trends by using an algorithm, which will only offer promotions to those needed to convert. This will ultimately raise a business’s bottom line, maximizing profits.

Though artificial intelligence is still in its early stages, progress is made daily. Ensure your business or marketing agency understands how to take a strategic approach to implementing AI as a component of your overall digital marketing strategy, allowing them to boost potential exposure and leads for your business.