Marketers are having a love/hate relationship with artificial intelligence (AI). Some marketers hate AI fearing it will take their jobs and make them redundant. The majority of marketers, however, seem to love AI because it makes their efforts more effective. Cal Ó Donnabháin (@CalODonnabhain), asks, “Isn’t it an all-time wish for every company to see through the minds of their customers and find out their preferences?”[1] He explains artificial intelligence can help marketers better understand their customers’ preferences. “Artificial Intelligence, for all the right reasons, is being employed by many companies to find out exactly what their potential customers are looking for and give it to them at the right time. On the other hand, AI is also used by companies to create a whole new set of target customers that sometimes they never knew existed!”[1]

Getting to know customers begins with the right data

Journalists at CIO Review believe companies can leverage big data analytics “to maintain the edge in this era of information-based competition.”[2] They explain, “Organizations can leverage big data analytics and enable a ‘Hyper Personalized Experience’ on a large scale. … In order to take this into effect, customer information footprint needs to expand from internal transaction systems to data from the online world such as social media and mobile devices to gain a 720-degree view of the customer.” You might have figured out a 720-degree view of the customer is one obtained from both internal and external data. Jayant Prabhu, General Manager and Global Practice Head for the Big Data Analytics at Wipro Analytics, explains, “A 360 degree view of the customer is not enough anymore. That is, businesses need to not only look at their internal data on a customer when they contact them through their own channels, but also look outside of their owned channels to sources like social media, reviews and experiences etc. to understand their real motivations to use the service.”[3]

Gathering data, however, is a meaningless activity if the collected data can’t be analyzed. Today, so much data is gathered traditional analytic methods are simply too slow to handle the task. Vance Reavie (@JunctionAI), CEO and Founder of Junction AI, explains artificial intelligence has come to the rescue. “Marketers are at the forefront of benefiting from artificial intelligence,” he writes. “This technology provides the ability to develop a unified customer view and deep understanding of each customer at an individual level previously not possible.”[4] Steve Olenski (@steveolenski), a self-described CMO whisperer, insists, “Marketing is one of the areas where AI is transforming how the process works.”[5]

Artificial intelligence and targeted marketing

Targeted marketing’s goal is to inform potential customers about products matching their preferences at price levels that will make those products attractive. As Ó Donnabháin explains, to achieve this goal, artificial intelligence is the best tool in the marketer’s kit. He writes:

“AI is changing the way companies sees the customers. Each and every potential customer is analyzed by AI. AI records and analyzes every action made by a user — those who visited the website, the products they browsed, the items they added to the cart and removed, the items left in the cart, a call-to-action followed and left in midway, customers who signed up but never visited and so on. AI analyzes these behaviors of each and every customer and finds out the reasons behind the customers for stopping in their pursuit. Personalization is, as everyone knows, the key to great marketing strategy. Personalizing a segment of customers is what marketers normally do. But AI goes a step beyond that and comes with the content that could focus on converting a particular lead to sales. It personalizes the content in line with what the customer wants to see.”

Robert Allen, Digital Content Manager at CITU, rightfully notes AI is an omnibus term covering a number of different techniques and approaches. He asks, “How the bloody hell are marketers supposed to do anything with that information? It’s just hype, you can’t implement it.”[6] He’s correct. Confusion and uncertainty can arise if marketers don’t know how to apply AI techniques. To help remedy that situation, Allen and his colleagues at CITU suggest 15 artificial intelligence techniques that businesses of all sizes can implement. They are:

1. AI generated content. “There are certain areas where AI generated content can be useful and help draw visitors to your site.”

2. Smart Content Curation. “AI powered content curation allows you to better engage visitors on your site by showing them content relevant to them.”

3. Voice search. “Voice search is another AI technology, but when it comes to using it for marketing, it’s about utilizing the technology developed by the major players (Google, Amazon, Apple) rather than developing your own capability.”

4. Programmatic Media Buying. “Programmatic Media buying can use propensity models generated by machine learning algorithms to more effectively target ads at the most relevant customers.”

5. Propensity modeling. “Predictive analytics … uses analytics data to make predictions about how customers behave.”

7. Lead scoring. “Machine learning can be trained to score leads based on certain criteria so that your sales team can establish how ‘hot’ a given lead is, and if they are worth devoting time to.”

8. Ad targeting. “Machine learning algorithms can run through vast amounts of historical data to establish which ads perform best on which people and at what stage in the buying process.”

9. Dynamic pricing. “All marketers know that sales are effective at shifting more product. Discounts are extremely powerful, but they can also hurt your bottom line. … Dynamic pricing can avoid this problem, by targeting special offers only at those likely to need them in order to convert.”

10. Web & App Personalization. “If someone is still new to a site, content that informs them and keeps them interested will be most effective, whilst if they have visited many times and are clearly interested in the product then more in-depth content about a product’s benefits will perform better.”

11. Chatbots. “Using open chatbot development platforms, it’s relatively easy to create your own chatbot without a big team of developers.”

12. Re-targeting. “Machine learning can be used to establish what content is most likely to bring customers back to the site based on historical data.”

13. Predictive customer service. “It’s far easier to make repeat sales to your existing customer base than it is to attract new customers. So keeping your existing customers happy is key to your bottom line. … Predictive analytics can be used to work out which customers are most likely to unsubscribe from a service, by assessing what features are most common in customers who do unsubscribe.”

14. Marketing automation. “Marketing automation techniques generally involve a series of rules, which when triggered initiative interactions with the customer. … Machine learning can run through billions of points of customer data and establish when are the most effective times to make contact, what words in subject lines are most effective and much more.”

15. 1:1 dynamic emails. “Applying insights generated from machine learning can create extremely effective 1:1 dynamic emails. Predictive analytics using a propensity model can establish a subscriber’s propensity to buy certain categories, sizes and colors through their previous behavior and displays the most relevant products in newsletters.”

Summary

As you can see, there are lots of ways artificial intelligence can improve marketing. Olenski concludes, “Being able to make better decisions related to your marketing strategy means money well spent and better return on what you do use from the budget. If you could see the future to make informed predictions and execute on targeted actions, then you’d be making the best decisions and garnering the best results for doing so. … The real risk … is in the non-adoption of AI, with a loss of competitive advantage that data and insights can provide.”

Footnotes
[1] Cal Ó Donnabháin, “Targeting the Right Customers using Artificial Intelligence,” Irish Tech News, 18 may 2018.
[2] Staff, “Combining Big Data and Machine Learning For Precision-Targeted Marketing,” CIO Review, 2 May 2018.
[3] Jayant Prabhu, “720 Degree Customer View: Big data unlocking the real potential for Utilities,” Wipro.
[4] Vance Reavie, “Three Ways Artificial Intelligence Can Enhance Your Personalization Strategy,” Forbes, 17 April 2018.
[5] Steve Olenski, “How Artificial Intelligence Is Raising The Bar On The Science Of Marketing,” Forbes, 16 may 2018.
[6] Robert Allen, “15 Applications of Artificial Intelligence in Marketing,” LinkedIn, 29 June 2017.