Artificial Intelligence (AI) has become part of the business landscape. It’s now accepted as a technology for many applications and platforms. However, marketing is one of the areas where AI is transforming how the process works. As such, it’s also solving some marketing challenges across industries.
However, like other technology slowly making its way into all aspects of work and life, such as the Internet of Things (IoT) and autonomous vehicles, the transformation process of AI in marketing may not quite be there yet. And, that may be for the best. Here’s the current state of AI’s disruption of marketing.
AI’s Impact on Marketing Science
Specific changes from AI’s influence on marketing are already being felt, according to Charles (Chuck) Davis, co-founder and CTO of Element Data, a company behind an AI tool called Decision Cloud. “AI has enabled the evolution of search engines, recommendation engines, chatbots and voice data analysis and other technologies employed by marketers every day.”
And, companies across industries are starting to understand how to incorporate AI and machine learning into their marketing efforts. Companies like Amazon and Netflix were early adopters. They used this technology to provide personalized recommendations to their customers. Although this marketing tactic is still used successfully, the marketing applications have progressed into many other areas.
Better Decisions Arrive Faster
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.
Catalant’s Pedro Pereira explains, “In sales and marketing, AI measures customer sentiment and tracks buying habits. Brands and advertisers use the information to make ecommerce more intuitive and for targeted promotions…AI creates efficiencies that wouldn’t be possible without sifting through piles of data.”
As you know, making the right decisions with the data you receive is challenging at best. That’s where AI has made the difference. Companies like Element Data, Selligent Marketing Cloud, and SetSchedule are helping marketers take the massive volumes of data that comes from all these channels and platforms and group it in a structured way to see what decisions need to be made. Questions about what motivates customers and why they act a certain way can be answered. And, those insights come more quickly than any human could ever figure out.
By speeding more accurate decisions, business intelligence rapidly grows. As a result, the return increases further. That means more time and money for creating the right campaigns and spending more time interacting with each customer. AI then becomes truly worth its weight in gold.
Personalization Gets Help
Being able to make each and every experience for what could be thousands of customers seems like an impossible task. However, that is what today’s customers want. Although Amazon and others have proved that it’s possible, they have AI to thank. And, so many other companies are seeing the potential.
According to Emme Yllesca, CEO of real estate investment platform, Asset Column, “AI provides deep insights, allowing our brand to use that data in order to bridge the gap, resulting in a marketing message that hits the right pain points.” That means matching audience segments with specific problems and solutions. That means a huge uplift in your response and success rate.
Aman Naimat, senior vice president of technology & engineering at Demandbase says personalization is at the crux of why marketing has to and will adopt AI. “Ultimately, marketing is all about how a brand communicates to its prospects and customers, and personalized, relevant customer experiences are the most effective way to reach their target audiences,” says Naimat. “Think about how easy it is to filter out spam with the glance of an eye.”
Naimat cautions that 1:1 conversations are difficult to have at scale. He believes the only way to achieve personalization at scale is to leverage AI and machine learning applications. “The knowledge you get from AI technology is akin to the knowledge most sales reps have when they research every single buyer in-depth. Today, many companies are already enabling this hyper-personalization at scale, creating context-rich conversations that help businesses understand, connect and relate to their audiences.”
Content Marketing Is Efficient
With content in such demand, it’s easy to focus on mass production. However, while quantity is important to a certain degree, it shouldn’t put quality at risk. What you create must be relevant for numerous audiences but also be adjustable to each segment. As you know, that leads to a considerable amount of content to manage, organize, and put to work.
To create these content assets most likely also used a large number of resources. Therefore, you want to be able to tap them, repurpose them, and leverage them again at will. That’s again when AI becomes the marketing superhero. According to Jim Vernon, CEO of RockHer,“The majority of our content management uses artificial intelligence to some degree, allowing us to catalog, search and find any piece of content related to a specific search query.
Go Deeper Into the Data
To beat out the competition means knowing more about the intended customer and existing base. It’s in the data, but it’s a race to find it first and understand what to do with it. “Consumer data is a very touchy subject,” says Saro Der Ohanesian, CEO of Vanguard Tax Relief, “and what and how data is collected is a completely different discussion.” As on simple example, we just need to look at how much Facebook has been in the newsin recently involving its data collection.
Real estate is a good example of an ideal place to put AI’s power to work on marketing to generate more effective results. For example, SetSchedule is a real estate marketing firm that has leveraged AI technology to create connections between realtors and local homeowners, home buyers, and investors to complete more property deals. The company uses AI to identify properties through predictive data. Then, it uses automated marketing to understand timing, seller and buyer intent, market conditions and more to develop leads that close more often than any marketing processes that did not use machine learning capability.
Marcos Meneguzzi, EVP and Head of Cards and Unsecured Lending for HSBC, also sees firsthand how AI is impacting the customer experience in his organization. “Customers want companies to treat them like individuals who matter – not interchangeable sources of revenue. The greatest promise for AI is about optimization of data and the valuable insights they can provide leading to greater personalization. This allows companies like HSBC to enhance and tailor our customer experiences.”
HSBC uses AI to predict the redemption of loyalty program rewards associated with their new suite of credit cards. Also, it is leveraged within Fraud Management in both models and rule building to detect anomalous behavior for the protection of our customers and the firm. Launching soon, HSBC’s new chat bot will augment the expertise of our bankers by providing fast and accurate responses to a wide range of questions that will reduce friction to getting answers and ultimately eliminate wait time.
In looking at future applications, Meneguzzi, states, “We’re actively evaluating and exploring additional innovative AI use cases across our businesses to deliver superior customer experiences. A number of projects look to improve the customer experience. This includes reducing fraud and card compromises. Others enable more personalized and relevant customer contacts within the personal banking space.”
Share the AI Love
Now, working with sales, customer service, and other areas of the business means sharing information and insights. And, it’s the CMO who can take the lead in pushing these efficiencies throughout the company by working with others on the executive team.
For example, this includes things like contract management. Although companies have typically relied on large sales platforms to cover this task, these platforms haven’t been able to optimize the process the way AI could do. The technology can do a lot of the heavy lifting for the legal and sales teams while also protecting the contracts better than any other tools available.
More to Come
These are huge strides AI has made in moving the science of marketing forward. Other opportunities include Decision Intelligence. Not only will it change how CMOs make decisions, but it will also influence consumer decisions related to how, when, and where they spend their money. AI tools will learn what consumers have previously done, mimic that decision-making process, and then understand what to deliver to consumers to influence that decision.
First, there are other challenges. This includes knowing where to start making changes internally with marketing tools to integrate AI with the various types of data, data sources, and channels. However, AI could determine how you achieve that.
Second, companies have to think about becoming too dependent on AI. Jesse Wolfersberger, Senior Director of Decision Sciences for Maritz Motivation Solutions, recommends when integrating AI into your business, you need to have experienced professionals run the show. “Even after that, we recommend substantial testing and gradual roll-outs,” he adds. “You don’t want to be in the situation where you are taking actions based on an AI’s recommendations and have it turn out that an analyst accidentally swapped the revenue column with the cost column.”
Naimat believes there is no risk in marketers becoming too dependent on AI. “Marketers will still need to drive AI tools that will help them do their jobs better and at scale,” he said. “In fact, I believe that as AI advances, there will be a new class of marketers whose sole responsibility will be to drive this AI machinery, understand and take advantage of AI algorithms, and strategically point to the right data and goals which in turn will spark the integration between data and marketing, and ultimately, bring them closer together.”
The real risk, as Naimat explained, is in the non-adoption of AI, with a loss of competitive advantage that data and insights can provide.
This article originally appeared on Forbes.