Artificial intelligence (AI) essentially refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. Although AI often refers to “artificial intelligence,” a more descriptive term for AI could be “augmented intelligence.” Augmented intelligence is different from artificial intelligence in that it uses technology to enhance, support and complement human cognitive functions (rather than replacing humans).
What role has AI played in the advertising industry?
AI is changing advertising and the surrounding landscape. Advertisers want to optimize the vast amounts of data at their disposal to create better campaigns and drive more impact.
The importance of AI in advertising continues to increase. Before the assistance of AI, it was difficult to measure the effectiveness of campaigns and where to allocate spend.
However, media spend is not the only sector of the advertising industry being affected. AI affects planning, analytics and creative. AI-based, cognitive advertising can therefore revolutionize a company’s approach to marketing and advertising. When combining AI, machine learning, and big data, advertisers can make better decisions with their budget to maximize ROI.
Figure 1 Employee leveraging AI for advertising
Benefits of using AI in advertising
AI can bring a competitive advantage to advertising campaigns through improved user experiences and reduction in human error. The potential benefits are evident, and organizations are taking notice. For example, according to findings from a recent IDC (opens outside of ibm.com) spending guide, global spending on AI is expected to double over the next four years, growing from USD 50.1 billion in 2020 to more than USD 110 billion in 2024. Some of the reasons that organizations are increasing their investment include:
More personalized experiences
Most consumers want experiences tailored to them. According to Forrester (opens outside of ibm.com), eighty percent of US customers are willing to trade some personal information for a more personalized approach from retailers.
Personalized ads allow you to establish relationships with consumers across touchpoints. Whether it be using conversational marketing or optimizing creative messaging to better connect with audiences, your team can benefit through increased brand loyalty and more relevant advertisements.
Target the right audiences
One of the biggest challenges for marketers is ensuring that the right people are targeted. AI can analyze different data sources to determine the probability of a user taking a specific action, making campaigns more effective and actionable. AI can create look-alike audiences based on past campaigns to target new contacts and build the sales funnel. Your team can also leverage artificial intelligence and location data to target individuals in the vicinity of your store to increase foot traffic or drive personalized recommendations based on weather triggers.
Make better decisions faster
With the right data and insights, marketers can make better decisions more quickly. In an ever-changing marketplace, this is becoming increasingly important to make sure ads stay relevant to the target audience. For example: With the COVID-19 pandemic, case counts may rise and fall in your area, which can impact how you market your products. When cases are increasing, consumers are less likely to enter your stores. By using AI, you can make quick decisions to tailor messaging and change campaign focus if needed.
John Wanamaker (opens outside of ibm.com), a US merchant, is often credited with saying, “Half the money I spend on advertising is wasted; the trouble is I don't know which half.” Advertisers and marketers have traditionally struggled with determining the effectiveness of their campaigns and the steps needed to improve their results. Leveraging analytics can help companies determine what is most effective. Additionally, by targeting the right audiences with the right messaging, your team can reduce advertising waste and improve marketing ROI.
Potential obstacles to avoid with AI in advertising
Be knowledgeable of ways to overcome potential obstacles to becoming successful in the use of AI in advertising. These obstacles may include:
Weak IT infrastructure
To implement a robust AI strategy in your advertising processes, you’ll need a strong IT infrastructure that can handle it. Before you do anything else, it’s crucial to speak to your IT department to determine what can be taken on, and what tasks need more preparation time.
Too little high-quality data
With the influx of data, it can be difficult to manage both the quality and insights derived from the information. Conversions and interactions happen across channels in both online and offline environments. The vast amounts of data can make it harder to plan for longer-term initiatives. Additionally, navigating the data and ensuring the collected information stays current can be difficult. The outputs and insights generated from AI can only be as useful as the data it is based on.
You can have all the data you need, but it’s useless if it’s low quality. Even if the data is high quality, if you don’t have the tools available to decipher it, you cannot create actionable insights for your team. Ensure that the data you are retrieving is of the highest quality possible and invest in a tool that can help you understand from these various information sources.
Privacy and regulations
New regulations concerning user privacy can make ensuring your strategy is compliant feel overwhelming. Regulations differ across countries (for example, GDPR) or even across state lines. When you’re using AI to connect with people, privacy concerns are bound to arise. Ensure you’re following the necessary privacy policies and regulations and consider cookieless targeting for your advertising efforts. Your legal team should be able to provide you with the necessary guidance before implementing a plan.
A user-base not wanting to accept AI
While personalization can be helpful to many customers, many people still feel uncomfortable with it due to data privacy issues. Try to ease your audience into it if they’re feeling hesitant. Balancing the right amount of personalization for consumers can be a struggle for many organizations. Many users think companies go a little too far with their personalization efforts.
Companies should use personalization as a tool that focuses on making the customer experience better for the end user. To see examples of brands using AI successfully, check out our case studies.
Today, investment in AI technology is a business imperative and can seem like a big line item. However, keep in mind this investment can lead to decreased expenses and more efficiency in other areas not previously realized. Therefore, having more reliable data can lead to making more-efficient decisions, which can decrease expenses in other areas. Another benefit that can lead to reduced expenses is due to more efficient utilization of your staff. For example, with AI comes automation. This process allows mundane tasks to be handled by a machine while allowing your team to dedicate resources to higher priority items.
As technology advances and threats become more sophisticated, fewer people are qualified to manage them. Often, data scientists are required to decipher the data, and managers are required to ensure that data remains relevant and clean.
How is AI used in advertising?
Artificial intelligence campaigns can better target audiences while providing relevant messaging. Advertisers can use these kinds of marketing campaigns to improve ROI and deliver more personalized ads. You can start applying machine learning to advertising in the following ways:
Leverage the right ad platforms
Applying ads to platforms your audience is using can help connect your customers with your product or service in a relevant method.
Create more effective ads
Bring conversational marketing to the forefront of your strategy. Personalization is key in conversational marketing: A personalized solution considers user data when creating responses to questions your prospective buyers might have about your brand. These interactions can strengthen the consumer’s relationship with your brand by nurturing a one-on-one connection.
Target the right people
AI can help you reach the right audience at the right time, so you can better reach the right customers when they're most poised to take action. These kinds of targeting strategies can include weather triggered ads or ads based on location. IBM Watson Advertising Weather Targeting leverages AI and the power weather has to predict consumer behavior, turning the relationship between weather, location, and complex data sets like health conditions, product sales, and consumer activity into actionable, proven solutions, without relying on third-party cookie data.
Use context to deliver better ads
Contextual ads use context cues to determine which ad is the most appropriate to serve to your target audience. It can analyze the content on the page and other factors to determine messaging and ad placements. Contextual ads are becoming increasingly important in a cookieless future. It allows advertisers to continue to deliver personalized messages without PII.
Brands Using AI: Examples of AI and advertising
Here are two AI in advertising examples:
Behr uses conversational marketing to engage with consumers
Behr came to IBM Watson Advertising with the intent of improving the paint selection process for its consumers through personalized recommendations. Behr was able to leverage AI advertising and conversational marketing to provide customers with real-time recommendations, resulting in a 17 percent increase in purchase consideration and an 8.5 percent incremental lift in foot traffic.
A leading boots brand uses location data to target customers
A leading boots brand wanted to increase foot traffic to their retail locations. They wanted to leverage IBM’s accurate weather data in combination with shopping behavior to drive brand awareness. Location-based marketing was an important component of this campaign, helping IBM target the right people across media types. The campaign resulted in a 41.4 percent increase in foot traffic (this was 360 percent above benchmark), 21,000 incremental visits to the store, and a 57 percent reduction in ad waste.
The performance data and client examples cited above are presented for illustrative purposes only. Actual performance results may vary depending on specific configurations and operating conditions.
Our AI in advertising solution: Getting started with AI advertising
At IBM, we’ve experienced the benefits of combining AI in advertising. That’s why we created IBM Watson Advertising.
Our mission with Watson is to:
- Help ensure brands and publishers can use data meaningfully in a cookieless future.
- Forge mutually beneficial relationships that allow these partners to tap into IBM’s first-party data and AI-powered solutions.
- Help re-establish trust, privacy, security, and transparency in the advertising industry.
Why IBM Watson Advertising?
Through our expanded suite of open, unbiased, and cookie- and identifier-free AI solutions, our mission is to help organizations realize their unused potential. With our solutions, you can reach your audience in ways you never have before.