5 Advertising techniques and strategies for you to try
By IBM Watson Advertising | 25 January 2022
5 Advertising techniques and strategies for you to try

As the pace of digital transformation continually quickens, all industries are challenged to keep up. Advertising is no exception. As advertising becomes increasingly digital, businesses need to find new advertising techniques and strategies that set them apart from their competitors. Current technologies offer advanced techniques that can give savvy firms the advantage.

What is an advertising strategy?

An advertising strategy is a comprehensive marketing plan for how your team will place your product or service in front of consumers and persuade them to buy. To make an advertising strategy effective, thorough research is required. This process includes having a deep understanding of the products or services you offer, your target audience, your competitors, and what your unique selling proposition (USP) is.

How to develop an advertising strategy

Although every organization has a slightly different advertising strategy with its own unique goals, there are some main components that should always be considered in development such as:

  1. Determining the target audience
  2. Setting key performance indicators (KPIs)
  3. Determining the steps needed to reach those KPIs
  4. Executing steps and strategies
  5. Testing new strategies, messaging, techniques or technology
  6. Measuring results
  7. Repeating or revising strategies based on learnings
5 Cutting-edge advertising techniques

Developing an effective strategy requires an innate understanding of the advertising techniques that are shaping the industry today. Here are five cutting-edge techniques and strategies to consider for your next campaign.

1. Improve decisions at scale through AI advertising

Artificial intelligence (AI) is transforming the advertising industry and 52% of survey respondents say that AI will play a critical or very important role in their jobs over the next twelve months. Therefore, advertisers who are looking to boost their strategy would be wise to realize the benefit of AI in analyzing vast amounts of data to optimize campaigns and drive more impact. 

Despite the massive amount of information available to advertisers, 64% struggle to measure KPIs accurately. With the loss of cookies and the increased pressure for privacy, it can be harder than ever to deliver relevant ads to the right people. AI can use contextual signals based on the content, weather and location to help advertisers make better decisions in terms of ad placements and creative.

AI advertising can help marketers and advertisers across a wide range of disciplines, including analytics, targeting and personalization. Different forms of AI Advertising may include cognitive advertisingconversational marketing and programmatic advertising. With AI, the possibilities are endless, and when used to make decisions in advertising strategy, can greatly help to scale efforts and improve ROI.

2. Interact with consumers through conversational marketing

According to a recent survey, the top use case for marketers looking to implement AI was to provide highly targeted content to users in real-time. With the challenges that data deprecation brings, 64% of marketers are concerned that consumers will lose trust in their marketing tactics and 47% are concerned with a loss in precision when delivering ads

However, conversational marketing can deliver hyper-personalized experiences, without the use of cookies or being intrusive. Conversational marketing is a method that engages consumers in dialogue-driven, interactive advertising experiences at a one-to-one level. It is a great way to interact with consumers in real-time while gaining unique customer insights that you can use in the future to better target your audience.

One company that used conversational marketing to advance its advertising campaign is Behr Paint. Looking to better reach consumers and help make their DIY process easier, they turned to the AI-powered IBM Watson Advertising Conversations solution to enable real-time, 1-on-1 dialogue with their customers regarding paint color recommendations.

The Conversations solution uses Watson’s machine learning capabilities to scale personalized connections with consumers. Through this solution, Behr gained valuable insights about what consumers are most interested in painting their living room, such as relaxing, comfortable, warm and friendly color moods. Behr was not only able to leverage these insights to improve ongoing product and marketing strategy, they were able to achieve the following results:

  • Over 10,000 1:1 conversations between Behr and consumers, helping each user find their own personalized paint color recommendation
  • 3.4x more time spent versus Google Rich Media interaction time benchmark
  • +108% engagement rate versus IBM Watson Advertising Conversations benchmark

Read the full case study here.

3. Achieve personalization through predictive targeting

Personalization is becoming increasingly important to consumers and marketers alike. Ninety-nine percent of marketers surveyed by Evergage agree that personalization has some sort of impact on the customer relationship and 78% agree that it has a strong or extremely strong impact.

Additionally, 92% of marketers also note that customers expect personalized experiences. In a separate report from Salesforce, 66% of customers want to be treated on an individual basis and 52% of survey respondents said they expect brands to always tailor their offers based on their tastes. However, only 34% of companies are delivering on this expectation. Ninety-one percent of advertisers strongly agree or agree that consumers’ demands are on the rise for personalized advertising, while 87% of advertisers acknowledge that heightened privacy demands have made delivering these personalized experiences more challenging to deliver.

With personalization becoming increasingly necessary, marketers will need to think strategically about how they deliver on personalized experiences and stand out from competitors. Some constraints may include ever-changing privacy regulations and a loss of cookie targeting. One way to provide personalized experiences without cookies is through predictive analytics and targeting. A predictive advertising tool works by using the latest in AI technology to analyze relevant data and score users based on the probability of taking a particular action. Predictive analytics can help advertisers anticipate consumer needs and 73% [3] of advertisers agree that the current landscape demands a predictive rather than reactive approach. Advertisers are able to save time and money by targeting the right audience the first time and putting ads in front of people who are likely to be interested.

4. Mitigate bias in advertising campaigns

Bias impacts nearly every decision we make, and in most cases this bias is unconscious. Positive or negative, these biases can become ingrained into the tools advertisers use, causing certain groups to become overlooked during campaigns.

Although CMOs and advertising executives strive to remain objective in their campaigns, bias can creep into the data being used and the algorithms deployed. However, AI and machine learning can also be leveraged to identify these advertising biases.

IBM’s AI tools can discover subgroups that are being advantaged or disadvantaged during campaigns, so companies can take proactive steps in mitigating these stereotypes. Through IBM, organizations can better scan for unconscious biases, so brands can more fairly target consumers across their entire advertising ecosystem.

5. Leverage weather targeting and weather-based ads

Another advertising technique that is often overlooked is weather-based advertising[4] . Also known as weather-triggered advertising, this AI-powered approach combines the power of weather’s ability to drive emotion and action with complex data sets like health conditions, product sales and consumer activity, into an actionable solution that drives sales.

One way advertisers can see weather’s power to elicit emotions and affect buying behaviors is when you compare the response of an individual on a rainy day versus a sunny day. On a cloudy, rainy day, consumers may spend the day indoors, leading to increased foot traffic or online sales. If they venture outside, they may realize they need to buy an umbrella or rain boots. On the other hand, if it’s sunny, consumers may be more inclined to buy sunscreen or ice cream.

It’s also important to consider where in the world these ads are being placed. For example, New Yorkers may wear shorts and a t-shirt in 60-degree weather, while consumers in Miami may opt for a jacket and long pants. With weather-based ads, advertisers can put the right ads in front of the right people depending on the weather in their specific area and their unique buying behavior.

Learn more about Watson Advertising

Whether you already have a strong advertising strategy under your belt or are looking to expand your techniques and stand out among competitors, IBM Watson Advertising can support your needs. With an array of AI-powered solutions that don’t rely on cookies, our solutions are designed for businesses looking to better predict future outcomes, automate complex processes and better optimize employees’ time.

Ready to start increasing sales and improving your bottom line? Learn more about IBM Watson Advertising’s solutions today.


The performance data and client examples cited are presented for illustrative purposes only. Actual performance results may vary depending on specific configurations and operating conditions