Get Smart: Three Ways to Use AI to Improve Your Next Digital Campaign

With the ability to synthesize large amounts of data points, Artificial Intelligence (AI) can transform marketers into proactive planners with precisely targeted campaigns that lead to better ROI. By processing insights in real-time and immediately putting that information to work, creation and delivery of hyper-personalized campaigns can happen in an instant, increasing lead-generation capabilities.

One of the strongest values of AI is its ability to improve as it gathers new data through progressive learning algorithms. Predictive Analytics can point to the likelihood of future outcomes based on historical data. The goal is to not only understand how a campaign performed, but to use that data to optimize future campaigns.

Narrow Your Focus to Unleash AI’s Power

AI allows marketers to analyze more data than a human mind can comprehend, but before this data can even be used to create a smarter response to an audience’s preferences, you’ll need to narrow your focus. Pixel tracking, for example, can provide an abundance of information, including whether the person opted in to receive your emails, visited your website, or added an item to a shopping cart. However, not all this information is useful for your ultimate goal, and could muddy the answers you really need. Narrowing down your scope to a specific event, such as driving new email subscribers, allows you to exclusively analyze data against the number of addresses you collect.

Read More: Good Bot, Bad Bot: How Machine Learning Is Fighting Fake News

With campaign intentions and business objectives clearly defined, AI’s power can then be unleashed to help you optimize against a specific action, and support your campaign performance in a number of different ways:

1. Enhanced Custom Content Curation

a. AI can help create highly personalized marketing campaigns that align with user interests and behavior patterns. Consumers already have a high level of expectation from bots that offer personalized recommendations to them for items such as books, housewares, and movies, based on their past behaviors. So, brands not using AI to customize offers and actions for their users will seem out of touch.

b. When looking at your campaign goals, did past performances yield better results on social? Or did you do find more success with banner ads? AI analyzes this type of information, filtering massive sets of data, to help marketers pinpoint which visitors should receive which content and on which platform(s). AI can also be used to optimize creative messages, titles, email subject lines, and even determine the best times of day to capture audience segments that are most likely to convert. AI can filter the content to ensure relevant offers, emails, and ads are appropriately delivered across all touchpoints. Continuing to use AI throughout the campaign gives real-time insights that you can immediately use to adjust and refine your content delivery approach.

2. Find New Audiences

a. Limiting market segmentation to basic demographics like job title, age, industry, and past behavior prevents marketers from identifying many of the nuances that can classify specific consumer traits. AI can gather and filter subtle differentiators to more accurately isolate characteristics that are shared by your most valuable customers by drilling down to more understated variances, to create new lookalike audiences with similar attributes.

b. Smaller, but much more relevant targets, allow you to spend less time and marketing dollars attempting to reach people who have n********** in your products or offerings. Instead, highly-targeted lookalike audiences, designed based on the information gathered from previous converting users, let you spend more time reaching lucrative and untapped targets.

Read More: The Power of Product Recommendation Engines

3. Optimize Content for Voice

a. The growing consumer preference for voice assistants is dramatically shifting the way content is found through search engines. According to a 2018 survey, 58% of consumers have used voice search to find local business information in the last 12 months, and 46% of voice search users look for local businesses on a daily basis. This matters to marketers because the keyword strings used for voice assistants are distinctly different than those used for typed keyword searches. Voice searches are often locally-driven and are more complex and long-tail, encompassing conversational phrases. Instead of typing “Netflix, Star Wars IV,” you would say, “Where can I watch Star Wars – A New Hope?”

b. AI can also help find phrases that match the natural language that your customers and prospects use when searching for your products. A study by Backlinko found that the average length of a voice search answer was 29 words. The answer will likely lead to more options and more questions, ultimately, resulting in a conversation between bot and consumer. Ensuring your content is voice-searchable could involve rewriting to incorporate long-tail keywords and semantic search strings. Figuring out how your audience will formulate search phrases, and what additional questions may be asked, can be difficult and time-consuming. AI tools cut this process down by helping predict questions for voice, and develop supporting content in advance by pulling information and patterns from historical internet searches to help marketers develop useful voice-searchable content.

The bottom line is that Machine Learning tools can make digital marketers smarter, without replacing them. Incorporating AI tools will help you attain a level of efficiency and profitability that would not be possible with traditional marketing tactics. While this list offers essential opportunities, it’s up to marketers to enhance their campaigns with AI-powered intelligence in order to put these strategies to work.

Read More: What’s the Next Game AI Will Solve?