introduction
In 2023, a well-known worldwide retailer began using an AI-based system that replaced part of their marketing plan. The result was that they were able to increase their campaign conversion rates by over 30% in one quarter. This wasn’t by chance or happenstance, but rather due to leveraging artificial intelligence as a true partner in developing their long-term strategic marketing plan.
With the rise of AI as an underlying source of innovation for today’s marketers, it can be easily seen how the use of artificial intelligence will allow marketers to better understand and serve their target customers through a large volume of data created by the consumer and a highly competitive landscape within the digital channel. Companies who utilize AI effectively will be able to gain better insight, speed up the execution process, and realize measurable competitive advantage.
This article will focus on the three major components of utilizing AI tools to help organizations develop smarter marketing: 1) Customer Insight Driven by Data 2) AI Driven Content and Personalization and 3) Predictive Analytics and Campaign Optimization. These components demonstrate how marketing departments can transition from reactive tactics to thoughtful, scalable strategies.
AI for Customer Data Analysis
Transforming Information Overload into Usable Data
The volume of information available to today’s marketers is staggering; this includes behavioural patterns on websites, sales activity through CRM systems, activity on social media, open rates on email campaigns, and previous purchases. The major challenge most marketers face is being able to access data and then analyze it quickly enough to provide actionable insights. The use of artificial intelligence is a great tool for quickly finding patterns and relationships that would be nearly impossible to uncover without the assistance of machine learning.
Machine Learning Tools Powered by AI That Help With Data Analysis
Machine learning-powered platforms are capable of:
- Segmenting customers by behavior as well as traditional demographics
- Determining which customer segments are most profitable and are most likely to leave
- Identifying relationships between different channels based on the time of day that a campaign was run.
An example of how Artificial Intelligence can enhance the way you analyze Consumer Data is if you determined that a certain customer segments respond better to e-mail campaigns sent over the weekend than they do to e-mail campaigns sent during the week; this information was obtained because of the use of machine learning.
Practical Applications of AI In A Marketing Environment
Many brands are beginning to employ artificial intelligence (AI) powered customer data platforms in order to aggregate and analyze data from multiple channels. Some common examples of the uses of AI in the Marketing environment are:
- Segmenting customers based on their behavioral pattern
- Finding customer sentiment from reviews, surveys, and social media activity
- Mapping customer journeys through a conversion funnel to identify friction points
These analytical tools provide marketing teams with the ability to make data-driven decisions vs. Making assumptions based on historical data or traditionally developed buyer personas.
The way in which this differs from traditional analytical methods.
Traditional Marketing Analytics are focused on past data – what occurred last month, or the last quarter. In contrast, Artificial Intelligence (AI) is a highly dynamic and adaptive system that continually learns from new data, allowing marketers to respond almost immediately to changes in consumer demand. This shift moves marketing from a descriptive function to a strategic, insight-driven discipline.
Enhancing Content Creation Through AI
Like Traditional Marketing Analytics Many Marketers Continue to Experience Difficulty in Producing High Quantity of Quality Content Consistently
Content is fundamental to any effective marketing strategy, yet producing high quality, consistent, personalized content in a manner that scales is an ongoing challenge for most marketers. With the introduction of AI, marketers are now being supported throughout every stage of the content lifecycle – such as ideation, production, optimization, etc…
Some examples where AI can assist with the above include:
- The generation of content outlines, headlines and first drafts
- The optimization of copy for search engine optimization and readability
- Changing the tone of content for different audiences and/or platforms
- AI does not replace human creativity; however, it does allow marketers to be more strategic thinkers and focus on brand voice, narrative and story-telling.
- The Use of Artificial Intelligence To Provide Personalized Experiences at Scale
Personalization is not something to be considered optional; it is now a requirement. Consumers should expect brands to understand what their preferences are and be able to create personalized experiences. AI enables marketers to develop and execute personalized experiences that meet the expectations of consumers, and exceed those that traditional methods have been able to achieve.
Examples of AI based personalization include:
- Dynamic web pages – changing content based on visitor activity
- Email marketing, etc.
Maximizing Your Campaign’s Results Using Predictive Analytics
Moving from Guesswork to Forecast-Driven Marketing (3H)
One of the most effective ways to use AI in marketing today is through the use of predictive analytics. By looking at both historical data as well as real-time data, these analytics allow marketers to plan how to spend their resources more wisely by being able to predict what will happen in the future.
With predictive models powered by AI, marketers can:
- Be able to predict how well a campaign will perform prior to launch
- Analyze which channels are going to give the greatest return on investment (ROI)
- Determine the expected lifetime value of a customer and how likely they will convert
- These tools enable marketing leadership to move from reporting reactively to planning proactively.
Examples of Practical Campaign Optimization
- in practice, here’s how predictive analytics can be used to make smarter marketing decisions:
- Budget allocation – Move your budget to the channels that are most likely to produce conversions
- A/B testing at scale – Automatically select winning variations for your campaigns
- Timing optimization – Find the right time to reach out to each customer
An example of this would be having an AI system recommend increasing paid search spending during specific time frames when there is a higher likelihood of converting, rather than spending equally over the course of the entire month.
Competitive Advantage of Optimizing Manually vs. AI-Based Optimizations
Manually optimizing a campaign relies heavily on experience and gut instinct, which can vary widely from one marketer to another and often takes much longer. An AI-optimized campaign is able to continually monitor and evaluate the various performance indicators of the campaign over time, allowing it to provide recommendations based on up to the second changes in the market. Therefore, there is constant improvement in the marketing campaign through the use of AI technology, as well as the ability to adapt to changes that occur in the market.
calculation
With the help of Artificial Intelligence (AI), marketing will continue to evolve into a more intelligent, efficient, and customer-driven experience. Three key capabilities are what support a smarter marketing experience with AI, i.e., deriving in-depth consumer data from vast amounts of information; increasing the quantity and customization of content without sacrificing quality; and leveraging predictive analytics to enhance the effectiveness of marketing campaigns while developing them and throughout their entire duration.
Over time, marketing departments will use AI in all areas of their operations, from developing financial models to executing marketing campaigns and measuring their effectiveness. Companies that develop AI literacy, invest in data quality, and use data ethically will have the best chance of succeeding in the current and future marketplaces due to their advantage over competitors.
The call to action
Marketers need to stop playing with AI and get serious about implementing AI solutions as part of their main marketing strategy; starting small, concentrating on tangible outcomes (which will drive greater long-term benefits), and building on their successes. In a world where both the amount of attention available for customers and the expectations of customers are declining, smarter marketing (with the assistance of AI) has become a necessity.