introduction
A small e-commerce company discovered that many of its customers made their final purchases much later in the evening than any of their competitors did, and they realized that when customers were browsing the web late at night, they would often make the best decisions to purchase items after being shown ideas for other things they may be interested in. This led them to implement an artificial intelligence-driven recommendation system that, just a few short months after implementing the AI system, caused sales from these customers to increase almost thirty percent. What previously took teams of analysts hours to complete, now happens in real time.
The use of artificial intelligence was once thought of as a futuristic concept that large technology firms would eventually use; however, today it plays an integral role in most aspects of the marketing experience we have from the playlists we build to the commercials we view on television. In today’s highly competitive marketplace due to the increase in competition among companies and the changing needs and demands of consumers, companies all around the world have started to treat AI not just like a tool, but as a partner that can help them gain a competitive advantage over their competitors.
In this article, I will review three ways that AI supports modern marketing, including providing greater insight into consumer behaviors via data analytics; providing more personalized marketing experiences to consumers through more sophisticated algorithms; and increasing productivity through automation.
Customer Insights Powered by Artificial Intelligence
Turning Data into Actionable Strategy.
The fundamental principle that drives modern marketing is an understanding of customers. There is, however, an abundance of data currently available to marketers, much more than one human could, or ever will, be able to interpret effectively. AI serves as a bridge to close this gap by providing actionable intelligence gained from the transformation of raw data (data that has not yet been transformed into actionable intelligence).
Improving Customer Understanding with AI
AI Systems are particularly effective in analyzing multiple data points (such as consumer behaviour patterns, purchase history, and consumer engagement metrics) to provide visibility of trends that historical data analysis fails to identify.
These trends can be seen in several examples:
Use of predictive analytics to allow retailers to forecast consumer buying behaviour based on previous consumer interactions with a retailer so that retailers can develop targeted consumer marketing campaigns to drive purchasing behaviour.
Sentiment analysis of social media and review sites for any product, service, or brand so that there is an accurate, real-time measure of public sentiment towards any product, service, or brand.
Customer Segmentation- traditional market segmentation has typically been based on broad demographic groupings. The use of AI enables the development of micro-segments from consumers based on their behaviours, likes, and likelihood to purchase.
An example of this is how many streaming services (such as Netflix) use machine learning to uncover viewing behaviours and provide viewers with highly accurate recommendations for content to view. This not only increases viewer engagement but will also provide marketing experts with clear direction for marketing strategies.
How This Differs from Traditional Market Research
Traditional market research uses surveys, focus groups, and historical reporting as its primary tools. Although effective, traditional market research has a tendency to be slow and generally reactive to emerging trends.
In contrast to traditional methods, AI:
Processes large datasets in a matter of seconds;
Identifies emerging trends early; and
Learns continuously and refines predictive capabilities.
As a result, marketing will continue to shift.
Hyper-Personalizing to Meet Customers’ Needs
Consumers do not want generic messaging anymore; they expect brands to understand their needs and provide them with what they want. This level of personalization can be accomplished in a scalable way with AI.
How Does Personalized Marketing Work?
AI analyzes an individual’s behavior on the web and personalizes the marketing messages dynamically across all channels.
Some examples include:
Dynamic email campaigns – Adjusting subject line and product recommendations by recipient.
Smart advertising – Automatically showing ads to those users most likely to click-through.
Website personalization – Visitors see different landing pages based on the person’s previous browsing history, geographic location, etc.
For example, e-commerce sites recommend products to enhance items already in a shopper’s cart. This increases the user experience and average order value.
Evidence of Impact
Research has consistently shown that using personalized marketing increases both engagement and conversion rates. Brands that create relevance for their customers will see increased interactions, as AI can drive relevance at a scalable level.
How It Beats Traditional Personalization
Traditional personalization involves placing customers in a category such as age, gender, or income level. With traditional personalization you can only assume what each customer will do based on the information you have collected. With AI-driven personalization, we no longer rely on assumptions but instead rely on actual behaviors.
Differences between old vs. new:
Static Marketing Campaigns ➜ Real-Time, Dynamic Response
Broad Marketing Messaging ➜ Targeted and Relevant to Each Individual
Guessing ➜ Data-Driven Analytical Precision
As competition continues to increase for both online and offline businesses, building relevance through personalization will help a business differentiate themselves from other brands in a crowded marketplace.
Scale Up Marketing Operations Use of Automation
Marketing teams continually under pressure to create greater amounts of content, manage additional channels, and respond even more quickly. Automation through artificial intelligence (AI) can help address this problem while maintaining consistency.
Immediate Benefits of AI-powered Automation
AI applications are now responsible for many of the tasks researchers previously took hours to do manually.
High-value examples of automation include:
Bots/virtual assistants for customer inquiry resolution in real time, providing better service and reducing operating costs.
Programmatic advertising, automated purchasing and placement of ad placements, providing maximum return on investment per advertisement.
Automated copywriting, marketing professionals’ assistance in writing copy, measuring copy performance metrics, and adjusting marketing copy messages accordingly.
Lead scoring, which identifies which potential customers are most likely to make a purchase so that sales teams can give their leads priority.
An example of where AI automation is handling a previously time-consuming task includes the use of chatbot technology by many financial services providers to answer frequently asked questions; thus allowing human associates to focus their efforts on resolving customer problems that require higher-level knowledge.
Why The Purpose of AI is Not Solely Speed
Some people criticize automation as reducing the human quality of marketing. However, when planned strategically, AI increases the quality of marketing.
Modern AI systems operate on a different level than previous automation technologies. Specifically, they:
Capture data from marketing campaigns and output that information;
Provide recommendations for improvement based on the previous outputs;
Use the captured data to help to determine the optimal time and channel to distribute a specific piece of content.
This creates a continuous improvement loop rather than a repeat execution cycle.
Companies that implement automation into their marketing process will have a significant advantage over companies that rely solely on manual processes.
In conclusion,
the rise of artificial intelligence has changed the way modern marketing works. By providing deep customer insights, enabling highly personalized experiences, and offering future intelligence through intelligent automation, artificial intelligence has changed the manner in which companies connect with their customers. An overview of the important aspects of AI’s relationship to marketing is as follows:
AI provides businesses with a means of translating complex data into strategic direction.
Personalization will be accurate, relevant, and scalable due to the use of artificial intelligence.
Automation increases productivity while improving campaign effectiveness.
The role of AI in marketing will continue to expand as algorithms become more sophisticated. Companies that do not quickly adopt AI technologies may fall behind their competitors who have sharper intelligence and faster execution.
Although adopting AI is critical to success, it is crucial that companies combine ethical data practices, human creativity, and defined strategic direction when utilizing AI. The best marketing approaches will occur when an organization’s insight and AI work together; they will not compete against each other; rather, they will collaborate to achieve successful outcomes.
The call to action
companies should first evaluate their marketing capabilities, identify the areas in which AI can provide immediate value, and then work on integrating AI into their marketing strategy. Organizations that take action right now will be able to keep up with changes in the marketplace while helping to create the future of marketing.
The question now is not whether AI can be used in marketing; it is how quickly your organization can adopt it.