Big data matters in marketing. Customer data, such as demographics and shopping patterns, are essential in creating an effective lead generation and marketing strategies.
However, managing big data is the biggest challenge in the digital era. For one, there are stringent laws on customer data capturing, and businesses face cybersecurity risks that can jeopardize data privacy.
Fortunately, marketing artificial intelligence (AI) technologies are now available, leveraging customer data and related tech concepts, such as data analytics, natural language processing, deep machine learning, and secure data access.
Learn the benefits of marketing AI technologies below.
1. Automate Marketing Processes
Automation technology minimizes human intervention. This technology involves programming machines and computers, equipping them with predetermination criteria and the ability to decipher subprocess relationships.
The types of AI that apply in marketing technology include stand-alone and integrated automation apps and stand-alone and integrated machine learning apps. These apps can help in automating marketing processes, such as the following:
- Automating email and chat messages
- Customer services, like chatbots that can recognize when to transfer a chat conversation to a live representative
- Recommendation engines of e-commerce platforms and other online platforms with search engines
2. Personalize Marketing Content
Marketing leaders must deliver the right message at the perfect timing. And that’s when marketing AI technologies can help through natural language processing, natural language understanding, and natural language generation. These AI technologies can help marketing teams quickly create personalized content to promote a consistent brand voice and meet consumer needs and demands.
Natural language processing (NLP) enables computers to understand spoken words and texts as humans do. By tracking website activities, this technology understands what online users want to read. For instance, NLP tracking algorithms can help identify which parts of content users highlight and scroll the most. NLP also determines what content users read or spend most of their time on.
3. Improve User Experience
When customers experience convenience, satisfaction, and happiness dealing with your brand, you can expect ripple effects in your business. For this reason, user experience is a priority across all marketing tactics. For instance, content marketing considers user experience to reflect overall customer satisfaction regarding content consumption.
Here’s how AI marketing technologies can help improve the user experience:
• Create Buyer Personas
Companies can use content and data intelligence platforms to know the customer personas reading their content. This step enables marketers to create specific and relevant content to deliver the best user experience.
• Audience Segmentation
Audience segmentation divides the audience into smaller groups for marketing research purposes. AI algorithms allow marketers to segment prospects according to their common characteristics, such as demographics and shopping behaviors.
• Find Keywords Based On User Intent
Marketing AI technologies like NLP can help customers get the information they need through search results. NLP research can help them find relevant keywords depending on user intent. It helps deliver the most relevant and helpful search results, improving user experience and overall brand experience.
4. Generate More Multi-Funnel Leads
Multi-funnel leads are prospects that come in different sales funnel stages, such as the top, middle, and bottom of the funnel. Generating multi-funnel leads is essential because it can significantly increase business revenues.
Marketing AI technologies can help generate more multi-funnel leads by determining where leads are in the buyer’s journey.
• Top-Of-Funnel Marketing
For instance, using AI technologies for top-of-funnel marketing can help marketers quickly spread brand awareness, generating leads that can become potential customers using AI and machine learning (ML) algorithms.
• Middle-Of-Funnel Marketing
In the middle of the funnel, marketers can use AI technologies to help marketers establish good relationships with already captured leads. Marketing specialists can distribute content, aligning their products and services with the prospect’s needs. Moreover, AI can help marketers understand the leads’ buying readiness, bringing them closer to the purchasing stage.
• Bottom-Of-Funnel Marketing
The bottom of the funnel is the part of the sales funnel where brands can convert leads into paying customers. Marketing AI technologies can make bottom-of-funnel marketing more successful, such as automatically generating promo offers for new customers.
5. Increase Marketing Campaign ROI
Using AI in marketing efforts can help teams gain higher returns on investment (ROI). It enhances and optimizes customer interaction by helping marketers create personalized content and optimize message delivery and timing. Moreover, AI marketing technologies can measure the impact of customer interactions to execute marketing campaigns more effectively.
6. Perform More Accurate Market Research
Companies can use AI marketing technologies to gather insights from data centers and market research.
Market research combines consumer behavior, economic trends, and other related elements to enhance and validate your business idea. AI technologies can help marketers understand their consumer base through market research, reducing business risks.
7. Improve Ad Targeting
AI captures the website activities of online users, which is helpful in ad targeting. Online users regularly search for a product on search engines. On their next visit, they’re surprised to see products related to what they’re searching for in the sidebar. This technology is ad-targeting AI.
With ad-targeting, AI measures the performance of ads and uses the data to serve the advertisements shown to maximize conversion, eliminating guesswork. AI technologies can help with creating more effective and profitable targeted ads.
8. Promote Better Pricing To Attract More Customers
Businesses that provide dynamic pricing tend to have higher sales. Customers always search for discounts to get great value for their hard-earned money. Hence, they search online and choose the seller that can offer the same product at the lowest price and best terms.
Machine learning can help promote dynamic pricing. ML works by sending discount offers only to leads who need the product and are bound to make a purchase. Furthermore, ML can help businesses send discounts to different customers. This capability can help marketers test several promotions simultaneously to determine the most effective ones and attract more customers.
Artificial intelligence marketing technologies provide many benefits to both business-to-consumer (B2C) and business-to-business (B2B) companies. These technologies enable marketing managers to plan and implement campaigns quickly with high accuracy, relevance, and security. As a result, brands can quickly boost their authority, good image, traffic, leads, and sales.