8 Best Marketing Automation Trends in 2023

Customer buying habits are constantly changing due to various factors such as social trends, economic conditions, and personal factors. Understanding buyer personas and delivering personalized content that meets their expectations is essential for companies to gain a competitive edge. However, building a personalized campaign and executing it across multiple channels is easier said than done. That's where marketing automation comes in.

In this article, we will look at the 8 key marketing automation trends, results, and real-life examples.

1. Omnichannel Engagement

Once a customer starts interacting with your brand, there are various channels to continue the engagement, such as chat, email, phone calls, social media, etc. These channels are valuable for companies, allowing them to promote their products/services and provide customer support across all devices, channels, and platforms.

Omnichannel marketing helps brands retarget prospects across multiple channels and convert them into potential buyers. However, there are some challenges marketers should be aware of when it comes to omnichannel marketing.

Customer Data Accuracy: Websites collect open online data of their visitors in various ways, including login/subscription pages, newsletter downloads, cookies, browser fingerprinting techniques, etc., to provide personalized customer experiences. However, over time, users may change their email addresses, phone numbers, and addresses. To keep customer information up to date, companies need to regularly check and identify outdated user data in their databases. Many important business data are available online, and B2B companies can use web solutions to update their data.
Data Management Across Different Platforms: Companies must integrate and manage data from various channels to provide a seamless customer experience across platforms. However, marketers face challenges in effectively managing customer data across different channels. Monitoring the customer journey at each stage is crucial for understanding the effectiveness of an omnichannel campaign and analyzing all digital interactions between prospects and the business. Otherwise, simply analyzing and measuring the overall campaign performance without considering each stage individually makes it difficult to identify where your customers are dropping off in your company's omnichannel journey.

Marketing automation allows companies to automatically manage content across all platforms. Marketing automation tools such as data collection tools and website tracking technologies should be used from the start of the customer journey to its completion. For example, marketers can spend less time troubleshooting technical issues and more time understanding customer needs and personalizing their omnichannel experience.

2. Multichannel Orchestration

Multichannel orchestration is using automation to reach and engage customers through various channels such as websites, email, SMS, and social media. Companies use different channels to bring customers back and empower them in the decision-making process to increase engagement between customers and brands. Automation tools enable brands to send:

Personalized push notifications in real time.
Hyper-personalized emails – adding customer names or product information to the email.
Scheduled SMS messages to customers.

3. Mobile Marketing Automation

Mobile marketing automation allows businesses to manage and automate manual mobile marketing processes. It tracks customer actions and collects data about them, such as location, gender, age, and purchase behavior, to offer personalized promotions and coupons through notifications, in-app advertising, and SMS.

Real-life example: Starbucks uses mobile marketing automation to offer special deals to its app users. The company allows customers to pay using the QR code app and earn stars for each order. These stars accumulate in Starbucks Rewards, which can then be redeemed for free food and drinks.

4. Marketing Funnel Automation

Marketing funnel automation is the use of software to automate manual marketing funnel processes in order to convert prospects into buyers.

Awareness: Automation tools allow companies to monitor websites and other social media platforms. With an automated data collector, companies can extract social media data from various web sources and track brand mentions based on specific keywords or relevant hashtags.
Consideration: Chatbots provide brand and product information to educate and inform customers.
Conversion: Chatbots collect customer contact information during conversations, such as email addresses, to send them personalized notifications about discounts, sales, and new products. Automation at the conversion stage aims to reach more prospects and assist them in the purchasing process.
Loyalty: Email automation software allows marketing teams to reach out to customers after purchase to collect feedback on the product or service.

5. Social Media Marketing Automation

Social media automation is the process of using software to automate and manage various social media marketing tasks and processes. Marketing teams can use social media automation to schedule posts in advance, analyze social media data in real time, and create custom reports for clients. Marketers can use automation tools to track brand mentions across various social media platforms by searching for specific hashtags, keywords, and topics.

6. Artificial Intelligence and Machine Learning

Artificial intelligence (AI) and machine learning (ML) technologies are used in marketing for various purposes, including content creation, real-time personalization, customer sentiment analysis, and marketing analytics.

Content Generation: Advances in AI such as natural language processing (NLP) and natural language generation (NLG) help companies automate manual content creation processes, such as product descriptions, real estate listings, emails, landing pages, etc. For example, e-commerce companies use AI-powered content generation tools to generate unique product descriptions for hundreds of different products.
Real-Time Personalization: Personalized content generators based on machine learning and natural language processing (NLP) allow companies to deliver personalized content to website visitors in real time through various marketing channels such as email, SMS, and website.
Customer Sentiment Analysis: AI and ML technologies help customer support and marketing teams extract customer feedback and comments from various platforms such as social media, emails, and blogs.

Real-life example: A research team collected 14,000 online reviews from Skytrax, a website dedicated to airport reviews and ratings. To better understand customer thoughts and expectations, sentiment analysis was applied to the collected data. Among the negative keywords frequently mentioned in the reviews were "delay," "late," and "refund." As a result, it turned out that the main issue for Asian airlines is delays and timing.

7. RPA for Marketing Automation

There are various areas where companies can implement RPA into their marketing processes. Below are the main marketing processes that can be automated with RPA:

Data Collection Automation with RPA
Marketers can use RPA tools to collect public customer data from social media platforms and web sources. Web scrapers combined with RPA allow for automatic collection of customer contact data and updating their database in the CRM system.

Competitive Analysis
Pricing is crucial for businesses; for example, if you set the price of your product/service too high compared to the current market price, you will likely be unable to increase sales unless your product has unique features.

On the other hand, setting prices too low will result in lost revenue. RPA helps companies determine the optimal pricing strategy for their products and services by analyzing current market and economic conditions. For example, companies can use web scrapers to browse and scan competitor websites to collect pricing data on e-commerce and retail sites such as eBay, Walmart, etc.

Automatic Bid Adjustment
Bid adjustment allows marketers and advertisers to understand how their ads perform across different platforms and devices. Marketers can determine how often their ads should appear on a particular device, in a particular location, and at a particular time. For example, if your ads receive the overwhelming majority of clicks from a specific device, such as a desktop, at a certain time, you can adjust bids accordingly and lower the campaign bid for tablet or mobile users.

Instead of manually analyzing and adjusting bids, advertisers and marketers can use RPA to automatically adjust bids based on target audience behavior and advertising goals. Suppose you are running a digital marketing campaign targeting a specific country and age group, and your target audience is most active on ads on weekends from 1 PM to 4 PM. To maximize impressions and conversions, RPA tools automatically adjust bids and show your ads to the target audience at the scheduled time.

Customer Engagement: RPA bots collect consumer information to understand their specific needs and help support representatives resolve issues quickly and efficiently. An RPA bot powered by OCR and NLP is able to read customer complaints and extract this data from various platforms. The extracted consumer data is then organized and converted into spreadsheets to create a consumer data report.
- Real-life example: The Cobmax sales center signed a new contract with one of the largest telecommunications companies in Brazil. However, Cobmax faced the challenge of handling a large volume of calls with its legacy and manual administrative systems. The company used an IBM RPA solution to automate time-consuming manual tasks and eliminate manual entry errors. With RPA, the company reduced back-office operations by 50%.

8. Conversational Marketing

Customer service and marketing teams can use chatbots and other conversational AI technologies to:

Provide quick responses to multiple customer inquiries simultaneously. Chatbots can be trained to answer common questions and solve simple problems using FAQs.
Initiate conversations with website visitors at a near-human level.
Provide personalized product recommendations based on visitor interactions.

Real-life example: Eureka Forbes, an Indian multinational consumer goods company, faced the challenge of meeting increased customer demand for products with its existing support service. The company needed a faster and more modern customer service solution to keep up with growing inquiries. Eureka Forbes partnered with Haptik to develop an AI-powered chatbot. By using the WhatsApp Chatbot solution in its customer service processes, the company was able to:

Provide quick responses to customer inquiries and more personalized products.
Engage over 1 million users via WhatsApp.
Handle over 1.5 million customer inquiries.
Save over 200,000 hours of call center agent work time.