Top 8 Marketing Automation Trends for 2024 (with case studies)

Customer buying habits constantly change due to several reasons, such as social trends, economic environment, and personal factors. Understanding buyer personas and providing personalized content to meet their expectations is critical for businesses to gain a competitive advantage. However, building a personalized campaign and executing it across multiple channels is easier said than done. This is where marketing automation comes into play. 

In this article, we will examine the top 8 marketing automation trends, business outcomes, and real-life examples.

1. Process automation

1. Omnichannel engagement

Once customers engage with your brand, there are various channels to continue that engagement such as live chat, email, phone calls, social media, etc. These channels are valuable for businesses to promote their products/services and provide customer support across all devices, channels, and platforms. 

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

• Customer data accuracy: Websites collect their visitors’ public online data in many different ways, including login/signup pages, whitepaper downloads, cookies, browser fingerprinting techniques, etc., to provide a tailored experience. However, users may change their email addresses, phone numbers, and addresses over time. In order to keep customer information up to date, businesses need to regularly check and identify obsolete user data in their customer databases. Many important business data is available online and B2B businesses can leverage web data solutions to refresh their data.

• Managing data across different platforms: Businesses must integrate and manage data from various channels in order to create a seamless omnichannel customer experience across multiple platforms. However, marketers face difficulties in effectively managing their customer data across multiple channels.  Monitoring the customer journey at each stage is crucial to understanding how your omnichannel campaign performs and analyzing all digital interactions between your potential customers and your business. Otherwise, just analyzing and measuring the effectiveness of the entire campaign without including each step separately will make it difficult to identify areas where your customers drop off in your company’s omnichannel journey.

Marketing automation enables businesses to manage their content across all platforms automatically. Marketing automation tools, such as data collection tools and website tracking technologies, should be used from the beginning of the customer journey to the end. Marketers, for example, might spend less time fixing technical issues and more time understanding customers’ needs and personalizing their omnichannel experiences.

Omnichannel marketing stats:

1. Omnichannel campaigns that use three or more channels increase the order rate by 494%

2. Multichannel orchestration

Multichannel orchestration is the use of automation to reach and engage customers through different channels such as websites, emails, SMS, and social media. Companies use various channels to bring customers back and empower them in their decision journeys in order to increase engagement between customers and brands (see Figure 1). Automation tools enable brands to send:

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

Figure 1: Comparison of multichannel and omnichannel marketing.

3. Mobile marketing automation

Mobile marketing automation allows businesses to manage and automate manual mobile marketing processes. It monitors customer activities and collects data about them, such as their location, gender, age, and purchase patterns, to offer personalized promotions and coupons via notifications, in-app ads, and SMS. 

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

Mobile marketing automation stats:

• The mobile advertising spending market in the United States is expected to reach $145.26

4. Marketing funnel automation

Marketing funnel automation refers to using software to automate manual marketing funnel workflows to convert prospects into customers (see Figure 2). 

1. Awareness: Automation tools enable businesses to monitor websites and other social media platforms. With an automated data collector, businesses can extract social media data from different web sources and monitor the mentions about brands using specific keywords or relevant hashtags. 
2. Consideration: Chatbots provide information about the brand and product to educate and inform customers.
3. Conversion: Chatbots collect customers’ contact information during the conversation, such as email addresses, to send them personalized notifications about discounts, sales, and new products. The conversion stage automation aims to reach out to more prospects and empower them in their purchasing process. 
4. Loyalty: Email automation software enables marketing teams to reach out to customers after purchase to collect feedback regarding the product or service.

Figure 2: The explanation of each stage in the marketing funnel.

5. Social media marketing automation 

Social media automation is the process of using automation software to automate and manage various social media marketing tasks and processes. Marketing teams can use social media automation to automate post scheduling in advance, analyze social media data in real time, and generate customized customer reporting. Marketers can use automation tools to track brand mentions across multiple social media platforms by searching specific hashtags, keywords, and topics.

2. Artificial Intelligence (AI)

6. Artificial Intelligence and Machine Learning

Artificial intelligence (AI) and machine learning (ML) technologies are used in marketing for different purposes, including content generation, 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 businesses to automate manual processes in content generation such as product description, real estate listing, sales emails, landing pages, etc. For example, eCommerce companies use AI content creation tools to generate unique product descriptions for hundreds of different products.

• Real-time personalization: AI-powered personalized content generators powered by machine learning and natural language processing (NLP) enable businesses to provide customized content to website visitors in real time via different marketing channels such as email, SMS, and website.

• Customer sentiment analysis: AI and ML technologies help customer service and marketing teams extract customer reviews and comments from different platforms such as social media, emails, and blogs. 

Real-life example: The research team collected 14,000 online reviews from Skytrax, an airport review and ranking site. Sentiment analysis was applied to the collected data to understand the customers’ thoughts and expectations better. The negative keywords frequently mentioned in online reviews were ‘delayed’, ‘late’, and ‘return’. The result revealed that delay and timing was the main issue in Asian airlines. 

AI & ML marketing stats:

• According to the survey, 1,000 businesses and 364 AI leaders adopt AI

3. RPA

7. RPA for marketing automation

There are different fields where companies can implement RPA in their marketing processes. The following are the primary marketing processes that can be automated using an RPA tool:

Automating data collection with RPA

Marketers can use RPA scraping tools to collect customer public data from social media platforms and web sources. Web scrapers combined with RPA allow businesses to collect customer contact data automatically and update the customer database in a CRM system.

Competitive analysis

Pricing is crucial for businesses; for instance, if you set your product/service prices too high compared to the current market price, you will most likely not increase sales unless your product has unique features.

On the other hand, if you set your pricing too low, you will lose revenue. RPA helps businesses to establish the best pricing strategy for their products and services by analyzing the current market and economic conditions. For instance, businesses can leverage web scrapers to browse and crawl competitors’ websites to collect pricing data from eCommerce and retail websites such as eBay, Walmart, and others.

To learn more about competitive intelligence:

• Ecommerce Competitive Intelligence: 5 Benefits & Tools
• Top 10 Competitive Intelligence Tools & Selection Guide

Automatic bid adjustments

Bid adjustments allow marketers and advertisers to understand how their ads perform across different platforms and devices. Marketers can decide how frequently their ads should appear for a certain device, location, and time. For example, if your ads receive the vast majority of clicks from a specific device, say a desktop, at a specific time, you can adjust bids accordingly and decrease the campaign’s bid for tablet or mobile users.

Instead of manually analyzing and adjusting bids, advertisers and marketers can leverage RPA to automatically set bids based on target audience behaviors and advertising goals. Suppose you’re running a digital marketing campaign focusing on a specific country and age range and your target audience is most engaged with your advertisement on weekends between 1 and 4 p.m. To maximize impressions and conversions, RPA tools will automatically adjust bids and show ads to your target audience at scheduled times.

• Customer engagement: RPA bots gather information about the consumer in order to understand their specific needs and assist customer service representatives in resolving problems quickly and efficiently. An RPA bot that is powered by OCR and NLP has the ability to read customers’ complaints and extract this data from various platforms. The extracted consumer data is then organized and converted into spreadsheets to generate a consumer data report.
  • Real-life example: Cobmax Sales Center signed a new contract with one of Brazil’s largest telecommunications companies. However, Cobmax was challenged in handling the high volume of calls with its outdated and manual administrative systems. The company used IBM’s RPA solution to automate time-consuming manual tasks and eliminate manual entry mistakes. With the RPA tool, the company reduced back-office operations by 50%.

RPA for marketing automation stats:

• Organizations that implemented RPA improved customer service (57%).

4. Conversational AI

8. Conversational marketing

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

• Provide quick answers to multiple customers’ queries simultaneously. Chatbots can be trained to answer common questions and resolve simple issues using FAQs. 
• Start conversations with website visitors on a near-human level.
•  Provide tailored product recommendations based on visitor interaction.

If you want to get started with automation in your marketing processes, feel free to check our data-driven list of marketing automation consultants.

If you need help in identifying marketing automation solutions for your business, we can help you get started:

Further reading

• 12 Best Practices of Ecommerce Market Intelligence
• Top 10 Market Intelligence Software
• Social Media Scraping: Tools, How-to & Case Studies
• How to Scrape Instagram and 6 Best Instagram Scrapers