AI Marketing: What, Why and How to use Artificial Intelligence in Marketing
In today's rapidly evolving business landscape, the role of marketing and marketing automation in transforming the way companies sell cannot be understated. While some firms may choose to segregate marketing and sales tasks, it is crucial for everyone involved to have a sound understanding of how these two areas interrelate and complement each other in order to facilitate closing deals.
Traditionally, sales funnels have started with marketing efforts, but there has been a noticeable shift in recent times due to changes in consumer buying habits. Such changes have had a profound impact on how marketers engage with prospective buyers, and it has become imperative for companies to adapt their marketing strategies accordingly. By staying ahead of the curve and embracing the latest marketing practices, businesses can stay competitive and build long-lasting relationships with their customers.
Marketing plays a large role in helping guide a prospective buyer through the sales sequence. This takes a significant workload off of sales staff and helps them focus on what they do best - closing the sale. One of the biggest evolutions is marketing automation. Salesforce describes this as “technology that manages marketing processes and multifunctional campaigns, across multiple channels, automatically.” Whereas before we took marketing from concept to development, and finally, deployed manually, now businesses can target customers with automated messages across email, web, social, and text.
Marketing automation itself is rapidly developing. One big change has been the use of machine learning (ML) to make automation ‘smarter.’ We break down how this happens in “How Machines Go From Dumb to Smart by Learning.” Below, we break down the areas where automation and machine learning are driving new revenue and productivity increases for tech-forward companies.
Why use machine learning in marketing?
Machine learning and marketing automation help content marketers reduce manual work, improve customer experience, and boost the performance of marketing campaigns.
With ML, companies can:
- Improve content with data-based recommendations
- Automatically classify content with tags
- Recognize the content in images and videos
- Create personalized messages for different audiences
- Automate repetitive tasks: social media posting, keyword research, email sending.
- Auto-optimize marketing messages and emails
- Auto-generate different content for simple stories
The incorporation of machine learning into marketing has completely transformed the approach companies take towards their marketing endeavors. With the assistance of machine learning algorithms, marketers can now analyze massive amounts of data, thereby gaining valuable insights into consumer behavior. This not only allows them to better understand their target audience, but it also empowers them to customize their marketing campaigns to suit their specific needs and preferences.
By integrating machine learning into marketing, businesses can stay ahead of the competition and drive growth by making data-driven marketing decisions.
By leveraging the power of machine learning, marketers can now create highly personalized experiences for their customers, which in turn results in a boost in engagement and loyalty. Another significant advantage of utilizing machine learning in marketing is its ability to optimize marketing campaigns in real-time. Machine learning algorithms can analyze data in real-time and make necessary adjustments to marketing campaigns based on consumer behavior. This means that marketers no longer need to depend on trial and error to determine the most effective marketing strategies. Instead, they can rely on machine learning algorithms to optimize their marketing campaigns and improve their return on investment. By integrating machine learning into marketing, businesses can stay ahead of the competition and drive growth by making data-driven marketing decisions.
Account-based marketing
Account-based marketing (ABM) can be a game-changer for B2B companies looking to increase sales. With the help of machine learning and marketing automation, businesses can effectively allocate their budget and prioritize accounts that have the highest likelihood of converting. By utilizing these technologies, companies can optimize their outreach and efficiently project the optimal time for sales outreach. This ensures that customers are contacted at the right time with the most appropriate message, avoiding outdated communication. Furthermore, by analyzing available data, marketers can predict lead behavior and customize messages to increase engagement and conversion rates.
In today's digital age, ABM has become a crucial tool for B2B marketing. By focusing on high-value accounts, companies can maximize their ROI and drive long-term growth. However, to reap the benefits of ABM, it is essential to utilize machine learning and marketing automation. These technologies can help businesses identify the most promising accounts, project the optimal time for sales outreach, and customize messages based on available data. By optimizing for SEO and expanding on these key points, companies can effectively leverage ABM to drive success in the B2B space.
HR and brand marketing
Machine learning and marketing automation help brands target the right people with the right content to increase awareness. In brand marketing, ML helps gauge brand sentiment by analyzing mentions of their business in social media. Also, it identifies gaps and areas of opportunities in the positioning compared with competitors. In HR marketing, ML helps attract and keep talents. Thanks to AI and ML, it is possible to develop personalized marketing campaigns and build the right plans for employees to learn and grow within the company.
The Future
Sales and marketing are rightfully obsessed with the future. The next big trend or product feature will excite customers and drive new revenue. Doing this at scale is a challenge, especially with consumers expecting more relevant (read niche) advertising specific to their interests. To do this well requires leveraging new technology, such as machine learning and marketing automation.