How AI Is Transforming B2B Marketing Strategies
Tags: ai, marketing, b2bmarketing, marketingstrategies
Published: 2023-02-22 08:50:50

Artificial Intelligence (AI) surrounds us in everyday life. From our phones to homes, AI is present in many popular consumer products like Alexa, Siri, and home automation systems like Nest and SmartThings. Robots are automating manufacturing and warehouse processes while car brands like Tesla are introducing self-driving features.

The stats mentioned below testify to how AI is growing —

- In 2023, the worldwide market for artificial intelligence is expected to grow to [$500 billion](https://www.expresscomputer.in/news/ai-sector-outlook-for-the-year-2023-expectations-from-the-upcoming-year/93836/).

- Moreover, [83% of businesses](https://pipeline.zoominfo.com/sales/statistics-about-artificial-intelligence) identify AI integration as a top strategic goal.

- [53% of IT firms](https://www.ibm.com/downloads/cas/GVAGA3JP) worldwide in 2022 said they had increased their use of AI during the previous two years.

As technology evolves, many departments tap into the power of technology to streamline and simplify key tasks. Currently, technology is primarily used in building software for different purposes. There is [software for product development](https://zeda.io/), tools for client services, robust sales software like Salesforce, and even marketing automation tools. 

All such software, at some point, uses AI. And marketing departments face an increasingly competitive landscape, pushing them to adopt AI. This helps better understand current clients, optimize campaigns, and gain a competitive edge. 

Let’s explore more.

## Understanding the working of AI and how businesses can use it
At its core, AI is an area of computer science that focuses on developing intelligent machines and software algorithms capable of performing tasks normally associated with human intelligence. Examples include image recognition, [natural language processing](https://dev.to/balapriya/natural-language-processing-101-4226) (NLP), machine learning (ML), predictive analytics, [deep learning](https://dev.to/ikatebaker/what-is-deep-learning-deep-learning-algorithms-take-center-stage-3i4l) (DL), and more. 

Here are some of the widely-used AI technologies for marketers —

- **Machine learning**: Algorithms can analyze and learn from data without being explicitly programmed.

- **Natural language processing**: It leverages AI to understand and process human languages, such as speech recognition or translation.

- Other aspects like computer vision and robotics. 

Marketing teams can use AI to drive more revenue while ensuring sales are targeted to those most likely to purchase. AI in sales and marketing can help understand clients better, especially for B2B companies that operate in a more complex buying cycle.

Let us now discuss how to get started with AI.

## Getting started with AI
B2B marketers increasingly leverage [Artificial Intelligence](https://dev.to/oleksiitsymbal/artificial-intelligence-in-marketing-boost-the-growth-in-2022-1g74) (AI) to streamline processes, generate meaningful insights, and personalize client engagement. However, before implementing an AI strategy, B2B marketers must be proactive in preparing to take advantage of AI’s capabilities.

Here are some key considerations for those looking to make the most out of AI in their marketing strategy.

## 1. Understanding the technology
B2B marketers must develop a thorough understanding of what algorithms can do and how they help create effective strategies. Ideally, key decision-makers will first comprehend how AI works to identify areas for improvement or involve external consultants if needed to move the needle. 

An ideal pathway to AI technology implementation is to —

I. Gather information on different types of AI technologies identifying the type of AI suitable for the task.

II. Evaluate research the implications before implementing it. This includes ethical implications and potential legal or regulatory implications.

III. Learn about the technology once you identify the most suitable AI technology. Also, consider its working and how it can be applied effectively across multiple departments that push marketing results.

IV. As AI technologies can be complex, consult experts who can provide advice and guidance that help you understand the technology better.

V. Lastly, before fully implementing the AI technology, test it to ensure that it performs as expected and meets your requirements.

## 2. Knowing the audience 
This includes knowing who the audience is, their likes and dislikes, and how they connect with the business. Marketers would rely on data collection tools to collate and analyze audience databases while leveraging AI in marketing campaigns (more on it later).

## 3. Know your data
This includes [structured data](https://dev.to/ruchernchong/making-seo-better-for-blog-posts-with-structured-data-3nmk), unstructured information gathered from social media conversations, or survey text analysis. Understanding such datasets will enable you to determine which algorithms suit your campaign needs. 

## 4. Setup performance metrics
Set up a system for measuring success across different channels, including tracking sales figures, website visits, clicks, impressions, etc., depending on your campaign objectives. This will enable continuous measuring of progress over time to identify trends and optimize marketing approaches where needed.

## 5. Integrate AI into existing processes
Identify where automation might be beneficial within existing workflows. For instance, using [sentiment analysis tools](https://www.altexsoft.com/blog/business/sentiment-analysis-types-tools-and-use-cases/) during client service interactions, chatbots during onboarding processes or leveraging ML algorithms when analyzing marketing success metrics. There are many ways to integrate AI into existing operations while providing value. 

## Role of AI in B2B Marketing
AI has become an integral part of modern business, soaking data from various sources and using it to create personalized, targeted campaigns. 

The scope of AI is now extended to the marketing department which helps identify client preferences to deliver a more tailored experience.

Let’s explore how B2B marketing can use AI to the fullest.

## Identify client patterns
Marketers use client data to identify patterns in consumer behavior that can create more effective marketing campaigns. For example, AI can target clients with specific types of content based on their interests, demographics, or purchase history. Such personalized marketing results in higher engagement and conversions as clients are more likely to respond to customized content.

Let’s explore how it works.

**Predictive analytics**
The most common application of AI in marketing is [predictive analytics](https://dev.to/lambdatest/how-can-you-use-predictive-analytics-to-optimize-your-testing-methods-2kl3). It starts with analyzing historical data where AI can detect patterns from past behavior and use them to predict how clients will behave. It allows marketers to plan campaigns better by allocating resources as required.

For example, a retailer might use an AI system to recognize when certain products are purchased together by a single client. It helps run targeted discount offers for them as a part of their next purchase. 

**Using NLP**
AI-enabled natural language processing (NLP) technology can help marketers understand clients better by analyzing conversations with support agents or on social media platforms like Twitter or Facebook. 

NLP systems can mine these conversations based on keywords, topics and sentiment, enabling audience segmentation. It analyzes large amounts of unstructured data, such as emails and social media posts to identify potential leads and client interests.

Also, businesses can adopt NLP to create chatbots that understand and respond to client inquiries in natural language. This helps marketers create personalized messages for each group, thus boosting client engagement and conversion rates.

**Updating segmentation strategies**
ML algorithms allow marketers to continually update their B2B segmentation strategies based on new insights emerging over time. This happens when more consumer behaviors and preferences data are collected, allowing marketers to not rely solely on static rules. 

Instead, they can adjust their strategies dynamically in response to changes in consumer demand to keep them relevant to current market trends.

**Task automation**
The growing technology of AI is prevalent in many departments and applications. The innovation in automation spans across technology, including audience segmentation for marketing, sales automation, [no code development](https://www.akveo.com/low-code-no-code-development) to eliminate the need for excessive coding, and other tasks that can be time-consuming. 

For marketers, it includes email campaigns, managing social media accounts, digital advertising content design, and much more. This saves marketers time and allows them to focus on more creative tasks.

AI is revolutionizing how B2B marketers approach their marketing efforts as there are tools to streamline many marketing processes, increasing efficiency and maximizing impact with potential clients.

**Content creation**
Content creators in the marketing team can use AI to generate relevant content that crafts engaging content for the target audience. 

For example, natural language generation (NLG) technology can automatically generate new content from existing data sources in different formats, such as blog posts and whitepapers. Think of how [NLG tools](https://en.ax-semantics.com/blog/top-natural-language-generation-nlg-software-in-2023/) help craft personalized and targeted content effortlessly.

**Personalization**
AI-based algorithms can analyze client data to determine what messaging is likely to be most effective with a business client. Understanding each client's interests, needs, and behaviors enables B2B marketers to create highly personalized experiences that drive engagement and conversions.

**Lead scoring**
Predictive analytics can also identify lead prospects who are most likely interested in a company’s products or services based on past behavior and other indicators such as demographics or purchase history.

Lead scoring can identify and rank potential clients based on their likelihood of becoming paying clients. AI can automate this process by analyzing large amounts of data and discovering patterns that indicate a high likelihood of conversion.

**AI helps lead scoring in the following manner—**

1. **Predictive modeling**: Help analyze data of past clients and identify patterns that indicate a high likelihood of a lead becoming a client. This can include demographics, job titles, industry, and online behavior.

2. **Machine learning**: Learning from historical data and adapting its lead scoring models to improve their accuracy over time.

3. **Real-time scoring**: Analyzing leads in real-time and immediately prioritizing the most promising leads for follow-up.

AI can help B2B marketers prioritize leads and focus their efforts on the most promising prospects, increasing the chances of conversion and reducing acquisition costs.

## Client Service Automation
Client service is gradually becoming one of the highly robust pillars of B2B marketing. Here, marketers can use AI to automate client service tasks such as answering basic queries and resolving client issues.

This can allow client service agents to focus on more complex tasks and provide a better client experience. Also, these client service executives can monitor feedback and provide insights into client satisfaction.

Overall, it opens up opportunities for businesses to use AI in the following manner.

**Live chats**
AI bots can interact with clients directly over the phone or live chat on websites. These robots are programmed to answer common questions, provide helpful information and ask follow-up questions. These bots reduce wait times by providing quick responses that require a real person to answer, freeing client service representatives to focus on more complex requests.

**Automate feedback surveys**
Client feedback surveys help gain valuable insights into what clients think about your products and services. The automated process eliminates manual labor while capturing valuable client feedback. In turn, marketers can analyze such feedback and improve future campaigns based on what works well and needs improvement. 

**Data-driven feedback analysis**
Marketers can use client feedback to enhance their strategies. One strategy includes leveraging data-driven feedback analysis that uses natural language processing and sentiment analysis to analyze client feedback. Here, AI can identify client sentiment and key topics in client feedback which help determine client satisfaction or dissatisfaction with the product or service.

## Optimize ad spend
AI analyzes existing client data and targets clients with ads more likely to convert. When it comes to paid marketing, businesses can test different ad variations and determine which ones perform best.

AI in ad spending can help in the following manner.

**Niche marketing**
AI algorithms can automatically target the right audience at the right time with the right ad message. AI-driven segmentation and targeting help pinpoint ideal client profiles and create hyper-personalized campaigns tailored to client interests and behaviors. This ensures that ads reach their intended audiences more precisely, resulting in higher click-through rates (CTRs) and improved return on investment (ROI).

**Automate bid management**
AI also automates bid management strategies based on business goals. With [machine learning](https://dev.to/makendrang/what-is-machine-learning-1mkl) algorithms, marketers no longer have to adjust bids across multiple channels and platforms manually. AI tools measure data points such as demographics or geography to maximize visibility for certain audiences. 

This helps save considerable time and money, allowing B2B marketers to focus more on the creative aspects of campaigns rather than spending hours researching keywords or analyzing trends.

**Campaign insights**
Get insight into campaign performance in real-time with AI in place. Marketers can identify what exactly works best for their particular approach. This data helps quickly decide where to allocate ad budgets for maximum effectiveness. 

AI-driven campaign insights help build new campaigns around areas where conversions are high or need shifting resources away if an activity needs to yield desirable results. Such readily available insights offer greater value to the business from their investments as they reduce ad spending over time due to increased efficiency within their digital marketing strategy.

## Wrapping up
The time has come for small and medium businesses to use technology that helps them compete with larger corporations. One such technology is AI, which can optimize campaigns in real-time, helping businesses maximize ROI from advertising campaigns. AI has the potential to redefine B2B marketing by providing a more personalized client experience and opening up new opportunities for businesses to engage with their clients. 

As mentioned above, a brief overview of AI technologies for B2B can help one get started in the right direction. Marketers can start with solutions that help automate tasks, provide more accurate customer segmentation, personalize messaging, and predict customer behavior. 

Cover Image Source: [Unsplash](https://unsplash.com/photos/m_HRfLhgABo)