Steps to Develop a Robust AI Marketing Strategy


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All marketers, from product to content marketers, can use AI at every customer journey stage. It uses deep learning, data analytics, and other machine-learning techniques.

AI uses client and business data to improve marketing outcomes and free up team time. Most firms are aware of the use cases of AI marketing, such as:

  •  Lead generation or upselling chatbots
  • Automating marketing campaigns
  • AI-written emails, ads, and blog posts
  • buying ads programmatically
  • leading ranking and scoring
  • Facebook sentiment analysis
  • Language localization and translation
  • Reviewing writing responses
  • segmenting customers

There are countless applications for artificial intelligence in marketing. Marketers must create an AI marketing plan that works for their team and their particular requirements.

Using AI to develop a marketing strategy

Firms must know the gaps and strengths in their current marketing strategy to use AI strategically. Each company has specific challenges, opportunities, and audiences.

A tried-and-tested template AI marketing strategy cannot work for everyone. Each business must develop its own to fit its goals.

1. Recognize the various applications of AI in marketing

Before implementing any solutions, comprehend how AI can benefit the marketing processes.  Here are the various applications of AI in marketing.

  •  Content creation

Implementing a Search Engine-Optimized (SEO) content strategy requires time, effort, and hard cash for many businesses. However, AI can significantly boost content production while reducing costs.

AI-powered content creation is intended to address the execution challenges that every content team faces. It’s a tool to increase production speed, not a replacement.

However, it’s crucial to schedule time for editing even when using AI-powered content production software. Content that looks like it is generated from generative AI will not work on search engines and may sound artificial to clients.

  •  Additional forms of content creation using AI

Purchasing an AI content generator would probably be a wise first step. AI could aid brands in developing briefs and handle the majority of the writing work.

This could result in a drop in spending and a sharp rise in content creation, improving SEO results more quickly. AI can also write copy for ads, social media posts, and email marketing that encourages conversions.

  •  Conversion rate improvement

AI can assist marketers in converting leads by tailoring the content of websites and landing pages for particular site visitors. Marketers can use AI platforms to personalize content for leads based on their persona, pain points, and needs.

It can create account-based landing pages matched to specific ads. Users can also run A/B tests on the website copy to determine which option converts the best and select it.

  •  Personalized recommendations

Consumers demand personalized interactions from brands.

According to the McKinsey & Company Value of Personalization report,

Value of Personalization

AI marketing platforms enable businesses to personalize their marketing. They help with:

  • Analyzing and forecasting customer purchases
  • Personalizing marketing messages
  • Adapting offers to customer preferences
  • Stronger content for sales enablement

Sales and marketing frequently collaborate, and AI can assist marketing teams in producing better sales enablement copy for their sales teams.

  • Social interaction

AI enables businesses to track and synchronize brand mentions on social media platforms and analyze sentiment. Social listening allows marketers to monitor customer feedback, industry trends, brand development, and customer sentiment.

Marketers can interact with customers, convert leads, and use real-time feedback to inform upcoming marketing campaigns by monitoring social media.

  • Adaptive pricing

Dynamic pricing enables businesses to adjust prices in response to current supply and demand. Some AI tools can even tailor pricing based on consumer behavior. It includes search history or demand for a particular product.

  • Localization and Translation

AI-powered translation simplifies the process for marketers to serve the increasingly global audiences that brands cater to. Marketers can quickly roll out their websites, apps, marketing and sales assets, and documents to new audiences in their native languages.

  • Put predictive analytics to work.

AI can help marketers predict customer churn because it can spot patterns. AI platforms can identify customers at risk of churning and flag them for marketers.

They work to win them back using signals like survey responses, general customer sentiment, and prior interactions with a client.

This is an area where investing in AI can have a high return on investment.

  • Automation

Even though this use case is not specific to marketing, it is still helpful for marketers in the modern world. Many previously manual tasks marketers perform can now be automated with AI.

This includes buying ads, scheduling and sending emails, managing projects, timing customer outreach, and tracking customer behavior.

2. Examine the needs of marketing teams

Most businesses are unable to implement all AI tools at once. For a start, analyze the present marketing objectives and workflows. Then, decide which apps are immediately required. Organizations might want to consider asking the following questions:

  • Where does the marketing department’s staff spend the most time?
  • What are the workflow bottlenecks currently?
  • Which key performance indicators (KPIs) do teams hope to raise?
  • Which platforms are most popular with the audience?
  • Where in the workflow might an AI solution fit in naturally?

The responses give you a better idea of what solutions to explore.

3. Decide on an app

Start by looking into several possibilities. Then, narrow the selections based on the criteria that are most significant to the firm, such as:

  •  Pricing
  • The tool’s usability and intuitiveness
  • User opinions
  • Simple onboarding
  • The capacity to integrate with other tech stack tools

If there is confusion between the two choices, check to see if the tools begin with a free trial. Teams can then put each choice to the test and determine which is best for them.

Here are some approaches to each use case in case firms are unsure of where to begin:

  •  AI tools for producing content
  • Tools for Automating Sales
  • Advertising tools with AI

4. Prepare the team

Adopting a tool is pointless if your team never uses it. Apty’s report – The Enterprise Secret to Software Adoption & Digital Transformation Success

Digital Transformation Success

Teams should be involved in the implementation process. It increases the likelihood that the staff will use the software consistently. Also, employees are more likely to rely on a product if it is simple.

Many businesses never teach their teams how to use new tools. Make a conscious effort to provide live training for the team; do your best to keep them interested.

Establish a training schedule for the deployment and use processes. Once deployed, include employee feedback as a critical element. Treat training as a constant conversation. Additionally, over time, this aids in gradually improving their understanding of the software.

Teams should have access to step-by-step instructions, product demos, and other useful materials. Ensure that new hires receive onboarding instructions on how to use the tool.

Also Read: Using AI to Enhance the Video Marketing Strategy


The impact of the new tool should be constantly measured. Track the KPIs over the coming months to ensure the new AI software delivers on its promises. It should measurably optimize cost and revenue and elevate customer satisfaction.

Organizations must identify another area where AI can help grow the business. It can help enhance marketing while saving time, effort, and money.

Swapnil Mishra
Swapnil Mishra
Swapnil Mishra is a global news correspondent at OnDot media, with over six years of experience in the field. Specializing in technology journalism encompassing enterprise tech, marketig automation, and marketing technologies, Swapnil has established herself as a trusted voice in the industry. Having collaborated with various media outlets, she has honed her skills in content strategy, executive leadership, business strategy, industry insights, best practices, and thought leadership. As a journalism graduate, Swapnil possesses a keen eye for editorial detail and a mastery of language, enabling her to deliver compelling and informative news stories. She has a keen eye for detail and a knack for breaking down complex technical concepts into easy-to-understand language.


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