Written by Shivani Koul on Digilah (Tech Thought Leadership).
As marketers, we fundamentally learn about the 4 Ps of Marketing: Product, Price, Place, and Promotion. Later, three more Ps were added: People, Process, and Physical evidence. Whatever we do revolves around the customer.
AI will disrupt all the Ps in many ways going forward, and many times there is an argument: will that take jobs? My assumption is that it will take non-productive jobs and give space to marketers to work on something newer, something smarter.
This is the role of technology! To assist humans in making the best possible product, but never forgetting that “human touch”. Marketing is all about creativity, empathy, and understanding human behavior. Successful marketing needs originality and a creative spark only humans can possess.
Having said that, a 2020 Deloitte global survey of early AI adopters showed that three of the top five AI objectives were marketing-oriented: enhancing existing products and services, creating new products and services, and enhancing relationships with customers.
The main job of any marketer is understanding the need of the customer, matching it with the offerings like product and services, and persuading the customer to buy the product and service.
This looks simply, a 3-step process, but there are a lot of critical steps & information involved in-between where marketers must analyze a lot of data and tweak the marketing strategy accordingly.
Let’s discuss it here with some real-time examples and see how marketers are using AI to support them.
1. Content Marketing –
Currently, AI can help in customizing the marketing content like product information, email writing, blogs, marketing messages, and copywriting. All this can be done using open AI tools available and should work on simple prompts.
With machine learning, this data can be used further for creating sales pitch, cross-selling pitch, customer engagement, last-minute deal or offer by considering different variables like demographics of the target consumer, behavior, demographic, along with deep analysis of the impact of communication. Example AI tools.
2. Data Analytics –
Slicing and dicing of data was done earlier as well, but AI has taken it to the next level where one can get predictive analysis and prompts/suggestions to enhance the content/marketing campaign.
Customer data like preferences, engagement, status as in which ladder of purchase funnel the customer and CRM, and that gives space to marketers for redefining the market strategy. Example CRM tools.
3. Search Engine Optimization –
This has been a game-changer with real-time examples like Google, Netflix, and other search engines. This will help segmentation of customers and suggest target advertising. This has also helped marketers to leverage cross-functional platforms.
So, if you search for some product on Amazon and open any social media like Instagram or Facebook, you will see recommendations of the same or similar products on that platform as well. By doing this, marketers can enhance the recall value of products or services.
4. Placement of advertisement –
This has been very important: where to post an advertisement for the best ROI. AI has made it easy to target or place advertisements based on consumer data like purchase history, preference, and context of purchase.
Example Google/YouTube advertisement.
5. E-commerce and Digital Marketing –
AI has been widely used by e-commerce websites and digital marketing to reach out to the right customers, understand their needs and buying patterns, and automate marketing workflows and course correction of marketing efforts which otherwise would have taken a lot of resources. Example any AI-enabled fitness app.
AI can be a game-changer in many ways, but Human decision-making is typically reserved for the most consequential questions, such as whether to continue a campaign or to approve expensive TV ads.
Training your algorithm enough that it should give expected results, training algorithms with correct prompts, and above all, safety and security of data.
Data privacy is going to be of utmost importance for AI. Clear and transparent policies need to be drafted against data security and privacy.
I believe AI is like a child which needs to be trained to become a responsible assistant; hence humans have a greater role as to how they are raising this child to serve mankind.
As marketers continue to embrace AI technologies, they must strike a balance between innovation and ethical considerations, leveraging AI’s capabilities to enhance customer experiences while upholding trust and transparency.
References:
https://hbr.org/2021/07/how-to-design-an-ai-marketing-strategy
Most asked questions
What are the 4 P’s of marketing?
4 P’s of Marketing: Product, Price, Place, and Promotion. Later, three more P’s were added: People, Process, and Physical evidence.
What is the key to successful marketing?
Successful marketing needs originality and a creative spark.
How is machine learning serving the marketing industry?
With machine learning, data is used for creating sales pitches, cross-selling pitches, customer engagements, last-minute deals, or offers along with deep analysis of the impact of communication.
Most searched queries
Machine learning
CRM (Customer Relationship Management)
SEO (Search Engine Optimization)
ROI (Return on Investment)
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