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AI In Marketing: Top Skills & Tools You Need In 2023

AI In Marketing: Top Skills & Tools You Need In 2023
Anton Klein
Marketing Associate

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Welcome back! Has ChatGPT crept into your conversations as well? Even with people you thought couldn't care less about AI or anything IT-related? Well, if you don't know what ChatGPT is yet, we sadly must admit you might be living under a rock.

The speed of AI's relevance and integration into our daily lives can be quite overwhelming, which is why our last blog started with the basics of AI in marketing. We looked at how and why AI has become relevant in marketing, why it's here to stay, and what customer surveys reveal about their preferences and behavior in relation to AI in personalized marketing. 

This extension goes a bit further, offering skills and statistics examined by top consulting firms for addressing AI challenges in marketing, as well as a list of AI tools that any business owner can implement to benefit from AI as well.

[#section1]Top Skills: Maximized Data Exploitation, Tech Talent & Inter-functional Data Sharing[#section1]

We believe that the AI enthusiasts at the Dartmouth Conference in 1957 would not have believed their eyes when they saw the amount of AI-based marketing technology solutions we now have. $15.84 billion – that was the estimated market value of AI in marketing in 2021. For 2028 - $107.5 billion is projected.

based on:

This makes sense because marketing and sales departments welcome AI solutions with a trillion-dollar-smile. According to McKinsey, AI has the biggest impact within these functions and especially in risk management across all business operations and service options towards customers.    

We couldn’t find stats for the growth of AI marketing technologies but we’re lucky that out of the 9,932 martech solutions in 2022 some are based on AI and thus contain Machine Learning (ML) capabilities to help us marketers with:

  1. Data collection
  2. Data governance (qualifying)
  3. Data treatment & consolidation
  4. Transformation into actionable steps.

However, for some, it’s difficult to find the right tools or to assess if enough features are provided. Less advanced tools like Data Management Platforms (DMP) help with steps 1-3 where internal and external data from various sources like Google Analytics, Google Search Console, social media, and various SEO tools are consolidated and displayed on a sleek dashboard. However, this data is anonymized and according to Segment, mostly reliant on 2nd and 3rd party data.  

Steps 3 and 4 have the potential to maximize data insights and help in designing customer journeys, but only when further ML capabilities are existent. Here the invention of Customer-Data Platforms (CDP) hit the nerve of marketing specialists a couple of years ago: Not only does it collect fragmented and personalized 1st party data across millions of internal and external touchpoints, but the integrated ML automation is also smart enough to sync multiple data points around one single customer, map customer segments and traits – and eventually execute campaigns in real time.  

However, the resulting potential to improve performance usually remains untapped if employees do not interpret the data provided correctly or comprehensively. That's why tech talent needs to be built, but also cross-functional communication needs to be accelerated:

1. Bridging the Gap Between Science and Economy:

To benefit from these platforms, organizations must invest in knowledge building that until now was exclusively demanded by specific professions. Newer technologies like Natural Language Processing or Artificial Reality can only be utilized for better customer experiences when the capabilities to implement, use and/or interpret the raw data are present – at best inhouse. In-house is ideal because at the end of the day, a business knows their own customers best. Moreover, it is necessary to iterate and test different AI solutions to choose the most effective ones.  

Continuous learning must be further promoted in corporate cultures, so employees learn about new technologies quickly and adapt best practices. The best example is ChatGPT that shook the marketing world to its core and now requires marketers to at least get an idea of how AI can be integrated into their everyday lives.

2. Agile Capabilities to Match the Inter-Disciplinary Nature:

Personalization cannot be done effectively if ideation, data collection, treatment, interpretation, and transformation are done within one silo: the marketing department. To accelerate the effectiveness of AI in marketing and rapid execution, the task must be done cross-functionally, meaning that information, expertise, and problem solving are shared between departments.

Thus, employees must be willing to express the need for expertise and help, be open to collaborate and transparent about insights. This can only make sense since the customer's journey is affected by all functions within an organization and vice versa. AI generated data gives insights for R&D, product and service optimization, accelerates marketing, adjusts delivery, and impacts customer services.

[#section2]Enhancing Data Privacy to Overcome Consumers’ Ambivalence in Data Security Concerns[#section2]

Even though consumers know that data is the heart of personalized experiences, a KPMG-survey from 2021 about US-citizens’ attitude towards data responsibility revealed that 86% are concerned and 30% aren’t even willing to share.  

Taking it to the global scale, a 2021 study from YoGovAmerica confirms the same predominant concerns:

based on:

Businesses walk on a very thin line between trying to meet customers’ expectations while also accessing the necessary data. Against the background of huge data breaches like Telekom last year or Cambridge Analytica during the 2016 elections, it’s clear that data collection enhances (non)monetary risks. Consumers' ambivalence between what they expect and what they are willing to give when it comes to their personalized experiences makes it critical for companies and marketers to be perceived as truly transparent, rather than intrusive. According to KPMG and McKinsey this can be achieved through:

  1. Data Transparency & Monitoring: Being proactively transparent regarding the form of data usage and monitoring third-party firms that treat clients’ personal data.
  2. Data Minimization: Anonymization of personal data, limiting data processing to what is necessary and discarding it when it’s no longer needed.
  3. User Control: Giving the customers control by ensuring them the right to have their data history eliminated and the control to access, correct, delete, or port their data.
  4. Corporate Data Responsibility: Defining, addressing and communicating data governance and data protection policies as strategic goals and transferring these goals to the operational level - through training - rather than viewing them as a risk management tool. Here it is necessary to formulate goals against which employees can be measured. In addition, frequent data protection risk assessments help to identify and mitigate potential risks.

Did you know there has been a hashtag named “creepymarketing” where consumers exchanged marketing attempts they found creepy? We should do our best not to raise concerns or suspicions among consumers by making advertising feel more natural.

[#section3]How AI Benefits Can Be Leveraged by Any Business and Size in Marketing: Top 8 AI Tools for Small Businesses[#section3]

Companies might think that AI tools require high initial investment and are more for medium to large enterprises that have in-house IT departments, IT experts, and talent that eat AI for breakfast. Fortunately, a company doesn't have to have a degree in AI to select and use a variety of tools. We've done the choosing for you and created a list of AI tools that are easy to use, compatible, affordable, and relevant to small businesses:

  1. Canva: A tool businesses might already know. Canva uses AI to suggest layouts, design elements and colors for anyone who wants to create professional marketing collateral for free without having to consult people like us.  
  2. Hootsuite Insights: For $99/month the social media analytics tool helps businesses analyze data from up to 10 social media platforms, identifying patterns and insights. It also suggests the best time to publish, customizable reports and templates (for clients).
  3. Hugging Face: As explained in the previous AI blog, social listening provides invaluable consumer insights. Hugging Face is an NLP library that enables small businesses to build and deploy models for NLP tasks such as sentiment analysis, text generation and language translation – without an IT degree. The pro account is priced at $9/month only.  
  4. Mailchimp Einstein: The email marketing tool uses AI to analyze customer data and personalize email campaigns for better engagement and conversion rates. It assists with e-mail scheduling, send time and content optimization for 6.000 mails per month at $18/month already.  
  5. OptinMonster: AI enhances the quality of leads and thus reduces call time and personalizes engagement. OptinMonster is an affordable lead generation tool that uses AI to personalize website interactions, increase conversion rates and reduce bounce rates. Price starts at $9/Month for 2.500 pageviews/ month.
  6. Tars: Chat bots are gold, especially for e-commerce business that receive tons of product specific questions.Tars helps businesses build a chatbot without coding experience that can be integrated with various platforms such as website, social media, and messaging apps. Another tool is CustomGPT that ingests your own website data to create a personalized AI chatbot. The new platform helps with content creation, customer service, research, and more.
  7. AI for HR: There’re also HR-related AI tools for a softer life. TextRecruit ($49/month) is a tool that helps in hiring hourly workers whereas Arya supports in finding specific and permanent talent. For everyday HR duties Zenefits ($8/month) helps automating and streamlining basic HR functions such as payrolls.

[#section4]Why Acceptance and Implementation of AI Determines Business Success[#section4]

Now with all these insights, it’s crystal clear that AI in marketing is invaluable for cost savings and more sales - remember the perfect match. The huge potential of AI in marketing, and growing demand and inventions of AI-based technologies show that AI has become an essential tool within business operations and is here to stay.  

Thus, we empower any business owner to implement the simplest and (mostly free) AI tools to not only reduce administrative burdens in day-to-day business but to also free up more room for creativity, as well as better customer service – and simultaneously reducing costs and making customers happier.  

We believe an open mind and experimentation within tools like ChatGPT will more likely amaze and inspire than intimidate. The most important thing is to use such tools wisely while staying reflective and critical. AI won't replace everything, but it will replace those who don't make use of it.

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