What is A.I marketing?

A.I is frequently implemented in marketing strategies where speed is key. A.I tools rely heavily on data and customer profiles to predict customer buying behavior, which in turn can help company communicate with customers. A.I tools can help marketing team serve tailored messages at the right time, to right customer base ensuring maximum efficacy.

A.I is used to augment marketing teams or to perform more tactical work that needs less human interactions.

A.I marketing eco system cycle includes:

1.  Content Generation
2.  Data Collection
3.  Data Analysis
4.  Natural Language processing
5.  Real Time Personalization
6.  Media Buying
7.  automated decision Making

Components of AI Marketing:

A.I marketing is a very generic term used to define processes of automation of marketing. It holds a very important role in helping marketers connect efficiently with their target customers. There are several components to AI in marketing that collectively helps to bridge the gap between the huge amount of real time data that is collected of the customer behavior and the actionable steps tat can be applied to future campaigns.

Big data and Analytics:

With the emergence of several digital media platforms, there has been a tremendous influx of data, which has provided an opportunity to marketers. These data can be analyzed by performing certain data analytics tools which can provide value across channels.

This has also led to some serious problems as the over saturation of data has led marketers struggle to determine which data sets are worth collecting and processing as wrong data set or biased data sets can lead to bad decision making.

Machine Learning:

Machine learning is a subset of Artificial Intelligence. It involves several high level computer algorithms, that can analyze information and improve automatically through self enhancement and self-learning. These algorithms analyze new information in the context of relevant historical data and uses predictive modeling to help make decisions based on what has or hasn’t worked in the past.

A.I Platform Solutions:

A.I powered marketing solutions provide marketers with a central platform for managing the vast amount of data that is collected through various social and digital media eco system. These A.I based platforms have the ability to derive insightful marketing intelligence into your target market audience cum customers that can help you make data-driven decisions.

Certain tools like the Bayesian learning and forgetting can help marketers gain a transparent and clearer understanding of how receptive a customer is to a specific marketing effort.

Challenges for AI powered marketing:

A.I marketing focuses heavily on data. It relies on an in-depth understanding of customer needs, preferences and behavior and then the ability to collate that data and use the information to make decision quickly, accurately and efficiently.

This ability to make real time, data driven decisions has helped AI to come to the forefront in terms of usage for generation next marketers.

Precautions need to be taken by the marketing teams as in how to best integrate AI into their campaigns and operations.

AI technology usage in the daily world scenario is still in its nascent stage. This makes it more ambiguous and challenging because if it’s not implemented properly it can have adverse effect to the overall marketing goals of the company.

Data Quality: AI tools is a set of algorithm or program that is fed in the computer which uses tools like data analytics to process the data and predict outcomes as any other computer program which makes it more of a concern. AI tools do not automatically understand which actions to take to achieve marketing goals. They require proper sorted data, time and training to learn business goals, objectives, customer preferences, historical trends, overall context etc.

This process not only requires time but also good quality data. If the AI program is not trained and fed with high quality accurate data, the program will make wrong and biased predictions. This will then be of no use and will be a futile effort spending huge resources of the company.

Privacy:

With the emergence of new rules and laws related to privacy and data policy the collection of data is becoming tougher day by day. Consumers and regulating bodies alike are coming heavily on how organizations use their data. Companies now need to follow the stringent data privacy policies and marketing team’s needs to ensure they are following data privacy policy ethically and in compliance with standard of GDPR. If found at fault, these companies can face penalties and brand damage as well. This is a major concern with the AI powered marketing.

ROI:

AI is not just another “Click Me” or “Call to action” Button In your website; it is a very complex process which is not always quantifiable. It can be difficult for marketers to demonstrate the value of AI investments to the organization.

While KPIs such as digital Marketing ROI and its efficiency are easily quantified, but depicting how AI has improved customer experience or helped in customer buying journey or maintain and enhancing Brand reputation is less obvious.

Ambiguity in Installation of Ai and Its best Practices:

AI is comparatively a new tool in the arsenal of the marketing gurus. Definitive best practices have not been established to guide marketing teams initial deployment/

Disruptive Marketing Scenario:

With AI emerging as a disruptive technology marketers must evaluate which jobs will be replaced and which jobs will be created. There is currently a sense of insecurity in the mind of marketers as well as overall organizational eco system with regards to AI technology being regarded as a automation tool that can destroy human jobs and replace human beings in offices. There are several studies suggesting that nearly 6 out of 10 jobs will be replaced by marketing automation technologies.

How to efficiently use AI in marketing

As in any case of marketing the first thing first is to begin with a thorough plan. A detailed plan needs to be made that shows clear picture of the current position of the company in terms of technology adaptor and how it can move gradually with implementing new AI tools and technology.

Top down approach goes well in adapting with these newer tools and technologies because people at the top level like the CEO or CTO can better understand these changes and adapt easily.

This will ensure marketing teams minimize costly challenges and get best out of their AI investment in least amount of time.

There are few very important factors to consider before implementing an AI tool for marketing: 

Goal Setting:

It’s very important that you set up a clear goal, so as to have a clear picture what is expected from the implementation of the AI tool in your organization. It can be started by identifying areas within campaigns or operations that AI can help in improving. After this you can set up KPIs that will help show how successful the AI campaign has been. Without this you can’t understand how successful your qualitative goals such as customer satisfaction have been after implementing AI tools.

Data Privacy setup:

Data privacy is becoming a very critical factor in any data related tools online especially with the GDPR rules. Before starting your AI program, be sure that AI tool will not hurt the data privacy policy set up by the international organizations.

Be certain that privacy standards are established and programmed into your AI tool as needed to maintain compliance and customer trust.

Quality and Quantity of Data:

AI tool be it Big or small depends on data only, so it becomes very critical as how good and unbiased your data set is.

In order to get started with AI powered marketing, marketers need to have a vast amount of data at their disposal. Only good amount and good quality of data can train your AI tool. Initially these data can be sourced from third party authentic data sources and then gradually from organization’s own CRM , marketing campaigns, social media sources, website data, local area location data, etc that may contribute or influence a customer’s purchasing decision.

Talent Acquisition- Data scientists and Data Analytics:

A sudden shift from a traditional marketing company to a AI powered organization is a sure shot recipe to failure. The organizational structure needs to be made more acceptable to the change. Many marketing departments lack roles and employees with necessary data science and Data analytics skills. This makes it nearly impossible to implement AI based tools in the organization.

To get AI programs off the ground, organization should initially outsource to AI marketing companies that can assist in the collection and analysis of data to train AI programs and help the company in gradually implementing AI technology in their core marketing.

Maintaining Data Quality:

Data reigns supreme when it comes to AI powered marketing, without good data AI is nothing more than any marketing jargon. As machine learning programs consume more data, the program will learn to make correct decisions. But, if the data is not of good and standard quality free from errors the insights will not be of any value. Poor data quality can cause AI programs to make decisions that hinder marketing goals.

Before setting up AI for marketing, the core marketing team must coordinate with Data management team (if any, if not than the outsourced third party team) and other business verticals and departments to establish free and smooth flow of data. Once data flow is smooth processes can be set up for data cleansing and data maintenance.

This needs to be done while keeping the below important data dimensions in mind.

1. Timeliness
2. Completeness
3. Consistency
4. Relevance
5. Transparency
6. Accuracy
7. Representativeness

Selecting Best AI platform for your business:

Once you have sorted out the process of data collection and have defined roles and responsibilities to new AI powered marketing Team (outsourced or in-house). Now comes the crucial step in getting an AI powered marketing program that best suit your company’s goal. The goal could be like speed and productivity enhancement which will require different functionality than tools used for improving customer satisfaction. Also things to consider will be how much transparency you need in reporting the decision that the AI tool used. All AI tools may not give a clear representation on why a certain decision was made and which data influenced the decision.

Benefits of Implementing Artificial Intelligence in marketing:

Benefits of AI powered Marketing:

Here is a vast number of examples in real life scenario where AI powered marketing is used. Each of these examples have yielded different results such as increase speed, greater customer satisfaction, increased ROI, risk reduction etc. The most common used case involve around increase in number of sales.

Increase campaign ROI:

If implemented correctly AI powered marketing can help transform the entire marketing eco system of any organization. By implementing the most valuable insights from their analyzed data sets and acting upon them in real time one can enhance the value creation. AI powered platforms can make lightning fast decisions on how to best allocate funds across various media channels or analyzed the most effective ad placement to the most engaged set of your target market thereby giving you the maximum return on your investment (ROI)

Enhanced Customer Relationship:

AI can help marketers identify probable customers and show them customized plans , discounts, rates etc which can make them go “WOW” that is the the real customer delight.

Real time personalization:

AI can help you deliver personalized messages to customers at appropriate points in the customer busying life cycle.

Marketing Measurements for Better Decision making:

You can now have a customized dashboard that allows for more comprehensive view into real time data, which can be implemented efficiently.

Make faster decision:

AI powered tools can conduct tactical data analysis faster than the human marketers. Machine learning can come to fast conclusion based on campaigns and customer profiles. This gives enough time to focus on strategic initiatives and market expansion. With perfect AI powered marketing program in action, marketers no longer have to wait until the end of a campaign to make decision but can use real time analytics to make best marketing choices.

Examples of Artificial Intelligence in Marketing:

AI in marketing is now gaining grounds. AI is being used in marketing initiatives across a huge array of industries primarily in finance and banking sector, government sectors, entertainment industry, healthcare industry, retail, real estate and many more.

Every sector has its own priorities and is used for different goals ranging from improvements to campaign performance, to enhance customer experience, or greater efficiency in marketing operations.

Here are some ways business can take advantage of machine learning to create a more holistic marketing approach:

• Buying Programmatic Media – One major drawbacks of using traditional marketing techniques that organizations often encounter was deciding where and when to place advertisements and their brand messages. Marketing team can now use AI powered marketing tools to create informed plans based on user preferences, on real time based on the latest consumer information. AI is being used by new generation marketers to mitigate this through programmatic ads. Programmatic platforms now leverages machine learning to place efficient bids on ads relevant to the target audiences in real time.

The bid is more informed backed up by real time data such as interests, locations, purchase behavior and buyer intent. This helps marketers target the right channels at the right time for competitive price. Programmatic ads buying, sets-up a great example as in how machine learning and AI can increase marketing flexibility.

• Right Messaging:

Placing right message in front of right customer at right time is a daunting task. Across various digital media channels, different consumers respond to different messages differently. Only way out till now was testing (A/B testing) which was time and resource consuming. Machine learning and AI in particular can track which messages your target consumer have responded to and cater accordingly. Marketing teams now equipped with advanced AI tools can serve more customized messages to users based on their preferences. Best example is of Netflix which uses AI tools to understand the genres a certain user is interested in. It can make consumer personas accordingly and customize the list that user sees depending upon their interest.

With the usage of AI tools these platforms can other valuable data on consumer that allow marketers increase conversions and also improve customer experience.

• Personalization

Almost human to human level personalization can be achieved by using AI powered marketing tools. Marketing messages today can be more informed with user’s interest, purchase history, location, past interactions etc. AI helps marketing teams learn more about an individual’s preferences on a granular, individual level. This helps brands create curated messages and offers as well as overall experience based on a customer’s unique preferences. Spotify uses AI to create customized playlist based on what a customer has listened in the past. It uses customer preferences and past history to suggest customized playlists for users. This has helped Spotify become a top streaming service in a very competitive entertainment sector.

• Chatbots

AI using natural language processing (NLP) can now interact almost like real human beings. AI chatbots are now used to augment customer service agents. Customers with general queries can refer to chatbots which will give real time accurate answers. These AI tools can now leverage past questions and historical data to deliver personalized results. This in turn gives the customer support team to work on more serious and complicated requests that need more human interactions.

• One thing that has acted as a catalyst to the AI ecosystem is availability of vast data sets.. With so much data available now AI allows marketing teams to perform predictive analytics, which helps in predicting the future of a particular consumer persona. This helps organizations understand the types of product a consumer will be looking for and when. This predictive modeling can help organizations, position campaigns more accurately.

Best example of predictive marketing is of Amazon which suggests products based on past purchases and behavior thereby increasing conversions and customer satisfaction. Marketing analytics can help marketing teams track the attribution and goal more accurately to see which campaign was successful.

• Dynamic pricing :

AI with its predictive capabilities can help make organizations more agile and competitive. AI tools can enable Businesses with options of maintaining dynamic pricing. AI platforms can suggest best prices for products or services in real time by examining huge quantity of historical and competitive data.  This technique can be very much effective on Airline Industries; it’s very much in practice in Online retail industry as well. It allows companies to tweak prices to reflect demand for certain products, boost sales, and give tough competition to their competitors.

• Marketing Ecosystem:

One of the main focus of all the major MNCs and Business houses currently is now on implementation of AI in marketing so as to increase efficiency across various processes. AI can help to automate certain processes such as the sorting of marketing data, answering common customer queries, content management , scheduling etc. this itself can give ample time to marketing professionals so that they can focu more time on creative planning as well as strategies and analysis.